Supplementary Tables:
Brain activity associated with regulating food cravings predicts changes in self-reported food craving and consumption over time# define aesthetic
palette = wesanderson::wes_palette("Zissou1", 15, "continuous")
# import data & check
food.dataW <- read.csv(file.path("~/Dropbox (University of Oregon)/Berkman Lab/CHIVES/Papers/ROCpredict/Analyses/AllData_wide_v4.csv", fsep=""))
food.dataL <- read.csv(file.path("~/Dropbox (University of Oregon)/Berkman Lab/CHIVES/Papers/ROCpredict/Analyses/AllData_long_v4.csv", fsep=""))
# center all IVs. month does not need to be centered since 0 is already baseline.
attach(food.dataL)
food.dataL$LCLNCvmpfc_c <- c(scale(LCLNC_vmpfc, center=TRUE, scale=FALSE))
food.dataL$LCLNCstria_c <- c(scale(LCLNC_striatum, center=TRUE, scale=FALSE))
food.dataL$RCLCdlpfc_c <- c(scale(RCLC_dlpfc, center=TRUE, scale=FALSE))
food.dataL$RCLCifg_c <- c(scale(RCLC_IFG, center=TRUE, scale=FALSE))
food.dataL$RCLCdacc_c <- c(scale(RCLC_dacc, center=TRUE, scale=FALSE))
food.dataL$RCLCvmpfc_c <- c(scale(RCLC_vmpfc, center=TRUE, scale=FALSE))
food.dataL$RCLCparhip_c <- c(scale(RCLC_Lparahip, center=TRUE, scale=FALSE))
food.dataL$RCLClifg_c <- c(scale(RCLC_Lifg, center=TRUE, scale=FALSE))
food.dataL$RCLClsupra_c <- c(scale(RCLC_Lsupra, center=TRUE, scale=FALSE))
food.dataL$RCLClcereb_c <- c(scale(RCLC_Lcereb, center=TRUE, scale=FALSE))
food.dataL$RCLCna_c <- c(scale(RCLC_na, center=TRUE, scale=FALSE))
food.dataL$RCLCrsupra_c <- c(scale(RCLC_Rsupra, center=TRUE, scale=FALSE))
food.dataL$RCLCrpmf_c <- c(scale(RCLC_RpostmedFront, center=TRUE, scale=FALSE))
food.dataL$BMI_c <- c(scale(BMI, center=TRUE, scale=FALSE))
food.dataL$age_c <- c(scale(age, center=TRUE, scale=FALSE))
# create regulation brain activity composites
food.dataL$regAnatROIAvg <- (food.dataL$RCLCdacc_c + food.dataL$RCLCdlpfc_c + food.dataL$RCLCifg_c) / 3
food.dataL$regPeakROIAvg <- (food.dataL$RCLCparhip_c + food.dataL$RCLClifg_c + food.dataL$RCLClsupra_c +
food.dataL$RCLClcereb_c + food.dataL$RCLCna_c + food.dataL$RCLCrsupra_c +
food.dataL$RCLCrpmf_c) / 7
# define modeling function
fit_mod = function(data){
mod = lmerTest::lmer(y_value ~ month * x_value + BMI_c + age_c + gender + condition + (1 | Participant), data = data)
return(mod)
}
make_table = function(df, predictors = ".*", short = FALSE) {
if (short == TRUE) {
df %>%
filter(effect == "fixed") %>%
rename("p" = p.value,
`neural predictor` = x_var) %>%
mutate(term = gsub("\\(Intercept\\)", "intercept", term),
term = gsub("x_value", "neural predictor", term),
term = gsub("_c", "", term),
term = gsub("month", "time", term),
term = gsub(":", " x ", term),
term = gsub("sd__", "", term),
`neural predictor` = gsub("LCLNC", " LC > LNC ", `neural predictor`),
`neural predictor` = gsub("RCLC", " RC > LC ", `neural predictor`),
`neural predictor` = gsub("_c", "", `neural predictor`),
`neural predictor` = gsub("pfc", "PFC", `neural predictor`),
`neural predictor` = gsub("stria", "striatum", `neural predictor`),
`neural predictor` = gsub("lifg", "l IFG", `neural predictor`),
`neural predictor` = gsub("ifg", "IFG", `neural predictor`),
`neural predictor` = gsub("dacc", "dACC", `neural predictor`),
`neural predictor` = gsub("parhip", "parahippocampal gyrus", `neural predictor`),
`neural predictor` = gsub("rsupra", "r supramarginal gyrus", `neural predictor`),
`neural predictor` = gsub("lsupra", "l supramarginal gyrus", `neural predictor`),
`neural predictor` = gsub("lcereb", "l cerebellum", `neural predictor`),
`neural predictor` = gsub("na$", "midbrain", `neural predictor`),
`neural predictor` = gsub("rpmf", "r posterior MFG", `neural predictor`),
`neural predictor` = gsub("regAnatROIAvg", "average anatomical ROIs", `neural predictor`),
`neural predictor` = gsub("regAnatROIAvg", "average peak ROIs", `neural predictor`),
`b [95% CI]` = ifelse(effect == "fixed",
sprintf("%.02f [%.02f, %.02f]", estimate, conf.low, conf.high),
sprintf("%.02f (variance)", estimate)),
p = ifelse(p < .001, "< .001", gsub("0.(.*)", ".\\1", sprintf("%.3f", p)))) %>%
select(`neural predictor`, term, `b [95% CI]`, p) %>%
mutate_if(is.numeric, funs(ifelse(is.na(.), "--", .))) %>%
mutate_if(is.character, funs(ifelse(. == "NA" | is.na(.), "--", .))) %>%
filter(grepl(!!(predictors), term))
} else {
df %>%
rename("SE" = std.error,
"t" = statistic,
"p" = p.value,
`neural predictor` = x_var) %>%
mutate(term = gsub("\\(Intercept\\)", "intercept", term),
term = gsub("x_value", "neural predictor", term),
term = gsub("_c", "", term),
term = gsub("month", "time", term),
term = gsub(":", " x ", term),
term = gsub("sd__", "", term),
term = ifelse(effect == "ran_pars", tolower(group), term),
`neural predictor` = gsub("LCLNC", " LC > LNC ", `neural predictor`),
`neural predictor` = gsub("RCLC", " RC > LC ", `neural predictor`),
`neural predictor` = gsub("_c", "", `neural predictor`),
`neural predictor` = gsub("pfc", "PFC", `neural predictor`),
`neural predictor` = gsub("stria", "striatum", `neural predictor`),
`neural predictor` = gsub("lifg", "l IFG", `neural predictor`),
`neural predictor` = gsub("ifg", "IFG", `neural predictor`),
`neural predictor` = gsub("dacc", "dACC", `neural predictor`),
`neural predictor` = gsub("parhip", "parahippocampal gyrus", `neural predictor`),
`neural predictor` = gsub("rsupra", "r supramarginal gyrus", `neural predictor`),
`neural predictor` = gsub("lsupra", "l supramarginal gyrus", `neural predictor`),
`neural predictor` = gsub("lcereb", "l cerebellum", `neural predictor`),
`neural predictor` = gsub("na$", "midbrain", `neural predictor`),
`neural predictor` = gsub("rpmf", "r posterior MFG", `neural predictor`),
`neural predictor` = gsub("regAnatROIAvg", "average anatomical ROIs", `neural predictor`),
`neural predictor` = gsub("regPeakROIAvg", "average peak ROIs", `neural predictor`),
effect = gsub("ran_pars", "random", effect),
`b [95% CI]` = ifelse(effect == "fixed",
sprintf("%.02f [%.02f, %.02f]", estimate, conf.low, conf.high),
sprintf("%.02f (variance)", estimate)),
SE = sprintf("%.02f", SE),
t = sprintf("%.02f", t),
df = sprintf("%.02f", df),
p = ifelse(p < .001, "< .001", gsub("0.(.*)", ".\\1", sprintf("%.3f", p)))) %>%
select(`neural predictor`, effect, term, `b [95% CI]`, SE, t, df, p) %>%
mutate_if(is.numeric, funs(ifelse(is.na(.), "--", .))) %>%
mutate_if(is.character, funs(ifelse(. == "NA" | is.na(.), "--", .))) %>%
filter(grepl(!!(predictors), term))
}
}
row_nums = c(1:10, 21:30, 41:50, 61:70, 81:90, 101:110, 121:130, 141:150)
print_table = function(tables, outcome, row_nums) {
tables %>%
filter(y_var == outcome) %>%
select(table) %>%
unnest() %>%
group_by(term) %>%
mutate(model = row_number()) %>%
select(model, `neural predictor`, term, everything(), -y_var) %>%
knitr::kable() %>%
kableExtra::kable_styling() %>%
kableExtra::row_spec(row_nums, background = "#f5f5f5")
}
Run the following multilevel model for each neural predictor and dependent variable:
lmer(y_value ~ month * x_value + BMI_c + age_c + gender + condition + (1 | Participant))
y_value
= dependent variablemonth
= time in monthsx_value
= grand-mean centered neural predictor (independent variable of interest)BMI_c
= grand-mean centered BMIage_c
= grand-mean centered agecondition
= intervention condition (not relevant for the present analyses)# tidy dataset
data_tables = food.dataL %>%
gather(y_var, y_value, FCI_unhelCrv, FCI_helCrv, FCI_unhelLike, FCI_helLike, HEItot, Kcal, Fvavg, Empty) %>%
gather(x_var, x_value, contains("_c"), contains("Avg"), -BMI_c, -age_c) %>%
select(Participant, month, BMI_c, age_c, gender, condition, contains("y"), contains("x"))
# run models
models = data_tables %>%
group_by(y_var, x_var) %>%
nest() %>%
mutate(test = map(data, fit_mod)) %>%
mutate(draws = map(test, broom.mixed::tidy, conf.int = TRUE)) %>%
select(-data, -test) %>%
unnest()
# make tables
tables = models %>%
group_by(y_var) %>%
nest() %>%
mutate(table = map(data, make_table, short = FALSE))
model | neural predictor | term | effect | b [95% CI] | SE | t | df | p |
---|---|---|---|---|---|---|---|---|
1 | LC > LNC vmPFC | intercept | fixed | 2.44 [2.15, 2.74] | 0.15 | 16.59 | 82.09 | < .001 |
1 | LC > LNC vmPFC | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.41 | 130.08 | .018 |
1 | LC > LNC vmPFC | neural predictor | fixed | 0.02 [-0.20, 0.24] | 0.11 | 0.18 | 99.15 | .858 |
1 | LC > LNC vmPFC | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.74 | 96.71 | .007 |
1 | LC > LNC vmPFC | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.37 | 77.64 | .173 |
1 | LC > LNC vmPFC | gender | fixed | -0.18 [-0.47, 0.11] | 0.15 | -1.21 | 79.19 | .229 |
1 | LC > LNC vmPFC | condition | fixed | 0.15 [-0.06, 0.36] | 0.11 | 1.42 | 79.40 | .159 |
1 | LC > LNC vmPFC | time x neural predictor | fixed | -0.01 [-0.06, 0.04] | 0.02 | -0.56 | 132.26 | .578 |
1 | LC > LNC vmPFC | participant | random | 0.42 (variance) | – | – | – | – |
1 | LC > LNC vmPFC | residual | random | 0.38 (variance) | – | – | – | – |
2 | LC > LNC striatum | intercept | fixed | 2.44 [2.15, 2.73] | 0.15 | 16.61 | 82.14 | < .001 |
2 | LC > LNC striatum | time | fixed | -0.03 [-0.05, -0.00] | 0.01 | -2.37 | 130.32 | .019 |
2 | LC > LNC striatum | neural predictor | fixed | 0.03 [-0.17, 0.23] | 0.10 | 0.30 | 97.00 | .765 |
2 | LC > LNC striatum | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.78 | 97.54 | .006 |
2 | LC > LNC striatum | age | fixed | -0.02 [-0.05, 0.01] | 0.02 | -1.31 | 77.77 | .194 |
2 | LC > LNC striatum | gender | fixed | -0.17 [-0.46, 0.12] | 0.15 | -1.17 | 79.61 | .247 |
2 | LC > LNC striatum | condition | fixed | 0.15 [-0.06, 0.36] | 0.11 | 1.41 | 79.15 | .163 |
2 | LC > LNC striatum | time x neural predictor | fixed | -0.03 [-0.07, 0.01] | 0.02 | -1.53 | 130.13 | .128 |
2 | LC > LNC striatum | participant | random | 0.42 (variance) | – | – | – | – |
2 | LC > LNC striatum | residual | random | 0.38 (variance) | – | – | – | – |
3 | RC > LC dlPFC | intercept | fixed | 2.42 [2.12, 2.72] | 0.15 | 16.21 | 83.04 | < .001 |
3 | RC > LC dlPFC | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.46 | 130.80 | .015 |
3 | RC > LC dlPFC | neural predictor | fixed | 0.11 [-0.18, 0.40] | 0.15 | 0.74 | 100.73 | .464 |
3 | RC > LC dlPFC | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.70 | 97.71 | .008 |
3 | RC > LC dlPFC | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.35 | 78.57 | .182 |
3 | RC > LC dlPFC | gender | fixed | -0.15 [-0.45, 0.15] | 0.15 | -0.99 | 81.20 | .326 |
3 | RC > LC dlPFC | condition | fixed | 0.15 [-0.06, 0.36] | 0.11 | 1.41 | 79.92 | .162 |
3 | RC > LC dlPFC | time x neural predictor | fixed | -0.00 [-0.06, 0.05] | 0.03 | -0.17 | 129.57 | .864 |
3 | RC > LC dlPFC | participant | random | 0.42 (variance) | – | – | – | – |
3 | RC > LC dlPFC | residual | random | 0.38 (variance) | – | – | – | – |
4 | RC > LC IFG | intercept | fixed | 2.42 [2.12, 2.72] | 0.15 | 16.08 | 82.91 | < .001 |
4 | RC > LC IFG | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.47 | 130.66 | .015 |
4 | RC > LC IFG | neural predictor | fixed | 0.07 [-0.23, 0.36] | 0.15 | 0.45 | 98.95 | .651 |
4 | RC > LC IFG | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.71 | 97.41 | .008 |
4 | RC > LC IFG | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.35 | 78.45 | .180 |
4 | RC > LC IFG | gender | fixed | -0.16 [-0.46, 0.14] | 0.15 | -1.04 | 81.21 | .300 |
4 | RC > LC IFG | condition | fixed | 0.16 [-0.06, 0.37] | 0.11 | 1.46 | 79.43 | .148 |
4 | RC > LC IFG | time x neural predictor | fixed | -0.00 [-0.06, 0.06] | 0.03 | -0.12 | 130.45 | .906 |
4 | RC > LC IFG | participant | random | 0.42 (variance) | – | – | – | – |
4 | RC > LC IFG | residual | random | 0.38 (variance) | – | – | – | – |
5 | RC > LC dACC | intercept | fixed | 2.41 [2.11, 2.71] | 0.15 | 16.20 | 82.82 | < .001 |
5 | RC > LC dACC | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.47 | 131.07 | .015 |
5 | RC > LC dACC | neural predictor | fixed | 0.16 [-0.13, 0.46] | 0.15 | 1.13 | 98.89 | .263 |
5 | RC > LC dACC | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.70 | 97.74 | .008 |
5 | RC > LC dACC | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.39 | 78.94 | .168 |
5 | RC > LC dACC | gender | fixed | -0.14 [-0.44, 0.15] | 0.15 | -0.95 | 81.04 | .343 |
5 | RC > LC dACC | condition | fixed | 0.16 [-0.05, 0.37] | 0.11 | 1.49 | 79.76 | .141 |
5 | RC > LC dACC | time x neural predictor | fixed | -0.01 [-0.06, 0.04] | 0.03 | -0.36 | 126.32 | .722 |
5 | RC > LC dACC | participant | random | 0.42 (variance) | – | – | – | – |
5 | RC > LC dACC | residual | random | 0.38 (variance) | – | – | – | – |
6 | RC > LC vmPFC | intercept | fixed | 2.43 [2.13, 2.72] | 0.15 | 16.36 | 82.65 | < .001 |
6 | RC > LC vmPFC | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.52 | 130.57 | .013 |
6 | RC > LC vmPFC | neural predictor | fixed | 0.06 [-0.14, 0.26] | 0.10 | 0.58 | 98.81 | .566 |
6 | RC > LC vmPFC | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.80 | 98.14 | .006 |
6 | RC > LC vmPFC | age | fixed | -0.02 [-0.05, 0.01] | 0.02 | -1.37 | 78.55 | .175 |
6 | RC > LC vmPFC | gender | fixed | -0.16 [-0.46, 0.13] | 0.15 | -1.10 | 80.49 | .273 |
6 | RC > LC vmPFC | condition | fixed | 0.15 [-0.06, 0.37] | 0.11 | 1.45 | 79.66 | .150 |
6 | RC > LC vmPFC | time x neural predictor | fixed | -0.01 [-0.05, 0.02] | 0.02 | -0.69 | 128.01 | .494 |
6 | RC > LC vmPFC | participant | random | 0.42 (variance) | – | – | – | – |
6 | RC > LC vmPFC | residual | random | 0.38 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | intercept | fixed | 2.44 [2.15, 2.73] | 0.15 | 16.69 | 82.77 | < .001 |
7 | RC > LC parahippocampal gyrus | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.46 | 130.86 | .015 |
7 | RC > LC parahippocampal gyrus | neural predictor | fixed | 0.09 [-0.08, 0.27] | 0.09 | 1.07 | 100.42 | .289 |
7 | RC > LC parahippocampal gyrus | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.76 | 97.73 | .007 |
7 | RC > LC parahippocampal gyrus | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.26 | 78.43 | .212 |
7 | RC > LC parahippocampal gyrus | gender | fixed | -0.17 [-0.46, 0.12] | 0.14 | -1.19 | 80.00 | .238 |
7 | RC > LC parahippocampal gyrus | condition | fixed | 0.14 [-0.07, 0.36] | 0.11 | 1.36 | 79.87 | .179 |
7 | RC > LC parahippocampal gyrus | time x neural predictor | fixed | -0.00 [-0.04, 0.03] | 0.02 | -0.11 | 129.16 | .909 |
7 | RC > LC parahippocampal gyrus | participant | random | 0.42 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | residual | random | 0.38 (variance) | – | – | – | – |
8 | RC > LC l IFG | intercept | fixed | 2.44 [2.14, 2.75] | 0.15 | 16.01 | 83.80 | < .001 |
8 | RC > LC l IFG | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.49 | 130.47 | .014 |
8 | RC > LC l IFG | neural predictor | fixed | 0.01 [-0.09, 0.10] | 0.05 | 0.14 | 99.23 | .888 |
8 | RC > LC l IFG | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.76 | 97.47 | .007 |
8 | RC > LC l IFG | age | fixed | -0.02 [-0.05, 0.01] | 0.02 | -1.36 | 78.45 | .178 |
8 | RC > LC l IFG | gender | fixed | -0.18 [-0.48, 0.12] | 0.15 | -1.21 | 81.49 | .230 |
8 | RC > LC l IFG | condition | fixed | 0.15 [-0.06, 0.37] | 0.11 | 1.42 | 79.37 | .161 |
8 | RC > LC l IFG | time x neural predictor | fixed | -0.01 [-0.02, 0.01] | 0.01 | -0.67 | 130.38 | .503 |
8 | RC > LC l IFG | participant | random | 0.42 (variance) | – | – | – | – |
