Results of ANOVA.

Results of ANOVA.</p

Reaction time (left), coefficients of variation (middle) and lapses (right) in the Psychomotor Vigilance Test.

Name = name condition, Other-name = other’s name condition, and Cont = control condition (no sound), PVT: Psychomotor Vigilance Test, CV: coefficient of variation.</p

Table_1_Common Neural Network for Different Functions: An Investigation of Proactive and Reactive Inhibition.DOCX

Successful behavioral inhibition involves both proactive and reactive inhibition, allowing people to prepare for restraining actions, and cancel their actions if the response becomes inappropriate. In the present study, we utilized the stop-signal paradigm to examine whole-brain contrasts and functional connectivity for proactive and reactive inhibition. The results of our functional magnetic resonance imaging (fMRI) data analysis show that the inferior frontal gyrus (IFG), the supplementary motor area (SMA), the subthalamic nucleus (STN), and the primary motor cortex (M1) were activated by both proactive and reactive inhibition. We then created 70 dynamic causal models (DCMs) representing the alternative hypotheses of modulatory effects from proactive and reactive inhibition in the IFG-SMA-STN-M1 network. Bayesian model selection (BMS) showed that causal connectivity from the IFG to the SMA was modulated by both proactive and reactive inhibition. To further investigate the possible brain circuits involved in behavioral control, including proactive inhibitory processes, we compared 13 DCMs representing the alternative hypotheses of proactive modulation in the dorsolateral prefrontal cortex (DLPFC)-caudate-IFG-SMA neural circuits. BMS revealed that the effective connectivity from the caudate to the IFG is modulated only in the proactive inhibition condition but not in the reactive inhibition. Together, our results demonstrate how fronto-basal ganglia pathways are commonly involved in proactive and reactive inhibitory control, with a “longer” pathway (DLPFC-caudate-IFG-SMA-STN-M1) playing a modulatory role in proactive inhibitory control, and a “shorter” pathway (IFG-SMA-STN-M1) involved in reactive inhibition. These results provide causal evidence for the roles of indirect and hyperdirect pathways in mediating proactive and reactive inhibitory control.</p

Sample of test session.

KSS = Karolinska Sleepiness Scale, PVT = Psychomotor Vigilance Test. Visual stimuli for PVT were presented with random inter-stimulus intervals between 2–10 sec, while a sound was presented every 20 sec in the stimuli epochs. The order of the conditions was counterbalanced among the participants.</p

Time schedule of the experiment.

Name = name condition, Other-name = other’s name condition, and Cont = control condition (no sound). The order of the conditions was counterbalanced among the participants.</p

Spectral power densities in alpha (left) and theta (right) band frequencies.

Name = name condition, Other-name = other’s name condition, and Cont = control condition (no sound).</p

Anatomical identification of near-infrared spectroscopy channels.

The coordinates for all probe and anatomical landmark positions (Nz, Iz, A1, A2, Cz) were obtained using a 3-dimensional digitizer. Probabilistic registration was used to transcribe the measuring points for each subject according to the protocol of the Montreal Neurological Institute and those points were projected onto the cortical surface. Anatomical localization was identified using the Platform for Optical Topography Analysis Tools, with reference to the Automated Anatomical Labeling system. Orange, red, yellow, green, blue, and purple represent DLPFC (BA9), DLPFC (BA46), FPA (BA10), BA (BA45), OFC (BA11), and IPG (BA47), respectively. Each circle corresponds to a channel and the pie chart within each circle shows the percentages of areas in that channel.</p

Numbers of residual, lost, and prosthetic teeth in 12 elderly edentulous subjects.

<p>Numbers of residual, lost, and prosthetic teeth in 12 elderly edentulous subjects.</p

Masticatory scores for Tooth Loss, Wearing Denture, and Young.

<p>Masticatory scores for Tooth Loss, Wearing Denture, and Young.</p

Temporal changes under Tooth Loss and Wearing Denture conditions.

<p>The values for [oxy-Hb] during the pre-chewing period for Wearing Denture were significantly (two-way repeated measures ANOVA and Bonferroni t-test, p<0.05) increased for DLPFC (BA46), and FPA (BA10), and during the chewing period for DLPFC (BA9, BA46), FPA (BA10), BA (BA45), and OFC (BA11), and remained increased during the post-chewing period for DLPFC (BA9, BA46), FPA (BA10), BA (BA45), and OFC (BA11) as compared to Tooth Loss. Significant differences between the conditions are indicated by a blue bar.</p