Testing Models of Human Declarative Memory at the Single-Neuron Level. Issue 6 (June 2019)

• Record Type: Journal Article
• Authors: Rutishauser, Ueli
• Is Part Of: Trends in cognitive sciences. Volume 23:Issue 6(2019)
• Page Start: 510
• Page End: 524
• Publication Date: 2019-06
• Subjects: declarative memory -- single-neuron level -- hippocampus -- dopamine -- memory retrieval -- medial temporal lobe; Cognitive science -- Periodicals; Cognitive neuroscience -- Periodicals; 153.05
• DOI: 10.1016/j.tics.2019.03.006
• Languages: English
• ISSNs: 1364-6613

Abstract

Abstract : Deciphering the mechanisms of declarative memory is a major goal of neuroscience. While much theoretical progress has been made, it has proven difficult to experimentally verify key predictions of some foundational models of memory. Recently, single-neuron recordings in human patients have started to provide direct experimental verification of some theories, including mnemonic evidence accumulation, balance-of-evidence for confidence judgments, sparse coding, contextual reinstatement, and the ventral tegmental area (VTA)–hippocampus loop model. Here, we summarize the cell types that have been described in the medial temporal lobe and posterior parietal cortex, discuss their properties, and reflect on how these findings inform theoretical work. This body of work exemplifies the scientific power of a synergistic combination of modeling and human single-neuron recordings to advance cognitive neuroscience. Highlights: Single-neuron recordings in humans are a powerful technique to bridge theory and experimentation in cognitive neuroscience Recordings of novelty-sensitive dopamine neurons confirm critical predictions of the VTA/SN–hippocampus loop model Visually and memory-selective cells in the human MTL form a sparse and highly abstract code that are a putative candidate for semantic and episodic memories, respectively. Neurons in PPC are candidates for mnemonic evidence accumulators. Contextual reinstatement during retrieval and slowly drifting neural state during encoding confirm key prediction of temporal context models of episodic memory.