8 | RC > LC l IFG | residual | random | 0.38 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | intercept | fixed | 2.44 [2.15, 2.73] | 0.15 | 16.66 | 82.97 | < .001 |
9 | RC > LC l supramarginal gyrus | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.56 | 131.09 | .012 |
9 | RC > LC l supramarginal gyrus | neural predictor | fixed | 0.11 [-0.06, 0.28] | 0.08 | 1.30 | 98.80 | .195 |
9 | RC > LC l supramarginal gyrus | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.74 | 99.76 | .007 |
9 | RC > LC l supramarginal gyrus | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.47 | 78.69 | .145 |
9 | RC > LC l supramarginal gyrus | gender | fixed | -0.17 [-0.46, 0.12] | 0.15 | -1.18 | 80.60 | .240 |
9 | RC > LC l supramarginal gyrus | condition | fixed | 0.15 [-0.06, 0.36] | 0.11 | 1.41 | 80.03 | .161 |
9 | RC > LC l supramarginal gyrus | time x neural predictor | fixed | -0.03 [-0.06, 0.00] | 0.02 | -1.94 | 129.30 | .055 |
9 | RC > LC l supramarginal gyrus | participant | random | 0.42 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | residual | random | 0.38 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | intercept | fixed | 2.44 [2.15, 2.72] | 0.15 | 16.76 | 82.42 | < .001 |
10 | RC > LC l cerebellum | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.49 | 130.93 | .014 |
10 | RC > LC l cerebellum | neural predictor | fixed | -0.12 [-0.30, 0.06] | 0.09 | -1.30 | 96.39 | .196 |
10 | RC > LC l cerebellum | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.80 | 97.78 | .006 |
10 | RC > LC l cerebellum | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.52 | 78.80 | .132 |
10 | RC > LC l cerebellum | gender | fixed | -0.18 [-0.47, 0.10] | 0.14 | -1.27 | 79.91 | .209 |
10 | RC > LC l cerebellum | condition | fixed | 0.17 [-0.04, 0.38] | 0.11 | 1.64 | 79.03 | .104 |
10 | RC > LC l cerebellum | time x neural predictor | fixed | -0.01 [-0.05, 0.03] | 0.02 | -0.40 | 131.03 | .689 |
10 | RC > LC l cerebellum | participant | random | 0.41 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | residual | random | 0.38 (variance) | – | – | – | – |
11 | RC > LC midbrain | intercept | fixed | 2.43 [2.14, 2.73] | 0.15 | 16.53 | 82.17 | < .001 |
11 | RC > LC midbrain | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.46 | 130.51 | .015 |
11 | RC > LC midbrain | neural predictor | fixed | -0.03 [-0.20, 0.14] | 0.09 | -0.38 | 97.34 | .708 |
11 | RC > LC midbrain | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.74 | 97.82 | .007 |
11 | RC > LC midbrain | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.39 | 78.39 | .169 |
11 | RC > LC midbrain | gender | fixed | -0.17 [-0.46, 0.13] | 0.15 | -1.13 | 79.96 | .262 |
11 | RC > LC midbrain | condition | fixed | 0.15 [-0.06, 0.36] | 0.11 | 1.44 | 79.19 | .155 |
11 | RC > LC midbrain | time x neural predictor | fixed | -0.01 [-0.04, 0.03] | 0.02 | -0.37 | 126.09 | .710 |
11 | RC > LC midbrain | participant | random | 0.42 (variance) | – | – | – | – |
11 | RC > LC midbrain | residual | random | 0.38 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | intercept | fixed | 2.44 [2.15, 2.73] | 0.15 | 16.61 | 82.27 | < .001 |
12 | RC > LC r supramarginal gyrus | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.42 | 130.43 | .017 |
12 | RC > LC r supramarginal gyrus | neural predictor | fixed | 0.00 [-0.17, 0.17] | 0.09 | 0.01 | 97.32 | .991 |
12 | RC > LC r supramarginal gyrus | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.84 | 98.48 | .005 |
12 | RC > LC r supramarginal gyrus | age | fixed | -0.02 [-0.05, 0.01] | 0.02 | -1.45 | 79.09 | .152 |
12 | RC > LC r supramarginal gyrus | gender | fixed | -0.18 [-0.47, 0.11] | 0.15 | -1.21 | 79.79 | .232 |
12 | RC > LC r supramarginal gyrus | condition | fixed | 0.15 [-0.06, 0.36] | 0.11 | 1.44 | 79.28 | .154 |
12 | RC > LC r supramarginal gyrus | time x neural predictor | fixed | -0.02 [-0.06, 0.01] | 0.02 | -1.27 | 129.60 | .208 |
12 | RC > LC r supramarginal gyrus | participant | random | 0.42 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | residual | random | 0.38 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | intercept | fixed | 2.45 [2.16, 2.75] | 0.15 | 16.54 | 82.49 | < .001 |
13 | RC > LC r posterior MFG | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.45 | 131.04 | .016 |
13 | RC > LC r posterior MFG | neural predictor | fixed | -0.06 [-0.26, 0.14] | 0.10 | -0.61 | 98.43 | .541 |
13 | RC > LC r posterior MFG | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.82 | 97.33 | .006 |
13 | RC > LC r posterior MFG | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.38 | 78.11 | .171 |
13 | RC > LC r posterior MFG | gender | fixed | -0.19 [-0.49, 0.10] | 0.15 | -1.30 | 80.14 | .198 |
13 | RC > LC r posterior MFG | condition | fixed | 0.16 [-0.05, 0.37] | 0.11 | 1.52 | 79.06 | .133 |
13 | RC > LC r posterior MFG | time x neural predictor | fixed | 0.00 [-0.04, 0.04] | 0.02 | 0.04 | 131.11 | .967 |
13 | RC > LC r posterior MFG | participant | random | 0.42 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | residual | random | 0.38 (variance) | – | – | – | – |
14 | average anatomical ROIs | intercept | fixed | 2.41 [2.12, 2.71] | 0.15 | 16.10 | 82.95 | < .001 |
14 | average anatomical ROIs | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.47 | 130.87 | .015 |
14 | average anatomical ROIs | neural predictor | fixed | 0.13 [-0.18, 0.44] | 0.16 | 0.82 | 99.32 | .414 |
14 | average anatomical ROIs | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.69 | 97.54 | .008 |
14 | average anatomical ROIs | age | fixed | -0.02 [-0.05, 0.01] | 0.01 | -1.36 | 78.68 | .178 |
14 | average anatomical ROIs | gender | fixed | -0.14 [-0.44, 0.15] | 0.15 | -0.97 | 81.23 | .337 |
14 | average anatomical ROIs | condition | fixed | 0.15 [-0.06, 0.37] | 0.11 | 1.45 | 79.79 | .150 |
14 | average anatomical ROIs | time x neural predictor | fixed | -0.01 [-0.06, 0.05] | 0.03 | -0.23 | 128.25 | .820 |
14 | average anatomical ROIs | participant | random | 0.42 (variance) | – | – | – | – |
14 | average anatomical ROIs | residual | random | 0.38 (variance) | – | – | – | – |
15 | average peak ROIs | intercept | fixed | 2.44 [2.15, 2.74] | 0.15 | 16.52 | 82.28 | < .001 |
15 | average peak ROIs | time | fixed | -0.03 [-0.05, -0.01] | 0.01 | -2.47 | 130.40 | .015 |
15 | average peak ROIs | neural predictor | fixed | 0.01 [-0.23, 0.26] | 0.13 | 0.11 | 97.09 | .910 |
15 | average peak ROIs | BMI | fixed | 0.04 [0.01, 0.06] | 0.01 | 2.82 | 98.03 | .006 |
15 | average peak ROIs | age | fixed | -0.02 [-0.05, 0.01] | 0.02 | -1.40 | 78.72 | .164 |
15 | average peak ROIs | gender | fixed | -0.18 [-0.47, 0.11] | 0.15 | -1.24 | 79.89 | .220 |
15 | average peak ROIs | condition | fixed | 0.15 [-0.06, 0.37] | 0.11 | 1.46 | 79.14 | .149 |
15 | average peak ROIs | time x neural predictor | fixed | -0.03 [-0.08, 0.02] | 0.02 | -1.09 | 128.92 | .278 |
15 | average peak ROIs | participant | random | 0.42 (variance) | – | – | – | – |
15 | average peak ROIs | residual | random | 0.38 (variance) | – | – | – | – |
model | neural predictor | term | effect | b [95% CI] | SE | t | df | p |
---|---|---|---|---|---|---|---|---|
1 | LC > LNC vmPFC | intercept | fixed | 1.95 [1.57, 2.33] | 0.19 | 10.23 | 81.55 | < .001 |
1 | LC > LNC vmPFC | time | fixed | -0.02 [-0.05, 0.00] | 0.01 | -1.88 | 125.39 | .062 |
1 | LC > LNC vmPFC | neural predictor | fixed | -0.22 [-0.50, 0.05] | 0.14 | -1.61 | 90.58 | .112 |
1 | LC > LNC vmPFC | BMI | fixed | 0.04 [0.01, 0.07] | 0.02 | 2.32 | 109.94 | .022 |
1 | LC > LNC vmPFC | age | fixed | 0.00 [-0.03, 0.04] | 0.02 | 0.22 | 79.13 | .824 |
1 | LC > LNC vmPFC | gender | fixed | 0.19 [-0.19, 0.57] | 0.19 | 1.00 | 80.08 | .319 |
1 | LC > LNC vmPFC | condition | fixed | -0.06 [-0.34, 0.21] | 0.14 | -0.47 | 79.85 | .641 |
1 | LC > LNC vmPFC | time x neural predictor | fixed | 0.03 [-0.02, 0.08] | 0.02 | 1.09 | 126.85 | .279 |
1 | LC > LNC vmPFC | participant | random | 0.59 (variance) | – | – | – | – |
1 | LC > LNC vmPFC | residual | random | 0.37 (variance) | – | – | – | – |
2 | LC > LNC striatum | intercept | fixed | 1.96 [1.58, 2.34] | 0.19 | 10.27 | 81.91 | < .001 |
2 | LC > LNC striatum | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.87 | 125.81 | .064 |
2 | LC > LNC striatum | neural predictor | fixed | -0.20 [-0.46, 0.05] | 0.13 | -1.57 | 89.54 | .119 |
2 | LC > LNC striatum | BMI | fixed | 0.04 [0.00, 0.07] | 0.02 | 2.18 | 111.11 | .032 |
2 | LC > LNC striatum | age | fixed | 0.01 [-0.03, 0.05] | 0.02 | 0.38 | 79.48 | .704 |
2 | LC > LNC striatum | gender | fixed | 0.18 [-0.20, 0.56] | 0.19 | 0.94 | 80.69 | .348 |
2 | LC > LNC striatum | condition | fixed | -0.06 [-0.33, 0.22] | 0.14 | -0.41 | 80.00 | .685 |
2 | LC > LNC striatum | time x neural predictor | fixed | 0.03 [-0.02, 0.07] | 0.02 | 1.24 | 125.41 | .218 |
2 | LC > LNC striatum | participant | random | 0.59 (variance) | – | – | – | – |
2 | LC > LNC striatum | residual | random | 0.37 (variance) | – | – | – | – |
3 | RC > LC dlPFC | intercept | fixed | 1.96 [1.57, 2.34] | 0.19 | 10.10 | 82.64 | < .001 |
3 | RC > LC dlPFC | time | fixed | -0.02 [-0.05, -0.00] | 0.01 | -2.05 | 125.82 | .043 |
3 | RC > LC dlPFC | neural predictor | fixed | 0.28 [-0.09, 0.65] | 0.19 | 1.50 | 91.67 | .136 |
3 | RC > LC dlPFC | BMI | fixed | 0.03 [0.00, 0.07] | 0.02 | 2.06 | 113.63 | .042 |
3 | RC > LC dlPFC | age | fixed | 0.00 [-0.03, 0.04] | 0.02 | 0.20 | 80.31 | .839 |
3 | RC > LC dlPFC | gender | fixed | 0.18 [-0.20, 0.57] | 0.20 | 0.94 | 82.03 | .349 |
3 | RC > LC dlPFC | condition | fixed | -0.06 [-0.33, 0.22] | 0.14 | -0.42 | 80.69 | .673 |
3 | RC > LC dlPFC | time x neural predictor | fixed | -0.08 [-0.14, -0.03] | 0.03 | -3.10 | 125.27 | .002 |
3 | RC > LC dlPFC | participant | random | 0.60 (variance) | – | – | – | – |
3 | RC > LC dlPFC | residual | random | 0.36 (variance) | – | – | – | – |
4 | RC > LC IFG | intercept | fixed | 1.96 [1.57, 2.34] | 0.20 | 9.99 | 82.63 | < .001 |
4 | RC > LC IFG | time | fixed | -0.02 [-0.05, -0.00] | 0.01 | -1.99 | 125.87 | .049 |
4 | RC > LC IFG | neural predictor | fixed | 0.27 [-0.11, 0.64] | 0.19 | 1.41 | 90.91 | .162 |
4 | RC > LC IFG | BMI | fixed | 0.03 [0.00, 0.07] | 0.02 | 2.03 | 113.08 | .045 |
4 | RC > LC IFG | age | fixed | 0.00 [-0.03, 0.04] | 0.02 | 0.21 | 80.24 | .832 |
4 | RC > LC IFG | gender | fixed | 0.18 [-0.21, 0.57] | 0.20 | 0.94 | 82.06 | .350 |
4 | RC > LC IFG | condition | fixed | -0.05 [-0.33, 0.22] | 0.14 | -0.38 | 80.39 | .707 |
4 | RC > LC IFG | time x neural predictor | fixed | -0.08 [-0.13, -0.02] | 0.03 | -2.70 | 125.76 | .008 |
4 | RC > LC IFG | participant | random | 0.60 (variance) | – | – | – | – |
4 | RC > LC IFG | residual | random | 0.36 (variance) | – | – | – | – |
5 | RC > LC dACC | intercept | fixed | 1.96 [1.57, 2.34] | 0.19 | 10.06 | 82.25 | < .001 |
5 | RC > LC dACC | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.90 | 125.91 | .059 |
5 | RC > LC dACC | neural predictor | fixed | 0.24 [-0.13, 0.61] | 0.19 | 1.28 | 90.38 | .206 |
5 | RC > LC dACC | BMI | fixed | 0.03 [0.00, 0.07] | 0.02 | 2.04 | 112.48 | .044 |
5 | RC > LC dACC | age | fixed | 0.00 [-0.04, 0.04] | 0.02 | 0.18 | 80.25 | .859 |
5 | RC > LC dACC | gender | fixed | 0.18 [-0.20, 0.57] | 0.19 | 0.95 | 81.59 | .347 |
5 | RC > LC dACC | condition | fixed | -0.05 [-0.33, 0.22] | 0.14 | -0.38 | 80.30 | .706 |
5 | RC > LC dACC | time x neural predictor | fixed | -0.06 [-0.11, -0.01] | 0.03 | -2.36 | 123.28 | .020 |
5 | RC > LC dACC | participant | random | 0.59 (variance) | – | – | – | – |
5 | RC > LC dACC | residual | random | 0.37 (variance) | – | – | – | – |
6 | RC > LC vmPFC | intercept | fixed | 1.94 [1.56, 2.32] | 0.19 | 10.16 | 82.41 | < .001 |
6 | RC > LC vmPFC | time | fixed | -0.02 [-0.05, -0.00] | 0.01 | -2.04 | 126.06 | .043 |
6 | RC > LC vmPFC | neural predictor | fixed | 0.27 [0.02, 0.52] | 0.13 | 2.11 | 90.80 | .037 |
6 | RC > LC vmPFC | BMI | fixed | 0.04 [0.00, 0.07] | 0.02 | 2.24 | 112.22 | .027 |
6 | RC > LC vmPFC | age | fixed | 0.00 [-0.04, 0.04] | 0.02 | 0.11 | 80.24 | .916 |
6 | RC > LC vmPFC | gender | fixed | 0.21 [-0.17, 0.59] | 0.19 | 1.11 | 81.41 | .271 |
6 | RC > LC vmPFC | condition | fixed | -0.07 [-0.34, 0.21] | 0.14 | -0.48 | 80.50 | .632 |
6 | RC > LC vmPFC | time x neural predictor | fixed | -0.04 [-0.08, -0.01] | 0.02 | -2.36 | 124.48 | .020 |
6 | RC > LC vmPFC | participant | random | 0.59 (variance) | – | – | – | – |
6 | RC > LC vmPFC | residual | random | 0.37 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | intercept | fixed | 1.98 [1.60, 2.36] | 0.19 | 10.37 | 81.72 | < .001 |
7 | RC > LC parahippocampal gyrus | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.83 | 125.50 | .070 |
7 | RC > LC parahippocampal gyrus | neural predictor | fixed | 0.14 [-0.08, 0.36] | 0.11 | 1.23 | 90.95 | .223 |
7 | RC > LC parahippocampal gyrus | BMI | fixed | 0.03 [0.00, 0.07] | 0.02 | 2.12 | 110.87 | .036 |
7 | RC > LC parahippocampal gyrus | age | fixed | 0.00 [-0.03, 0.04] | 0.02 | 0.25 | 79.43 | .805 |
7 | RC > LC parahippocampal gyrus | gender | fixed | 0.16 [-0.22, 0.54] | 0.19 | 0.86 | 80.36 | .393 |
7 | RC > LC parahippocampal gyrus | condition | fixed | -0.07 [-0.35, 0.20] | 0.14 | -0.52 | 79.95 | .603 |
7 | RC > LC parahippocampal gyrus | time x neural predictor | fixed | -0.01 [-0.05, 0.02] | 0.02 | -0.89 | 124.51 | .374 |
7 | RC > LC parahippocampal gyrus | participant | random | 0.59 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | residual | random | 0.37 (variance) | – | – | – | – |
8 | RC > LC l IFG | intercept | fixed | 2.07 [1.67, 2.46] | 0.20 | 10.50 | 82.96 | < .001 |
8 | RC > LC l IFG | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.84 | 125.91 | .067 |
8 | RC > LC l IFG | neural predictor | fixed | -0.08 [-0.19, 0.04] | 0.06 | -1.28 | 91.75 | .204 |
8 | RC > LC l IFG | BMI | fixed | 0.04 [0.01, 0.07] | 0.02 | 2.42 | 111.34 | .017 |
8 | RC > LC l IFG | age | fixed | -0.00 [-0.04, 0.04] | 0.02 | -0.02 | 79.94 | .983 |
8 | RC > LC l IFG | gender | fixed | 0.09 [-0.30, 0.47] | 0.19 | 0.44 | 81.89 | .659 |
8 | RC > LC l IFG | condition | fixed | -0.11 [-0.39, 0.17] | 0.14 | -0.76 | 80.03 | .451 |
8 | RC > LC l IFG | time x neural predictor | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.90 | 125.90 | .368 |
8 | RC > LC l IFG | participant | random | 0.59 (variance) | – | – | – | – |
8 | RC > LC l IFG | residual | random | 0.37 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | intercept | fixed | 1.98 [1.60, 2.36] | 0.19 | 10.33 | 81.81 | < .001 |
9 | RC > LC l supramarginal gyrus | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.81 | 125.82 | .072 |
9 | RC > LC l supramarginal gyrus | neural predictor | fixed | -0.07 [-0.28, 0.14] | 0.11 | -0.65 | 90.71 | .519 |
9 | RC > LC l supramarginal gyrus | BMI | fixed | 0.04 [0.00, 0.07] | 0.02 | 2.25 | 112.17 | .027 |
9 | RC > LC l supramarginal gyrus | age | fixed | 0.00 [-0.04, 0.04] | 0.02 | 0.21 | 79.39 | .838 |
9 | RC > LC l supramarginal gyrus | gender | fixed | 0.15 [-0.23, 0.53] | 0.19 | 0.81 | 80.68 | .423 |
9 | RC > LC l supramarginal gyrus | condition | fixed | -0.06 [-0.34, 0.22] | 0.14 | -0.42 | 79.94 | .678 |
9 | RC > LC l supramarginal gyrus | time x neural predictor | fixed | -0.00 [-0.03, 0.03] | 0.02 | -0.08 | 124.99 | .939 |
9 | RC > LC l supramarginal gyrus | participant | random | 0.59 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | residual | random | 0.37 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | intercept | fixed | 1.98 [1.60, 2.36] | 0.19 | 10.29 | 81.99 | < .001 |
