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•We investigate the function of rIFC and preSMA based on the PTC model.•The rIFC activation was associated with the delay of the go process.•The activation in the preSMA predicted the inhibition efficiency.•The findings provide insights into the neural mechanism of response inhibition. Response inhibition is an essential component of cognitive function. A large body of literature has used neuroimaging data to uncover the neural architecture that regulates inhibitory control in general and movement cancelation. The presupplementary motor area (preSMA) and the right inferior frontal cortex (rIFC) are the key nodes in the inhibitory control network. However, how these two regions contribute to response inhibition remains controversial. Based on the Pause-then-Cancel Model (PTC), this study employed functional magnetic resonance imaging (fMRI) to investigate the functional specificity of two regions in the stopping process. The Go/No-Go task (GNGT) and the Stop Signal Task (SST) were administered to the same group of participants. We used the GNGT to dissociate the pause process and both the GNGT and the SST to investigate the inhibition mechanism. Imaging data revealed that response inhibition produced by both tasks activated the preSMA and rIFC. Furthermore, an across-participants analysis showed that increased activation in the rIFC was associated with a delay in the go response in the GNGT. In contrast, increased activation in the preSMA was associated with good inhibition efficiency via the striatum in both GNGT and SST. These behavioral and imaging findings support the PTC model of the role of rIFC and preSMA, that the former is involved in a pause process to delay motor responses, whereas the preSMA is involved in the stopping of motor responses.

Recent evidence suggests that presupplementary motor area (pre‐SMA) and inferior frontal gyrus (IFG) play an important role in response inhibition. However, no study has investigated the relationship between these brain networks at resting‐state and response inhibition in obsessive–compulsive disorder (OCD). We performed resting‐state functional magnetic resonance imaging scans and then measured the response inhibition of 41 medication‐free OCD patients and 49 healthy control (HC) participants by using the stop‐signal task outside the scanner. We explored the differences between OCD and HC groups in the functional connectivity of pre‐SMA and IFG associated with the ability of motor response inhibition. OCD patients showed a longer stop‐signal reaction time (SSRT). Compared to HC, OCD patients exhibit different associations between the ability of motor response inhibition and the functional connectivity between pre‐SMA and IFG, inferior parietal lobule, dorsal anterior cingulate cortex, insula, and anterior prefrontal cortex. Additional analysis to investigate the functional connectivity difference from the seed ROIs to the whole brain voxels revealed that, compared to HC, OCD exhibited greater functional connectivity between pre‐SMA and IFG. Also, this functional connectivity was positively correlated with the SSRT score. These results provide additional insight into the characteristics of the resting‐state functional connectivity of the regions belonging to the cortico‐striato‐thalamo‐cortical circuit and the cingulo‐opercular salience network, underlying the impaired motor response inhibition of OCD. In particular, we emphasize the importance of altered functional connectivity between pre‐SMA and IFG for the pathophysiology of motor response inhibition in OCD. Obsessive–compulsive disorder patients had significantly different associations between the abilities of motor response inhibition and the resting‐state functional connectivity from pre‐SMA to IPL, IFG, dACC and anterior‐insula. Additionally, compared to healthy control, OCD exhibited greater functional connectivity between pre‐SMA and IFG, and this functional connectivity was correlated with the the abilities of motor response inhibition.

Motor inhibitory control implemented as response inhibition is an essential cognitive function required to dynamically adapt to rapidly changing environments. Despite over a decade of research on the neural mechanisms of response inhibition, it remains unclear, how exactly response inhibition is initiated and implemented. Using a multimodal MEG/fMRI approach in 59 subjects, our results reliably reveal that response inhibition is initiated by the right inferior frontal gyrus (rIFG) as a form of attention-independent top-down control that involves the modulation of beta-band activity. Furthermore, stopping performance was predicted by beta-band power, and beta-band connectivity was directed from rIFG to pre-supplementary motor area (pre-SMA), indicating rIFG’s dominance over pre-SMA. Thus, these results strongly support the hypothesis that rIFG initiates stopping, implemented by beta-band oscillations with potential to open up new ways of spatially localized oscillation-based interventions.

