Literature DB >> 31015339

Contribution of Sensory Encoding to Measured Bias.

Miaomiao Jin1, Lindsey L Glickfeld2.   

Abstract

Signal detection theory (SDT) is a widely used theoretical framework that describes how variable sensory signals are integrated with a decision criterion to support perceptual decision-making. SDT provides two key measurements: sensitivity (d') and bias (c), which reflect the separability of decision variable distributions (signal and noise) and the position of the decision criterion relative to optimal, respectively. Although changes in the subject's decision criterion can be reflected in changes in bias, decision criterion placement is not the sole contributor to measured bias. Indeed, neuronal representations of bias have been observed in sensory areas, suggesting that some changes in bias are because of effects on sensory encoding. To directly test whether the sensory encoding process can influence bias, we optogenetically manipulated neuronal excitability in primary visual cortex (V1) in mice of both sexes during either an orientation discrimination or a contrast detection task. Increasing excitability in V1 significantly decreased behavioral bias, whereas decreasing excitability had the opposite effect. To determine whether this change in bias is consistent with effects on sensory encoding, we made extracellular recordings from V1 neurons in passively viewing mice. Indeed, we found that optogenetic manipulation of excitability shifted the neuronal bias in the same direction as the behavioral bias. Moreover, manipulating the quality of V1 encoding by changing stimulus contrast or interstimulus interval also resulted in consistent changes in both behavioral and neuronal bias. Thus, changes in sensory encoding are sufficient to drive changes in bias measured using SDT.SIGNIFICANCE STATEMENT Perceptual decision-making involves sensory integration followed by application of a cognitive criterion. Using signal detection theory, one can extract features of the underlying decision variables and rule: sensitivity (d') and bias (c). Because bias is measured as the difference between the optimal and actual criterion, it is sensitive to both the sensory encoding processes and the placement of the decision criterion. Here, we use behavioral and electrophysiological approaches to demonstrate that measures of bias depend on sensory processes. Optogenetic manipulations of V1 in mice bidirectionally affect both behavioral and neuronal measures of bias with little effect on sensitivity. Thus, changes in sensory encoding influence bias, and the absence of changes in sensitivity do not preclude changes in sensory encoding.
Copyright © 2019 the authors.

Entities:  

Keywords:  contrast; mouse visual cortex; optogenetics; orientation; psychophysics; signal detection theory

Year:  2019        PMID: 31015339      PMCID: PMC6595953          DOI: 10.1523/JNEUROSCI.0076-19.2019

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  48 in total

1.  Calculation of signal detection theory measures.

Authors:  H Stanislaw; N Todorov
Journal:  Behav Res Methods Instrum Comput       Date:  1999-02

2.  Rapid adaptation in visual cortex to the structure of images.

Authors:  J R Müller; A B Metha; J Krauskopf; P Lennie
Journal:  Science       Date:  1999-08-27       Impact factor: 47.728

3.  Feature-based attention influences motion processing gain in macaque visual cortex.

Authors:  S Treue; J C Martínez Trujillo
Journal:  Nature       Date:  1999-06-10       Impact factor: 49.962

4.  Involuntary orienting to sound improves visual perception.

Authors:  J J McDonald; W A Teder-Sälejärvi; S A Hillyard
Journal:  Nature       Date:  2000-10-19       Impact factor: 49.962

5.  Adaptation-induced plasticity of orientation tuning in adult visual cortex.

Authors:  V Dragoi; J Sharma; M Sur
Journal:  Neuron       Date:  2000-10       Impact factor: 17.173

6.  Microstimulation of visual cortex affects the speed of perceptual decisions.

Authors:  Jochen Ditterich; Mark E Mazurek; Michael N Shadlen
Journal:  Nat Neurosci       Date:  2003-08       Impact factor: 24.884

7.  Area map of mouse visual cortex.

Authors:  Quanxin Wang; Andreas Burkhalter
Journal:  J Comp Neurol       Date:  2007-05-20       Impact factor: 3.215

Review 8.  Visual adaptation: neural, psychological and computational aspects.

Authors:  Colin W G Clifford; Michael A Webster; Garrett B Stanley; Alan A Stocker; Adam Kohn; Tatyana O Sharpee; Odelia Schwartz
Journal:  Vision Res       Date:  2007-10-22       Impact factor: 1.886

Review 9.  The neural basis of decision making.

Authors:  Joshua I Gold; Michael N Shadlen
Journal:  Annu Rev Neurosci       Date:  2007       Impact factor: 12.449

10.  Noise characteristics and prior expectations in human visual speed perception.

Authors:  Alan A Stocker; Eero P Simoncelli
Journal:  Nat Neurosci       Date:  2006-03-19       Impact factor: 24.884

View more
  8 in total

1.  Mouse Higher Visual Areas Provide Both Distributed and Specialized Contributions to Visually Guided Behaviors.

Authors:  Miaomiao Jin; Lindsey L Glickfeld
Journal:  Curr Biol       Date:  2020-10-08       Impact factor: 10.834

2.  Attention can be subdivided into neurobiological components corresponding to distinct behavioral effects.

Authors:  Thomas Zhihao Luo; John H R Maunsell
Journal:  Proc Natl Acad Sci U S A       Date:  2019-12-23       Impact factor: 11.205

3.  Effects of Altered Excitation-Inhibition Balance on Decision Making in a Cortical Circuit Model.

Authors:  Norman H Lam; Thiago Borduqui; Jaime Hallak; Antonio Roque; Alan Anticevic; John H Krystal; Xiao-Jing Wang; John D Murray
Journal:  J Neurosci       Date:  2021-12-09       Impact factor: 6.709

4.  Mice Preferentially Use Increases in Cerebral Cortex Spiking to Detect Changes in Visual Stimuli.

Authors:  Jackson J Cone; Morgan L Bade; Nicolas Y Masse; Elizabeth A Page; David J Freedman; John H R Maunsell
Journal:  J Neurosci       Date:  2020-09-11       Impact factor: 6.167

5.  Response Bias Reflects Individual Differences in Sensory Encoding.

Authors:  Dobromir Rahnev
Journal:  Psychol Sci       Date:  2021-07-01

6.  Defending subjective inflation: an inference to the best explanation.

Authors:  J D Knotts; Matthias Michel; Brian Odegaard
Journal:  Neurosci Conscious       Date:  2020-12-12

7.  Emergence of probabilistic representation in the neural network of primary visual cortex.

Authors:  Ang A Li; Fengchao Wang; Si Wu; Xiaohui Zhang
Journal:  iScience       Date:  2022-02-26

8.  Diminished Cortical Excitation and Elevated Inhibition During Perceptual Impairments in a Mouse Model of Autism.

Authors:  Joseph Del Rosario; Anderson Speed; Hayley Arrowood; Cara Motz; Machelle Pardue; Bilal Haider
Journal:  Cereb Cortex       Date:  2021-06-10       Impact factor: 5.357

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.