Dataset Information

Low-dimensional dynamics for working memory and time encoding.

ABSTRACT: Our decisions often depend on multiple sensory experiences separated by time delays. The brain can remember these experiences and, simultaneously, estimate the timing between events. To understand the mechanisms underlying working memory and time encoding, we analyze neural activity recorded during delays in four experiments on nonhuman primates. To disambiguate potential mechanisms, we propose two analyses, namely, decoding the passage of time from neural data and computing the cumulative dimensionality of the neural trajectory over time. Time can be decoded with high precision in tasks where timing information is relevant and with lower precision when irrelevant for performing the task. Neural trajectories are always observed to be low-dimensional. In addition, our results further constrain the mechanisms underlying time encoding as we find that the linear "ramping" component of each neuron's firing rate strongly contributes to the slow timescale variations that make decoding time possible. These constraints rule out working memory models that rely on constant, sustained activity and neural networks with high-dimensional trajectories, like reservoir networks. Instead, recurrent networks trained with backpropagation capture the time-encoding properties and the dimensionality observed in the data.

SUBMITTER: Cueva CJ

PROVIDER: S-EPMC7502752 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Low-dimensional dynamics for working memory and time encoding.

Cueva Christopher J CJ Saez Alex A Marcos Encarni E Genovesio Aldo A Jazayeri Mehrdad M Romo Ranulfo R Salzman C Daniel CD Shadlen Michael N MN Fusi Stefano S

Proceedings of the National Academy of Sciences of the United States of America 20200828 37

Our decisions often depend on multiple sensory experiences separated by time delays. The brain can remember these experiences and, simultaneously, estimate the timing between events. To understand the mechanisms underlying working memory and time encoding, we analyze neural activity recorded during delays in four experiments on nonhuman primates. To disambiguate potential mechanisms, we propose two analyses, namely, decoding the passage of time from neural data and computing the cumulative dimen ...[more]

PMID: 32859756

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Project description:Access to WM can be restricted on the basis of goal-relevant properties such as spatial location. However, the extent of voluntary control over which features of an attended multi-feature object are encoded and maintained in WM is debated. Some evidence suggests that attending to an object leads to obligatory storage of all of its features, whereas other evidence suggests that access to WM can be restricted to only goal-relevant features. Another possibility is that all features are initially encoded, but irrelevant features are removed from WM over time. To address these various possibilities, we used pattern classification of EEG signals to track the temporal evolution of representations reflecting the encoding and storage of task-relevant and irrelevant features in WM. In different blocks, participants remembered the orientation, color or both orientation and color of a colored, oriented grating. The color and orientation of the grating was randomly drawn from two distinct feature bins on each trial. To examine trial-specific activity reflecting storage of the object's features, a support vector machine (SVM) classifier was trained to classify what bin the stimulus features came from. Importantly, for orientation, the classifier produced reliably above-chance classification across the delay when orientation was task-relevant but not when it was task-irrelevant. Interestingly, orientation could be accurately classified on trials for which both orientation and color were remembered. Moreover, a separate measure corresponding to the probability of a feature belonging to the correct bin was significantly higher when orientation was task-relevant compared to task-irrelevant during encoding. Above-chance classification for color was only present during the initial 500 msec across all conditions. Our results suggest that although information about all of an object's features is present in the initial stimulus-evoked neural response, information about the task-irrelevant features is attenuated during stimulus encoding and is largely absent throughout the delay.

Dataset Information

Low-dimensional dynamics for working memory and time encoding.

Publications

Low-dimensional dynamics for working memory and time encoding.

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