Welcome
UC Davis is among the foremost universities in the study of learning, memory and neural plasticity. The UC Davis Memory and Plasticity Program (MAP) is a central hub for learning and memory research.
Featured PublicationOctober 2020Task-specific Disruptions in Theta Oscillations during Working Memory for Temporal Order in People with Schizophrenia
Liu, Xiaonan L., ... [Charan Ranganath, J. Daniel Ragland, Cameron S. Carter] ..., et al. "Task-specific Disruptions in Theta Oscillations during Working Memory for Temporal Order in People with Schizophrenia." Journal of cognitive neuroscience 32.11 (2020): 2117-2130.
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Upcoming Talk - Dr. Robert Cabeza
Friday, January 15th at 12:10pm
Dr. Roberto Cabeza
Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
Department of Psychology, Humboldt University-Berlin, Germany
Episodic Memory Network and Representations
Episodic memory is assumed to depend on a complex network of brain regions that mediate encoding and retrieval processes and store memory representations. Memory representations are assumed to be distributed over the cortex, which are recovered by the hippocampus during retrieval. Consistent with this hypothesis, our fMRI network studies show that the hippocampus becomes more integrated with the rest of the network during successful retrieval. The hippocampus is part of a medial temporal lobe (MTL) sub-network, or module, which is impaired by aging. Our data suggest that this age-related MTL deficit is partly compensated by the prefrontal cortex (PFC) module, which displays increased memory-related network integration and reconfiguration in older than younger adults. Turning to memory representations, we used representational similarity analyses (RSA) to distinguish visual vs. semantic representations and examine how their encoding predicts subsequent memory in perceptual vs. conceptual tests. Our results showed a complex interaction between representation type and brain storage location, suggesting an interaction between representations and networks. Finally, we examined the finding that the neural representations for different types of stimuli are less distinct in older than younger adults (age-related dedifferentiation). Our results showed that although older adults displayed dedifferentiation for sensory representations in early visual cortex regions, they show hyper differentiation for categorical representations in the anterior temporal lobes. This finding is consistent with evidence that older adults may tap on semantic knowledge to compensate for deficits in other cognitive abilities. Taken together, our results illustrate how network and representational analyses can clarify the mechanisms of episodic memory in young and older adults.
Recent News - MAP Seed Grant Year 2 Awarded
From the Director, Charan Ranganath -- Dear MAP Faculty, we are embarking on the third year of the Memory and Plasticity (MAP) program at UC Davis. One of the MAP program’s most important initiatives is the seed grant competition.
The goal of this program is to support the collection of pilot data to stimulate new collaborations, and develop basic or translational research projects that are relevant to the study of learning and memory. This year, we received 10 proposals and were able to award two, one-year grants of $25,000 each. Each proposal was evaluated by a committee with expertise across neuroscience and psychology-- Randy O’Reilly (Psychology/CNS), Lin Tian (Biochemistry and Molecular Medicine), and Brian Wiltgen (Psychology/CNS). I sincerely appreciate the time and effort they put in to the difficult task of ranking these extremely competitive proposals. I’m pleased to announce the awards for this year’s competition:
Title: “High-dimensional distributed memory reservoirs for information maintenance and integration.”
Principal Investigators: Rishidev Chaudhuri (Mathematics and Neurobiology, Physiology & Behavior) and Tim Hanks (Neurobiology, Physiology & Behavior)
Project summary: The PIs will test the idea that the brain creates general purpose “memory reservoirs” that simultaneously accumulate and maintain information in a diversity of formats. This idea will be tested with a newly-developed experimental paradigm, cutting-edge recording technology for in vivo recordings from large neural populations, and neural circuit modeling.
Title: “Machine-learning decoding of human memories during consolidation and recall using distributed invasive recordings.”
Principal Investigators: Karen Moxon (Biomedical Engineering) and Ignacio Saez (Neurological Surgery)
Project summary: In this project, the PIs will use intracranial electroencephalographic (iEEG) recordings in the brains of human neurosurgical epilepsy patients, and machine learning methods to decode and characterize human memory traces in hippocampal and cortical regions.
I want to express my sincere thanks to all of the applicants -- the submitted projects highlight the range of expertise, innovative ideas, and thriving culture of collaboration that has made UC Davis among the world’s most important sites for memory and plasticity research. Also, special thanks to the many sources of university support for the MAP program that made this program possible.
The goal of this program is to support the collection of pilot data to stimulate new collaborations, and develop basic or translational research projects that are relevant to the study of learning and memory. This year, we received 10 proposals and were able to award two, one-year grants of $25,000 each. Each proposal was evaluated by a committee with expertise across neuroscience and psychology-- Randy O’Reilly (Psychology/CNS), Lin Tian (Biochemistry and Molecular Medicine), and Brian Wiltgen (Psychology/CNS). I sincerely appreciate the time and effort they put in to the difficult task of ranking these extremely competitive proposals. I’m pleased to announce the awards for this year’s competition:
Title: “High-dimensional distributed memory reservoirs for information maintenance and integration.”
Principal Investigators: Rishidev Chaudhuri (Mathematics and Neurobiology, Physiology & Behavior) and Tim Hanks (Neurobiology, Physiology & Behavior)
Project summary: The PIs will test the idea that the brain creates general purpose “memory reservoirs” that simultaneously accumulate and maintain information in a diversity of formats. This idea will be tested with a newly-developed experimental paradigm, cutting-edge recording technology for in vivo recordings from large neural populations, and neural circuit modeling.
Title: “Machine-learning decoding of human memories during consolidation and recall using distributed invasive recordings.”
Principal Investigators: Karen Moxon (Biomedical Engineering) and Ignacio Saez (Neurological Surgery)
Project summary: In this project, the PIs will use intracranial electroencephalographic (iEEG) recordings in the brains of human neurosurgical epilepsy patients, and machine learning methods to decode and characterize human memory traces in hippocampal and cortical regions.
I want to express my sincere thanks to all of the applicants -- the submitted projects highlight the range of expertise, innovative ideas, and thriving culture of collaboration that has made UC Davis among the world’s most important sites for memory and plasticity research. Also, special thanks to the many sources of university support for the MAP program that made this program possible.
