Literature DB >> 26894512

A solid frame for the window on cognition: Modeling event-related pupil responses.

Christoph W Korn, Dominik R Bach.   

Abstract

Pupil size is often used to infer central processes, including attention, memory, and emotion. Recent research has spotlighted its relation to behavioral variables from decision-making models and to neural variables such as locus coeruleus activity and cortical oscillations. As yet, a unified and principled approach for analyzing pupil responses is lacking. Here we seek to establish a formal, quantitative forward model for pupil responses by describing them with linear time-invariant systems. Based on empirical data from human participants, we show that a combination of two linear time-invariant systems can parsimoniously explain approximately all variance evoked by illuminance changes. Notably, the model makes a counterintuitive prediction that pupil constriction dominates the responses to darkness flashes, as in previous empirical reports. This prediction was quantitatively confirmed for responses to light and darkness flashes in an independent group of participants. Crucially, illuminance- and nonilluminance-related inputs to the pupillary system are presumed to share a common final pathway, composed of muscles and nerve terminals. Hence, we can harness our illuminance-based model to estimate the temporal evolution of this neural input for an auditory-oddball task, an emotional-words task, and a visual-detection task. Onset and peak latencies of the estimated neural inputs furnish plausible hypotheses for the complexity of the underlying neural circuit. To conclude, this mathematical description of pupil responses serves as a prerequisite to refining their relation to behavioral and brain indices of cognitive processes.

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Mesh:

Year:  2016        PMID: 26894512      PMCID: PMC4993241          DOI: 10.1167/16.3.28

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  41 in total

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Authors:  D Friedman; Y M Cycowicz; H Gaeta
Journal:  Neurosci Biobehav Rev       Date:  2001-06       Impact factor: 8.989

2.  Pupillary responses to stimulus structure, colour and movement.

Authors:  J L Barbur; A J Harlow; A Sahraie
Journal:  Ophthalmic Physiol Opt       Date:  1992-04       Impact factor: 3.117

Review 3.  Pupillometric measures of cognitive and emotional processes.

Authors:  Eric Granholm; Stuart R Steinhauer
Journal:  Int J Psychophysiol       Date:  2004-03       Impact factor: 2.997

Review 4.  Models of brain function in neuroimaging.

Authors:  Karl J Friston
Journal:  Annu Rev Psychol       Date:  2005       Impact factor: 24.137

Review 5.  An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance.

Authors:  Gary Aston-Jones; Jonathan D Cohen
Journal:  Annu Rev Neurosci       Date:  2005       Impact factor: 12.449

6.  The coupling of emotion and cognition in the eye: introducing the pupil old/new effect.

Authors:  Melissa L-H Võ; Arthur M Jacobs; Lars Kuchinke; Markus Hofmann; Markus Conrad; Annekathrin Schacht; Florian Hutzler
Journal:  Psychophysiology       Date:  2007-10-01       Impact factor: 4.016

7.  The pupil as a measure of emotional arousal and autonomic activation.

Authors:  Margaret M Bradley; Laura Miccoli; Miguel A Escrig; Peter J Lang
Journal:  Psychophysiology       Date:  2008-02-11       Impact factor: 4.016

8.  Pupil dilation reflects perceptual selection and predicts subsequent stability in perceptual rivalry.

Authors:  Wolfgang Einhäuser; James Stout; Christof Koch; Olivia Carter
Journal:  Proc Natl Acad Sci U S A       Date:  2008-02-04       Impact factor: 11.205

9.  The Berlin Affective Word List Reloaded (BAWL-R).

Authors:  Melissa L-H Võ; Markus Conrad; Lars Kuchinke; Karolina Urton; Markus J Hofmann; Arthur M Jacobs
Journal:  Behav Res Methods       Date:  2009-05

10.  Time-series analysis for rapid event-related skin conductance responses.

Authors:  Dominik R Bach; Guillaume Flandin; Karl J Friston; Raymond J Dolan
Journal:  J Neurosci Methods       Date:  2009-08-15       Impact factor: 2.390

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  17 in total

1.  Spatial sampling in human visual cortex is modulated by both spatial and feature-based attention.

Authors:  Daniel Marten van Es; Jan Theeuwes; Tomas Knapen
Journal:  Elife       Date:  2018-12-07       Impact factor: 8.140

2.  Dynamic modulation of decision biases by brainstem arousal systems.

Authors:  Jan Willem de Gee; Olympia Colizoli; Niels A Kloosterman; Tomas Knapen; Sander Nieuwenhuis; Tobias H Donner
Journal:  Elife       Date:  2017-04-11       Impact factor: 8.140

3.  The confounding effects of eye blinking on pupillometry, and their remedy.

Authors:  Kyung Yoo; Jeongyeol Ahn; Sang-Hun Lee
Journal:  PLoS One       Date:  2021-12-17       Impact factor: 3.240

4.  Comparing methods of analysis in pupillometry: application to the assessment of listening effort in hearing-impaired patients.

Authors:  Lou Seropian; Mathieu Ferschneider; Fanny Cholvy; Christophe Micheyl; Aurélie Bidet-Caulet; Annie Moulin
Journal:  Heliyon       Date:  2022-06-03

5.  Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing.

Authors:  Thomas Pfeffer; Christian Keitel; Tobias H Donner; Joachim Gross; Daniel S Kluger; Anne Keitel; Alena Russmann; Gregor Thut
Journal:  Elife       Date:  2022-02-08       Impact factor: 8.713

6.  Inter- and intra-individual coupling between pupillary, electrophysiological, and behavioral responses in a visual oddball task.

Authors:  Sara LoTemplio; Jack Silcox; Kara D Federmeier; Brennan R Payne
Journal:  Psychophysiology       Date:  2020-12-21       Impact factor: 4.348

7.  Modeling startle eyeblink electromyogram to assess fear learning.

Authors:  Saurabh Khemka; Athina Tzovara; Samuel Gerster; Boris B Quednow; Dominik R Bach
Journal:  Psychophysiology       Date:  2016-10-18       Impact factor: 4.016

8.  Individual differences in eye blink rate predict both transient and tonic pupil responses during reversal learning.

Authors:  Joanne C Van Slooten; Sara Jahfari; Tomas Knapen; Jan Theeuwes
Journal:  PLoS One       Date:  2017-09-29       Impact factor: 3.240

9.  Testing a linear time invariant model for skin conductance responses by intraneural recording and stimulation.

Authors:  Samuel Gerster; Barbara Namer; Mikael Elam; Dominik R Bach
Journal:  Psychophysiology       Date:  2017-09-01       Impact factor: 4.016

10.  A pupil size response model to assess fear learning.

Authors:  Christoph W Korn; Matthias Staib; Athina Tzovara; Giuseppe Castegnetti; Dominik R Bach
Journal:  Psychophysiology       Date:  2016-12-07       Impact factor: 4.016

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