Literature DB >> 23322402

Spatial attention, precision, and Bayesian inference: a study of saccadic response speed.

Simone Vossel1, Christoph Mathys, Jean Daunizeau, Markus Bauer, Jon Driver, Karl J Friston, Klaas E Stephan.   

Abstract

Inferring the environment's statistical structure and adapting behavior accordingly is a fundamental modus operandi of the brain. A simple form of this faculty based on spatial attentional orienting can be studied with Posner's location-cueing paradigm in which a cue indicates the target location with a known probability. The present study focuses on a more complex version of this task, where probabilistic context (percentage of cue validity) changes unpredictably over time, thereby creating a volatile environment. Saccadic response speed (RS) was recorded in 15 subjects and used to estimate subject-specific parameters of a Bayesian learning scheme modeling the subjects' trial-by-trial updates of beliefs. Different response models-specifying how computational states translate into observable behavior-were compared using Bayesian model selection. Saccadic RS was most plausibly explained as a function of the precision of the belief about the causes of sensory input. This finding is in accordance with current Bayesian theories of brain function, and specifically with the proposal that spatial attention is mediated by a precision-dependent gain modulation of sensory input. Our results provide empirical support for precision-dependent changes in beliefs about saccade target locations and motivate future neuroimaging and neuropharmacological studies of how Bayesian inference may determine spatial attention.

Entities:  

Keywords:  cue validity; hierarchical models; variational Bayes; visuospatial processing; volatility

Mesh:

Year:  2013        PMID: 23322402      PMCID: PMC4014178          DOI: 10.1093/cercor/bhs418

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  64 in total

1.  Covert visual spatial orienting and saccades: overlapping neural systems.

Authors:  A C Nobre; D R Gitelman; E C Dias; M M Mesulam
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2.  The neurology of saccades and covert shifts in spatial attention: an event-related fMRI study.

Authors:  R J Perry; S Zeki
Journal:  Brain       Date:  2000-11       Impact factor: 13.501

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5.  Primate frontal eye fields. I. Single neurons discharging before saccades.

Authors:  C J Bruce; M E Goldberg
Journal:  J Neurophysiol       Date:  1985-03       Impact factor: 2.714

6.  Striatal prediction error modulates cortical coupling.

Authors:  Hanneke E M den Ouden; Jean Daunizeau; Jonathan Roiser; Karl J Friston; Klaas E Stephan
Journal:  J Neurosci       Date:  2010-03-03       Impact factor: 6.167

7.  Comparing families of dynamic causal models.

Authors:  Will D Penny; Klaas E Stephan; Jean Daunizeau; Maria J Rosa; Karl J Friston; Thomas M Schofield; Alex P Leff
Journal:  PLoS Comput Biol       Date:  2010-03-12       Impact factor: 4.475

8.  Neural basis of saccade target selection in frontal eye field during visual search.

Authors:  J D Schall; D P Hanes
Journal:  Nature       Date:  1993-12-02       Impact factor: 49.962

9.  Observing the observer (II): deciding when to decide.

Authors:  Jean Daunizeau; Hanneke E M den Ouden; Matthias Pessiglione; Stefan J Kiebel; Karl J Friston; Klaas E Stephan
Journal:  PLoS One       Date:  2010-12-14       Impact factor: 3.240

10.  Integrated Bayesian models of learning and decision making for saccadic eye movements.

Authors:  Kay H Brodersen; Will D Penny; Lee M Harrison; Jean Daunizeau; Christian C Ruff; Emrah Duzel; Karl J Friston; Klaas E Stephan
Journal:  Neural Netw       Date:  2008-09-07
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  58 in total

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2.  Contextual factors multiplex to control multisensory processes.

Authors:  Beatriz R Sarmiento; Pawel J Matusz; Daniel Sanabria; Micah M Murray
Journal:  Hum Brain Mapp       Date:  2015-10-15       Impact factor: 5.038

3.  Sure enough: efficient Bayesian learning and choice.

Authors:  Brad R Foley; Paul Marjoram
Journal:  Anim Cogn       Date:  2017-07-01       Impact factor: 3.084

4.  Prior knowledge of spatiotemporal configuration facilitates crossmodal saccadic response : A TWIN analysis.

Authors:  Adele Diederich; Hans Colonius; Farid I Kandil
Journal:  Exp Brain Res       Date:  2016-03-15       Impact factor: 1.972

Review 5.  Understanding active sampling strategies: Empirical approaches and implications for attention and decision research.

Authors:  Jacqueline Gottlieb
Journal:  Cortex       Date:  2017-08-24       Impact factor: 4.027

6.  Ketamine Affects Prediction Errors about Statistical Regularities: A Computational Single-Trial Analysis of the Mismatch Negativity.

Authors:  Lilian A Weber; Andreea O Diaconescu; Christoph Mathys; André Schmidt; Michael Kometer; Franz Vollenweider; Klaas E Stephan
Journal:  J Neurosci       Date:  2020-06-19       Impact factor: 6.167

7.  A Computational Account of Optimizing Social Predictions Reveals That Adolescents Are Conservative Learners in Social Contexts.

Authors:  Gabriela Rosenblau; Christoph W Korn; Kevin A Pelphrey
Journal:  J Neurosci       Date:  2017-12-18       Impact factor: 6.167

8.  Causal Evidence for Learning-Dependent Frontal Lobe Contributions to Cognitive Control.

Authors:  Paul S Muhle-Karbe; Jiefeng Jiang; Tobias Egner
Journal:  J Neurosci       Date:  2017-12-11       Impact factor: 6.167

Review 9.  Bayesian modeling of flexible cognitive control.

Authors:  Jiefeng Jiang; Katherine Heller; Tobias Egner
Journal:  Neurosci Biobehav Rev       Date:  2014-06-11       Impact factor: 8.989

10.  Disruption of the Right Temporoparietal Junction Impairs Probabilistic Belief Updating.

Authors:  Paola Mengotti; Pascasie L Dombert; Gereon R Fink; Simone Vossel
Journal:  J Neurosci       Date:  2017-05-04       Impact factor: 6.167

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