We propose a circuit-level principal underlying how brains acquire 'episodic' memories and reprocess them into compact, efficient 'schemas': The attributes or 'contents' of experience are represented primarily in the deeper layers of neocortex (NC), whereas the superficial layers are dedicated to encoding the contexts in which the attributes occur.
Project Summary A fundamental gap in our knowledge of the nervous system is understanding how variations in wiring and connectivity of neuronal circuits relate to variability in neural computations and behavior. This gap has arisen because anatomical connectivity and function are typically studied separately. Here, we will assemble a team of researchers with complementary skills to tackle this problem.
Project Summary / Abstract This grant focuses on how very recent experiences––over the past few seconds to minutes––allow brains to update expectations about the world and then use these expectations to guide behavior. The ability to flexibly adjust one's course of action in this manner is a hallmark of adaptive human behavior. At the neural level, relevant cellular-activity correlates have been described in non-human primates and other vertebrate model systems.
The ability to generate complex motor behaviors by assembling sequences of movements is essential for purposeful actions and survival. Defects in the brain regions thought to drive such movement selection can lead to behaviors becoming abnormally repetitive (e.g. autism spectrum disorder). Yet, the neural circuit architectures that underlie this fundamental function of the nervous system remain poorly understood. A central model of a neural circuit architecture that can account for how movements are assembled into sequences has emerged from studies across multiple species.
Project summary The plight of the neuroscientist trying to understand the brain using linear analysis methods is akin to studying the makeup of the ocean using the bits you find with a metal detector. Everything we know about the neural basis of decision making, from biology to computation to behavior, makes it clear that the relationship between neurons and behavior is profoundly nonlinear. However, for good mathematical reasons, our attempts to understand that relationship typically rely only on linear measures.
PROJECT SUMMARY How does the brain balance the need to preserve prior knowledge with the necessity to continuously learn new information? The tradeoff between stability and plasticity is inherent in both biological and artificial learning systems constrained by finite resources and capacity. The hippocampus is a brain region critical for memory formation and spatial learning, which can provide a powerful experimental system for characterizing this tradeoff.
Project summary Vision plays a key role in our ability to navigate through the environment, from identifying landmarks and obstacles to determining location and heading. While studies of visual cortex have provided an understanding of properties such as orientation selectivity and object recognition, much less is known about how cortical circuitry extracts and processes features from the visual scene to support navigation. In particular, there are two challenges.
Project Summary The goal of the proposed research is to probe object-recognition circuitry in inferotemporal cortex by specific manipulations of early visual experience. In adult humans and monkeys discrete regions of the temporal lobe are specialized for processing particular object categories, such as faces, text, bodies, or places. These domains underlie complex object recognition. Visual experience of these categories is both necessary and sufficient to produce domains, and the goal is to explore how specific abnormal early visual experience changes neuronal selectivity.
ABSTRACT The remarkable efficiency of human perception derives from the fact that we do not process each stimulus as a novel event. Instead, past experiences and scene context inform internal, working models of the world that allow us to generate predictions for our physical environment. A leading theory suggests that perceptual predictions are accomplished via flexible normalization: local inhibitory neuronal populations are regulated by long-range connections so that responses are suppressed when they do not provide helpful information about object boundaries.
SUMMARY It is our long-term goal to understand computations that underlie sensori-motor transformations in the context of thermoregulatory behaviors. Generating appropriate behaviors in response to sensory stimuli is critical for the survival of any animal. Larval zebrafish will be used for these studies as it is the only vertebrate model which allows comprehensive identification and manipulation of thermoregulatory circuits. Importantly, larval zebrafish is an ectotherm animal and therefore exclusively relies on thermal gradient navigation for thermoregulation.