10 | RC > LC l cerebellum | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.80 | 125.90 | .075 |
10 | RC > LC l cerebellum | neural predictor | fixed | 0.00 [-0.23, 0.24] | 0.12 | 0.04 | 88.74 | .969 |
10 | RC > LC l cerebellum | BMI | fixed | 0.04 [0.00, 0.07] | 0.02 | 2.16 | 111.82 | .033 |
10 | RC > LC l cerebellum | age | fixed | 0.00 [-0.04, 0.04] | 0.02 | 0.13 | 80.14 | .894 |
10 | RC > LC l cerebellum | gender | fixed | 0.16 [-0.22, 0.54] | 0.19 | 0.83 | 80.83 | .410 |
10 | RC > LC l cerebellum | condition | fixed | -0.06 [-0.34, 0.22] | 0.14 | -0.44 | 79.86 | .659 |
10 | RC > LC l cerebellum | time x neural predictor | fixed | -0.01 [-0.05, 0.03] | 0.02 | -0.40 | 125.55 | .691 |
10 | RC > LC l cerebellum | participant | random | 0.60 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | residual | random | 0.37 (variance) | – | – | – | – |
11 | RC > LC midbrain | intercept | fixed | 1.99 [1.60, 2.37] | 0.19 | 10.30 | 81.98 | < .001 |
11 | RC > LC midbrain | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.82 | 125.85 | .071 |
11 | RC > LC midbrain | neural predictor | fixed | 0.03 [-0.19, 0.25] | 0.11 | 0.30 | 89.63 | .766 |
11 | RC > LC midbrain | BMI | fixed | 0.04 [0.00, 0.07] | 0.02 | 2.20 | 112.02 | .030 |
11 | RC > LC midbrain | age | fixed | 0.00 [-0.04, 0.04] | 0.02 | 0.17 | 79.99 | .862 |
11 | RC > LC midbrain | gender | fixed | 0.15 [-0.23, 0.53] | 0.19 | 0.77 | 80.99 | .442 |
11 | RC > LC midbrain | condition | fixed | -0.06 [-0.34, 0.22] | 0.14 | -0.43 | 80.09 | .665 |
11 | RC > LC midbrain | time x neural predictor | fixed | 0.01 [-0.02, 0.04] | 0.02 | 0.76 | 123.17 | .447 |
11 | RC > LC midbrain | participant | random | 0.60 (variance) | – | – | – | – |
11 | RC > LC midbrain | residual | random | 0.37 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | intercept | fixed | 1.99 [1.61, 2.37] | 0.19 | 10.47 | 81.73 | < .001 |
12 | RC > LC r supramarginal gyrus | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.75 | 125.73 | .083 |
12 | RC > LC r supramarginal gyrus | neural predictor | fixed | -0.12 [-0.34, 0.10] | 0.11 | -1.12 | 89.67 | .264 |
12 | RC > LC r supramarginal gyrus | BMI | fixed | 0.04 [0.00, 0.07] | 0.02 | 2.25 | 111.16 | .026 |
12 | RC > LC r supramarginal gyrus | age | fixed | -0.00 [-0.04, 0.04] | 0.02 | -0.02 | 80.07 | .986 |
12 | RC > LC r supramarginal gyrus | gender | fixed | 0.14 [-0.23, 0.52] | 0.19 | 0.76 | 80.49 | .449 |
12 | RC > LC r supramarginal gyrus | condition | fixed | -0.05 [-0.33, 0.22] | 0.14 | -0.38 | 79.81 | .705 |
12 | RC > LC r supramarginal gyrus | time x neural predictor | fixed | -0.02 [-0.06, 0.01] | 0.02 | -1.19 | 124.95 | .237 |
12 | RC > LC r supramarginal gyrus | participant | random | 0.59 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | residual | random | 0.37 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | intercept | fixed | 2.02 [1.64, 2.41] | 0.19 | 10.55 | 82.11 | < .001 |
13 | RC > LC r posterior MFG | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.62 | 126.28 | .108 |
13 | RC > LC r posterior MFG | neural predictor | fixed | -0.15 [-0.40, 0.10] | 0.13 | -1.18 | 90.54 | .240 |
13 | RC > LC r posterior MFG | BMI | fixed | 0.04 [0.00, 0.07] | 0.02 | 2.21 | 111.22 | .029 |
13 | RC > LC r posterior MFG | age | fixed | 0.00 [-0.04, 0.04] | 0.02 | 0.12 | 79.82 | .904 |
13 | RC > LC r posterior MFG | gender | fixed | 0.09 [-0.29, 0.48] | 0.19 | 0.49 | 81.00 | .625 |
13 | RC > LC r posterior MFG | condition | fixed | -0.04 [-0.32, 0.23] | 0.14 | -0.31 | 80.03 | .755 |
13 | RC > LC r posterior MFG | time x neural predictor | fixed | -0.03 [-0.07, 0.01] | 0.02 | -1.25 | 126.20 | .213 |
13 | RC > LC r posterior MFG | participant | random | 0.59 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | residual | random | 0.37 (variance) | – | – | – | – |
14 | average anatomical ROIs | intercept | fixed | 1.95 [1.56, 2.34] | 0.19 | 10.02 | 82.54 | < .001 |
14 | average anatomical ROIs | time | fixed | -0.02 [-0.05, -0.00] | 0.01 | -1.99 | 125.88 | .049 |
14 | average anatomical ROIs | neural predictor | fixed | 0.29 [-0.10, 0.69] | 0.20 | 1.48 | 90.90 | .143 |
14 | average anatomical ROIs | BMI | fixed | 0.03 [0.00, 0.07] | 0.02 | 2.02 | 113.08 | .046 |
14 | average anatomical ROIs | age | fixed | 0.00 [-0.03, 0.04] | 0.02 | 0.20 | 80.29 | .839 |
14 | average anatomical ROIs | gender | fixed | 0.19 [-0.20, 0.58] | 0.20 | 0.97 | 81.97 | .337 |
14 | average anatomical ROIs | condition | fixed | -0.05 [-0.33, 0.22] | 0.14 | -0.39 | 80.52 | .699 |
14 | average anatomical ROIs | time x neural predictor | fixed | -0.08 [-0.14, -0.02] | 0.03 | -2.84 | 124.50 | .005 |
14 | average anatomical ROIs | participant | random | 0.59 (variance) | – | – | – | – |
14 | average anatomical ROIs | residual | random | 0.36 (variance) | – | – | – | – |
15 | average peak ROIs | intercept | fixed | 2.00 [1.62, 2.39] | 0.19 | 10.41 | 81.99 | < .001 |
15 | average peak ROIs | time | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.80 | 125.88 | .074 |
15 | average peak ROIs | neural predictor | fixed | -0.12 [-0.44, 0.20] | 0.16 | -0.74 | 89.89 | .459 |
15 | average peak ROIs | BMI | fixed | 0.04 [0.00, 0.07] | 0.02 | 2.28 | 111.80 | .025 |
15 | average peak ROIs | age | fixed | 0.00 [-0.04, 0.04] | 0.02 | 0.05 | 80.15 | .964 |
15 | average peak ROIs | gender | fixed | 0.13 [-0.25, 0.51] | 0.19 | 0.68 | 80.88 | .497 |
15 | average peak ROIs | condition | fixed | -0.06 [-0.34, 0.21] | 0.14 | -0.46 | 79.99 | .650 |
15 | average peak ROIs | time x neural predictor | fixed | -0.02 [-0.07, 0.03] | 0.02 | -0.88 | 124.87 | .380 |
15 | average peak ROIs | participant | random | 0.59 (variance) | – | – | – | – |
15 | average peak ROIs | residual | random | 0.37 (variance) | – | – | – | – |
model | neural predictor | term | effect | b [95% CI] | SE | t | df | p |
---|---|---|---|---|---|---|---|---|
1 | LC > LNC vmPFC | intercept | fixed | 2.81 [2.59, 3.03] | 0.11 | 25.35 | 83.72 | < .001 |
1 | LC > LNC vmPFC | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -1.99 | 122.70 | .049 |
1 | LC > LNC vmPFC | neural predictor | fixed | 0.07 [-0.09, 0.23] | 0.08 | 0.87 | 92.40 | .385 |
1 | LC > LNC vmPFC | BMI | fixed | 0.01 [-0.01, 0.02] | 0.01 | 0.55 | 109.06 | .586 |
1 | LC > LNC vmPFC | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.42 | 81.11 | .159 |
1 | LC > LNC vmPFC | gender | fixed | -0.23 [-0.45, -0.01] | 0.11 | -2.12 | 82.11 | .037 |
1 | LC > LNC vmPFC | condition | fixed | 0.10 [-0.06, 0.27] | 0.08 | 1.30 | 81.70 | .197 |
1 | LC > LNC vmPFC | time x neural predictor | fixed | -0.01 [-0.03, 0.02] | 0.01 | -0.36 | 123.96 | .716 |
1 | LC > LNC vmPFC | participant | random | 0.34 (variance) | – | – | – | – |
1 | LC > LNC vmPFC | residual | random | 0.22 (variance) | – | – | – | – |
2 | LC > LNC striatum | intercept | fixed | 2.80 [2.58, 3.02] | 0.11 | 25.38 | 83.53 | < .001 |
2 | LC > LNC striatum | time | fixed | -0.01 [-0.03, 0.00] | 0.01 | -1.93 | 122.61 | .056 |
2 | LC > LNC striatum | neural predictor | fixed | 0.03 [-0.11, 0.18] | 0.07 | 0.47 | 90.90 | .639 |
2 | LC > LNC striatum | BMI | fixed | 0.01 [-0.01, 0.02] | 0.01 | 0.59 | 109.90 | .560 |
2 | LC > LNC striatum | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.39 | 80.81 | .169 |
2 | LC > LNC striatum | gender | fixed | -0.22 [-0.44, -0.01] | 0.11 | -2.04 | 82.17 | .045 |
2 | LC > LNC striatum | condition | fixed | 0.10 [-0.06, 0.26] | 0.08 | 1.25 | 81.30 | .215 |
2 | LC > LNC striatum | time x neural predictor | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.66 | 122.23 | .100 |
2 | LC > LNC striatum | participant | random | 0.34 (variance) | – | – | – | – |
2 | LC > LNC striatum | residual | random | 0.22 (variance) | – | – | – | – |
3 | RC > LC dlPFC | intercept | fixed | 2.79 [2.56, 3.01] | 0.11 | 24.80 | 84.31 | < .001 |
3 | RC > LC dlPFC | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.00 | 123.03 | .047 |
3 | RC > LC dlPFC | neural predictor | fixed | 0.10 [-0.12, 0.31] | 0.11 | 0.92 | 94.27 | .362 |
3 | RC > LC dlPFC | BMI | fixed | 0.00 [-0.01, 0.02] | 0.01 | 0.52 | 110.45 | .605 |
3 | RC > LC dlPFC | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.37 | 81.61 | .176 |
3 | RC > LC dlPFC | gender | fixed | -0.20 [-0.43, 0.02] | 0.11 | -1.78 | 83.42 | .079 |
3 | RC > LC dlPFC | condition | fixed | 0.10 [-0.06, 0.26] | 0.08 | 1.23 | 81.91 | .223 |
3 | RC > LC dlPFC | time x neural predictor | fixed | -0.00 [-0.04, 0.03] | 0.02 | -0.26 | 122.20 | .799 |
3 | RC > LC dlPFC | participant | random | 0.34 (variance) | – | – | – | – |
3 | RC > LC dlPFC | residual | random | 0.22 (variance) | – | – | – | – |
4 | RC > LC IFG | intercept | fixed | 2.78 [2.56, 3.01] | 0.11 | 24.55 | 84.31 | < .001 |
4 | RC > LC IFG | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.01 | 122.98 | .046 |
4 | RC > LC IFG | neural predictor | fixed | 0.10 [-0.12, 0.31] | 0.11 | 0.87 | 93.17 | .384 |
4 | RC > LC IFG | BMI | fixed | 0.00 [-0.01, 0.02] | 0.01 | 0.51 | 110.43 | .613 |
4 | RC > LC IFG | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.36 | 81.60 | .176 |
4 | RC > LC IFG | gender | fixed | -0.20 [-0.43, 0.02] | 0.11 | -1.78 | 83.51 | .079 |
4 | RC > LC IFG | condition | fixed | 0.10 [-0.06, 0.27] | 0.08 | 1.30 | 81.70 | .198 |
4 | RC > LC IFG | time x neural predictor | fixed | -0.01 [-0.04, 0.03] | 0.02 | -0.34 | 122.55 | .736 |
4 | RC > LC IFG | participant | random | 0.34 (variance) | – | – | – | – |
4 | RC > LC IFG | residual | random | 0.22 (variance) | – | – | – | – |
5 | RC > LC dACC | intercept | fixed | 2.79 [2.56, 3.01] | 0.11 | 24.77 | 83.94 | < .001 |
5 | RC > LC dACC | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.14 | 122.84 | .034 |
5 | RC > LC dACC | neural predictor | fixed | 0.13 [-0.09, 0.35] | 0.11 | 1.19 | 93.47 | .238 |
5 | RC > LC dACC | BMI | fixed | 0.00 [-0.01, 0.02] | 0.01 | 0.48 | 111.27 | .631 |
5 | RC > LC dACC | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.35 | 81.79 | .180 |
5 | RC > LC dACC | gender | fixed | -0.21 [-0.43, 0.01] | 0.11 | -1.86 | 83.09 | .066 |
5 | RC > LC dACC | condition | fixed | 0.11 [-0.05, 0.27] | 0.08 | 1.34 | 81.78 | .183 |
5 | RC > LC dACC | time x neural predictor | fixed | -0.03 [-0.06, 0.00] | 0.02 | -1.74 | 120.33 | .085 |
5 | RC > LC dACC | participant | random | 0.34 (variance) | – | – | – | – |
5 | RC > LC dACC | residual | random | 0.22 (variance) | – | – | – | – |
6 | RC > LC vmPFC | intercept | fixed | 2.82 [2.59, 3.04] | 0.11 | 25.21 | 83.84 | < .001 |
6 | RC > LC vmPFC | time | fixed | -0.02 [-0.03, -0.00] | 0.01 | -2.18 | 122.73 | .032 |
6 | RC > LC vmPFC | neural predictor | fixed | -0.04 [-0.19, 0.11] | 0.07 | -0.56 | 91.92 | .574 |
6 | RC > LC vmPFC | BMI | fixed | 0.01 [-0.01, 0.02] | 0.01 | 0.59 | 110.79 | .555 |
6 | RC > LC vmPFC | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.32 | 81.49 | .189 |
6 | RC > LC vmPFC | gender | fixed | -0.24 [-0.47, -0.02] | 0.11 | -2.17 | 82.68 | .033 |
6 | RC > LC vmPFC | condition | fixed | 0.11 [-0.05, 0.27] | 0.08 | 1.35 | 81.68 | .182 |
6 | RC > LC vmPFC | time x neural predictor | fixed | -0.01 [-0.04, 0.01] | 0.01 | -1.24 | 120.71 | .217 |
6 | RC > LC vmPFC | participant | random | 0.34 (variance) | – | – | – | – |
6 | RC > LC vmPFC | residual | random | 0.22 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | intercept | fixed | 2.81 [2.59, 3.03] | 0.11 | 25.56 | 84.10 | < .001 |
7 | RC > LC parahippocampal gyrus | time | fixed | -0.01 [-0.03, 0.00] | 0.01 | -1.86 | 123.01 | .065 |
7 | RC > LC parahippocampal gyrus | neural predictor | fixed | 0.05 [-0.08, 0.17] | 0.06 | 0.71 | 92.89 | .480 |
7 | RC > LC parahippocampal gyrus | BMI | fixed | 0.01 [-0.01, 0.02] | 0.01 | 0.63 | 110.27 | .528 |
7 | RC > LC parahippocampal gyrus | age | fixed | -0.01 [-0.04, 0.01] | 0.01 | -1.23 | 81.72 | .222 |
7 | RC > LC parahippocampal gyrus | gender | fixed | -0.22 [-0.44, -0.01] | 0.11 | -2.05 | 82.61 | .043 |
7 | RC > LC parahippocampal gyrus | condition | fixed | 0.09 [-0.07, 0.25] | 0.08 | 1.12 | 82.31 | .267 |
7 | RC > LC parahippocampal gyrus | time x neural predictor | fixed | 0.02 [-0.00, 0.04] | 0.01 | 1.63 | 122.22 | .105 |
7 | RC > LC parahippocampal gyrus | participant | random | 0.34 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | residual | random | 0.22 (variance) | – | – | – | – |
8 | RC > LC l IFG | intercept | fixed | 2.75 [2.52, 2.97] | 0.11 | 24.33 | 85.43 | < .001 |
8 | RC > LC l IFG | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.01 | 123.45 | .047 |
8 | RC > LC l IFG | neural predictor | fixed | 0.07 [-0.00, 0.13] | 0.03 | 1.92 | 95.44 | .057 |
8 | RC > LC l IFG | BMI | fixed | 0.00 [-0.02, 0.02] | 0.01 | 0.28 | 110.43 | .778 |
8 | RC > LC l IFG | age | fixed | -0.01 [-0.04, 0.01] | 0.01 | -1.17 | 81.94 | .245 |
8 | RC > LC l IFG | gender | fixed | -0.18 [-0.40, 0.04] | 0.11 | -1.61 | 84.13 | .110 |
8 | RC > LC l IFG | condition | fixed | 0.14 [-0.03, 0.30] | 0.08 | 1.68 | 82.21 | .097 |
8 | RC > LC l IFG | time x neural predictor | fixed | -0.00 [-0.01, 0.01] | 0.01 | -0.35 | 123.48 | .728 |
8 | RC > LC l IFG | participant | random | 0.33 (variance) | – | – | – | – |
8 | RC > LC l IFG | residual | random | 0.22 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | intercept | fixed | 2.80 [2.58, 3.02] | 0.11 | 25.40 | 83.97 | < .001 |
9 | RC > LC l supramarginal gyrus | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.01 | 123.18 | .046 |
9 | RC > LC l supramarginal gyrus | neural predictor | fixed | 0.07 [-0.05, 0.20] | 0.06 | 1.18 | 92.70 | .243 |
9 | RC > LC l supramarginal gyrus | BMI | fixed | 0.00 [-0.01, 0.02] | 0.01 | 0.46 | 111.06 | .648 |
9 | RC > LC l supramarginal gyrus | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.49 | 81.38 | .141 |
9 | RC > LC l supramarginal gyrus | gender | fixed | -0.22 [-0.44, -0.00] | 0.11 | -2.01 | 82.70 | .048 |
9 | RC > LC l supramarginal gyrus | condition | fixed | 0.10 [-0.06, 0.26] | 0.08 | 1.22 | 81.81 | .225 |
9 | RC > LC l supramarginal gyrus | time x neural predictor | fixed | -0.01 [-0.02, 0.01] | 0.01 | -0.53 | 122.09 | .599 |
9 | RC > LC l supramarginal gyrus | participant | random | 0.34 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | residual | random | 0.22 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | intercept | fixed | 2.80 [2.58, 3.02] | 0.11 | 25.73 | 84.11 | < .001 |
10 | RC > LC l cerebellum | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.04 | 123.45 | .044 |
10 | RC > LC l cerebellum | neural predictor | fixed | -0.11 [-0.24, 0.02] | 0.07 | -1.67 | 91.25 | .098 |
10 | RC > LC l cerebellum | BMI | fixed | 0.01 [-0.01, 0.02] | 0.01 | 0.61 | 110.05 | .545 |
10 | RC > LC l cerebellum | age | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.57 | 81.90 | .121 |
10 | RC > LC l cerebellum | gender | fixed | -0.23 [-0.45, -0.02] | 0.11 | -2.15 | 82.79 | .035 |
10 | RC > LC l cerebellum | condition | fixed | 0.12 [-0.04, 0.28] | 0.08 | 1.51 | 81.63 | .134 |
10 | RC > LC l cerebellum | time x neural predictor | fixed | -0.01 [-0.03, 0.02] | 0.01 | -0.69 | 123.27 | .490 |
10 | RC > LC l cerebellum | participant | random | 0.33 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | residual | random | 0.22 (variance) | – | – | – | – |
11 | RC > LC midbrain | intercept | fixed | 2.80 [2.58, 3.01] | 0.11 | 25.29 | 83.80 | < .001 |
