2022
DOI: 10.1101/2022.03.25.485823
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Degeneracy in the neurological model of auditory speech repetition

Abstract: In the neurological model of language, repeating heard speech involves four left hemisphere regions: primary auditory cortex for processing sounds; Wernicke's area for processing auditory images of speech; Broca's area for processing motor images of speech; and primary motor cortex for overt speech articulation. Previous functional-MRI (fMRI) studies confirm that auditory repetition activates these regions. Here, we used dynamic causal modelling (DCM) to test how the four regions interact with each other durin… Show more

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“…Naturally, gain control is accompanied by neuronal variability, i.e., sharpened neural responses for the same task over time. Consistent with gain control, these fluctuations in neural responses across trials can be explained by precision engineered message passing (Clark, 2013) via (i) normalization models (Reynolds and Heeger, 2009;Ruff and Cohen, 2016), (ii) temperature parameter manipulation (Feldman and Friston, 2010;Parr and Friston, 2017a;Parr et al, 2018Mirza et al, 2019), or (iii) introduction of (conjugate hyper-)priors that are either pre-specified (Sajid et al, 2020(Sajid et al, , 2021b or optimized using uninformed priors (Friston et al, 2003;Anil Meera and Wisse, 2021). Recently, these approaches have been used to simulate attention by accentuating predictions about a given visual stimulus (Reynolds and Heeger, 2009;Feldman and Friston, 2010;Ruff and Cohen, 2016).…”
Section: Attention As Neural Gain Controlmentioning
confidence: 99%
“…Naturally, gain control is accompanied by neuronal variability, i.e., sharpened neural responses for the same task over time. Consistent with gain control, these fluctuations in neural responses across trials can be explained by precision engineered message passing (Clark, 2013) via (i) normalization models (Reynolds and Heeger, 2009;Ruff and Cohen, 2016), (ii) temperature parameter manipulation (Feldman and Friston, 2010;Parr and Friston, 2017a;Parr et al, 2018Mirza et al, 2019), or (iii) introduction of (conjugate hyper-)priors that are either pre-specified (Sajid et al, 2020(Sajid et al, , 2021b or optimized using uninformed priors (Friston et al, 2003;Anil Meera and Wisse, 2021). Recently, these approaches have been used to simulate attention by accentuating predictions about a given visual stimulus (Reynolds and Heeger, 2009;Feldman and Friston, 2010;Ruff and Cohen, 2016).…”
Section: Attention As Neural Gain Controlmentioning
confidence: 99%