Our confidence in a choice and the evidence pertaining to a choice appear to be inseparable. However, an emerging computational consensus holds that the brain should maintain separate estimates of these quantities for adaptive behavioral control. We have devised a psychophysical task to decouple confidence in a perceptual decision from both the reliability of sensory evidence and the relation of such evidence with respect to a choice boundary. Using human fMRI, we found that an area in the medial prefrontal cortex, the perigenual anterior cingulate cortex (pgACC), tracked expected performance, an aggregate signature of decision confidence, whereas neural areas previously proposed to encode decision confidence instead tracked sensory reliability (posterior parietal cortex and ventral striatum) or boundary distance (presupplementary motor area). Supporting that information encoded by pgACC is central to a subjective sense of decision confidence, we show that pgACC activity does not simply covary with expected performance, but is also linked to within-subject and between-subject variation in explicit confidence estimates. Our study is consistent with the proposal that the brain maintains choice-dependent and choice-independent estimates of certainty, and sheds light on why dysfunctional confidence often emerges following prefrontal lesions and/or degeneration.

Peripheral measures of autonomic nervous system (ANS) activity at rest have been extensively employed as putative biomarkers of autonomic cardiac control. However, a comprehensive characterization of the brain-based central autonomic network (CAN) sustaining cardiovascular oscillations at rest is missing, limiting the interpretability of these ANS measures as biomarkers of cardiac control. We evaluated combined cardiac and fMRI data from 34 healthy subjects from the Human Connectome Project to detect brain areas functionally linked to cardiovagal modulation at rest. Specifically, we combined voxel-wise fMRI analysis with instantaneous heartbeat and spectral estimates obtained from inhomogeneous linear point-process models. We found exclusively negative associations between cardiac parasympathetic activity at rest and a widespread network including bilateral anterior insulae, right dorsal middle and left posterior insula, right parietal operculum, bilateral medial dorsal and ventrolateral posterior thalamic nuclei, anterior and posterior mid-cingulate cortex, medial frontal gyrus/pre-supplementary motor area. Conversely, we found only positive associations between instantaneous heart rate and brain activity in areas including frontopolar cortex, dorsomedial prefrontal cortex, anterior, middle and posterior cingulate cortices, superior frontal gyrus, and precuneus. Taken together, our data suggests a much wider involvement of diverse brain areas in the CAN at rest than previously thought, which could reflect a differential (both spatially and directionally) CAN activation according to the underlying task. Our insight into CAN activity at rest also allows the investigation of its impairment in clinical populations in which task-based fMRI is difficult to obtain (e.g., comatose patients or infants). •We combine fMRI with instantaneous autonomic outflow estimates•The central autonomic network (CAN) sustains cardiovascular oscillations at rest•Cardio-vagal and CAN activities at rest are negatively correlated•CAN activity at rest involves much wider brain networks than previously thought

Our motor commands can be exquisitely timed according to the demands of the environment, and the ability to generate rhythms of different tempos is a hallmark of musical cognition. Yet, the neuronal underpinnings behind rhythmic tapping remain elusive. Here, we found that the activity of hundreds of primate medial premotor cortices (MPCs; pre-supplementary motor area [preSMA] and supplementary motor area [SMA]) neurons show a strong periodic pattern that becomes evident when their responses are projected into a state space using dimensionality reduction analysis. We show that different tapping tempos are encoded by circular trajectories that travelled at a constant speed but with different radii, and that this neuronal code is highly resilient to the number of participating neurons. Crucially, the changes in the amplitude of the oscillatory dynamics in neuronal state space are a signature of duration encoding during rhythmic timing, regardless of whether it is guided by an external metronome or is internally controlled and is not the result of repetitive motor commands. This dynamic state signal predicted the duration of the rhythmically produced intervals on a trial-by-trial basis. Furthermore, the increase in variability of the neural trajectories accounted for the scalar property, a hallmark feature of temporal processing across tasks and species. Finally, we found that the interval-dependent increments in the radius of periodic neural trajectories are the result of a larger number of neurons engaged in the production of longer intervals. Our results support the notion that rhythmic timing during tapping behaviors is encoded in the radial curvature of periodic MPC neural population trajectories.