11 | RC > LC midbrain | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.04 | 122.96 | .044 |
11 | RC > LC midbrain | neural predictor | fixed | -0.07 [-0.20, 0.06] | 0.07 | -1.02 | 91.42 | .311 |
11 | RC > LC midbrain | BMI | fixed | 0.00 [-0.01, 0.02] | 0.01 | 0.52 | 110.14 | .602 |
11 | RC > LC midbrain | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.45 | 81.65 | .150 |
11 | RC > LC midbrain | gender | fixed | -0.21 [-0.43, 0.01] | 0.11 | -1.90 | 82.64 | .061 |
11 | RC > LC midbrain | condition | fixed | 0.10 [-0.06, 0.26] | 0.08 | 1.21 | 81.68 | .230 |
11 | RC > LC midbrain | time x neural predictor | fixed | -0.00 [-0.02, 0.02] | 0.01 | -0.41 | 120.60 | .680 |
11 | RC > LC midbrain | participant | random | 0.34 (variance) | – | – | – | – |
11 | RC > LC midbrain | residual | random | 0.22 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | intercept | fixed | 2.81 [2.58, 3.03] | 0.11 | 25.29 | 83.85 | < .001 |
12 | RC > LC r supramarginal gyrus | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -1.99 | 122.89 | .049 |
12 | RC > LC r supramarginal gyrus | neural predictor | fixed | -0.01 [-0.14, 0.12] | 0.06 | -0.10 | 91.69 | .919 |
12 | RC > LC r supramarginal gyrus | BMI | fixed | 0.01 [-0.01, 0.03] | 0.01 | 0.66 | 110.91 | .509 |
12 | RC > LC r supramarginal gyrus | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.43 | 81.79 | .158 |
12 | RC > LC r supramarginal gyrus | gender | fixed | -0.23 [-0.45, -0.01] | 0.11 | -2.05 | 82.49 | .044 |
12 | RC > LC r supramarginal gyrus | condition | fixed | 0.10 [-0.06, 0.26] | 0.08 | 1.26 | 81.76 | .212 |
12 | RC > LC r supramarginal gyrus | time x neural predictor | fixed | -0.01 [-0.03, 0.01] | 0.01 | -1.00 | 123.02 | .320 |
12 | RC > LC r supramarginal gyrus | participant | random | 0.34 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | residual | random | 0.22 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | intercept | fixed | 2.79 [2.57, 3.01] | 0.11 | 25.02 | 84.18 | < .001 |
13 | RC > LC r posterior MFG | time | fixed | -0.01 [-0.03, 0.00] | 0.01 | -1.94 | 123.14 | .054 |
13 | RC > LC r posterior MFG | neural predictor | fixed | 0.09 [-0.06, 0.24] | 0.07 | 1.22 | 93.64 | .225 |
13 | RC > LC r posterior MFG | BMI | fixed | 0.00 [-0.01, 0.02] | 0.01 | 0.50 | 110.58 | .621 |
13 | RC > LC r posterior MFG | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.35 | 81.63 | .181 |
13 | RC > LC r posterior MFG | gender | fixed | -0.21 [-0.43, 0.02] | 0.11 | -1.83 | 83.02 | .070 |
13 | RC > LC r posterior MFG | condition | fixed | 0.10 [-0.07, 0.26] | 0.08 | 1.18 | 81.70 | .241 |
13 | RC > LC r posterior MFG | time x neural predictor | fixed | -0.01 [-0.04, 0.01] | 0.01 | -1.15 | 124.60 | .254 |
13 | RC > LC r posterior MFG | participant | random | 0.34 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | residual | random | 0.22 (variance) | – | – | – | – |
14 | average anatomical ROIs | intercept | fixed | 2.78 [2.56, 3.01] | 0.11 | 24.64 | 84.22 | < .001 |
14 | average anatomical ROIs | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.06 | 122.99 | .042 |
14 | average anatomical ROIs | neural predictor | fixed | 0.12 [-0.11, 0.35] | 0.12 | 1.05 | 93.62 | .295 |
14 | average anatomical ROIs | BMI | fixed | 0.00 [-0.01, 0.02] | 0.01 | 0.50 | 110.61 | .620 |
14 | average anatomical ROIs | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.36 | 81.69 | .177 |
14 | average anatomical ROIs | gender | fixed | -0.20 [-0.43, 0.02] | 0.11 | -1.78 | 83.40 | .078 |
14 | average anatomical ROIs | condition | fixed | 0.10 [-0.06, 0.26] | 0.08 | 1.29 | 81.84 | .200 |
14 | average anatomical ROIs | time x neural predictor | fixed | -0.01 [-0.05, 0.02] | 0.02 | -0.83 | 121.43 | .406 |
14 | average anatomical ROIs | participant | random | 0.34 (variance) | – | – | – | – |
14 | average anatomical ROIs | residual | random | 0.22 (variance) | – | – | – | – |
15 | average peak ROIs | intercept | fixed | 2.79 [2.57, 3.02] | 0.11 | 25.04 | 84.02 | < .001 |
15 | average peak ROIs | time | fixed | -0.01 [-0.03, -0.00] | 0.01 | -2.02 | 123.02 | .046 |
15 | average peak ROIs | neural predictor | fixed | 0.07 [-0.11, 0.26] | 0.09 | 0.79 | 92.59 | .433 |
15 | average peak ROIs | BMI | fixed | 0.01 [-0.01, 0.02] | 0.01 | 0.54 | 111.03 | .590 |
15 | average peak ROIs | age | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.31 | 81.89 | .192 |
15 | average peak ROIs | gender | fixed | -0.22 [-0.44, 0.01] | 0.11 | -1.94 | 82.81 | .056 |
15 | average peak ROIs | condition | fixed | 0.10 [-0.06, 0.26] | 0.08 | 1.29 | 81.71 | .201 |
15 | average peak ROIs | time x neural predictor | fixed | -0.01 [-0.04, 0.02] | 0.01 | -0.52 | 122.23 | .606 |
15 | average peak ROIs | participant | random | 0.34 (variance) | – | – | – | – |
15 | average peak ROIs | residual | random | 0.22 (variance) | – | – | – | – |
model | neural predictor | term | effect | b [95% CI] | SE | t | df | p |
---|---|---|---|---|---|---|---|---|
1 | LC > LNC vmPFC | intercept | fixed | 2.55 [2.28, 2.81] | 0.13 | 19.34 | 82.69 | < .001 |
1 | LC > LNC vmPFC | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.35 | 119.01 | .001 |
1 | LC > LNC vmPFC | neural predictor | fixed | -0.04 [-0.23, 0.15] | 0.09 | -0.46 | 87.10 | .649 |
1 | LC > LNC vmPFC | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.76 | 130.34 | .447 |
1 | LC > LNC vmPFC | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 1.04 | 81.40 | .303 |
1 | LC > LNC vmPFC | gender | fixed | 0.07 [-0.20, 0.33] | 0.13 | 0.50 | 82.06 | .621 |
1 | LC > LNC vmPFC | condition | fixed | 0.09 [-0.10, 0.28] | 0.10 | 0.94 | 81.47 | .351 |
1 | LC > LNC vmPFC | time x neural predictor | fixed | -0.02 [-0.05, 0.00] | 0.01 | -1.70 | 120.48 | .091 |
1 | LC > LNC vmPFC | participant | random | 0.42 (variance) | – | – | – | – |
1 | LC > LNC vmPFC | residual | random | 0.19 (variance) | – | – | – | – |
2 | LC > LNC striatum | intercept | fixed | 2.54 [2.27, 2.80] | 0.13 | 19.23 | 82.60 | < .001 |
2 | LC > LNC striatum | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.44 | 118.94 | < .001 |
2 | LC > LNC striatum | neural predictor | fixed | -0.09 [-0.26, 0.09] | 0.09 | -1.01 | 86.21 | .317 |
2 | LC > LNC striatum | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.65 | 130.96 | .518 |
2 | LC > LNC striatum | age | fixed | 0.02 [-0.01, 0.04] | 0.01 | 1.18 | 81.21 | .242 |
2 | LC > LNC striatum | gender | fixed | 0.07 [-0.19, 0.33] | 0.13 | 0.54 | 82.13 | .593 |
2 | LC > LNC striatum | condition | fixed | 0.10 [-0.09, 0.29] | 0.10 | 1.04 | 81.21 | .303 |
2 | LC > LNC striatum | time x neural predictor | fixed | -0.00 [-0.02, 0.02] | 0.01 | -0.11 | 118.68 | .916 |
2 | LC > LNC striatum | participant | random | 0.42 (variance) | – | – | – | – |
2 | LC > LNC striatum | residual | random | 0.19 (variance) | – | – | – | – |
3 | RC > LC dlPFC | intercept | fixed | 2.51 [2.25, 2.77] | 0.13 | 19.06 | 82.71 | < .001 |
3 | RC > LC dlPFC | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.39 | 118.86 | < .001 |
3 | RC > LC dlPFC | neural predictor | fixed | 0.20 [-0.04, 0.45] | 0.12 | 1.63 | 88.25 | .107 |
3 | RC > LC dlPFC | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.82 | 130.09 | .415 |
3 | RC > LC dlPFC | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 1.05 | 81.24 | .297 |
3 | RC > LC dlPFC | gender | fixed | 0.11 [-0.15, 0.38] | 0.13 | 0.84 | 82.57 | .404 |
3 | RC > LC dlPFC | condition | fixed | 0.09 [-0.10, 0.28] | 0.09 | 0.93 | 81.15 | .353 |
3 | RC > LC dlPFC | time x neural predictor | fixed | 0.00 [-0.02, 0.03] | 0.01 | 0.30 | 118.41 | .767 |
3 | RC > LC dlPFC | participant | random | 0.42 (variance) | – | – | – | – |
3 | RC > LC dlPFC | residual | random | 0.19 (variance) | – | – | – | – |
4 | RC > LC IFG | intercept | fixed | 2.50 [2.24, 2.77] | 0.13 | 18.79 | 82.84 | < .001 |
4 | RC > LC IFG | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.45 | 118.91 | < .001 |
4 | RC > LC IFG | neural predictor | fixed | 0.21 [-0.05, 0.46] | 0.13 | 1.63 | 87.80 | .107 |
4 | RC > LC IFG | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.84 | 130.68 | .402 |
4 | RC > LC IFG | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 1.05 | 81.35 | .297 |
4 | RC > LC IFG | gender | fixed | 0.11 [-0.16, 0.38] | 0.13 | 0.82 | 82.76 | .415 |
4 | RC > LC IFG | condition | fixed | 0.10 [-0.09, 0.29] | 0.10 | 1.08 | 81.12 | .285 |
4 | RC > LC IFG | time x neural predictor | fixed | -0.00 [-0.03, 0.03] | 0.02 | -0.26 | 118.65 | .797 |
4 | RC > LC IFG | participant | random | 0.42 (variance) | – | – | – | – |
4 | RC > LC IFG | residual | random | 0.19 (variance) | – | – | – | – |
5 | RC > LC dACC | intercept | fixed | 2.50 [2.24, 2.77] | 0.13 | 19.03 | 82.65 | < .001 |
5 | RC > LC dACC | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.48 | 119.03 | < .001 |
5 | RC > LC dACC | neural predictor | fixed | 0.25 [-0.00, 0.50] | 0.13 | 1.97 | 87.97 | .052 |
5 | RC > LC dACC | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.82 | 130.24 | .415 |
5 | RC > LC dACC | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 0.99 | 81.48 | .323 |
5 | RC > LC dACC | gender | fixed | 0.11 [-0.16, 0.37] | 0.13 | 0.81 | 82.47 | .423 |
5 | RC > LC dACC | condition | fixed | 0.11 [-0.08, 0.29] | 0.09 | 1.11 | 81.20 | .270 |
5 | RC > LC dACC | time x neural predictor | fixed | -0.01 [-0.04, 0.02] | 0.01 | -0.65 | 117.55 | .516 |
5 | RC > LC dACC | participant | random | 0.42 (variance) | – | – | – | – |
5 | RC > LC dACC | residual | random | 0.19 (variance) | – | – | – | – |
6 | RC > LC vmPFC | intercept | fixed | 2.53 [2.27, 2.80] | 0.13 | 19.04 | 82.63 | < .001 |
6 | RC > LC vmPFC | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.43 | 118.90 | < .001 |
6 | RC > LC vmPFC | neural predictor | fixed | 0.08 [-0.09, 0.25] | 0.09 | 0.92 | 86.75 | .360 |
6 | RC > LC vmPFC | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.61 | 131.46 | .544 |
6 | RC > LC vmPFC | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 0.97 | 81.46 | .336 |
6 | RC > LC vmPFC | gender | fixed | 0.08 [-0.19, 0.35] | 0.13 | 0.60 | 82.25 | .550 |
6 | RC > LC vmPFC | condition | fixed | 0.10 [-0.10, 0.29] | 0.10 | 0.99 | 81.29 | .327 |
6 | RC > LC vmPFC | time x neural predictor | fixed | -0.00 [-0.02, 0.02] | 0.01 | -0.07 | 117.69 | .947 |
6 | RC > LC vmPFC | participant | random | 0.42 (variance) | – | – | – | – |
6 | RC > LC vmPFC | residual | random | 0.19 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | intercept | fixed | 2.55 [2.28, 2.81] | 0.13 | 19.25 | 82.68 | < .001 |
7 | RC > LC parahippocampal gyrus | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.43 | 118.87 | < .001 |
7 | RC > LC parahippocampal gyrus | neural predictor | fixed | -0.02 [-0.17, 0.13] | 0.08 | -0.26 | 87.10 | .798 |
7 | RC > LC parahippocampal gyrus | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.60 | 131.28 | .552 |
7 | RC > LC parahippocampal gyrus | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 0.98 | 81.51 | .328 |
7 | RC > LC parahippocampal gyrus | gender | fixed | 0.06 [-0.21, 0.32] | 0.13 | 0.43 | 82.14 | .667 |
7 | RC > LC parahippocampal gyrus | condition | fixed | 0.10 [-0.09, 0.29] | 0.10 | 1.02 | 81.58 | .309 |
7 | RC > LC parahippocampal gyrus | time x neural predictor | fixed | 0.00 [-0.01, 0.02] | 0.01 | 0.38 | 118.73 | .701 |
7 | RC > LC parahippocampal gyrus | participant | random | 0.43 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | residual | random | 0.19 (variance) | – | – | – | – |
8 | RC > LC l IFG | intercept | fixed | 2.54 [2.27, 2.82] | 0.14 | 18.55 | 83.37 | < .001 |
8 | RC > LC l IFG | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.52 | 118.81 | < .001 |
8 | RC > LC l IFG | neural predictor | fixed | 0.02 [-0.06, 0.10] | 0.04 | 0.40 | 88.91 | .693 |
8 | RC > LC l IFG | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.64 | 133.94 | .524 |
8 | RC > LC l IFG | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 1.02 | 81.63 | .309 |
8 | RC > LC l IFG | gender | fixed | 0.06 [-0.21, 0.33] | 0.14 | 0.44 | 83.05 | .662 |
8 | RC > LC l IFG | condition | fixed | 0.10 [-0.09, 0.30] | 0.10 | 1.06 | 81.33 | .294 |
8 | RC > LC l IFG | time x neural predictor | fixed | -0.01 [-0.01, 0.00] | 0.00 | -1.08 | 118.81 | .282 |
8 | RC > LC l IFG | participant | random | 0.43 (variance) | – | – | – | – |
8 | RC > LC l IFG | residual | random | 0.19 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | intercept | fixed | 2.55 [2.29, 2.81] | 0.13 | 19.31 | 82.67 | < .001 |
9 | RC > LC l supramarginal gyrus | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.47 | 119.06 | < .001 |
9 | RC > LC l supramarginal gyrus | neural predictor | fixed | -0.06 [-0.20, 0.09] | 0.07 | -0.79 | 87.64 | .431 |
9 | RC > LC l supramarginal gyrus | BMI | fixed | -0.01 [-0.03, 0.02] | 0.01 | -0.48 | 132.54 | .631 |
9 | RC > LC l supramarginal gyrus | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 1.08 | 81.30 | .284 |
9 | RC > LC l supramarginal gyrus | gender | fixed | 0.05 [-0.21, 0.32] | 0.13 | 0.42 | 82.29 | .679 |
9 | RC > LC l supramarginal gyrus | condition | fixed | 0.10 [-0.09, 0.29] | 0.10 | 1.06 | 81.36 | .290 |
9 | RC > LC l supramarginal gyrus | time x neural predictor | fixed | 0.00 [-0.02, 0.02] | 0.01 | 0.05 | 118.96 | .963 |
9 | RC > LC l supramarginal gyrus | participant | random | 0.43 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | residual | random | 0.19 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | intercept | fixed | 2.55 [2.28, 2.81] | 0.13 | 19.25 | 82.61 | < .001 |
10 | RC > LC l cerebellum | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.52 | 118.91 | < .001 |
10 | RC > LC l cerebellum | neural predictor | fixed | -0.00 [-0.16, 0.16] | 0.08 | -0.03 | 85.85 | .980 |
10 | RC > LC l cerebellum | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.60 | 132.64 | .547 |
10 | RC > LC l cerebellum | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 0.96 | 81.59 | .341 |
10 | RC > LC l cerebellum | gender | fixed | 0.06 [-0.20, 0.32] | 0.13 | 0.43 | 82.21 | .666 |
10 | RC > LC l cerebellum | condition | fixed | 0.10 [-0.09, 0.30] | 0.10 | 1.05 | 81.14 | .299 |
10 | RC > LC l cerebellum | time x neural predictor | fixed | -0.01 [-0.03, 0.01] | 0.01 | -1.41 | 118.61 | .162 |
10 | RC > LC l cerebellum | participant | random | 0.43 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | residual | random | 0.19 (variance) | – | – | – | – |
11 | RC > LC midbrain | intercept | fixed | 2.55 [2.29, 2.82] | 0.13 | 19.27 | 82.73 | < .001 |
11 | RC > LC midbrain | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.49 | 119.02 | < .001 |
11 | RC > LC midbrain | neural predictor | fixed | 0.05 [-0.10, 0.20] | 0.08 | 0.64 | 86.46 | .526 |
11 | RC > LC midbrain | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.61 | 131.89 | .545 |
11 | RC > LC midbrain | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 1.02 | 81.66 | .310 |
11 | RC > LC midbrain | gender | fixed | 0.05 [-0.21, 0.31] | 0.13 | 0.37 | 82.41 | .710 |
11 | RC > LC midbrain | condition | fixed | 0.10 [-0.09, 0.29] | 0.10 | 1.06 | 81.41 | .292 |
11 | RC > LC midbrain | time x neural predictor | fixed | -0.01 [-0.02, 0.01] | 0.01 | -0.67 | 117.83 | .504 |
11 | RC > LC midbrain | participant | random | 0.43 (variance) | – | – | – | – |
11 | RC > LC midbrain | residual | random | 0.19 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | intercept | fixed | 2.55 [2.29, 2.81] | 0.13 | 19.45 | 82.62 | < .001 |
