Passive perceptual learning modulates motor inhibitory control in superior frontal regions

Subregional prefrontal cortex recruitment as a function of inhibitory demand: an fMRI metanalysis

Convergent studies corroborated the idea that the right prefrontal cortex is the crucial brain region responsible for inhibiting our actions. However, which sub-regions of the right prefrontal cortex are involved is still a matter of debate. To map the inhibitory function of the sub-regions of the right prefrontal cortex, we performed Activation Likelihood Estimation (ALE) meta-analyses and meta-regressions (ES-SDM) of fMRI studies exploring inhibitory control. Sixty-eight studies (1684 subjects, 912 foci) were identified and divided in three groups depending on the incremental demand. Overall, our results showed that higher was the inhibitory demand based on the individual differences in performances, more the upper portion of the right prefrontal cortex was activated to achieve a successful inhibition. Conversely, a lower demand of the inhibitory function, was associated with the inferior portions of the right prefrontal cortex recruitment. Notably, in the latter case, we also observed activation of areas associated with working memory and responsible for cognitive strategies.

Perception-action integration during inhibitory control is reflected in a concomitant multi-region processing of specific codes in the neurophysiological signal

The integration of perception and action has long been studied in psychological science using overarching cognitive frameworks. Despite these being very successful in explaining perception-action integration, little is known about its neurophysiological and especially the functional neuroanatomical foundations. It is unknown whether distinct brain structures are simultaneously involved in the processing of perception-action integration codes and also to what extent demands on perception-action integration modulate activities in these structures. We investigate these questions in an EEG study integrating temporal and ICA-based EEG signal decomposition with source localization. For this purpose, we used data from 32 healthy participants who performed a 'TEC Go/Nogo' task. We show that the EEG signal can be decomposed into components carrying different informational aspects or processing codes relevant for perception-action integration. Importantly, these specific codes are processed independently in different brain structures, and their specific roles during the processing of perception-action integration differ. Some regions (i.e., the anterior cingulate and insular cortex) take a 'default role' because these are not modulated in their activity by demands or the complexity of event file coding processes. In contrast, regions in the motor cortex, middle frontal, temporal, and superior parietal cortices were not activated by 'default' but revealed modulations depending on the complexity of perception-action integration (i.e., whether an event file has to be reconfigured). Perception-action integration thus reflects a multi-region processing of specific fractions of information in the neurophysiological signal. This needs to be taken into account when further developing a cognitive science framework detailing perception-action integration.

Effect of NEUROG3 polymorphism rs144643855 on regional spontaneous brain activity in major depressive disorder

PURPOSE

Our previous study identified a significant association between a single nucleotide polymorphism (SNP) located in the neurogenin3 (NEUROG3) gene and post-stroke depression (PSD) in Chinese populations. The present work explores whether polymorphism rs144643855 affects regional brain activity and clinical phenotypes in major depressive disorder (MDD).

METHOD

A total of 182 participants were included: 116 MDD patients and 66 normal controls. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning at baseline. Spontaneous brain activity was assessed using amplitude of low-frequency fluctuation (ALFF). The Hamilton Depression Scale-24 (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS) were used to assess participants at baseline. Two-way analysis of covariance (ANCOVA) was used to explore the interaction between diagnostic groups and NEUROG3 rs144643855 on regional brain activity. We performed correlation analysis to further test the association between these interactive brain regions and clinical manifestations of MDD.

RESULTS

Genotype and disease significantly interacted in the left inferior frontal gyrus (IFG-L), right superior frontal gyrus (SFG-R), and left paracentral lobule (PCL-L) (P < 0.05). ALFF values of the IFG-L were found to be significantly associated with anhedonia in MDD patients.

CONCLUSION

These findings suggest a potential relationship between rs144643855 variations and altered frontal brain activity in MDD. NEUROG3 may play an important role in the neuropathophysiology of MDD.

Neurophysiological correlates of perception-action binding in the somatosensory system

Action control requires precisely and flexibly linking sensory input and motor output. This is true for both, visuo-motor and somatosensory-motor integration. However, while perception–action integration has been extensively investigated for the visual modality, data on how somatosensory and action-related information is associated are scarce. We use the Theory of Event Coding (TEC) as a framework to investigate perception–action integration in the somatosensory-motor domain. Based on studies examining the neural mechanisms underlying stimulus–response binding in the visuo-motor domain, the current study investigates binding mechanisms in the somatosensory-motor domain using EEG signal decomposition and source localization analyses. The present study clearly demonstrates binding between somatosensory stimulus and response features. Importantly, repetition benefits but no repetition costs are evident in the somatosensory modality, which differs from findings in the visual domain. EEG signal decomposition indicates that response selection mechanisms, rather than stimulus-related processes, account for the behavioral binding effects. This modulation is associated with activation differences in the left superior parietal cortex (BA 7), an important relay of sensorimotor integration.

Passive perceptual learning modulates motor inhibitory control in superior frontal regions

Response inhibition is of vital importance in the context of controlling inappropriate responses. The role of perceptual processes during inhibitory control has attracted increased interest. Yet, we are far from an understanding of the mechanisms. One candidate mechanism by which perceptual processes may affect response inhibition refers to “gain control” that is closely linked to the signal‐to‐noise ratio of incoming information. A means to modulate the signal‐to‐noise ratio and gain control mechanisms is perceptual learning. In the current study, we examine the impact of perceptual learning (i.e., passive repetitive sensory stimulation) on response inhibition combining EEG signal decomposition with source localization analyses. A tactile GO/NOGO paradigm was conducted to measure action restraint as one subcomponent of response inhibition. We show that passive perceptual learning modulates response inhibition processes. In particular, perceptual learning attenuates the detrimental effect of response automation during inhibitory control. Temporally decomposed EEG data show that stimulus‐related and not response selection processes during conflict monitoring are linked to these effects. The superior and middle frontal gyrus (BA6), as well as the motor cortex (BA4), are associated with the effects of perceptual learning on response inhibition. Reliable neurophysiological effects were not evident on the basis of standard ERPs, which has important methodological implications for perceptual learning research. The results detail how lower level sensory plasticity protocols affect higher‐order cognitive control functions in frontal cortical structures.