Learning, Memory and Decision Making in the Mammalian Brain

We use rodent models to investigate the physiological mechanisms that underlie information processing and coordinated interactions between multiple brain regions that are necessary for memory and cognition. Several of our past studies have particular focused on hippocampal – prefrontal cortical interactions. The hippocampus is known to be critical for episodic memories, and the prefrontal cortex is involved in executive control, working memory and decision making. Communication between the prefrontal executive system and the hippocampal memory system is key for learning, remembering, planning, prediction and memory-guided decision making. However, the nature of communication between these two regions, the underling neural mechanisms and causal contributions of this pivotal interaction remain largely unknown.

We address these questions using a combination of techniques, including behavior, large scale multielectrode recordings in awake behaving animals, real time detection and perturbation of neural activity patterns, targeted optogenetic interventions, and computational analysis. We have shown that hippocampal replay during awake sharp-wave ripples (SWRs) is critical for spatial memory, and SWRs are associated with coordinated reactivation of hippocampal-prefrontal neurons during memory-guided decision making. This approach thus allows us to characterize the neurophysiological basis of hippocampal-cortical interactions, and also to provide causal evidence linking specific forms of neural activity to behavior and cognition.

We posit that neural dynamics at the ensemble level and network coordination still remains a “missing link” that can bridge between molecular/ cellular processes and behavioral phenomena in our understanding of mechanisms that underlie cognitive function and dysfunction. Our findings provide a crucial foundation to investigate if impairments in physiological network patterns lead to deficits in memory and cognition in disorders that involve hippocampus and prefrontal cortex. Our research will thus provide crucial insight into several neurological and neuropsychiatric disorders involving these two key regions, such as dementia, Alzheimer’s disease, depression, autism and schizophrenia. 

Our work has uncovered novel mechanisms and roles for coordination of neural activity at the ensemble level, and how this coordination or synchronization in distributed circuits supports behavior and cognition. We have contributed to the discovery of fundamental physiological mechanisms in the mammalian brain that enables learning, storage and retrieval of memory, planning and decision making. The lab continues to focus on understanding how multiple brain regions, including hippocampal-cortical-subcortical networks, interact with each other to form representations of the external environment, learn new experiences, store and retrieve memories, and make decisions. We aim to comprehensively characterize mechanisms at the neural dynamic level that mediate inter-regional interactions. 

The long-term goal of the lab is to gain a comprehensive understanding of the neural circuitry and dynamics that underlie learning and memory guided behavior in health and disease, and we aim to use tools for monitoring and manipulating neural activity patterns to rescue cognitive deficits in neurodegenerative disorders. An understanding of cognitive deficits at the neural ensemble level will be a critical step in linking existing characterizations at the genetic and molecular level to novel characterizations at the circuit and neural dynamic level. A major focus is on Autism Spectrum Disorders (ASD), and we were recently awarded grants from the Simons Foundation for Autism Research Initiative (SFARI) to investigate cognitive deficits in rat autism models as a core member of the Autism Rat Model Consortium, and for a Cross-Species Study of sleep in ASD.


Major Findings and Discoveries

Awake And Sleep Replay

Tang W, Shin JD, Frank LM, Jadhav SP (2017), “Hippocampal-prefrontal reactivation during learning is stronger in awake as compared to sleep states”, Journal of Neuroscience, 37(49):

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