Dynamics of neural microstates in the VTA-striatal-prefrontal loop during novelty exploration in the rat

Abstract EEG microstates refer to quasi-stable spatial patterns of scalp potentials, and their dynamics have been linked to cognitive and behavioral states. Neural activity at single and multiunit levels also exhibit spatiotemporal coordination, but this spatial scale is difficult to relate to EEG. Here, we translated EEG microstate analysis to triple-area local field potential (LFP) recordings from up to 192 electrodes in rats to investigate the mesoscopic dynamics of neural microstates within and across brain regions. We performed simultaneous recordings from the prefrontal cortex (PFC), striatum (STR), and ventral tegmental area (VTA) during awake behavior (object novelty and exploration). We found that the LFP data can be accounted for by multiple, recurring, quasi-stable spatial activity patterns with an average period of stability of ~60-100 ms. The top four maps accounted for 60-80% of the total variance, compared to ~25% for shuffled data. Cross-correlation of the microstate time-series across brain regions revealed rhythmic patterns of microstate activations, which we interpret as a novel indicator of inter-regional, mesoscale synchronization. Furthermore, microstate features, and patterns of temporal correlations across microstates, were modulated by behavioural states such as movement and novel object exploration. These results support the existence of a functional mesoscopic organization across multiple brain areas, and open up the opportunity to investigate their relation to EEG microstates, of particular interest to the human research community. Significance Statement The coordination of neural activity across the entire brain has remained elusive. Here we combine large-scale neural recordings at fine spatial resolution with the analysis of microstates, i.e. short-lived, recurring spatial patterns of neural activity. We demonstrate that the local activity in different brain areas can be accounted for by only a few microstates per region. These microstates exhibited temporal dynamics that were correlated across regions in rhythmic patterns. We demonstrate that these microstates are linked to behavior and exhibit different properties in the frequency domain during different behavioural states. In summary, LFP microstates provide an insightful approach to studying both mesoscopic and large-scale brain activation within and across regions.