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. Synaptic associations between superficial context codes and deep attribute codes permit contexts to evoke appropriate attribute output hence enabling memory recall and predictive behavior. The hippocampus (HC) is essential for acquisition of memories and for their reprocessing into efficient, schematic representations of the world. NC exhibits dense local but sparse long-range connectivity, which severely limits its ability to make rapid, long-range associations. HC likely solves this dilemma by merging the totality of the brain's current internal state (i.e., sensory input and internal variables such as hunger, fear, current goals) into a unique, 'index' code that is projected to NC, and associated with its current, distributed, attribute representation. Retrieval of an index code evokes the corresponding attributes. Such HC-orchestrated retrieval may enable the gradual rewiring of NC circuitry in a manner that captures the overall statistics of experience, much the same way as deep, artificial, neural networks learn incrementally by small connection weight adjustments directed by the overall statistics of the input. Our hypothesis on the laminar division of labor in this process is based on the facts that HC output is directed primarily to upper layers of NC, which implements a 'spatial' coding scheme that is lost after HC lesions; and that the deeper layers of NC frequently exhibit more robust responsiveness to and discrimination of sensory inputs than the superficial ones. We propose to record cellular level, neural ensemble activity simultaneously from deep and superficial layers in primary and association cortex, using high-density, electrophysiological recording. First, we attempt to establish the 'attribute vs index' principal by showing that deep cells shift their firing locations with shifts in the relevant sensory attributes, whereas superficial cells do not. Next we test the hypothesis that, as NC accumulates large amounts of diverse experience, attribute representations in deeper layers becomes sparser and more categorically organized, whereas superficial layer coding is relatively unchanged. To accomplish this, we employ a recent chemogenetic advance that enables us to acquire large amounts of resting-state cellular data, in which we expect the predicted changes will be most easily observed. We also explore the statistics of excitatory-inhibitory cell functional connectivity that may underlie such coding statistics changes. The expected advances in understanding cortical memory and schema encoding circuits will ultimately improve clinical assessment of, and intervention in memory and cognitive disorders.

This project uses advanced electrophysiological neural ensemble recording to test circuit-level hypotheses about the fundamental interactions between the hippocampal formation and the neocortex that enables episodic memories to be captured quickly and subsequently consolidated into efficient schemas for adaptive behavior. The overarching hypothesis is that the laminar structure of neocortex is optimized to subserve a particular type of information representation, in which the global context of experiences is encoded in sparse activity patterns in Layer II-III that are derived from the output of the hippocampal formation and that associatively link together the attributes (i.e., content) of experience, which are represented more densely in the deeper layers (Layer V). Overall, these experiments will shed new light on the cortex-wide, circuit-level details of how memory works, leading ultimately to improved interventions in cases of memory impairment due to trauma, disease and the aging process and other cognitive deficits such as schizophrenia and autism spectrum disorders.