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Review
. 2021 Feb 3;41(5):883-890.
doi: 10.1523/JNEUROSCI.1648-20.2020. Epub 2020 Nov 30.

The Architecture of Human Memory: Insights from Human Single-Neuron Recordings

Affiliations
Review

The Architecture of Human Memory: Insights from Human Single-Neuron Recordings

Ueli Rutishauser et al. J Neurosci. .

Abstract

Deciphering the mechanisms of human memory is a central goal of neuroscience, both from the point of view of the fundamental biology of memory and for its translational relevance. Here, we review some contributions that recordings from neurons in humans implanted with electrodes for clinical purposes have made toward this goal. Recordings from the medial temporal lobe, including the hippocampus, reveal the existence of two classes of cells: those encoding highly selective and invariant representations of abstract concepts, and memory-selective cells whose activity is related to familiarity and episodic retrieval. Insights derived from observing these cells in behaving humans include that semantic representations are activated before episodic representations, that memory content and memory strength are segregated, and that the activity of both types of cells is related to subjective awareness as expected from a substrate for declarative memory. Visually selective cells can remain persistently active for several seconds, thereby revealing a cellular substrate for working memory in humans. An overarching insight is that the neural code of human memory is interpretable at the single-neuron level. Jointly, intracranial recording studies are starting to reveal aspects of the building blocks of human memory at the single-cell level. This work establishes a bridge to cellular-level work in animals on the one hand, and the extensive literature on noninvasive imaging in humans on the other hand. More broadly, this work is a step toward a detailed mechanistic understanding of human memory that is needed to develop therapies for human memory disorders.

Keywords: amygdala; entorhinal cortex; episodic memory; hippocampus; human memory; single-neuron.

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Figures

Figure 1.
Figure 1.
Encoding episodic memory strength and retrieval mode. A, Example memory-selective cells. Left, Cell that fires most to familiar (old) stimuli. Right, Cell that fires most to novel (new) stimuli. t = 0 is stimulus onset. Top, Raster plots. Each row represents an individual trial. Each dot represents an action potential. Bottom, Average firing rate across all trials binned 250 ms bins. B, Activity of both types of memory-selective cells scale with confidence for their preferred, but not their nonpreferred, stimulus (either old [left] or new [right] stimuli). TP, True positive (old stimuli recognized correctly) shown as a cumulative density function (cdf); TN, true negative (new stimuli recognized correctly). C, Orthogonal tuning to either visual category (x axis) or familiarity (y axis) during recognition memory. Each data point is a neuron. Red and green represent neurons that are primarily influenced by novelty/familiarity or category, respectively. D, Orthogonal tuning to either visual category (y axis) or successful retrieval versus familiarity only (x axis). Shown are two example neurons (marked): one only visually selective (Neuron A), the other only differentiating successful retrieval from familiarity alone (Neuron B). Each data point is a neuron. Red and blue represent neurons that are primarily influenced by visual identity and success of retrieval of the associated stimulus, respectively. A, Adapted from Faraut et al. (2018). B, C, Adapted from Rutishauser et al. (2015). D, Adapted from Staresina et al. (2019).
Figure 2.
Figure 2.
Abstract semantic representations and their role in episodic retrieval. A-C, Example of visually selective neurons with tuning compatible with semantic representations. A, Top, Visually selective neuron responding to many different images showing clothes (from hippocampus). Bottom, Visually selective neuron only responding to a single image of a food item (from amygdala). B, Invariant multimodal concept neuron that responds only to images and written and spoken name of an experimenter. C, Visually selective category neuron. t = 0 is stimulus onset. Top, Raster plot represents the spiking response to different stimulus categories (indicated by color). Bottom, Average firing rate across trials in bins of 250 ms. D, Visually selective neuron in the entorhinal cortex with a response to “raspberries,” but not to “scorpion,” during encoding. E, Same neuron as shown in D, but now during cued retrieval. This neuron increased its firing selectively only if associated to-be-retrieved image was “raspberries.” This is a signature of content-specific reinstatement during cued retrieval. A, Adapted from Reber et al. (2019b). B, Adapted from Quiroga et al. (2009). C, Adapted from Rutishauser (2019). D, E, Adapted from Staresina et al. (2019).
Figure 3.
Figure 3.
Persistently active cells as a substrate for WM. A-C, Example of a visually selective neuron recorded from the amygdala during a WM task with pictures as items. Shown is the encoding (A), maintenance (B), and probe (C) period. The firing rate of this neuron increases starting during encoding when its preferred stimulus is shown (magenta) and maintains this activity during the maintenance period if its preferred image is held in memory (B). B, Inset, The mean waveform of this neuron. D, Example neuron in the hippocampus recorded during a WM task with letters as items. This neuron increases its activity during the maintenance period as a function of load but not memory content. A-D, Bottom, Raster plots represent the spiking response in individual trials (one per row), with identity of the trial marked by color. Top, Average firing rate as a function of time across all trials as a function of time. A-C, Adapted from Kamiński et al. (2020). D, Adapted from Boran et al. (2019).

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