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A neurocomputational model of the mismatch negativity
- Source :
- PLoS Computational Biology, Vol 9, Iss 11, p e1003288 (2013), PLoS Computational Biology, 9 (11), PLoS Computational Biology
- Publication Year :
- 2013
- Publisher :
- Public Library of Science (PLoS), 2013.
-
Abstract
- The mismatch negativity (MMN) is an event related potential evoked by violations of regularity. Here, we present a model of the underlying neuronal dynamics based upon the idea that auditory cortex continuously updates a generative model to predict its sensory inputs. The MMN is then modelled as the superposition of the electric fields evoked by neuronal activity reporting prediction errors. The process by which auditory cortex generates predictions and resolves prediction errors was simulated using generalised (Bayesian) filtering – a biologically plausible scheme for probabilistic inference on the hidden states of hierarchical dynamical models. The resulting scheme generates realistic MMN waveforms, explains the qualitative effects of deviant probability and magnitude on the MMN – in terms of latency and amplitude – and makes quantitative predictions about the interactions between deviant probability and magnitude. This work advances a formal understanding of the MMN and – more generally – illustrates the potential for developing computationally informed dynamic causal models of empirical electromagnetic responses.<br />PLoS Computational Biology, 9 (11)<br />ISSN:1553-734X<br />ISSN:1553-7358
- Subjects :
- Auditory Cortex
Models, Statistical
Quantitative Biology::Neurons and Cognition
Models, Neurological
2804 Cellular and Molecular Neuroscience
Computational Biology
610 Medicine & health
Bayes Theorem
Electroencephalography
170 Ethics
1105 Ecology, Evolution, Behavior and Systematics
1311 Genetics
lcsh:Biology (General)
1312 Molecular Biology
Humans
10237 Institute of Biomedical Engineering
Computer Simulation
2303 Ecology
Evoked Potentials
lcsh:QH301-705.5
Algorithms
2611 Modeling and Simulation
1703 Computational Theory and Mathematics
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 15537358 and 1553734X
- Volume :
- 9
- Issue :
- 11
- Database :
- OpenAIRE
- Journal :
- PLoS Computational Biology
- Accession number :
- edsair.doi.dedup.....2f147694ef9a1ebde0cca7d36859b489