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Towards a computational model of Dyslexia
BMC Neuroscience volume 16, Article number: O12 (2015)
Dyslexics are diagnosed for their poor reading skills. Yet, they characteristically also suffer from poor verbal memory, and often from poor auditory skills. We now hypothesize that dyslexia can be understood computationally as a deficit in integrating prior information with noisy observations. To test this hypothesis we analyzed performance in two tones pitch discrimination task using a two-parameter computational model. One parameter captures the internal noise in representing the current event and the other captures the impact of recently acquired prior information [1]. We found that dyslexics' perceptual deficit can be accounted for by inadequate adjustment of these components: low weighting of their implicit memory in relation to their internal noise (Figure 1). Using ERP measurements we found evidence for dyslexics' deficient automatic integration of experiment's statistics (Figure 2). Taken together, these results suggest that dyslexia can be understood as a well-defined computational deficit.
References
Raviv O, Ahissar M, Loewenstein Y: How recent history affects perception: the normative approach and its heuristic approximation. PLoS Comput Biol. 2012, 8: e1002731-
Acknowledgements
This work was supported by Israel Science Foundation (grant no. 616/11).
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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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Jaffe-Dax, S., Raviv, O., Jacoby, N. et al. Towards a computational model of Dyslexia. BMC Neurosci 16 (Suppl 1), O12 (2015). https://doi.org/10.1186/1471-2202-16-S1-O12
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DOI: https://doi.org/10.1186/1471-2202-16-S1-O12