12 | RC > LC r supramarginal gyrus | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.47 | 118.94 | < .001 |
12 | RC > LC r supramarginal gyrus | neural predictor | fixed | -0.07 [-0.23, 0.08] | 0.08 | -0.98 | 86.51 | .328 |
12 | RC > LC r supramarginal gyrus | BMI | fixed | -0.01 [-0.03, 0.02] | 0.01 | -0.55 | 131.85 | .585 |
12 | RC > LC r supramarginal gyrus | age | fixed | 0.01 [-0.02, 0.04] | 0.01 | 0.89 | 81.64 | .377 |
12 | RC > LC r supramarginal gyrus | gender | fixed | 0.05 [-0.21, 0.31] | 0.13 | 0.37 | 82.14 | .712 |
12 | RC > LC r supramarginal gyrus | condition | fixed | 0.10 [-0.09, 0.29] | 0.10 | 1.08 | 81.31 | .283 |
12 | RC > LC r supramarginal gyrus | time x neural predictor | fixed | -0.01 [-0.03, 0.01] | 0.01 | -1.25 | 118.86 | .213 |
12 | RC > LC r supramarginal gyrus | participant | random | 0.42 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | residual | random | 0.19 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | intercept | fixed | 2.55 [2.29, 2.82] | 0.13 | 19.10 | 82.74 | < .001 |
13 | RC > LC r posterior MFG | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.39 | 118.95 | < .001 |
13 | RC > LC r posterior MFG | neural predictor | fixed | 0.02 [-0.15, 0.19] | 0.09 | 0.24 | 87.52 | .809 |
13 | RC > LC r posterior MFG | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.71 | 133.07 | .477 |
13 | RC > LC r posterior MFG | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 1.01 | 81.54 | .315 |
13 | RC > LC r posterior MFG | gender | fixed | 0.05 [-0.22, 0.32] | 0.13 | 0.38 | 82.44 | .705 |
13 | RC > LC r posterior MFG | condition | fixed | 0.10 [-0.09, 0.29] | 0.10 | 1.03 | 81.30 | .306 |
13 | RC > LC r posterior MFG | time x neural predictor | fixed | -0.02 [-0.04, 0.00] | 0.01 | -1.82 | 119.79 | .072 |
13 | RC > LC r posterior MFG | participant | random | 0.43 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | residual | random | 0.19 (variance) | – | – | – | – |
14 | average anatomical ROIs | intercept | fixed | 2.50 [2.24, 2.76] | 0.13 | 18.92 | 82.74 | < .001 |
14 | average anatomical ROIs | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.44 | 118.95 | < .001 |
14 | average anatomical ROIs | neural predictor | fixed | 0.25 [-0.02, 0.51] | 0.13 | 1.86 | 88.02 | .067 |
14 | average anatomical ROIs | BMI | fixed | -0.01 [-0.03, 0.01] | 0.01 | -0.85 | 130.05 | .395 |
14 | average anatomical ROIs | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 1.04 | 81.34 | .304 |
14 | average anatomical ROIs | gender | fixed | 0.12 [-0.15, 0.38] | 0.13 | 0.87 | 82.62 | .386 |
14 | average anatomical ROIs | condition | fixed | 0.10 [-0.09, 0.29] | 0.09 | 1.04 | 81.16 | .301 |
14 | average anatomical ROIs | time x neural predictor | fixed | -0.00 [-0.03, 0.03] | 0.02 | -0.22 | 118.05 | .823 |
14 | average anatomical ROIs | participant | random | 0.42 (variance) | – | – | – | – |
14 | average anatomical ROIs | residual | random | 0.19 (variance) | – | – | – | – |
15 | average peak ROIs | intercept | fixed | 2.55 [2.29, 2.82] | 0.13 | 19.15 | 82.69 | < .001 |
15 | average peak ROIs | time | fixed | -0.02 [-0.03, -0.01] | 0.01 | -3.54 | 118.87 | < .001 |
15 | average peak ROIs | neural predictor | fixed | -0.01 [-0.23, 0.21] | 0.11 | -0.10 | 87.17 | .919 |
15 | average peak ROIs | BMI | fixed | -0.01 [-0.03, 0.02] | 0.01 | -0.57 | 133.32 | .569 |
15 | average peak ROIs | age | fixed | 0.01 [-0.01, 0.04] | 0.01 | 0.95 | 81.71 | .344 |
15 | average peak ROIs | gender | fixed | 0.05 [-0.21, 0.31] | 0.13 | 0.37 | 82.36 | .709 |
15 | average peak ROIs | condition | fixed | 0.10 [-0.09, 0.29] | 0.10 | 1.03 | 81.27 | .308 |
15 | average peak ROIs | time x neural predictor | fixed | -0.02 [-0.04, 0.01] | 0.01 | -1.26 | 118.36 | .211 |
15 | average peak ROIs | participant | random | 0.43 (variance) | – | – | – | – |
15 | average peak ROIs | residual | random | 0.19 (variance) | – | – | – | – |
model | neural predictor | term | effect | b [95% CI] | SE | t | df | p |
---|---|---|---|---|---|---|---|---|
1 | LC > LNC vmPFC | intercept | fixed | 50.60 [45.07, 56.12] | 2.78 | 18.21 | 82.99 | < .001 |
1 | LC > LNC vmPFC | time | fixed | 0.48 [-0.15, 1.11] | 0.32 | 1.51 | 146.12 | .132 |
1 | LC > LNC vmPFC | neural predictor | fixed | -3.10 [-7.45, 1.26] | 2.20 | -1.41 | 126.91 | .162 |
1 | LC > LNC vmPFC | BMI | fixed | 0.24 [-0.26, 0.73] | 0.25 | 0.95 | 88.58 | .343 |
1 | LC > LNC vmPFC | age | fixed | -0.18 [-0.74, 0.37] | 0.28 | -0.66 | 75.74 | .508 |
1 | LC > LNC vmPFC | gender | fixed | 2.26 [-3.18, 7.70] | 2.73 | 0.83 | 76.87 | .410 |
1 | LC > LNC vmPFC | condition | fixed | -1.42 [-5.38, 2.55] | 1.99 | -0.71 | 79.52 | .479 |
1 | LC > LNC vmPFC | time x neural predictor | fixed | 0.58 [-0.71, 1.87] | 0.65 | 0.89 | 151.24 | .374 |
1 | LC > LNC vmPFC | participant | random | 6.00 (variance) | – | – | – | – |
1 | LC > LNC vmPFC | residual | random | 10.71 (variance) | – | – | – | – |
2 | LC > LNC striatum | intercept | fixed | 50.83 [45.23, 56.42] | 2.81 | 18.08 | 83.25 | < .001 |
2 | LC > LNC striatum | time | fixed | 0.49 [-0.13, 1.12] | 0.32 | 1.56 | 145.59 | .122 |
2 | LC > LNC striatum | neural predictor | fixed | -1.04 [-5.06, 2.99] | 2.03 | -0.51 | 123.37 | .611 |
2 | LC > LNC striatum | BMI | fixed | 0.21 [-0.28, 0.71] | 0.25 | 0.85 | 88.81 | .399 |
2 | LC > LNC striatum | age | fixed | -0.18 [-0.75, 0.39] | 0.29 | -0.62 | 75.86 | .537 |
2 | LC > LNC striatum | gender | fixed | 1.98 [-3.52, 7.48] | 2.76 | 0.72 | 77.53 | .476 |
2 | LC > LNC striatum | condition | fixed | -1.36 [-5.35, 2.64] | 2.01 | -0.68 | 78.88 | .500 |
2 | LC > LNC striatum | time x neural predictor | fixed | 0.22 [-0.88, 1.32] | 0.56 | 0.40 | 147.05 | .688 |
2 | LC > LNC striatum | participant | random | 6.15 (variance) | – | – | – | – |
2 | LC > LNC striatum | residual | random | 10.71 (variance) | – | – | – | – |
3 | RC > LC dlPFC | intercept | fixed | 50.60 [44.96, 56.24] | 2.84 | 17.84 | 83.26 | < .001 |
3 | RC > LC dlPFC | time | fixed | 0.50 [-0.12, 1.12] | 0.31 | 1.60 | 145.29 | .111 |
3 | RC > LC dlPFC | neural predictor | fixed | 3.91 [-1.91, 9.72] | 2.94 | 1.33 | 126.09 | .186 |
3 | RC > LC dlPFC | BMI | fixed | 0.20 [-0.30, 0.69] | 0.25 | 0.79 | 88.71 | .433 |
3 | RC > LC dlPFC | age | fixed | -0.18 [-0.74, 0.38] | 0.28 | -0.64 | 75.93 | .521 |
3 | RC > LC dlPFC | gender | fixed | 2.27 [-3.35, 7.89] | 2.82 | 0.81 | 77.92 | .423 |
3 | RC > LC dlPFC | condition | fixed | -1.42 [-5.40, 2.57] | 2.00 | -0.71 | 78.68 | .481 |
3 | RC > LC dlPFC | time x neural predictor | fixed | -1.15 [-2.63, 0.32] | 0.75 | -1.54 | 140.99 | .125 |
3 | RC > LC dlPFC | participant | random | 6.15 (variance) | – | – | – | – |
3 | RC > LC dlPFC | residual | random | 10.63 (variance) | – | – | – | – |
4 | RC > LC IFG | intercept | fixed | 50.42 [44.75, 56.08] | 2.85 | 17.70 | 83.47 | < .001 |
4 | RC > LC IFG | time | fixed | 0.49 [-0.12, 1.11] | 0.31 | 1.58 | 145.87 | .116 |
4 | RC > LC IFG | neural predictor | fixed | 4.46 [-1.39, 10.30] | 2.95 | 1.51 | 122.91 | .134 |
4 | RC > LC IFG | BMI | fixed | 0.18 [-0.31, 0.68] | 0.25 | 0.74 | 89.08 | .463 |
4 | RC > LC IFG | age | fixed | -0.18 [-0.74, 0.38] | 0.28 | -0.64 | 76.64 | .525 |
4 | RC > LC IFG | gender | fixed | 2.44 [-3.19, 8.06] | 2.83 | 0.86 | 78.56 | .391 |
4 | RC > LC IFG | condition | fixed | -1.32 [-5.28, 2.65] | 1.99 | -0.66 | 79.05 | .511 |
4 | RC > LC IFG | time x neural predictor | fixed | -1.15 [-2.66, 0.36] | 0.76 | -1.51 | 142.32 | .134 |
4 | RC > LC IFG | participant | random | 6.11 (variance) | – | – | – | – |
4 | RC > LC IFG | residual | random | 10.64 (variance) | – | – | – | – |
5 | RC > LC dACC | intercept | fixed | 50.56 [44.93, 56.19] | 2.83 | 17.86 | 82.72 | < .001 |
5 | RC > LC dACC | time | fixed | 0.50 [-0.12, 1.12] | 0.31 | 1.59 | 145.91 | .115 |
5 | RC > LC dACC | neural predictor | fixed | 3.76 [-2.13, 9.66] | 2.98 | 1.26 | 126.17 | .209 |
5 | RC > LC dACC | BMI | fixed | 0.19 [-0.30, 0.69] | 0.25 | 0.77 | 89.08 | .441 |
5 | RC > LC dACC | age | fixed | -0.19 [-0.75, 0.37] | 0.28 | -0.67 | 77.04 | .503 |
5 | RC > LC dACC | gender | fixed | 2.26 [-3.30, 7.83] | 2.80 | 0.81 | 77.46 | .421 |
5 | RC > LC dACC | condition | fixed | -1.29 [-5.28, 2.69] | 2.00 | -0.65 | 79.22 | .520 |
5 | RC > LC dACC | time x neural predictor | fixed | -0.92 [-2.35, 0.51] | 0.72 | -1.27 | 136.18 | .206 |
5 | RC > LC dACC | participant | random | 6.16 (variance) | – | – | – | – |
5 | RC > LC dACC | residual | random | 10.65 (variance) | – | – | – | – |
6 | RC > LC vmPFC | intercept | fixed | 50.68 [45.11, 56.25] | 2.80 | 18.09 | 83.10 | < .001 |
6 | RC > LC vmPFC | time | fixed | 0.48 [-0.13, 1.10] | 0.31 | 1.55 | 145.57 | .124 |
6 | RC > LC vmPFC | neural predictor | fixed | 2.77 [-1.31, 6.85] | 2.06 | 1.34 | 132.81 | .182 |
6 | RC > LC vmPFC | BMI | fixed | 0.22 [-0.27, 0.71] | 0.25 | 0.90 | 88.85 | .373 |
6 | RC > LC vmPFC | age | fixed | -0.19 [-0.75, 0.36] | 0.28 | -0.69 | 76.34 | .489 |
6 | RC > LC vmPFC | gender | fixed | 2.13 [-3.38, 7.64] | 2.77 | 0.77 | 77.26 | .444 |
6 | RC > LC vmPFC | condition | fixed | -1.36 [-5.32, 2.60] | 1.99 | -0.68 | 78.70 | .495 |
6 | RC > LC vmPFC | time x neural predictor | fixed | -0.97 [-2.09, 0.16] | 0.57 | -1.70 | 144.76 | .091 |
6 | RC > LC vmPFC | participant | random | 6.06 (variance) | – | – | – | – |
6 | RC > LC vmPFC | residual | random | 10.65 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | intercept | fixed | 50.99 [45.37, 56.61] | 2.82 | 18.05 | 82.79 | < .001 |
7 | RC > LC parahippocampal gyrus | time | fixed | 0.50 [-0.11, 1.12] | 0.31 | 1.61 | 144.80 | .109 |
7 | RC > LC parahippocampal gyrus | neural predictor | fixed | -0.75 [-4.27, 2.77] | 1.78 | -0.42 | 124.98 | .674 |
7 | RC > LC parahippocampal gyrus | BMI | fixed | 0.21 [-0.29, 0.71] | 0.25 | 0.82 | 88.93 | .412 |
7 | RC > LC parahippocampal gyrus | age | fixed | -0.19 [-0.76, 0.38] | 0.28 | -0.67 | 75.77 | .504 |
7 | RC > LC parahippocampal gyrus | gender | fixed | 1.86 [-3.66, 7.38] | 2.77 | 0.67 | 77.19 | .504 |
7 | RC > LC parahippocampal gyrus | condition | fixed | -1.44 [-5.49, 2.61] | 2.03 | -0.71 | 78.98 | .481 |
7 | RC > LC parahippocampal gyrus | time x neural predictor | fixed | 0.43 [-0.49, 1.34] | 0.46 | 0.92 | 142.48 | .360 |
7 | RC > LC parahippocampal gyrus | participant | random | 6.32 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | residual | random | 10.63 (variance) | – | – | – | – |
8 | RC > LC l IFG | intercept | fixed | 51.25 [45.43, 57.06] | 2.93 | 17.51 | 85.50 | < .001 |
8 | RC > LC l IFG | time | fixed | 0.50 [-0.13, 1.12] | 0.31 | 1.58 | 145.60 | .117 |
8 | RC > LC l IFG | neural predictor | fixed | -0.15 [-2.00, 1.71] | 0.94 | -0.16 | 124.00 | .873 |
8 | RC > LC l IFG | BMI | fixed | 0.23 [-0.28, 0.74] | 0.25 | 0.91 | 89.47 | .368 |
8 | RC > LC l IFG | age | fixed | -0.20 [-0.77, 0.36] | 0.28 | -0.72 | 76.28 | .477 |
8 | RC > LC l IFG | gender | fixed | 1.60 [-4.08, 7.28] | 2.85 | 0.56 | 80.43 | .576 |
8 | RC > LC l IFG | condition | fixed | -1.53 [-5.62, 2.57] | 2.06 | -0.74 | 79.07 | .460 |
8 | RC > LC l IFG | time x neural predictor | fixed | -0.08 [-0.57, 0.41] | 0.25 | -0.33 | 145.03 | .745 |
8 | RC > LC l IFG | participant | random | 6.22 (variance) | – | – | – | – |
8 | RC > LC l IFG | residual | random | 10.69 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | intercept | fixed | 50.93 [45.36, 56.50] | 2.80 | 18.18 | 83.30 | < .001 |
9 | RC > LC l supramarginal gyrus | time | fixed | 0.51 [-0.11, 1.13] | 0.31 | 1.61 | 145.85 | .109 |
9 | RC > LC l supramarginal gyrus | neural predictor | fixed | 1.57 [-1.74, 4.89] | 1.67 | 0.94 | 120.36 | .349 |
9 | RC > LC l supramarginal gyrus | BMI | fixed | 0.20 [-0.31, 0.70] | 0.26 | 0.76 | 91.47 | .447 |
9 | RC > LC l supramarginal gyrus | age | fixed | -0.21 [-0.78, 0.35] | 0.28 | -0.75 | 76.22 | .454 |
9 | RC > LC l supramarginal gyrus | gender | fixed | 1.95 [-3.54, 7.43] | 2.75 | 0.71 | 77.77 | .482 |
9 | RC > LC l supramarginal gyrus | condition | fixed | -1.50 [-5.50, 2.50] | 2.01 | -0.75 | 79.24 | .457 |
9 | RC > LC l supramarginal gyrus | time x neural predictor | fixed | -0.34 [-1.16, 0.47] | 0.41 | -0.84 | 136.22 | .405 |
9 | RC > LC l supramarginal gyrus | participant | random | 6.19 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | residual | random | 10.67 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | intercept | fixed | 50.95 [45.52, 56.38] | 2.73 | 18.65 | 84.10 | < .001 |
10 | RC > LC l cerebellum | time | fixed | 0.50 [-0.12, 1.12] | 0.31 | 1.59 | 147.45 | .114 |
10 | RC > LC l cerebellum | neural predictor | fixed | 4.18 [0.64, 7.72] | 1.79 | 2.34 | 124.12 | .021 |
10 | RC > LC l cerebellum | BMI | fixed | 0.22 [-0.26, 0.71] | 0.24 | 0.92 | 89.51 | .359 |
10 | RC > LC l cerebellum | age | fixed | -0.15 [-0.70, 0.39] | 0.28 | -0.56 | 77.89 | .576 |
10 | RC > LC l cerebellum | gender | fixed | 2.17 [-3.18, 7.51] | 2.69 | 0.81 | 78.37 | .422 |
10 | RC > LC l cerebellum | condition | fixed | -1.86 [-5.78, 2.06] | 1.97 | -0.95 | 79.54 | .347 |
10 | RC > LC l cerebellum | time x neural predictor | fixed | -0.54 [-1.57, 0.49] | 0.52 | -1.04 | 150.30 | .302 |
10 | RC > LC l cerebellum | participant | random | 5.85 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | residual | random | 10.66 (variance) | – | – | – | – |
11 | RC > LC midbrain | intercept | fixed | 51.09 [45.48, 56.70] | 2.82 | 18.12 | 83.13 | < .001 |
11 | RC > LC midbrain | time | fixed | 0.49 [-0.13, 1.11] | 0.31 | 1.57 | 145.34 | .120 |
11 | RC > LC midbrain | neural predictor | fixed | 0.61 [-2.80, 4.02] | 1.72 | 0.36 | 119.72 | .723 |
11 | RC > LC midbrain | BMI | fixed | 0.22 [-0.28, 0.72] | 0.25 | 0.88 | 89.21 | .379 |
11 | RC > LC midbrain | age | fixed | -0.18 [-0.74, 0.39] | 0.28 | -0.62 | 76.79 | .537 |
11 | RC > LC midbrain | gender | fixed | 1.66 [-3.88, 7.19] | 2.78 | 0.60 | 77.84 | .553 |
11 | RC > LC midbrain | condition | fixed | -1.32 [-5.34, 2.70] | 2.02 | -0.65 | 79.14 | .515 |
11 | RC > LC midbrain | time x neural predictor | fixed | 0.42 [-0.45, 1.29] | 0.44 | 0.96 | 139.07 | .339 |
11 | RC > LC midbrain | participant | random | 6.29 (variance) | – | – | – | – |
11 | RC > LC midbrain | residual | random | 10.61 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | intercept | fixed | 50.90 [45.40, 56.40] | 2.77 | 18.40 | 83.01 | < .001 |
12 | RC > LC r supramarginal gyrus | time | fixed | 0.54 [-0.08, 1.15] | 0.31 | 1.72 | 145.70 | .087 |
12 | RC > LC r supramarginal gyrus | neural predictor | fixed | 4.07 [0.63, 7.52] | 1.74 | 2.34 | 123.28 | .021 |
12 | RC > LC r supramarginal gyrus | BMI | fixed | 0.21 [-0.28, 0.70] | 0.25 | 0.84 | 90.38 | .401 |
12 | RC > LC r supramarginal gyrus | age | fixed | -0.17 [-0.72, 0.39] | 0.28 | -0.59 | 77.02 | .557 |
12 | RC > LC r supramarginal gyrus | gender | fixed | 2.14 [-3.28, 7.56] | 2.72 | 0.79 | 77.38 | .434 |
12 | RC > LC r supramarginal gyrus | condition | fixed | -1.76 [-5.72, 2.19] | 1.99 | -0.89 | 78.93 | .378 |
12 | RC > LC r supramarginal gyrus | time x neural predictor | fixed | -0.93 [-1.87, 0.01] | 0.48 | -1.95 | 144.43 | .053 |
12 | RC > LC r supramarginal gyrus | participant | random | 6.11 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | residual | random | 10.53 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | intercept | fixed | 51.17 [45.55, 56.80] | 2.83 | 18.10 | 83.72 | < .001 |
13 | RC > LC r posterior MFG | time | fixed | 0.49 [-0.13, 1.12] | 0.32 | 1.55 | 147.37 | .122 |
