Literature DB >> 29698768

Is working memory stored along a logarithmic timeline? Converging evidence from neuroscience, behavior and models.

Inder Singh1, Zoran Tiganj2, Marc W Howard3.   

Abstract

A growing body of evidence suggests that short-term memory does not only store the identity of recently experienced stimuli, but also information about when they were presented. This representation of 'what' happened 'when' constitutes a neural timeline of recent past. Behavioral results suggest that people can sequentially access memories for the recent past, as if they were stored along a timeline to which attention is sequentially directed. In the short-term judgment of recency (JOR) task, the time to choose between two probe items depends on the recency of the more recent probe but not on the recency of the more remote probe. This pattern of results suggests a backward self-terminating search model. We review recent neural evidence from the macaque lateral prefrontal cortex (lPFC) (Tiganj, Cromer, Roy, Miller, & Howard, in press) and behavioral evidence from human JOR task (Singh & Howard, 2017) bearing on this question. Notably, both lines of evidence suggest that the timeline is logarithmically compressed as predicted by Weber-Fechner scaling. Taken together, these findings provide an integrative perspective on temporal organization and neural underpinnings of short-term memory.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Judgments of recency; Time cells; Working memory

Mesh:

Year:  2018        PMID: 29698768      PMCID: PMC6064661          DOI: 10.1016/j.nlm.2018.04.008

Source DB:  PubMed          Journal:  Neurobiol Learn Mem        ISSN: 1074-7427            Impact factor:   2.877


  65 in total

Review 1.  Information processing with population codes.

Authors:  A Pouget; P Dayan; R Zemel
Journal:  Nat Rev Neurosci       Date:  2000-11       Impact factor: 34.870

2.  A working memory model based on fast Hebbian learning.

Authors:  A Sandberg; J Tegnér; A Lansner
Journal:  Network       Date:  2003-11       Impact factor: 1.273

3.  Theta and gamma power increases and alpha/beta power decreases with memory load in an attractor network model.

Authors:  Mikael Lundqvist; Pawel Herman; Anders Lansner
Journal:  J Cogn Neurosci       Date:  2011-03-31       Impact factor: 3.225

4.  Learning 10,000 pictures.

Authors:  L Standing
Journal:  Q J Exp Psychol       Date:  1973-05       Impact factor: 2.143

5.  Sequential Firing Codes for Time in Rodent Medial Prefrontal Cortex.

Authors:  Zoran Tiganj; Min Whan Jung; Jieun Kim; Marc W Howard
Journal:  Cereb Cortex       Date:  2017-12-01       Impact factor: 5.357

6.  Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions.

Authors:  Warasinee Chaisangmongkon; Sruthi K Swaminathan; David J Freedman; Xiao-Jing Wang
Journal:  Neuron       Date:  2017-03-22       Impact factor: 17.173

Review 7.  Time and space in the hippocampus.

Authors:  Marc W Howard; Howard Eichenbaum
Journal:  Brain Res       Date:  2014-11-10       Impact factor: 3.252

8.  Hippocampal "time cells": time versus path integration.

Authors:  Benjamin J Kraus; Robert J Robinson; John A White; Howard Eichenbaum; Michael E Hasselmo
Journal:  Neuron       Date:  2013-05-23       Impact factor: 17.173

9.  Internally generated cell assembly sequences in the rat hippocampus.

Authors:  Eva Pastalkova; Vladimir Itskov; Asohan Amarasingham; György Buzsáki
Journal:  Science       Date:  2008-09-05       Impact factor: 47.728

10.  Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex.

Authors:  Eelke Spaak; Kei Watanabe; Shintaro Funahashi; Mark G Stokes
Journal:  J Neurosci       Date:  2017-05-30       Impact factor: 6.167

View more
  1 in total

1.  Discrete Sequential Information Coding: Heteroclinic Cognitive Dynamics.

Authors:  Mikhail I Rabinovich; Pablo Varona
Journal:  Front Comput Neurosci       Date:  2018-09-07       Impact factor: 2.380

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.