Stochastic Motion Stimuli Influence Perceptual Choices in Human Participants

Overview

Journal Front Neurosci

Date 2022 Mar 21

PMID 35309084

Authors

Pouyan R Fard

Sebastian Bitzer

Sebastian Pannasch

Stefan J Kiebel

Affiliations

Soon will be listed here.

Abstract

In the study of perceptual decision making, it has been widely assumed that random fluctuations of motion stimuli are irrelevant for a participant's choice. Recently, evidence was presented that these random fluctuations have a measurable effect on the relationship between neuronal and behavioral variability, the so-called choice probability. Here, we test, in a behavioral experiment, whether stochastic motion stimuli influence the choices of human participants. Our results show that for specific stochastic motion stimuli, participants indeed make biased choices, where the bias is consistent over participants. Using a computational model, we show that this consistent choice bias is caused by subtle motion information contained in the motion noise. We discuss the implications of this finding for future studies of perceptual decision making. Specifically, we suggest that future experiments should be complemented with a stimulus-informed modeling approach to control for the effects of apparent decision evidence in random stimuli.

References

Kiani R, Hanks T, Shadlen M . Bounded integration in parietal cortex underlies decisions even when viewing duration is dictated by the environment. J Neurosci. 2008; 28(12):3017-29. PMC: 6670720. DOI: 10.1523/JNEUROSCI.4761-07.2008. View

Zylberberg A, Barttfeld P, Sigman M . The construction of confidence in a perceptual decision. Front Integr Neurosci. 2012; 6:79. PMC: 3448113. DOI: 10.3389/fnint.2012.00079. View

Penny W, Stephan K, Daunizeau J, Rosa M, Friston K, Schofield T . Comparing families of dynamic causal models. PLoS Comput Biol. 2010; 6(3):e1000709. PMC: 2837394. DOI: 10.1371/journal.pcbi.1000709. View

Stephan K, Penny W, Daunizeau J, Moran R, Friston K . Bayesian model selection for group studies. Neuroimage. 2009; 46(4):1004-17. PMC: 2703732. DOI: 10.1016/j.neuroimage.2009.03.025. View

Newsome W, Pare E . A selective impairment of motion perception following lesions of the middle temporal visual area (MT). J Neurosci. 1988; 8(6):2201-11. PMC: 6569328. View

Daunizeau J, Adam V, Rigoux L . VBA: a probabilistic treatment of nonlinear models for neurobiological and behavioural data. PLoS Comput Biol. 2014; 10(1):e1003441. PMC: 3900378. DOI: 10.1371/journal.pcbi.1003441. View

Cohen M, Newsome W . Estimates of the contribution of single neurons to perception depend on timescale and noise correlation. J Neurosci. 2009; 29(20):6635-48. PMC: 2705937. DOI: 10.1523/JNEUROSCI.5179-08.2009. View

Wimmer K, Compte A, Roxin A, Peixoto D, Renart A, de la Rocha J . Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT. Nat Commun. 2015; 6:6177. PMC: 4347303. DOI: 10.1038/ncomms7177. View

Brunton B, Botvinick M, Brody C . Rats and humans can optimally accumulate evidence for decision-making. Science. 2013; 340(6128):95-8. DOI: 10.1126/science.1233912. View

10.

Jazayeri M, Movshon J . Optimal representation of sensory information by neural populations. Nat Neurosci. 2006; 9(5):690-6. DOI: 10.1038/nn1691. View

11.

Fard P, Park H, Warkentin A, Kiebel S, Bitzer S . A Bayesian Reformulation of the Extended Drift-Diffusion Model in Perceptual Decision Making. Front Comput Neurosci. 2017; 11:29. PMC: 5425616. DOI: 10.3389/fncom.2017.00029. View

12.

Urai A, Braun A, Donner T . Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias. Nat Commun. 2017; 8:14637. PMC: 5337963. DOI: 10.1038/ncomms14637. View

13.

Bair W, Koch C . Temporal precision of spike trains in extrastriate cortex of the behaving macaque monkey. Neural Comput. 1996; 8(6):1185-202. DOI: 10.1162/neco.1996.8.6.1185. View

14.

Adelson E, Bergen J . Spatiotemporal energy models for the perception of motion. J Opt Soc Am A. 1985; 2(2):284-99. DOI: 10.1364/josaa.2.000284. View

15.

Wong K, Huk A, Shadlen M, Wang X . Neural circuit dynamics underlying accumulation of time-varying evidence during perceptual decision making. Front Comput Neurosci. 2008; 1:6. PMC: 2525934. DOI: 10.3389/neuro.10.006.2007. View

16.

Celebrini S, Newsome W . Neuronal and psychophysical sensitivity to motion signals in extrastriate area MST of the macaque monkey. J Neurosci. 1994; 14(7):4109-24. PMC: 6577020. View

17.

Shadlen M, Newsome W . Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J Neurophysiol. 2001; 86(4):1916-36. DOI: 10.1152/jn.2001.86.4.1916. View

18.

Friston K, Kiebel S . Predictive coding under the free-energy principle. Philos Trans R Soc Lond B Biol Sci. 2009; 364(1521):1211-21. PMC: 2666703. DOI: 10.1098/rstb.2008.0300. View

19.

Roitman J, Shadlen M . Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J Neurosci. 2002; 22(21):9475-89. PMC: 6758024. View

20.

Shadlen M, Carney T . Mechanisms of human motion perception revealed by a new cyclopean illusion. Science. 1986; 232(4746):95-7. DOI: 10.1126/science.3952502. View