Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't.


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Authors
Noreika, Valdas 
Shtyrov, Yury 
Bekinschtein, Tristan A 
Abstract

UNLABELLED: 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 and MEG to 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. SIGNIFICANCE STATEMENT: Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future.

Description
Keywords
dynamic causal modeling, electroencephalography, hierarchical predictive coding, magnetoencephalography, mismatch effect, omission effect, Adult, Attention, Auditory Perception, Brain Mapping, Cerebral Cortex, Electroencephalography, Evoked Potentials, Auditory, Female, Humans, Magnetic Resonance Imaging, Magnetoencephalography, Male, Models, Neurological, Nonlinear Dynamics, Sound, Young Adult
Journal Title
J Neurosci
Conference Name
Journal ISSN
0270-6474
1529-2401
Volume Title
36
Publisher
Society for Neuroscience
Sponsorship
MRC (unknown)
Wellcome Trust (093875/Z/10/Z)
Medical Research Council (MC_U105579226)
Medical Research Council (MR/K005464/1)
Medical Research Council (G1000183)
This work was supported by the UK Medical Research Council Programme [MC-A060-5PR10 to RH], in addition to grants from the Wellcome Trust [WT093811MA to TAB], the James S. McDonnell Foundation, and the Evelyn Trust [15/07 to SC].