Inhibitory control has been linked to beta oscillations in the fronto-basal ganglia network. Here we aim to investigate the functional role of the phase of this oscillatory beta rhythm for successful motor inhibition. We applied 20 Hz transcranial alternating current stimulation (tACS) to the pre-supplementary motor area (pre-SMA) while presenting stop signals at 4 (Experiment 1) and 8 (Experiment 2) equidistant phases of the tACS entrained beta oscillations. Participants showed better inhibitory performance when stop signals were presented at the trough of the beta oscillation whereas their inhibitory control performance decreased with stop signals being presented at the oscillatory beta peak. These results are consistent with the communication through coherence theory, in which postsynaptic effects are thought to be greater when an input arrives at an optimal phase within the oscillatory cycle of the target neuronal population. The current study provides mechanistic insights into the neural communication principles underlying successful motor inhibition and may have implications for phase-specific interventions aimed at treating inhibitory control disorders such as PD or OCD. •Motor inhibition performance cycles with beta oscillatory phase.•Trough of the beta cycle provides an optimal window for exerting inhibitory control.•Phase-locked stimulation could potentially enhance inhibitory control treatments.

In the primate brain, a set of areas in the ventrolateral frontal (VLF) cortex and the dorsomedial frontal (DMF) cortex appear to control vocalizations. The basic role of this network in the human brain and how it may have evolved to enable complex speech remain unknown. In the present functional neuroimaging study of the human brain, a multidomain protocol was utilized to investigate the roles of the various areas that comprise the VLF–DMF network in learning rule-based cognitive selections between different types of motor actions: manual, orofacial, nonspeech vocal, and speech vocal actions. Ventrolateral area 44 (a key component of the Broca’s language production region in the human brain) is involved in the cognitive selection of orofacial, as well as, speech and nonspeech vocal responses; and the midcingulate cortex is involved in the analysis of speech and nonspeech vocal feedback driving adaptation of these responses. By contrast, the cognitive selection of speech vocal information requires this former network and the additional recruitment of area 45 and the presupplementary motor area. We propose that the basic function expressed by the VLF–DMF network is to exert cognitive control of orofacial and vocal acts and, in the language dominant hemisphere of the human brain, has been adapted to serve higher speech function. These results pave the way to understand the potential changes that could have occurred in this network across primate evolution to enable speech production.

The dorsal mesial frontal cortex contains the supplementary motor area (SMA) and the pre-supplementary motor area (pre-SMA), which play an important role in action and cognition. Evidence from cytoarchitectonic, stimulation, and functional studies suggests structural and functional divergence between the two subregions. However, a microstructural map of these areas obtained in a representative sample of brains in a stereotaxic reference space is still lacking. In the present study we show that the dorsal mesial frontal motor cortex comprises two microstructurally different brain regions: area SMA and area pre-SMA. Area-specific cytoarchitectonic patterns were studied in serial histological sections stained for cell bodies of ten human postmortem brains. Borders of the two cortical areas were identified using image analysis and statistical features. The 3D reconstructed areas were transferred to a common reference space, and probabilistic maps were calculated by superimposing the individual maps. A coordinate-based meta-analysis of functional imaging data was subsequently performed using the two probabilistic maps as microstructurally defined seed regions. It revealed that areas SMA and pre-SMA were strongly co-activated with areas in precentral, supramarginal and superior frontal gyri, Rolandic operculum, thalamus, putamen and cerebellum. Both areas were related to motor functions, but area pre-SMA was involved in more complex processes such as learning, cognitive processes and perception. The here described subsequent analyses led to converging evidence supporting the microstructural, and functional segregation of areas SMA and pre-SMA, and maps will be made available to the scientific community to further elucidate the microstructural substrates of motor and cognitive control.

Based on prior findings of content-specific beta synchronization in working memory and decision making, we hypothesized that beta oscillations support the (re-)activation of cortical representations by mediating neural ensemble formation. We found that beta activity in monkey dorsolateral prefrontal cortex (dlPFC) and pre-supplementary motor area (preSMA) reflects the content of a stimulus in relation to the task context, regardless of its objective properties. In duration- and distance-categorization tasks, we changed the boundary between categories from one block of trials to the next. We found that two distinct beta-band frequencies were consistently associated with the two relative categories, with activity in these bands predicting the animals’ responses. We characterized beta at these frequencies as transient bursts, and showed that dlPFC and preSMA are connected via these distinct frequency channels. These results support the role of beta in forming neural ensembles, and further show that such ensembles synchronize at different beta frequencies. How the brain achieves context-dependent, flexible categorization remains poorly understood. By looking at neural ensemble formation, this study finds that distinct beta rhythms signal categorical decisions, and category-selective neurons synchronize at those frequencies.