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Generative Predictive Codes by Multiplexed Hippocampal Neuronal Tuplets

delete2018-09-01
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OA
AI
K
Kefei Liu
J
Jérémie Sibille
G
George Drăgoi *
DOI:10.1016/j.neuron.2018.07.047delete
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Abstract

Abstract

En 中文
Rapid internal representations are continuously formed based on single experiential episodes in space and time, but the neuronal ensemble mechanisms enabling rapid encoding without constraining the capacity for multiple distinct representations are unknown. We developed a probabilistic statistical model of hippocampal spontaneous sequential activity and revealed existence of an internal model of generative predictive codes for the regularities of multiple future novel spatial sequences. During navigation, the inferred difference between external stimuli and the internal model was encoded by emergence of intrinsic-unlikely, novel functional connections, which updated the model by preferentially potentiating post-experience. This internal model and these predictive codes depended on neuronal organization into inferred modules of short, high-repeat sequential neuronal tuplets'' operating as neuro-codons.'' We propose that flexible multiplexing of neuronal tuplets into repertoires of extended sequences vastly expands the capacity of hippocampal predictive codes, which could initiate top-down hierarchical cortical loops for spatial and mental navigation and rapid learning.
Keywords:
PLACE-CELL SEQUENCES
SHARP WAVE-RIPPLES
VISUAL-CORTEX
SPATIAL MAP
MEMORY
SLEEP
REPLAY
REPRESENTATIONS
EXPERIENCES
BRAIN
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Journal

Neuron cover
Neuron
IF:
15
Papers:
1.4W
Citations:
9.9W

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Y
Yale University
Scholars:
6.5W
Papers: 6.0W
Citations: 10.0W