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Literature DB >> 32864401

The dimensionality of neural representations for control.

David Badre¹, Apoorva Bhandari¹, Haley Keglovits¹, Atsushi Kikumoto¹.

Abstract

Cognitive control allows us to think and behave flexibly based on our context and goals. At the heart of theories of cognitive control is a control representation that enables the same input to produce different outputs contingent on contextual factors. In this review, we focus on an important property of the control representation's neural code: its representational dimensionality. Dimensionality of a neural representation balances a basic separability/generalizability trade-off in neural computation. We will discuss the implications of this trade-off for cognitive control. We will then briefly review current neuroscience findings regarding the dimensionality of control representations in the brain, particularly the prefrontal cortex. We conclude by highlighting open questions and crucial directions for future research.

Entities: Chemical

Keywords: cognitive control; executive function; frontal lobes; neural computation; neural representation

Year: 2020 PMID： 32864401 PMCID： PMC7451207 DOI： 10.1016/j.cobeha.2020.07.002

Source DB: PubMed Journal: Curr Opin Behav Sci ISSN： 2352-1546

37 in total

1. Heterogenous population coding of a short-term memory and decision task.

Authors: Joseph K Jun; Paul Miller; Adrián Hernández; Antonio Zainos; Luis Lemus; Carlos D Brody; Ranulfo Romo
Journal: J Neurosci Date: 2010-01-20 Impact factor: 6.167

Review 2. Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior.

Authors: Stefano Panzeri; Christopher D Harvey; Eugenio Piasini; Peter E Latham; Tommaso Fellin
Journal: Neuron Date: 2017-02-08 Impact factor: 17.173

3. The importance of mixed selectivity in complex cognitive tasks.

Authors: Mattia Rigotti; Omri Barak; Melissa R Warden; Xiao-Jing Wang; Nathaniel D Daw; Earl K Miller; Stefano Fusi
Journal: Nature Date: 2013-05-19 Impact factor: 49.962

4. Frontal cortex and the discovery of abstract action rules.

Authors: David Badre; Andrew S Kayser; Mark D'Esposito
Journal: Neuron Date: 2010-04-29 Impact factor: 17.173

5. Effective learning is accompanied by high-dimensional and efficient representations of neural activity.

Authors: Evelyn Tang; Marcelo G Mattar; Chad Giusti; David M Lydon-Staley; Sharon L Thompson-Schill; Danielle S Bassett
Journal: Nat Neurosci Date: 2019-05-20 Impact factor: 28.771

6. Conjunctive representations that integrate stimuli, responses, and rules are critical for action selection.

Authors: Atsushi Kikumoto; Ulrich Mayr
Journal: Proc Natl Acad Sci U S A Date: 2020-04-27 Impact factor: 11.205

7. Time-invariant working memory representations in the presence of code-morphing in the lateral prefrontal cortex.

Authors: Aishwarya Parthasarathy; Cheng Tang; Roger Herikstad; Loong Fah Cheong; Shih-Cheng Yen; Camilo Libedinsky
Journal: Nat Commun Date: 2019-11-01 Impact factor: 14.919

Review 8. The structure of cognition: attentional episodes in mind and brain.

Authors: John Duncan
Journal: Neuron Date: 2013-10-02 Impact factor: 17.173

9. Dynamic coding for cognitive control in prefrontal cortex.

Authors: Mark G Stokes; Makoto Kusunoki; Natasha Sigala; Hamed Nili; David Gaffan; John Duncan
Journal: Neuron Date: 2013-04-04 Impact factor: 17.173

10. Gradual progression from sensory to task-related processing in cerebral cortex.

Authors: Scott L Brincat; Markus Siegel; Constantin von Nicolai; Earl K Miller
Journal: Proc Natl Acad Sci U S A Date: 2018-07-10 Impact factor: 11.205

13 in total

Review 1. Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making.

Authors: R Frömer; A Shenhav
Journal: Neurosci Biobehav Rev Date: 2021-12-10 Impact factor: 8.989

The dimensionality of neural representations for control.

1. Heterogenous population coding of a short-term memory and decision task.

Review 2. Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior.

3. The importance of mixed selectivity in complex cognitive tasks.

4. Frontal cortex and the discovery of abstract action rules.

5. Effective learning is accompanied by high-dimensional and efficient representations of neural activity.

6. Conjunctive representations that integrate stimuli, responses, and rules are critical for action selection.

7. Time-invariant working memory representations in the presence of code-morphing in the lateral prefrontal cortex.

Review 8. The structure of cognition: attentional episodes in mind and brain.

9. Dynamic coding for cognitive control in prefrontal cortex.

10. Gradual progression from sensory to task-related processing in cerebral cortex.

Review 1. Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making.

2. Detailed mapping of behavior reveals the formation of prelimbic neural ensembles across operant learning.

3. Is the Dorsolateral Prefrontal Cortex Actually Several Different Brain Areas?

Review 4. Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity.

5. Geometry of neural computation unifies working memory and planning.

6. Emotional Context Sculpts Action Goal Representations in the Lateral Frontal Pole.

7. The polarized mind in context: Interdisciplinary approaches to the psychology of political polarization.

Review 8. Neural Coding of Cognitive Control: The Representational Similarity Analysis Approach.

9. The Role of Conjunctive Representations in Stopping Actions.

10. Orthogonal representations for robust context-dependent task performance in brains and neural networks.