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The ventral premotor cortex (PMv) is an important component of cortico-cortical pathways mediating prefrontal control over primary motor cortex (M1) function. Paired associative stimulation (ccPAS) is known to change PMv influence over M1 in humans, which manifests differently depending on the behavioural context. Here we show that these changes in influence are functionally linked to PMv-M1 phase synchrony changes induced by repeated paired stimulation of the two areas. PMv-to-M1 ccPAS leads to increased phase synchrony in alpha and beta bands while reversed order M1-to-PMv ccPAS leads to decreased theta phase synchrony. These changes are visible at rest but they are predictive of changes in oscillatory power in the same frequencies during movement execution and inhibition, respectively. The results unveil a link between the physiology of the motor network and the resonant frequencies mediating its interactions, and provide a putative mechanism underpinning the relationship between synaptic efficacy and brain oscillations.

Humans learn about the environment either directly by interacting with it or indirectly by seeking information about it from social sources such as conspecifics. The degree of confidence in the information obtained through either route should determine the impact that it has on adapting and changing behaviour. We examined whether and how behavioural and neural computations differ during non-social learning as opposed to learning from social sources. Trial-wise confidence judgments about non-social and social information sources offered a window into this learning process. Despite matching exactly the statistical features of social and non-social conditions, confidence judgments were more accurate and less changeable when they were made about social as opposed to non-social information sources. In addition to subjective reports of confidence, differences were also apparent in the Bayesian estimates of participants’ subjective beliefs. Univariate activity in dorsomedial prefrontal cortex (dmPFC) and posterior temporo-parietal junction (pTPJ) more closely tracked confidence about social as opposed to non-social information sources. In addition, the multivariate patterns of activity in the same areas encoded identities of social information sources compared to non-social information sources.

SummaryOscillatory activity may reflect interactions between brain areas[1]. Here we tested whether inducing corticocortical plasticity in a specific set of connections changes oscillatory activity and cortico-cortical interactions and, if this is the case, whether the changes manifest in a manner that is behaviour state-dependent. We either increased or decreased the influence of activity in human ventral premotor cortex (PMv) over activity in primary motor cortex (M1) using cortico-cortical paired associative stimulation (ccPAS)[2, 3]. Before and after stimulation participants performed a Go/No-Go task. While M1 TMS pulses revealed the excitatory state of the motor system at specific time points, the electroencephalogram (EEG) revealed the evolution of oscillatory activity dynamics in the motor system over several hundreds of milliseconds before, during, and after each movement. Augmenting cortical connectivity between PMv and M1, by evoking synchronous pre- and postsynaptic activity in the PMv-M1 pathways, led to a state-dependent modulation of the causal influence of PMv over M1, and at the same time, enhanced oscillatory beta and theta rhythms in Go and No-Go trials, respectively. No changes were observed in the alpha rhythm. The plasticity induction effect was dependent on PMv-M1 stimulation order; the opposite patterns of results were observed after an equal amount of stimulation of PMv and M1 but applied in a temporal pattern that did not augment PMv’s influence over M1. These results are consistent with Hebbian principles of synaptic plasticity[4] and show that artificial manipulation of cortico-cortical connectivity produces state-dependent functional changes in the spectral fingerprints of the motor circuit.

Social behaviour is coordinated by a network of brain regions, including those involved in the perception of social stimuli and those involved in complex functions like inferring perceptual and mental states and controlling social interactions. The properties and function of many of these regions in isolation is relatively well understood but little is known about how these regions interact whilst processing dynamic social interactions. To investigate whether social network connectivity is modulated by social context we collected fMRI data from monkeys viewing “affiliative”, “aggressive”, or “ambiguous” social interactions. We show activation relating to the perception of social interactions along both banks of the superior temporal sulcus, parietal, medial and lateral PFC and caudate nucleus. Within this network we demonstrate that fronto-temporal connectivity are significantly modulated by social context. Crucially, we link the observation of specific behaviours to changes in connectivity within our network. Viewing aggressive or affiliative behaviour was associated with a limited increase in temporo-temporal and premotor-temporal connectivity respectively. By contrast, viewing ambiguous interactions was associated with a pronounced increase in cingulate-cingulate, temporo-temporal, and cingulate-temporal connectivity. We hypothesise that this widespread network synchronisation occurs when cingulate and temporal areas coordinate their activity when more difficult social inferences are made.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience.Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMate Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 13 independent data collections aggregated across 11 sites (total = 98 macaque monkeys). We also outline the unique pitfalls and challenges that should be considered in the analysis of the non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.