Literature DB >> 15390162

Reconstruction of the postsubiculum head direction signal from neural ensembles.

Adam Johnson1, Kelsey Seeland, A David Redish.   

Abstract

Head direction cells change their firing rates as a function of the orientation of an animal within an environment. Typically, these cells display a unimodal tuning curve with maximal firing at the cell's preferred direction. As different cells have different preferred directions, the population of cells has been hypothesized to represent the orientation of the animal within the environment. Previous research has shown that pairs of simultaneously recorded head direction cells respond similarly to cue manipulations, suggesting that a population of head direction cells acts in concert to represent the animal's orientation within its environment. Ensembles of head direction cells were recorded from the postsubiculum from rats foraging in an open field. Directional responses of each cell were quantified by the nonparametric Watson's U2 statistic, a measure which makes no explicit assumptions of tuning curve shape. Directionally responsive cells were then used to reconstruct each animal's orientation within the open field using population vector, optimal-linear estimator, and Bayesian methods. The results indicated that postsubiculum contained a complete representation of the animal's orientation. The internal consistency of a neural ensemble can be assessed by comparing the ensemble activity to the expected activity given the reconstructed orientation. This has been termed the "coherency" of the neural ensemble. Reconstruction error decreased as the coherency of the orientation representation increased, indicating that coherency could be used to measure a level of confidence in the representation quality. Because coherency is a linear measure dependent only on internal variables, coherency may be a behaviorally relevant measure used to ascertain the animal's confidence in its representation of orientation. Copyright (c) 2004 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  2005        PMID: 15390162     DOI: 10.1002/hipo.20033

Source DB:  PubMed          Journal:  Hippocampus        ISSN: 1050-9631            Impact factor:   3.899


  20 in total

1.  Fear conditioning is disrupted by damage to the postsubiculum.

Authors:  Siobhan Robinson; David J Bucci
Journal:  Hippocampus       Date:  2011-11-11       Impact factor: 3.899

2.  A simple measure of the coding efficiency of a neuronal population.

Authors:  Emilio Salinas; Nicholas M Bentley
Journal:  Biosystems       Date:  2006-11-11       Impact factor: 1.973

3.  Fragmentation of grid cell maps in a multicompartment environment.

Authors:  Dori Derdikman; Jonathan R Whitlock; Albert Tsao; Marianne Fyhn; Torkel Hafting; May-Britt Moser; Edvard I Moser
Journal:  Nat Neurosci       Date:  2009-09-13       Impact factor: 24.884

4.  Oscillatory synchrony between head direction cells recorded bilaterally in the anterodorsal thalamic nuclei.

Authors:  William N Butler; Jeffrey S Taube
Journal:  J Neurophysiol       Date:  2017-03-01       Impact factor: 2.714

5.  Anticipatory Neural Activity Improves the Decoding Accuracy for Dynamic Head-Direction Signals.

Authors:  Johannes Zirkelbach; Martin Stemmler; Andreas V M Herz
Journal:  J Neurosci       Date:  2019-01-28       Impact factor: 6.167

6.  Head direction cells in the postsubiculum do not show replay of prior waking sequences during sleep.

Authors:  Mark P Brandon; Andrew R Bogaard; Chris M Andrews; Michael E Hasselmo
Journal:  Hippocampus       Date:  2011-04-20       Impact factor: 3.899

7.  The Head-Direction Signal Plays a Functional Role as a Neural Compass during Navigation.

Authors:  William N Butler; Kyle S Smith; Matthijs A A van der Meer; Jeffrey S Taube
Journal:  Curr Biol       Date:  2017-04-13       Impact factor: 10.834

8.  The nucleus prepositus hypoglossi contributes to head direction cell stability in rats.

Authors:  William N Butler; Jeffrey S Taube
Journal:  J Neurosci       Date:  2015-02-11       Impact factor: 6.167

9.  Phase coding by grid cells in unconstrained environments: two-dimensional phase precession.

Authors:  Jason R Climer; Ehren L Newman; Michael E Hasselmo
Journal:  Eur J Neurosci       Date:  2013-05-29       Impact factor: 3.386

10.  Temporal-difference reinforcement learning with distributed representations.

Authors:  Zeb Kurth-Nelson; A David Redish
Journal:  PLoS One       Date:  2009-10-20       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.