TY - JOUR

T1 - Silent expectations

T2 - Dynamic causal modeling of cortical prediction and attention to sounds that weren’t

AU - Chennu, Srivas

AU - Noreika, Valdas

AU - Gueorguiev, David

AU - Shtyrov, Yury

AU - Bekinschtein, Tristan A.

AU - Henson, Richard

PY - 2016/8/10

Y1 - 2016/8/10

N2 - There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called “mismatch response”). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an “omission” response). This situation arguably provides a more direct measure of “top-down” predictions in the absence of confounding “bottom-up” input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG andMEGto an auditory paradigm in which we factorially crossed the presence versus absence of “bottom-up” stimuli with the presence versus absence of “top-down” attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward “prediction” connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction.

AB - There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called “mismatch response”). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an “omission” response). This situation arguably provides a more direct measure of “top-down” predictions in the absence of confounding “bottom-up” input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG andMEGto an auditory paradigm in which we factorially crossed the presence versus absence of “bottom-up” stimuli with the presence versus absence of “top-down” attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward “prediction” connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction.

KW - Dynamic causal modeling

KW - Electroencephalography

KW - Hierarchical predictive coding

KW - Magnetoencephalography

KW - Mismatch effect

KW - Omission effect

UR - http://www.scopus.com/inward/record.url?scp=84981311973&partnerID=8YFLogxK

U2 - 10.1523/JNEUROSCI.1125-16.2016

DO - 10.1523/JNEUROSCI.1125-16.2016

M3 - Article

C2 - 27511005

AN - SCOPUS:84981311973

VL - 36

SP - 8305

EP - 8316

JO - Journal of Neuroscience

JF - Journal of Neuroscience

SN - 0270-6474

IS - 32

ER -