13 | RC > LC r posterior MFG | neural predictor | fixed | -1.55 [-5.56, 2.45] | 2.03 | -0.77 | 126.30 | .444 |
13 | RC > LC r posterior MFG | BMI | fixed | 0.22 [-0.27, 0.72] | 0.25 | 0.89 | 89.39 | .376 |
13 | RC > LC r posterior MFG | age | fixed | -0.20 [-0.76, 0.36] | 0.28 | -0.71 | 76.83 | .482 |
13 | RC > LC r posterior MFG | gender | fixed | 1.53 [-4.06, 7.11] | 2.81 | 0.54 | 77.81 | .588 |
13 | RC > LC r posterior MFG | condition | fixed | -1.25 [-5.27, 2.77] | 2.02 | -0.62 | 79.14 | .537 |
13 | RC > LC r posterior MFG | time x neural predictor | fixed | 0.15 [-0.94, 1.23] | 0.55 | 0.26 | 147.02 | .792 |
13 | RC > LC r posterior MFG | participant | random | 6.19 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | residual | random | 10.68 (variance) | – | – | – | – |
14 | average anatomical ROIs | intercept | fixed | 50.47 [44.81, 56.12] | 2.84 | 17.76 | 83.06 | < .001 |
14 | average anatomical ROIs | time | fixed | 0.50 [-0.12, 1.12] | 0.31 | 1.59 | 145.73 | .114 |
14 | average anatomical ROIs | neural predictor | fixed | 4.54 [-1.66, 10.75] | 3.14 | 1.45 | 124.48 | .150 |
14 | average anatomical ROIs | BMI | fixed | 0.19 [-0.31, 0.68] | 0.25 | 0.75 | 88.85 | .453 |
14 | average anatomical ROIs | age | fixed | -0.18 [-0.74, 0.38] | 0.28 | -0.65 | 76.56 | .519 |
14 | average anatomical ROIs | gender | fixed | 2.39 [-3.22, 8.01] | 2.82 | 0.85 | 77.86 | .398 |
14 | average anatomical ROIs | condition | fixed | -1.34 [-5.31, 2.63] | 2.00 | -0.67 | 79.03 | .503 |
14 | average anatomical ROIs | time x neural predictor | fixed | -1.18 [-2.71, 0.36] | 0.78 | -1.51 | 138.64 | .132 |
14 | average anatomical ROIs | participant | random | 6.13 (variance) | – | – | – | – |
14 | average anatomical ROIs | residual | random | 10.63 (variance) | – | – | – | – |
15 | average peak ROIs | intercept | fixed | 50.70 [45.12, 56.29] | 2.81 | 18.05 | 83.19 | < .001 |
15 | average peak ROIs | time | fixed | 0.50 [-0.13, 1.12] | 0.32 | 1.58 | 145.97 | .116 |
15 | average peak ROIs | neural predictor | fixed | 2.31 [-2.64, 7.26] | 2.50 | 0.92 | 121.39 | .357 |
15 | average peak ROIs | BMI | fixed | 0.19 [-0.31, 0.69] | 0.25 | 0.76 | 89.77 | .450 |
15 | average peak ROIs | age | fixed | -0.18 [-0.74, 0.38] | 0.28 | -0.63 | 76.43 | .532 |
15 | average peak ROIs | gender | fixed | 2.16 [-3.35, 7.67] | 2.77 | 0.78 | 77.63 | .438 |
15 | average peak ROIs | condition | fixed | -1.39 [-5.37, 2.59] | 2.00 | -0.70 | 78.93 | .488 |
15 | average peak ROIs | time x neural predictor | fixed | -0.30 [-1.61, 1.01] | 0.66 | -0.45 | 142.14 | .652 |
15 | average peak ROIs | participant | random | 6.12 (variance) | – | – | – | – |
15 | average peak ROIs | residual | random | 10.70 (variance) | – | – | – | – |
model | neural predictor | term | effect | b [95% CI] | SE | t | df | p |
---|---|---|---|---|---|---|---|---|
1 | LC > LNC vmPFC | intercept | fixed | 2371.65 [2018.58, 2724.71] | 177.60 | 13.35 | 85.84 | < .001 |
1 | LC > LNC vmPFC | time | fixed | -51.38 [-84.02, -18.74] | 16.51 | -3.11 | 142.95 | .002 |
1 | LC > LNC vmPFC | neural predictor | fixed | 231.69 [-37.06, 500.44] | 135.66 | 1.71 | 113.84 | .090 |
1 | LC > LNC vmPFC | BMI | fixed | 14.94 [-16.06, 45.93] | 15.62 | 0.96 | 98.50 | .341 |
1 | LC > LNC vmPFC | age | fixed | -35.37 [-71.17, 0.42] | 17.99 | -1.97 | 81.32 | .053 |
1 | LC > LNC vmPFC | gender | fixed | -575.42 [-925.05, -225.78] | 175.75 | -3.27 | 81.84 | .002 |
1 | LC > LNC vmPFC | condition | fixed | 205.69 [-49.20, 460.59] | 128.18 | 1.60 | 84.04 | .112 |
1 | LC > LNC vmPFC | time x neural predictor | fixed | -48.29 [-115.75, 19.18] | 34.14 | -1.41 | 146.25 | .159 |
1 | LC > LNC vmPFC | participant | random | 470.70 (variance) | – | – | – | – |
1 | LC > LNC vmPFC | residual | random | 549.26 (variance) | – | – | – | – |
2 | LC > LNC striatum | intercept | fixed | 2349.60 [1992.54, 2706.67] | 179.60 | 13.08 | 85.52 | < .001 |
2 | LC > LNC striatum | time | fixed | -52.79 [-85.42, -20.16] | 16.51 | -3.20 | 142.36 | .002 |
2 | LC > LNC striatum | neural predictor | fixed | 67.40 [-181.71, 316.52] | 125.72 | 0.54 | 110.97 | .593 |
2 | LC > LNC striatum | BMI | fixed | 16.90 [-14.36, 48.15] | 15.75 | 1.07 | 98.14 | .286 |
2 | LC > LNC striatum | age | fixed | -35.38 [-72.12, 1.35] | 18.46 | -1.92 | 80.91 | .059 |
2 | LC > LNC striatum | gender | fixed | -549.10 [-902.22, -195.98] | 177.50 | -3.09 | 81.81 | .003 |
2 | LC > LNC striatum | condition | fixed | 204.41 [-52.59, 461.41] | 129.21 | 1.58 | 83.08 | .117 |
2 | LC > LNC striatum | time x neural predictor | fixed | -19.62 [-77.20, 37.97] | 29.13 | -0.67 | 143.17 | .502 |
2 | LC > LNC striatum | participant | random | 477.21 (variance) | – | – | – | – |
2 | LC > LNC striatum | residual | random | 552.13 (variance) | – | – | – | – |
3 | RC > LC dlPFC | intercept | fixed | 2313.89 [1953.44, 2674.35] | 181.32 | 12.76 | 85.94 | < .001 |
3 | RC > LC dlPFC | time | fixed | -53.32 [-85.88, -20.76] | 16.47 | -3.24 | 142.39 | .002 |
3 | RC > LC dlPFC | neural predictor | fixed | 127.91 [-231.54, 487.35] | 181.45 | 0.70 | 113.95 | .482 |
3 | RC > LC dlPFC | BMI | fixed | 14.98 [-16.35, 46.31] | 15.79 | 0.95 | 97.74 | .345 |
3 | RC > LC dlPFC | age | fixed | -34.48 [-70.51, 1.54] | 18.11 | -1.90 | 80.93 | .060 |
3 | RC > LC dlPFC | gender | fixed | -504.72 [-865.54, -143.90] | 181.40 | -2.78 | 82.52 | .007 |
3 | RC > LC dlPFC | condition | fixed | 200.16 [-56.08, 456.41] | 128.83 | 1.55 | 82.92 | .124 |
3 | RC > LC dlPFC | time x neural predictor | fixed | 13.44 [-64.15, 91.04] | 39.25 | 0.34 | 139.70 | .732 |
3 | RC > LC dlPFC | participant | random | 473.92 (variance) | – | – | – | – |
3 | RC > LC dlPFC | residual | random | 552.68 (variance) | – | – | – | – |
4 | RC > LC IFG | intercept | fixed | 2327.20 [1962.21, 2692.19] | 183.60 | 12.68 | 85.83 | < .001 |
4 | RC > LC IFG | time | fixed | -53.38 [-85.94, -20.83] | 16.47 | -3.24 | 142.32 | .001 |
4 | RC > LC IFG | neural predictor | fixed | 58.44 [-306.29, 423.18] | 184.05 | 0.32 | 110.52 | .751 |
4 | RC > LC IFG | BMI | fixed | 15.85 [-15.69, 47.39] | 15.89 | 1.00 | 97.97 | .321 |
4 | RC > LC IFG | age | fixed | -34.64 [-70.87, 1.59] | 18.21 | -1.90 | 81.24 | .061 |
4 | RC > LC IFG | gender | fixed | -524.95 [-889.07, -160.83] | 183.06 | -2.87 | 82.78 | .005 |
4 | RC > LC IFG | condition | fixed | 207.40 [-49.82, 464.61] | 129.32 | 1.60 | 82.89 | .113 |
4 | RC > LC IFG | time x neural predictor | fixed | 7.73 [-71.50, 86.97] | 40.08 | 0.19 | 139.93 | .847 |
4 | RC > LC IFG | participant | random | 477.81 (variance) | – | – | – | – |
4 | RC > LC IFG | residual | random | 552.48 (variance) | – | – | – | – |
5 | RC > LC dACC | intercept | fixed | 2300.89 [1943.75, 2658.04] | 179.62 | 12.81 | 84.70 | < .001 |
5 | RC > LC dACC | time | fixed | -53.09 [-85.66, -20.52] | 16.48 | -3.22 | 142.31 | .002 |
5 | RC > LC dACC | neural predictor | fixed | 216.72 [-143.21, 576.65] | 181.65 | 1.19 | 111.87 | .235 |
5 | RC > LC dACC | BMI | fixed | 14.80 [-16.21, 45.81] | 15.62 | 0.95 | 96.67 | .346 |
5 | RC > LC dACC | age | fixed | -35.76 [-71.54, 0.02] | 17.98 | -1.99 | 80.92 | .050 |
5 | RC > LC dACC | gender | fixed | -495.29 [-849.92, -140.66] | 178.24 | -2.78 | 81.28 | .007 |
5 | RC > LC dACC | condition | fixed | 209.78 [-44.17, 463.74] | 127.67 | 1.64 | 82.36 | .104 |
5 | RC > LC dACC | time x neural predictor | fixed | 7.79 [-66.61, 82.19] | 37.62 | 0.21 | 135.30 | .836 |
5 | RC > LC dACC | participant | random | 467.75 (variance) | – | – | – | – |
5 | RC > LC dACC | residual | random | 553.20 (variance) | – | – | – | – |
6 | RC > LC vmPFC | intercept | fixed | 2349.64 [1989.82, 2709.45] | 180.99 | 12.98 | 85.67 | < .001 |
6 | RC > LC vmPFC | time | fixed | -53.29 [-85.87, -20.71] | 16.48 | -3.23 | 142.23 | .002 |
6 | RC > LC vmPFC | neural predictor | fixed | -43.94 [-297.16, 209.27] | 127.87 | -0.34 | 118.26 | .732 |
6 | RC > LC vmPFC | BMI | fixed | 16.58 [-14.72, 47.87] | 15.77 | 1.05 | 98.37 | .296 |
6 | RC > LC vmPFC | age | fixed | -34.39 [-70.65, 1.87] | 18.23 | -1.89 | 81.37 | .063 |
6 | RC > LC vmPFC | gender | fixed | -550.86 [-908.62, -193.10] | 179.84 | -3.06 | 81.85 | .003 |
6 | RC > LC vmPFC | condition | fixed | 207.20 [-50.11, 464.52] | 129.37 | 1.60 | 82.94 | .113 |
6 | RC > LC vmPFC | time x neural predictor | fixed | 13.09 [-46.02, 72.20] | 29.90 | 0.44 | 141.75 | .662 |
6 | RC > LC vmPFC | participant | random | 477.78 (variance) | – | – | – | – |
6 | RC > LC vmPFC | residual | random | 552.47 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | intercept | fixed | 2333.52 [1981.28, 2685.76] | 177.17 | 13.17 | 85.45 | < .001 |
7 | RC > LC parahippocampal gyrus | time | fixed | -53.97 [-86.48, -21.46] | 16.44 | -3.28 | 142.58 | .001 |
7 | RC > LC parahippocampal gyrus | neural predictor | fixed | -128.18 [-342.54, 86.18] | 108.21 | -1.18 | 114.07 | .239 |
7 | RC > LC parahippocampal gyrus | BMI | fixed | 17.55 [-13.42, 48.52] | 15.61 | 1.12 | 97.70 | .264 |
7 | RC > LC parahippocampal gyrus | age | fixed | -36.93 [-72.84, -1.01] | 18.05 | -2.05 | 80.77 | .044 |
7 | RC > LC parahippocampal gyrus | gender | fixed | -545.91 [-893.85, -197.98] | 174.89 | -3.12 | 81.51 | .002 |
7 | RC > LC parahippocampal gyrus | condition | fixed | 227.33 [-28.12, 482.77] | 128.44 | 1.77 | 83.26 | .080 |
7 | RC > LC parahippocampal gyrus | time x neural predictor | fixed | -11.53 [-59.53, 36.46] | 24.28 | -0.48 | 141.21 | .636 |
7 | RC > LC parahippocampal gyrus | participant | random | 469.44 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | residual | random | 551.72 (variance) | – | – | – | – |
8 | RC > LC l IFG | intercept | fixed | 2279.57 [1913.54, 2645.60] | 184.17 | 12.38 | 87.42 | < .001 |
8 | RC > LC l IFG | time | fixed | -53.41 [-85.94, -20.88] | 16.46 | -3.25 | 142.93 | .001 |
8 | RC > LC l IFG | neural predictor | fixed | 80.70 [-32.81, 194.20] | 57.30 | 1.41 | 113.42 | .162 |
8 | RC > LC l IFG | BMI | fixed | 12.53 [-19.02, 44.07] | 15.90 | 0.79 | 98.39 | .433 |
8 | RC > LC l IFG | age | fixed | -31.68 [-67.70, 4.34] | 18.10 | -1.75 | 81.28 | .084 |
8 | RC > LC l IFG | gender | fixed | -490.88 [-849.61, -132.16] | 180.39 | -2.72 | 84.05 | .008 |
8 | RC > LC l IFG | condition | fixed | 244.33 [-15.67, 504.34] | 130.73 | 1.87 | 83.28 | .065 |
8 | RC > LC l IFG | time x neural predictor | fixed | -4.31 [-29.85, 21.24] | 12.92 | -0.33 | 143.12 | .739 |
8 | RC > LC l IFG | participant | random | 469.93 (variance) | – | – | – | – |
8 | RC > LC l IFG | residual | random | 552.34 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | intercept | fixed | 2344.59 [1987.77, 2701.41] | 179.47 | 13.06 | 85.28 | < .001 |
9 | RC > LC l supramarginal gyrus | time | fixed | -53.35 [-85.95, -20.75] | 16.49 | -3.24 | 142.27 | .002 |
9 | RC > LC l supramarginal gyrus | neural predictor | fixed | 26.25 [-180.13, 232.62] | 104.12 | 0.25 | 108.56 | .801 |
9 | RC > LC l supramarginal gyrus | BMI | fixed | 16.37 [-15.71, 48.44] | 16.17 | 1.01 | 99.98 | .314 |
9 | RC > LC l supramarginal gyrus | age | fixed | -34.78 [-71.19, 1.63] | 18.30 | -1.90 | 80.82 | .061 |
9 | RC > LC l supramarginal gyrus | gender | fixed | -544.54 [-897.51, -191.57] | 177.42 | -3.07 | 81.69 | .003 |
9 | RC > LC l supramarginal gyrus | condition | fixed | 205.58 [-52.44, 463.61] | 129.73 | 1.58 | 82.99 | .117 |
9 | RC > LC l supramarginal gyrus | time x neural predictor | fixed | -3.99 [-46.35, 38.38] | 21.42 | -0.19 | 135.78 | .853 |
9 | RC > LC l supramarginal gyrus | participant | random | 479.54 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | residual | random | 552.08 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | intercept | fixed | 2343.02 [1988.73, 2697.32] | 178.22 | 13.15 | 85.81 | < .001 |
10 | RC > LC l cerebellum | time | fixed | -53.52 [-86.04, -21.01] | 16.45 | -3.25 | 142.98 | .001 |
10 | RC > LC l cerebellum | neural predictor | fixed | -131.74 [-355.12, 91.65] | 112.72 | -1.17 | 109.78 | .245 |
10 | RC > LC l cerebellum | BMI | fixed | 16.29 [-14.85, 47.43] | 15.69 | 1.04 | 98.39 | .302 |
10 | RC > LC l cerebellum | age | fixed | -35.77 [-71.96, 0.41] | 18.19 | -1.97 | 82.21 | .053 |
10 | RC > LC l cerebellum | gender | fixed | -553.90 [-904.49, -203.30] | 176.25 | -3.14 | 82.24 | .002 |
10 | RC > LC l cerebellum | condition | fixed | 223.10 [-34.48, 480.68] | 129.51 | 1.72 | 83.17 | .089 |
10 | RC > LC l cerebellum | time x neural predictor | fixed | 13.84 [-40.57, 68.26] | 27.53 | 0.50 | 144.48 | .616 |
10 | RC > LC l cerebellum | participant | random | 474.51 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | residual | random | 551.70 (variance) | – | – | – | – |
11 | RC > LC midbrain | intercept | fixed | 2358.80 [2004.80, 2712.80] | 178.04 | 13.25 | 84.95 | < .001 |
11 | RC > LC midbrain | time | fixed | -53.61 [-86.15, -21.06] | 16.46 | -3.26 | 142.37 | .001 |
11 | RC > LC midbrain | neural predictor | fixed | 101.24 [-108.54, 311.03] | 105.84 | 0.96 | 108.54 | .341 |
11 | RC > LC midbrain | BMI | fixed | 17.59 [-13.51, 48.69] | 15.67 | 1.12 | 97.46 | .265 |
11 | RC > LC midbrain | age | fixed | -33.78 [-69.71, 2.14] | 18.06 | -1.87 | 80.95 | .065 |
11 | RC > LC midbrain | gender | fixed | -566.26 [-917.20, -215.32] | 176.39 | -3.21 | 81.32 | .002 |
11 | RC > LC midbrain | condition | fixed | 212.29 [-42.94, 467.52] | 128.31 | 1.65 | 82.66 | .102 |
11 | RC > LC midbrain | time x neural predictor | fixed | 7.80 [-37.80, 53.39] | 23.06 | 0.34 | 137.62 | .736 |
11 | RC > LC midbrain | participant | random | 471.74 (variance) | – | – | – | – |
11 | RC > LC midbrain | residual | random | 552.45 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | intercept | fixed | 2343.65 [1987.68, 2699.62] | 179.03 | 13.09 | 84.98 | < .001 |
12 | RC > LC r supramarginal gyrus | time | fixed | -54.13 [-86.87, -21.38] | 16.57 | -3.27 | 142.24 | .001 |
12 | RC > LC r supramarginal gyrus | neural predictor | fixed | 20.84 [-195.29, 236.97] | 109.07 | 0.19 | 110.64 | .849 |
12 | RC > LC r supramarginal gyrus | BMI | fixed | 16.21 [-15.12, 47.55] | 15.79 | 1.03 | 98.66 | .307 |
12 | RC > LC r supramarginal gyrus | age | fixed | -33.70 [-70.06, 2.65] | 18.27 | -1.84 | 81.29 | .069 |
12 | RC > LC r supramarginal gyrus | gender | fixed | -542.93 [-895.32, -190.55] | 177.12 | -3.07 | 81.31 | .003 |
12 | RC > LC r supramarginal gyrus | condition | fixed | 205.69 [-52.14, 463.53] | 129.63 | 1.59 | 82.71 | .116 |
12 | RC > LC r supramarginal gyrus | time x neural predictor | fixed | 7.85 [-42.24, 57.94] | 25.34 | 0.31 | 141.04 | .757 |
12 | RC > LC r supramarginal gyrus | participant | random | 477.42 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | residual | random | 552.64 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | intercept | fixed | 2326.96 [1968.41, 2685.52] | 180.35 | 12.90 | 85.54 | < .001 |
13 | RC > LC r posterior MFG | time | fixed | -51.36 [-84.20, -18.52] | 16.62 | -3.09 | 143.43 | .002 |
13 | RC > LC r posterior MFG | neural predictor | fixed | 141.66 [-105.23, 388.54] | 124.61 | 1.14 | 112.74 | .258 |
13 | RC > LC r posterior MFG | BMI | fixed | 15.29 [-16.01, 46.60] | 15.77 | 0.97 | 98.04 | .335 |
13 | RC > LC r posterior MFG | age | fixed | -33.76 [-69.91, 2.39] | 18.17 | -1.86 | 81.23 | .067 |
13 | RC > LC r posterior MFG | gender | fixed | -518.70 [-877.10, -160.29] | 180.16 | -2.88 | 81.71 | .005 |
13 | RC > LC r posterior MFG | condition | fixed | 194.61 [-63.32, 452.54] | 129.68 | 1.50 | 82.91 | .137 |
