Table 2. Generalized linear mixed effects modeling details.

ID	Model	Akaike's information criterion (AIC)	k-Value	p-Value	R2
1	${\displaystyle \text{RT}\sim 1+k\times T\text{or}N+1|\text{SubID}}$	−1201.4	$k=-0.0158\pm 0.0072$	${\displaystyle \text{p}=0.0278}$	0.1893
2	${\displaystyle \text{RT}\sim 1+k\times \beta \text{LFP}+1|\text{SubID}}$	−1194.6	$k=0.0061\pm 0.0019$	${\displaystyle \text{p}=0.0011}$	0.1912
3	${\displaystyle \text{RT}\sim 1+k\times \text{Dur1LFP}+1|\text{SubID}}$	−1189.5	$k=0.0284\pm 0.0092$	${\displaystyle \text{p}=0.0021}$	0.1897
4	${\displaystyle \text{RT}\sim 1+k\times \text{Dur2LFP}+1|\text{SubID}}$	−1182.4	$k=0.0274\pm 0.0136$	${\displaystyle \text{p}=0.0436}$	0.1869
5	${\displaystyle \text{RT}\sim 1+k\times \text{NumLFP}+1|\text{SubID}}$	−1190	$k=0.0231\pm 0.0086$	${\displaystyle \text{p}=0.0074}$	0.1888
6	${\displaystyle \text{RT}\sim 1+k_1\times T\text{or}N+k_2\times \beta \text{LFP}+k_3\times \gamma \text{LFP}+k_4\times \alpha \text{LFP}+1|\text{SubID}}$	−1236.5	$k_1=-0.0152\pm 0.0071$ $k_2=0.0069\pm 0.0020$ $k_3=-0.0010\pm 0.0024$ $k_4=0.0003\pm 0.0013$	${\displaystyle {\text{p}}_1=0.0316}$ ${\displaystyle {\text{p}}_2=0.0008}$ ${\displaystyle {\text{p}}_3=0.00003}$ ${\displaystyle {\text{p}}_4=0.8365}$	0.2072
7	${\displaystyle \text{RT}\sim 1+k\times \beta \text{EEG}+1|\text{SubID}}$	−1195.7	$k=0.0074\pm 0.0019$	${\displaystyle \text{p}=0.0001}$	0.1924
8	${\displaystyle \text{RT}\sim 1+k_1\times T\text{or}N+k_2\times \beta \text{EEG}+k_3\times \alpha \text{EEG}+1|\text{SubID}}$	−1218.1	$k_1=-0.0158\pm 0.0071$ $k_2=0.0067\pm 0.0024$ $k_3=0.0007\pm 0.0016$	${\displaystyle {\text{p}}_1=0.0276}$ ${\displaystyle {\text{p}}_2=0.0058}$ ${\displaystyle {\text{p}}_3=0.6469}$	0.1965
9	${\displaystyle \text{RT}\sim 1+k_1\times T\text{or}N+k_2\times \beta \text{LFP}+k_3\times \gamma \text{LFP}+k_4\times \beta \text{EEG}+1|\text{SubID}}$	−1236.6	$k_1=-0.0154\pm 0.0071$ $k_2=0.0061\pm 0.0020$ $k_3=-0.0085\pm 0.0026$ $k_4=0.0029\pm 0.0022$	${\displaystyle {\text{p}}_1=0.0297}$ ${\displaystyle {\text{p}}_2=0.0017}$ ${\displaystyle {\text{p}}_3=0.0014}$ ${\displaystyle {\text{p}}_4=0.1948}$	0.2076

Response distribution: Inverse Gaussian.

Link function: identity.

T or N: ‘Training’ (valued 1) or ‘No Training’ (valued 0) conditions.

${\displaystyle \beta \text{LFP}}$: Average LFP beta power during the 2 s before the Go-cue.

${\displaystyle \text{Dur1LFP}}$: Accumulated LFP beta burst duration during the 2 s before the Go-cue.

${\displaystyle \text{Dur2LFP}}$: Average LFP beta burst duration during the 2 s before the Go-cue.

${\displaystyle \text{NumLFP}}$: LFP beta burst number during the 2 s before the Go-cue.

${\displaystyle \gamma \text{LFP}}$: Average LFP gamma (55–95 Hz) power during the 2 s before the Go-cue.

${\displaystyle \alpha \text{LFP}}$: Average LFP alpha (8–12 Hz) power during the 2 s before the Go-cue.

${\displaystyle \beta \text{EEG}}$: Average EEG beta power during the 2 s before the Go-cue.

${\displaystyle \alpha \text{EEG}}$: Average EEG alpha (8–12 Hz) power during the 2 s before the Go-cue.