Project Summary / Abstract Although BRAIN 2.0 called for the BRAIN Initiative to “prioritize diversity and inclusion as a fundamental pillar,” research with the human neuroimaging technologies being developed by BRAIN Initiative continues to rely on non-representative convenience samples.
PROJECT SUMMARY Within every brain region, neurons can be classified into dozens or hundreds of different cell types, each with unique functional roles and unique impacts on disease states. Traditionally, in vivo electrophysiological recordings—which have made invaluable contributions to our understanding of the neural basis of behavior— have not been able to distinguish the activity of genetically defined cell types.
PROJECT SUMMARY Sensory representations are influenced by an animal’s external context, internal state, past experiences, expectations, and future goals. Prior information – including the history of recent stimuli, actions and rewards – plays an important role in guiding ongoing behavior, and can modulate the neural code even at the level of primary sensory cortex. The involvement of sensory cortex in mediating history- dependent shifts in behavior, and the contributions of specific cell types to these effects are not well understood.
PROJECT SUMMARY To guide decisions, visual information must flow from primary visual cortex (V1) to prefrontal cortex (PFC), via multiple, parallel cortico-cortical and cortico-thalamo-cortical connections. Both V1 and PFC have direct connections with the pulvinar, a higher-order nucleus of the thalamus, but the role of this nucleus in sensory processing is still largely mysterious. Importantly, much of the pulvinar has no homologue in rodents or carnivores, which makes studying it in nonhuman primates all the more important.
PROJECT SUMMARY As we get older, we learn to modulate our behaviors to optimize reward outcomes. These adaptive choices are orchestrated by current sensory conditions, internal cognitive states, and future expectations. In adolescence, rewards circuits that link peripheral detection of sensory stimuli to central circuits involved in decision-making and motivational states continue to grow, remodeling the microcircuit connectivity within the medial prefrontal cortex (mPFC).
PROJECT SUMMARY/ABSTRACT Because neurons integrate and process information via modulation of their membrane potential, the ability to monitor voltage is critical to understanding how single and groups of neurons compute. Genetically encoded voltage indicators (GEVIs) —fluorescent proteins that report voltage dynamics as changes in brightness— are emerging as a preferred recording method because they can track voltage transients with high spatiotemporal resolution and cell type specificity.
Project Summary Social interactions are critical to the physical and emotional health of a wide variety of species. Perturbations in social functioning, a hallmark symptom of many psychiatric and neurodevelopmental disorders such as autism and schizophrenia, can profoundly impair an individual’s ability to sustain healthy social relations. While a growing body of literature has elucidated neural circuits for dyadic social interactions (interactions between two individuals), our understanding of higher order interactions at the level of larger groups is remarkably weak.
PROJECT SUMMARY Postnatal sensory experience has a profound effect on the maturation, composition, and connectivity of cortical cell types, but systematic analyses of these changes have not yet been feasible. This lack of methods for systematic analysis had made it difficult to define principles in how neural activity re-wires brain circuits and whether connectivity changes precede or follow molecular changes in brain cell types.
Project Summary Many social behaviors, such as defense and aggression, are innate- requiring no prior experience to be expressed and presumably ‘hardwired’ into neural circuits. Interestingly, however, these ‘hardwired’ behaviors vary in expression among individuals and can be altered by experience. What are the neural circuits and mechanisms that support such flexible expression of innate behaviors?
Abstract In recent years, the number of neurons that we can record simultaneously has seen an exponential increase, presenting a daunting challenge: how do we analyze these complex and high-dimensional datasets to gain insight into how neural circuits perform computation? Tools from dynamical systems theory have successfully unraveled the computational machinery of artificial recurrent neural networks (RNNs) trained to perform goal-directed tasks.