13 | RC > LC r posterior MFG | time x neural predictor | fixed | -28.48 [-85.13, 28.18] | 28.66 | -0.99 | 143.26 | .322 |
13 | RC > LC r posterior MFG | participant | random | 477.82 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | residual | random | 549.93 (variance) | – | – | – | – |
14 | average anatomical ROIs | intercept | fixed | 2308.73 [1947.06, 2670.40] | 181.92 | 12.69 | 85.47 | < .001 |
14 | average anatomical ROIs | time | fixed | -53.25 [-85.81, -20.68] | 16.47 | -3.23 | 142.33 | .002 |
14 | average anatomical ROIs | neural predictor | fixed | 152.21 [-231.70, 536.12] | 193.75 | 0.79 | 111.69 | .434 |
14 | average anatomical ROIs | BMI | fixed | 14.89 [-16.42, 46.20] | 15.78 | 0.94 | 97.33 | .347 |
14 | average anatomical ROIs | age | fixed | -34.91 [-70.92, 1.10] | 18.10 | -1.93 | 81.02 | .057 |
14 | average anatomical ROIs | gender | fixed | -501.89 [-862.86, -140.91] | 181.46 | -2.77 | 82.16 | .007 |
14 | average anatomical ROIs | condition | fixed | 205.40 [-50.30, 461.11] | 128.56 | 1.60 | 82.76 | .114 |
14 | average anatomical ROIs | time x neural predictor | fixed | 10.45 [-69.95, 90.85] | 40.66 | 0.26 | 137.47 | .798 |
14 | average anatomical ROIs | participant | random | 473.24 (variance) | – | – | – | – |
14 | average anatomical ROIs | residual | random | 552.85 (variance) | – | – | – | – |
15 | average peak ROIs | intercept | fixed | 2334.95 [1976.49, 2693.40] | 180.29 | 12.95 | 85.25 | < .001 |
15 | average peak ROIs | time | fixed | -53.37 [-85.97, -20.78] | 16.49 | -3.24 | 142.32 | .002 |
15 | average peak ROIs | neural predictor | fixed | 86.95 [-221.20, 395.11] | 155.48 | 0.56 | 108.95 | .577 |
15 | average peak ROIs | BMI | fixed | 15.81 [-15.74, 47.37] | 15.90 | 0.99 | 98.67 | .322 |
15 | average peak ROIs | age | fixed | -33.69 [-70.03, 2.66] | 18.27 | -1.84 | 81.10 | .069 |
15 | average peak ROIs | gender | fixed | -534.12 [-889.47, -178.77] | 178.62 | -2.99 | 81.70 | .004 |
15 | average peak ROIs | condition | fixed | 207.34 [-49.96, 464.64] | 129.36 | 1.60 | 82.84 | .113 |
15 | average peak ROIs | time x neural predictor | fixed | -7.72 [-75.97, 60.52] | 34.52 | -0.22 | 139.71 | .823 |
15 | average peak ROIs | participant | random | 478.36 (variance) | – | – | – | – |
15 | average peak ROIs | residual | random | 552.10 (variance) | – | – | – | – |
model | neural predictor | term | effect | b [95% CI] | SE | t | df | p |
---|---|---|---|---|---|---|---|---|
1 | LC > LNC vmPFC | intercept | fixed | 2.36 [1.76, 2.95] | 0.30 | 7.83 | 79.94 | < .001 |
1 | LC > LNC vmPFC | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.29 | 139.35 | .024 |
1 | LC > LNC vmPFC | neural predictor | fixed | -0.24 [-0.69, 0.22] | 0.23 | -1.02 | 110.77 | .310 |
1 | LC > LNC vmPFC | BMI | fixed | 0.02 [-0.03, 0.07] | 0.03 | 0.80 | 90.28 | .426 |
1 | LC > LNC vmPFC | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.75 | 75.23 | .458 |
1 | LC > LNC vmPFC | gender | fixed | 0.21 [-0.38, 0.81] | 0.30 | 0.72 | 75.57 | .475 |
1 | LC > LNC vmPFC | condition | fixed | 0.08 [-0.35, 0.52] | 0.22 | 0.38 | 77.68 | .704 |
1 | LC > LNC vmPFC | time x neural predictor | fixed | 0.02 [-0.10, 0.14] | 0.06 | 0.32 | 143.18 | .749 |
1 | LC > LNC vmPFC | participant | random | 0.77 (variance) | – | – | – | – |
1 | LC > LNC vmPFC | residual | random | 0.98 (variance) | – | – | – | – |
2 | LC > LNC striatum | intercept | fixed | 2.36 [1.76, 2.96] | 0.30 | 7.80 | 80.48 | < .001 |
2 | LC > LNC striatum | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.32 | 139.50 | .022 |
2 | LC > LNC striatum | neural predictor | fixed | -0.17 [-0.60, 0.25] | 0.21 | -0.82 | 108.72 | .415 |
2 | LC > LNC striatum | BMI | fixed | 0.02 [-0.03, 0.07] | 0.03 | 0.72 | 90.79 | .472 |
2 | LC > LNC striatum | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.62 | 75.67 | .538 |
2 | LC > LNC striatum | gender | fixed | 0.21 [-0.39, 0.80] | 0.30 | 0.69 | 76.37 | .493 |
2 | LC > LNC striatum | condition | fixed | 0.09 [-0.34, 0.53] | 0.22 | 0.43 | 77.53 | .669 |
2 | LC > LNC striatum | time x neural predictor | fixed | 0.01 [-0.09, 0.11] | 0.05 | 0.15 | 140.52 | .883 |
2 | LC > LNC striatum | participant | random | 0.78 (variance) | – | – | – | – |
2 | LC > LNC striatum | residual | random | 0.98 (variance) | – | – | – | – |
3 | RC > LC dlPFC | intercept | fixed | 2.29 [1.69, 2.89] | 0.30 | 7.59 | 79.23 | < .001 |
3 | RC > LC dlPFC | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.37 | 137.99 | .019 |
3 | RC > LC dlPFC | neural predictor | fixed | 0.68 [0.07, 1.28] | 0.31 | 2.21 | 108.96 | .029 |
3 | RC > LC dlPFC | BMI | fixed | 0.02 [-0.04, 0.07] | 0.03 | 0.60 | 88.98 | .552 |
3 | RC > LC dlPFC | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.73 | 74.14 | .470 |
3 | RC > LC dlPFC | gender | fixed | 0.28 [-0.32, 0.88] | 0.30 | 0.94 | 75.62 | .349 |
3 | RC > LC dlPFC | condition | fixed | 0.08 [-0.35, 0.51] | 0.21 | 0.38 | 75.85 | .702 |
3 | RC > LC dlPFC | time x neural predictor | fixed | -0.14 [-0.27, -0.00] | 0.07 | -2.00 | 134.70 | .047 |
3 | RC > LC dlPFC | participant | random | 0.76 (variance) | – | – | – | – |
3 | RC > LC dlPFC | residual | random | 0.96 (variance) | – | – | – | – |
4 | RC > LC IFG | intercept | fixed | 2.29 [1.69, 2.90] | 0.31 | 7.52 | 80.13 | < .001 |
4 | RC > LC IFG | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.32 | 138.99 | .022 |
4 | RC > LC IFG | neural predictor | fixed | 0.56 [-0.05, 1.17] | 0.31 | 1.82 | 107.74 | .072 |
4 | RC > LC IFG | BMI | fixed | 0.02 [-0.04, 0.07] | 0.03 | 0.57 | 89.88 | .573 |
4 | RC > LC IFG | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.73 | 75.36 | .466 |
4 | RC > LC IFG | gender | fixed | 0.28 [-0.33, 0.88] | 0.30 | 0.91 | 76.73 | .368 |
4 | RC > LC IFG | condition | fixed | 0.10 [-0.33, 0.53] | 0.22 | 0.46 | 76.71 | .648 |
4 | RC > LC IFG | time x neural predictor | fixed | -0.11 [-0.25, 0.03] | 0.07 | -1.54 | 136.28 | .125 |
4 | RC > LC IFG | participant | random | 0.77 (variance) | – | – | – | – |
4 | RC > LC IFG | residual | random | 0.97 (variance) | – | – | – | – |
5 | RC > LC dACC | intercept | fixed | 2.28 [1.68, 2.88] | 0.30 | 7.59 | 79.80 | < .001 |
5 | RC > LC dACC | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.35 | 139.40 | .020 |
5 | RC > LC dACC | neural predictor | fixed | 0.71 [0.10, 1.32] | 0.31 | 2.30 | 108.43 | .023 |
5 | RC > LC dACC | BMI | fixed | 0.02 [-0.04, 0.07] | 0.03 | 0.61 | 90.06 | .541 |
5 | RC > LC dACC | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.80 | 75.99 | .429 |
5 | RC > LC dACC | gender | fixed | 0.28 [-0.31, 0.87] | 0.30 | 0.94 | 76.24 | .353 |
5 | RC > LC dACC | condition | fixed | 0.11 [-0.32, 0.54] | 0.21 | 0.51 | 77.02 | .609 |
5 | RC > LC dACC | time x neural predictor | fixed | -0.13 [-0.26, 0.00] | 0.07 | -1.96 | 131.54 | .052 |
5 | RC > LC dACC | participant | random | 0.76 (variance) | – | – | – | – |
5 | RC > LC dACC | residual | random | 0.96 (variance) | – | – | – | – |
6 | RC > LC vmPFC | intercept | fixed | 2.36 [1.76, 2.97] | 0.30 | 7.76 | 80.26 | < .001 |
6 | RC > LC vmPFC | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.29 | 138.83 | .024 |
6 | RC > LC vmPFC | neural predictor | fixed | 0.23 [-0.22, 0.68] | 0.22 | 1.03 | 109.28 | .307 |
6 | RC > LC vmPFC | BMI | fixed | 0.02 [-0.03, 0.07] | 0.03 | 0.76 | 91.31 | .448 |
6 | RC > LC vmPFC | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.75 | 76.05 | .457 |
6 | RC > LC vmPFC | gender | fixed | 0.19 [-0.41, 0.79] | 0.30 | 0.63 | 76.46 | .529 |
6 | RC > LC vmPFC | condition | fixed | 0.10 [-0.33, 0.53] | 0.22 | 0.45 | 77.32 | .650 |
6 | RC > LC vmPFC | time x neural predictor | fixed | -0.11 [-0.21, -0.00] | 0.05 | -2.03 | 137.64 | .045 |
6 | RC > LC vmPFC | participant | random | 0.78 (variance) | – | – | – | – |
6 | RC > LC vmPFC | residual | random | 0.96 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | intercept | fixed | 2.37 [1.77, 2.98] | 0.30 | 7.85 | 80.53 | < .001 |
7 | RC > LC parahippocampal gyrus | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.31 | 139.37 | .022 |
7 | RC > LC parahippocampal gyrus | neural predictor | fixed | -0.14 [-0.51, 0.23] | 0.19 | -0.75 | 111.08 | .455 |
7 | RC > LC parahippocampal gyrus | BMI | fixed | 0.02 [-0.03, 0.07] | 0.03 | 0.74 | 91.06 | .459 |
7 | RC > LC parahippocampal gyrus | age | fixed | -0.03 [-0.09, 0.04] | 0.03 | -0.82 | 75.75 | .414 |
7 | RC > LC parahippocampal gyrus | gender | fixed | 0.18 [-0.41, 0.78] | 0.30 | 0.61 | 76.33 | .545 |
7 | RC > LC parahippocampal gyrus | condition | fixed | 0.10 [-0.34, 0.54] | 0.22 | 0.46 | 77.88 | .645 |
7 | RC > LC parahippocampal gyrus | time x neural predictor | fixed | 0.02 [-0.07, 0.10] | 0.04 | 0.40 | 137.88 | .691 |
7 | RC > LC parahippocampal gyrus | participant | random | 0.78 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | residual | random | 0.97 (variance) | – | – | – | – |
8 | RC > LC l IFG | intercept | fixed | 2.41 [1.79, 3.04] | 0.31 | 7.67 | 82.46 | < .001 |
8 | RC > LC l IFG | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.31 | 139.57 | .022 |
8 | RC > LC l IFG | neural predictor | fixed | -0.02 [-0.22, 0.17] | 0.10 | -0.22 | 109.66 | .829 |
8 | RC > LC l IFG | BMI | fixed | 0.02 [-0.03, 0.08] | 0.03 | 0.78 | 91.59 | .436 |
8 | RC > LC l IFG | age | fixed | -0.02 [-0.09, 0.04] | 0.03 | -0.80 | 76.16 | .428 |
8 | RC > LC l IFG | gender | fixed | 0.15 [-0.46, 0.77] | 0.31 | 0.50 | 78.75 | .621 |
8 | RC > LC l IFG | condition | fixed | 0.08 [-0.37, 0.52] | 0.22 | 0.34 | 77.94 | .738 |
8 | RC > LC l IFG | time x neural predictor | fixed | -0.01 [-0.05, 0.04] | 0.02 | -0.28 | 139.75 | .781 |
8 | RC > LC l IFG | participant | random | 0.79 (variance) | – | – | – | – |
8 | RC > LC l IFG | residual | random | 0.97 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | intercept | fixed | 2.38 [1.78, 2.98] | 0.30 | 7.87 | 80.66 | < .001 |
9 | RC > LC l supramarginal gyrus | time | fixed | 0.07 [0.01, 0.13] | 0.03 | 2.33 | 139.69 | .021 |
9 | RC > LC l supramarginal gyrus | neural predictor | fixed | 0.01 [-0.34, 0.36] | 0.18 | 0.07 | 106.04 | .944 |
9 | RC > LC l supramarginal gyrus | BMI | fixed | 0.02 [-0.03, 0.08] | 0.03 | 0.75 | 93.34 | .454 |
9 | RC > LC l supramarginal gyrus | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.76 | 76.00 | .447 |
9 | RC > LC l supramarginal gyrus | gender | fixed | 0.18 [-0.41, 0.78] | 0.30 | 0.61 | 76.71 | .544 |
9 | RC > LC l supramarginal gyrus | condition | fixed | 0.09 [-0.35, 0.53] | 0.22 | 0.40 | 77.89 | .688 |
9 | RC > LC l supramarginal gyrus | time x neural predictor | fixed | -0.01 [-0.09, 0.06] | 0.04 | -0.37 | 132.47 | .714 |
9 | RC > LC l supramarginal gyrus | participant | random | 0.78 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | residual | random | 0.98 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | intercept | fixed | 2.38 [1.81, 2.96] | 0.29 | 8.25 | 81.32 | < .001 |
10 | RC > LC l cerebellum | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.34 | 141.44 | .021 |
10 | RC > LC l cerebellum | neural predictor | fixed | 0.58 [0.21, 0.95] | 0.18 | 3.13 | 109.81 | .002 |
10 | RC > LC l cerebellum | BMI | fixed | 0.02 [-0.03, 0.07] | 0.03 | 0.81 | 90.83 | .422 |
10 | RC > LC l cerebellum | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.63 | 77.35 | .532 |
10 | RC > LC l cerebellum | gender | fixed | 0.22 [-0.35, 0.79] | 0.29 | 0.78 | 77.07 | .439 |
10 | RC > LC l cerebellum | condition | fixed | 0.02 [-0.40, 0.44] | 0.21 | 0.10 | 78.05 | .922 |
10 | RC > LC l cerebellum | time x neural predictor | fixed | -0.07 [-0.17, 0.02] | 0.05 | -1.50 | 143.42 | .135 |
10 | RC > LC l cerebellum | participant | random | 0.73 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | residual | random | 0.97 (variance) | – | – | – | – |
11 | RC > LC midbrain | intercept | fixed | 2.40 [1.80, 3.00] | 0.30 | 7.96 | 80.84 | < .001 |
11 | RC > LC midbrain | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.31 | 140.13 | .023 |
11 | RC > LC midbrain | neural predictor | fixed | 0.18 [-0.17, 0.54] | 0.18 | 1.03 | 106.68 | .308 |
11 | RC > LC midbrain | BMI | fixed | 0.02 [-0.03, 0.07] | 0.03 | 0.78 | 91.40 | .435 |
11 | RC > LC midbrain | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.76 | 76.69 | .449 |
11 | RC > LC midbrain | gender | fixed | 0.15 [-0.44, 0.75] | 0.30 | 0.51 | 76.88 | .609 |
11 | RC > LC midbrain | condition | fixed | 0.10 [-0.34, 0.53] | 0.22 | 0.45 | 78.07 | .657 |
11 | RC > LC midbrain | time x neural predictor | fixed | -0.01 [-0.09, 0.07] | 0.04 | -0.26 | 135.03 | .795 |
11 | RC > LC midbrain | participant | random | 0.78 (variance) | – | – | – | – |
11 | RC > LC midbrain | residual | random | 0.98 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | intercept | fixed | 2.37 [1.79, 2.95] | 0.29 | 8.13 | 80.45 | < .001 |
12 | RC > LC r supramarginal gyrus | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.31 | 140.64 | .022 |
12 | RC > LC r supramarginal gyrus | neural predictor | fixed | 0.49 [0.13, 0.85] | 0.18 | 2.72 | 110.40 | .008 |
12 | RC > LC r supramarginal gyrus | BMI | fixed | 0.02 [-0.04, 0.07] | 0.03 | 0.63 | 91.06 | .530 |
12 | RC > LC r supramarginal gyrus | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.59 | 76.37 | .558 |
12 | RC > LC r supramarginal gyrus | gender | fixed | 0.23 [-0.35, 0.80] | 0.29 | 0.79 | 76.09 | .433 |
12 | RC > LC r supramarginal gyrus | condition | fixed | 0.04 [-0.38, 0.46] | 0.21 | 0.19 | 77.52 | .846 |
12 | RC > LC r supramarginal gyrus | time x neural predictor | fixed | -0.04 [-0.13, 0.04] | 0.04 | -1.00 | 139.40 | .319 |
12 | RC > LC r supramarginal gyrus | participant | random | 0.74 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | residual | random | 0.97 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | intercept | fixed | 2.41 [1.81, 3.02] | 0.30 | 7.92 | 81.15 | < .001 |
13 | RC > LC r posterior MFG | time | fixed | 0.07 [0.01, 0.13] | 0.03 | 2.36 | 141.23 | .020 |
13 | RC > LC r posterior MFG | neural predictor | fixed | -0.14 [-0.56, 0.29] | 0.21 | -0.64 | 110.36 | .522 |
13 | RC > LC r posterior MFG | BMI | fixed | 0.02 [-0.03, 0.07] | 0.03 | 0.73 | 91.57 | .465 |
13 | RC > LC r posterior MFG | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.78 | 76.66 | .441 |
13 | RC > LC r posterior MFG | gender | fixed | 0.14 [-0.47, 0.74] | 0.30 | 0.44 | 77.06 | .658 |
13 | RC > LC r posterior MFG | condition | fixed | 0.10 [-0.33, 0.54] | 0.22 | 0.47 | 78.13 | .638 |
13 | RC > LC r posterior MFG | time x neural predictor | fixed | -0.01 [-0.11, 0.09] | 0.05 | -0.27 | 140.96 | .789 |
13 | RC > LC r posterior MFG | participant | random | 0.78 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | residual | random | 0.97 (variance) | – | – | – | – |
14 | average anatomical ROIs | intercept | fixed | 2.28 [1.67, 2.88] | 0.30 | 7.53 | 79.57 | < .001 |
14 | average anatomical ROIs | time | fixed | 0.07 [0.01, 0.12] | 0.03 | 2.35 | 138.74 | .020 |
14 | average anatomical ROIs | neural predictor | fixed | 0.73 [0.08, 1.37] | 0.33 | 2.24 | 108.06 | .027 |
14 | average anatomical ROIs | BMI | fixed | 0.01 [-0.04, 0.07] | 0.03 | 0.57 | 89.33 | .571 |
14 | average anatomical ROIs | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.75 | 75.03 | .457 |
14 | average anatomical ROIs | gender | fixed | 0.29 [-0.31, 0.89] | 0.30 | 0.98 | 76.03 | .332 |
14 | average anatomical ROIs | condition | fixed | 0.10 [-0.33, 0.52] | 0.21 | 0.46 | 76.43 | .650 |
