» Articles » PMID: 26350626

Prior Probability Modulates Anticipatory Activity in Category-specific Areas

Overview
Publisher Springer
Date 2015 Sep 10
PMID 26350626
Citations 11
Authors
Affiliations
Soon will be listed here.
Abstract

Bayesian models are currently a dominant framework for describing human information processing. However, it is not clear yet how major tenets of this framework can be translated to brain processes. In this study, we addressed the neural underpinning of prior probability and its effect on anticipatory activity in category-specific areas. Before fMRI scanning, participants were trained in two behavioral sessions to learn the prior probability and correct order of visual events within a sequence. The events of each sequence included two different presentations of a geometric shape and one picture of either a house or a face, which appeared with either a high or a low likelihood. Each sequence was preceded by a cue that gave participants probabilistic information about which items to expect next. This allowed examining cue-related anticipatory modulation of activity as a function of prior probability in category-specific areas (fusiform face area and parahippocampal place area). Our findings show that activity in the fusiform face area was higher when faces had a higher prior probability. The finding of a difference between levels of expectations is consistent with graded, probabilistically modulated activity, but the data do not rule out the alternative explanation of a categorical neural response. Importantly, these differences were only visible during anticipation, and vanished at the time of stimulus presentation, calling for a functional distinction when considering the effects of prior probability. Finally, there were no anticipatory effects for houses in the parahippocampal place area, suggesting sensitivity to stimulus material when looking at effects of prediction.

Citing Articles

Prior probability cues bias sensory encoding with increasing task exposure.

Walsh K, McGovern D, Dully J, Kelly S, OConnell R Elife. 2024; 12.

PMID: 38564237 PMC: 10987094. DOI: 10.7554/eLife.91135.


Predictive Brain Activity Shows Congruent Semantic Specificity in Language Comprehension and Production.

Grisoni L, Boux I, Pulvermuller F J Neurosci. 2024; 44(12).

PMID: 38267261 PMC: 10957213. DOI: 10.1523/JNEUROSCI.1723-23.2023.


Bayesian decision-making under stress-preserved weighting of prior and likelihood information.

Trapp S, Vilares I Sci Rep. 2020; 10(1):21456.

PMID: 33293616 PMC: 7722735. DOI: 10.1038/s41598-020-76493-5.


Object recognition is enabled by an experience-dependent appraisal of visual features in the brain's value system.

Kozunov V, West T, Nikolaeva A, Stroganova T, Friston K Neuroimage. 2020; 221:117143.

PMID: 32650054 PMC: 7762843. DOI: 10.1016/j.neuroimage.2020.117143.


Evaluating the neurophysiological evidence for predictive processing as a model of perception.

Walsh K, McGovern D, Clark A, OConnell R Ann N Y Acad Sci. 2020; 1464(1):242-268.

PMID: 32147856 PMC: 7187369. DOI: 10.1111/nyas.14321.


References
1.
de Gardelle V, Waszczuk M, Egner T, Summerfield C . Concurrent repetition enhancement and suppression responses in extrastriate visual cortex. Cereb Cortex. 2012; 23(9):2235-44. PMC: 3729201. DOI: 10.1093/cercor/bhs211. View

2.
Summerfield C, Egner T . Expectation (and attention) in visual cognition. Trends Cogn Sci. 2009; 13(9):403-9. DOI: 10.1016/j.tics.2009.06.003. View

3.
Gauthier I, Skudlarski P, Gore J, Anderson A . Expertise for cars and birds recruits brain areas involved in face recognition. Nat Neurosci. 2000; 3(2):191-7. DOI: 10.1038/72140. View

4.
Kording K, Wolpert D . Bayesian integration in sensorimotor learning. Nature. 2004; 427(6971):244-7. DOI: 10.1038/nature02169. View

5.
Kok P, Jehee J, de Lange F . Less is more: expectation sharpens representations in the primary visual cortex. Neuron. 2012; 75(2):265-70. DOI: 10.1016/j.neuron.2012.04.034. View