14 | average anatomical ROIs | time x neural predictor | fixed | -0.14 [-0.28, 0.00] | 0.07 | -1.93 | 133.15 | .055 |
14 | average anatomical ROIs | participant | random | 0.76 (variance) | – | – | – | – |
14 | average anatomical ROIs | residual | random | 0.97 (variance) | – | – | – | – |
15 | average peak ROIs | intercept | fixed | 2.36 [1.75, 2.96] | 0.30 | 7.78 | 80.49 | < .001 |
15 | average peak ROIs | time | fixed | 0.07 [0.01, 0.13] | 0.03 | 2.34 | 139.70 | .021 |
15 | average peak ROIs | neural predictor | fixed | 0.27 [-0.25, 0.79] | 0.26 | 1.02 | 106.83 | .311 |
15 | average peak ROIs | BMI | fixed | 0.02 [-0.04, 0.07] | 0.03 | 0.64 | 91.63 | .524 |
15 | average peak ROIs | age | fixed | -0.02 [-0.08, 0.04] | 0.03 | -0.71 | 76.12 | .478 |
15 | average peak ROIs | gender | fixed | 0.21 [-0.39, 0.81] | 0.30 | 0.71 | 76.54 | .482 |
15 | average peak ROIs | condition | fixed | 0.09 [-0.34, 0.52] | 0.22 | 0.41 | 77.56 | .684 |
15 | average peak ROIs | time x neural predictor | fixed | -0.04 [-0.16, 0.08] | 0.06 | -0.70 | 136.85 | .488 |
15 | average peak ROIs | participant | random | 0.78 (variance) | – | – | – | – |
15 | average peak ROIs | residual | random | 0.97 (variance) | – | – | – | – |
model | neural predictor | term | effect | b [95% CI] | SE | t | df | p |
---|---|---|---|---|---|---|---|---|
1 | LC > LNC vmPFC | intercept | fixed | 10.93 [8.63, 13.23] | 1.16 | 9.45 | 82.73 | < .001 |
1 | LC > LNC vmPFC | time | fixed | 0.30 [0.01, 0.59] | 0.15 | 2.04 | 152.17 | .043 |
1 | LC > LNC vmPFC | neural predictor | fixed | -1.79 [-3.65, 0.08] | 0.94 | -1.89 | 139.32 | .061 |
1 | LC > LNC vmPFC | BMI | fixed | 0.10 [-0.11, 0.30] | 0.10 | 0.96 | 85.27 | .341 |
1 | LC > LNC vmPFC | age | fixed | 0.12 [-0.11, 0.35] | 0.12 | 1.02 | 75.04 | .310 |
1 | LC > LNC vmPFC | gender | fixed | 1.26 [-0.99, 3.51] | 1.13 | 1.12 | 74.64 | .268 |
1 | LC > LNC vmPFC | condition | fixed | -1.11 [-2.77, 0.54] | 0.83 | -1.34 | 79.77 | .184 |
1 | LC > LNC vmPFC | time x neural predictor | fixed | 0.25 [-0.35, 0.84] | 0.30 | 0.82 | 158.52 | .415 |
1 | LC > LNC vmPFC | participant | random | 2.07 (variance) | – | – | – | – |
1 | LC > LNC vmPFC | residual | random | 4.99 (variance) | – | – | – | – |
2 | LC > LNC striatum | intercept | fixed | 11.02 [8.67, 13.38] | 1.18 | 9.32 | 81.96 | < .001 |
2 | LC > LNC striatum | time | fixed | 0.31 [0.02, 0.60] | 0.15 | 2.11 | 150.25 | .036 |
2 | LC > LNC striatum | neural predictor | fixed | -0.23 [-1.97, 1.51] | 0.88 | -0.26 | 132.95 | .793 |
2 | LC > LNC striatum | BMI | fixed | 0.08 [-0.12, 0.29] | 0.11 | 0.81 | 84.89 | .422 |
2 | LC > LNC striatum | age | fixed | 0.12 [-0.11, 0.36] | 0.12 | 1.04 | 74.57 | .303 |
2 | LC > LNC striatum | gender | fixed | 1.15 [-1.16, 3.45] | 1.16 | 0.99 | 74.58 | .324 |
2 | LC > LNC striatum | condition | fixed | -1.09 [-2.77, 0.60] | 0.85 | -1.28 | 78.19 | .203 |
2 | LC > LNC striatum | time x neural predictor | fixed | -0.13 [-0.64, 0.38] | 0.26 | -0.49 | 152.11 | .621 |
2 | LC > LNC striatum | participant | random | 2.23 (variance) | – | – | – | – |
2 | LC > LNC striatum | residual | random | 4.98 (variance) | – | – | – | – |
3 | RC > LC dlPFC | intercept | fixed | 11.18 [8.79, 13.57] | 1.20 | 9.32 | 82.54 | < .001 |
3 | RC > LC dlPFC | time | fixed | 0.30 [0.01, 0.59] | 0.15 | 2.05 | 150.27 | .042 |
3 | RC > LC dlPFC | neural predictor | fixed | -0.81 [-3.33, 1.71] | 1.28 | -0.63 | 136.32 | .527 |
3 | RC > LC dlPFC | BMI | fixed | 0.09 [-0.12, 0.30] | 0.11 | 0.83 | 84.96 | .408 |
3 | RC > LC dlPFC | age | fixed | 0.11 [-0.13, 0.35] | 0.12 | 0.93 | 74.70 | .354 |
3 | RC > LC dlPFC | gender | fixed | 0.96 [-1.40, 3.33] | 1.19 | 0.81 | 75.60 | .419 |
3 | RC > LC dlPFC | condition | fixed | -1.06 [-2.75, 0.62] | 0.85 | -1.26 | 78.27 | .213 |
3 | RC > LC dlPFC | time x neural predictor | fixed | 0.19 [-0.50, 0.88] | 0.35 | 0.54 | 144.83 | .590 |
3 | RC > LC dlPFC | participant | random | 2.22 (variance) | – | – | – | – |
3 | RC > LC dlPFC | residual | random | 4.99 (variance) | – | – | – | – |
4 | RC > LC IFG | intercept | fixed | 11.10 [8.69, 13.50] | 1.21 | 9.18 | 82.33 | < .001 |
4 | RC > LC IFG | time | fixed | 0.30 [0.01, 0.59] | 0.15 | 2.06 | 150.32 | .041 |
4 | RC > LC IFG | neural predictor | fixed | -0.32 [-2.86, 2.22] | 1.28 | -0.25 | 132.06 | .804 |
4 | RC > LC IFG | BMI | fixed | 0.08 [-0.13, 0.30] | 0.11 | 0.80 | 84.92 | .428 |
4 | RC > LC IFG | age | fixed | 0.11 [-0.13, 0.35] | 0.12 | 0.93 | 75.04 | .356 |
4 | RC > LC IFG | gender | fixed | 1.07 [-1.31, 3.45] | 1.19 | 0.89 | 75.93 | .374 |
4 | RC > LC IFG | condition | fixed | -1.08 [-2.77, 0.60] | 0.85 | -1.28 | 78.18 | .204 |
4 | RC > LC IFG | time x neural predictor | fixed | 0.14 [-0.57, 0.84] | 0.36 | 0.38 | 145.98 | .702 |
4 | RC > LC IFG | participant | random | 2.22 (variance) | – | – | – | – |
4 | RC > LC IFG | residual | random | 4.99 (variance) | – | – | – | – |
5 | RC > LC dACC | intercept | fixed | 11.31 [8.96, 13.67] | 1.18 | 9.55 | 81.02 | < .001 |
5 | RC > LC dACC | time | fixed | 0.30 [0.01, 0.59] | 0.15 | 2.04 | 150.49 | .043 |
5 | RC > LC dACC | neural predictor | fixed | -1.15 [-3.67, 1.37] | 1.27 | -0.91 | 134.93 | .367 |
5 | RC > LC dACC | BMI | fixed | 0.09 [-0.12, 0.30] | 0.10 | 0.88 | 83.65 | .379 |
5 | RC > LC dACC | age | fixed | 0.12 [-0.11, 0.35] | 0.12 | 1.03 | 74.68 | .308 |
5 | RC > LC dACC | gender | fixed | 0.82 [-1.50, 3.13] | 1.16 | 0.70 | 74.03 | .485 |
5 | RC > LC dACC | condition | fixed | -1.08 [-2.75, 0.59] | 0.84 | -1.29 | 77.55 | .200 |
5 | RC > LC dACC | time x neural predictor | fixed | -0.00 [-0.67, 0.66] | 0.34 | -0.01 | 138.03 | .991 |
5 | RC > LC dACC | participant | random | 2.14 (variance) | – | – | – | – |
5 | RC > LC dACC | residual | random | 5.01 (variance) | – | – | – | – |
6 | RC > LC vmPFC | intercept | fixed | 11.13 [8.77, 13.49] | 1.19 | 9.38 | 81.29 | < .001 |
6 | RC > LC vmPFC | time | fixed | 0.30 [0.01, 0.59] | 0.15 | 2.03 | 149.69 | .044 |
6 | RC > LC vmPFC | neural predictor | fixed | -0.07 [-1.85, 1.71] | 0.90 | -0.08 | 142.97 | .938 |
6 | RC > LC vmPFC | BMI | fixed | 0.08 [-0.12, 0.29] | 0.10 | 0.80 | 84.16 | .428 |
6 | RC > LC vmPFC | age | fixed | 0.12 [-0.12, 0.35] | 0.12 | 0.97 | 74.20 | .333 |
6 | RC > LC vmPFC | gender | fixed | 1.02 [-1.30, 3.34] | 1.17 | 0.87 | 73.81 | .385 |
6 | RC > LC vmPFC | condition | fixed | -1.06 [-2.74, 0.61] | 0.84 | -1.26 | 77.28 | .211 |
6 | RC > LC vmPFC | time x neural predictor | fixed | -0.07 [-0.59, 0.45] | 0.27 | -0.26 | 148.40 | .792 |
6 | RC > LC vmPFC | participant | random | 2.18 (variance) | – | – | – | – |
6 | RC > LC vmPFC | residual | random | 5.01 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | intercept | fixed | 11.12 [8.76, 13.48] | 1.19 | 9.38 | 81.89 | < .001 |
7 | RC > LC parahippocampal gyrus | time | fixed | 0.31 [0.02, 0.59] | 0.14 | 2.13 | 149.33 | .035 |
7 | RC > LC parahippocampal gyrus | neural predictor | fixed | -0.85 [-2.36, 0.67] | 0.77 | -1.10 | 134.38 | .271 |
7 | RC > LC parahippocampal gyrus | BMI | fixed | 0.08 [-0.13, 0.29] | 0.11 | 0.75 | 85.44 | .454 |
7 | RC > LC parahippocampal gyrus | age | fixed | 0.11 [-0.13, 0.35] | 0.12 | 0.94 | 74.69 | .352 |
7 | RC > LC parahippocampal gyrus | gender | fixed | 1.06 [-1.25, 3.37] | 1.16 | 0.91 | 74.73 | .363 |
7 | RC > LC parahippocampal gyrus | condition | fixed | -1.11 [-2.81, 0.59] | 0.86 | -1.30 | 78.49 | .198 |
7 | RC > LC parahippocampal gyrus | time x neural predictor | fixed | 0.39 [-0.03, 0.81] | 0.21 | 1.86 | 146.59 | .065 |
7 | RC > LC parahippocampal gyrus | participant | random | 2.33 (variance) | – | – | – | – |
7 | RC > LC parahippocampal gyrus | residual | random | 4.91 (variance) | – | – | – | – |
8 | RC > LC l IFG | intercept | fixed | 11.15 [8.71, 13.59] | 1.23 | 9.09 | 84.89 | < .001 |
8 | RC > LC l IFG | time | fixed | 0.30 [0.01, 0.59] | 0.15 | 2.07 | 150.72 | .040 |
8 | RC > LC l IFG | neural predictor | fixed | -0.32 [-1.12, 0.48] | 0.40 | -0.79 | 134.50 | .429 |
8 | RC > LC l IFG | BMI | fixed | 0.09 [-0.12, 0.30] | 0.11 | 0.82 | 85.93 | .413 |
8 | RC > LC l IFG | age | fixed | 0.11 [-0.13, 0.34] | 0.12 | 0.89 | 75.05 | .377 |
8 | RC > LC l IFG | gender | fixed | 1.05 [-1.32, 3.42] | 1.19 | 0.88 | 78.10 | .380 |
8 | RC > LC l IFG | condition | fixed | -1.15 [-2.87, 0.57] | 0.86 | -1.33 | 78.69 | .186 |
8 | RC > LC l IFG | time x neural predictor | fixed | 0.11 [-0.12, 0.34] | 0.11 | 0.96 | 149.79 | .338 |
8 | RC > LC l IFG | participant | random | 2.21 (variance) | – | – | – | – |
8 | RC > LC l IFG | residual | random | 4.98 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | intercept | fixed | 11.07 [8.74, 13.40] | 1.17 | 9.44 | 82.12 | < .001 |
9 | RC > LC l supramarginal gyrus | time | fixed | 0.29 [0.00, 0.58] | 0.15 | 2.01 | 150.88 | .047 |
9 | RC > LC l supramarginal gyrus | neural predictor | fixed | 0.33 [-1.09, 1.76] | 0.72 | 0.46 | 131.03 | .644 |
9 | RC > LC l supramarginal gyrus | BMI | fixed | 0.06 [-0.15, 0.28] | 0.11 | 0.59 | 87.75 | .560 |
9 | RC > LC l supramarginal gyrus | age | fixed | 0.11 [-0.13, 0.34] | 0.12 | 0.90 | 74.60 | .373 |
9 | RC > LC l supramarginal gyrus | gender | fixed | 1.11 [-1.18, 3.39] | 1.15 | 0.97 | 74.74 | .337 |
9 | RC > LC l supramarginal gyrus | condition | fixed | -1.09 [-2.76, 0.59] | 0.84 | -1.29 | 78.47 | .201 |
9 | RC > LC l supramarginal gyrus | time x neural predictor | fixed | 0.07 [-0.31, 0.45] | 0.19 | 0.38 | 139.76 | .706 |
9 | RC > LC l supramarginal gyrus | participant | random | 2.18 (variance) | – | – | – | – |
9 | RC > LC l supramarginal gyrus | residual | random | 5.00 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | intercept | fixed | 11.09 [8.76, 13.42] | 1.17 | 9.46 | 82.06 | < .001 |
10 | RC > LC l cerebellum | time | fixed | 0.30 [0.01, 0.59] | 0.15 | 2.07 | 150.87 | .040 |
10 | RC > LC l cerebellum | neural predictor | fixed | 0.58 [-0.98, 2.13] | 0.78 | 0.73 | 132.04 | .464 |
10 | RC > LC l cerebellum | BMI | fixed | 0.09 [-0.12, 0.29] | 0.10 | 0.83 | 85.17 | .411 |
10 | RC > LC l cerebellum | age | fixed | 0.11 [-0.13, 0.35] | 0.12 | 0.93 | 75.88 | .355 |
10 | RC > LC l cerebellum | gender | fixed | 1.09 [-1.19, 3.38] | 1.15 | 0.95 | 74.80 | .344 |
10 | RC > LC l cerebellum | condition | fixed | -1.11 [-2.79, 0.58] | 0.85 | -1.31 | 78.08 | .194 |
10 | RC > LC l cerebellum | time x neural predictor | fixed | -0.22 [-0.70, 0.26] | 0.24 | -0.89 | 154.67 | .373 |
10 | RC > LC l cerebellum | participant | random | 2.18 (variance) | – | – | – | – |
10 | RC > LC l cerebellum | residual | random | 4.99 (variance) | – | – | – | – |
11 | RC > LC midbrain | intercept | fixed | 11.05 [8.70, 13.41] | 1.18 | 9.33 | 80.84 | < .001 |
11 | RC > LC midbrain | time | fixed | 0.30 [0.01, 0.58] | 0.14 | 2.05 | 149.31 | .042 |
11 | RC > LC midbrain | neural predictor | fixed | -0.58 [-2.05, 0.89] | 0.74 | -0.78 | 128.58 | .438 |
11 | RC > LC midbrain | BMI | fixed | 0.08 [-0.13, 0.29] | 0.11 | 0.76 | 84.19 | .450 |
11 | RC > LC midbrain | age | fixed | 0.12 [-0.12, 0.35] | 0.12 | 0.97 | 74.33 | .336 |
11 | RC > LC midbrain | gender | fixed | 1.13 [-1.19, 3.45] | 1.16 | 0.97 | 73.82 | .335 |
11 | RC > LC midbrain | condition | fixed | -1.09 [-2.78, 0.60] | 0.85 | -1.28 | 77.42 | .203 |
11 | RC > LC midbrain | time x neural predictor | fixed | 0.19 [-0.21, 0.60] | 0.20 | 0.94 | 142.15 | .347 |
11 | RC > LC midbrain | participant | random | 2.27 (variance) | – | – | – | – |
11 | RC > LC midbrain | residual | random | 4.96 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | intercept | fixed | 11.08 [8.74, 13.41] | 1.17 | 9.44 | 82.08 | < .001 |
12 | RC > LC r supramarginal gyrus | time | fixed | 0.30 [0.02, 0.59] | 0.15 | 2.08 | 150.94 | .039 |
12 | RC > LC r supramarginal gyrus | neural predictor | fixed | 0.77 [-0.73, 2.27] | 0.76 | 1.02 | 134.10 | .311 |
12 | RC > LC r supramarginal gyrus | BMI | fixed | 0.08 [-0.13, 0.29] | 0.11 | 0.78 | 86.58 | .437 |
12 | RC > LC r supramarginal gyrus | age | fixed | 0.12 [-0.12, 0.36] | 0.12 | 1.00 | 75.73 | .320 |
12 | RC > LC r supramarginal gyrus | gender | fixed | 1.13 [-1.16, 3.41] | 1.15 | 0.98 | 74.71 | .330 |
12 | RC > LC r supramarginal gyrus | condition | fixed | -1.15 [-2.83, 0.54] | 0.85 | -1.35 | 78.45 | .179 |
12 | RC > LC r supramarginal gyrus | time x neural predictor | fixed | -0.16 [-0.60, 0.29] | 0.22 | -0.70 | 149.71 | .488 |
12 | RC > LC r supramarginal gyrus | participant | random | 2.20 (variance) | – | – | – | – |
12 | RC > LC r supramarginal gyrus | residual | random | 4.99 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | intercept | fixed | 11.28 [8.95, 13.61] | 1.17 | 9.61 | 83.45 | < .001 |
13 | RC > LC r posterior MFG | time | fixed | 0.27 [-0.01, 0.56] | 0.15 | 1.88 | 153.06 | .062 |
13 | RC > LC r posterior MFG | neural predictor | fixed | -1.80 [-3.50, -0.09] | 0.86 | -2.08 | 136.97 | .039 |
13 | RC > LC r posterior MFG | BMI | fixed | 0.10 [-0.11, 0.31] | 0.10 | 0.95 | 85.89 | .347 |
13 | RC > LC r posterior MFG | age | fixed | 0.11 [-0.13, 0.34] | 0.12 | 0.90 | 75.87 | .368 |
13 | RC > LC r posterior MFG | gender | fixed | 0.79 [-1.52, 3.09] | 1.16 | 0.68 | 75.84 | .499 |
13 | RC > LC r posterior MFG | condition | fixed | -0.93 [-2.60, 0.74] | 0.84 | -1.11 | 79.01 | .270 |
13 | RC > LC r posterior MFG | time x neural predictor | fixed | 0.41 [-0.08, 0.91] | 0.25 | 1.64 | 152.28 | .103 |
13 | RC > LC r posterior MFG | participant | random | 2.18 (variance) | – | – | – | – |
13 | RC > LC r posterior MFG | residual | random | 4.94 (variance) | – | – | – | – |
14 | average anatomical ROIs | intercept | fixed | 11.23 [8.84, 13.62] | 1.20 | 9.35 | 81.87 | < .001 |
14 | average anatomical ROIs | time | fixed | 0.30 [0.01, 0.59] | 0.15 | 2.05 | 150.31 | .043 |
14 | average anatomical ROIs | neural predictor | fixed | -0.86 [-3.54, 1.82] | 1.36 | -0.63 | 133.72 | .528 |
14 | average anatomical ROIs | BMI | fixed | 0.09 [-0.12, 0.30] | 0.11 | 0.86 | 84.34 | .394 |
14 | average anatomical ROIs | age | fixed | 0.11 [-0.12, 0.35] | 0.12 | 0.95 | 74.79 | .343 |
14 | average anatomical ROIs | gender | fixed | 0.91 [-1.45, 3.28] | 1.19 | 0.77 | 75.10 | .444 |
14 | average anatomical ROIs | condition | fixed | -1.07 [-2.75, 0.61] | 0.84 | -1.27 | 78.02 | .207 |
14 | average anatomical ROIs | time x neural predictor | fixed | 0.11 [-0.61, 0.83] | 0.36 | 0.31 | 141.48 | .760 |
14 | average anatomical ROIs | participant | random | 2.20 (variance) | – | – | – | – |
14 | average anatomical ROIs | residual | random | 5.00 (variance) | – | – | – | – |
15 | average peak ROIs | intercept | fixed | 11.07 [8.71, 13.44] | 1.19 | 9.33 | 82.27 | < .001 |
15 | average peak ROIs | time | fixed | 0.29 [0.00, 0.58] | 0.15 | 2.01 | 150.47 | .047 |
15 | average peak ROIs | neural predictor | fixed | -0.67 [-2.81, 1.47] | 1.08 | -0.62 | 130.81 | .537 |
15 | average peak ROIs | BMI | fixed | 0.08 [-0.13, 0.29] | 0.11 | 0.76 | 86.29 | .448 |
15 | average peak ROIs | age | fixed | 0.11 [-0.12, 0.35] | 0.12 | 0.95 | 75.22 | .346 |
15 | average peak ROIs | gender | fixed | 1.09 [-1.23, 3.41] | 1.16 | 0.94 | 75.14 | .351 |
15 | average peak ROIs | condition | fixed | -1.07 [-2.75, 0.62] | 0.85 | -1.26 | 78.43 | .211 |
15 | average peak ROIs | time x neural predictor | fixed | 0.31 [-0.29, 0.92] | 0.31 | 1.02 | 146.28 | .309 |
15 | average peak ROIs | participant | random | 2.24 (variance) | – | – | – | – |
15 | average peak ROIs | residual | random | 4.97 (variance) | – | – | – | – |