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Dynamic causal modelling of eye movements during pursuit: Confirming precision-encoding in V1 using MEG.

Adams RA, Bauer M, Pinotsis D, Friston KJ - Neuroimage (2016)

Bottom Line: We compared (noisy motion-induced) changes in the synaptic gain based on the modelling of MEG data to changes in subjective precision estimated using the pursuit data.Furthermore, increases in sensory precision - inferred by our behavioural DCM - correlate with the increase in gain in V1, across subjects.This is a step towards a fully integrated model of brain computations, cortical responses and behaviour that may provide a useful clinical tool in conditions like schizophrenia.

View Article: PubMed Central - PubMed

Affiliation: The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK. Electronic address: rick.adams@ucl.ac.uk.

No MeSH data available.


Related in: MedlinePlus

DCM results.This graph plots the log model evidences for each combination of two factors: connection type (precision, i.e. self-inhibitory, and forward) and hierarchical level (low, i.e. V1/2 and high, i.e. V5). Model 5 — in which only lower connections (both forward and self-inhibitory) are modulated by stimulus noise — is the clear winner, with > 100 times the evidence of the runner up.
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f0045: DCM results.This graph plots the log model evidences for each combination of two factors: connection type (precision, i.e. self-inhibitory, and forward) and hierarchical level (low, i.e. V1/2 and high, i.e. V5). Model 5 — in which only lower connections (both forward and self-inhibitory) are modulated by stimulus noise — is the clear winner, with > 100 times the evidence of the runner up.

Mentions: The results of the DCM analysis of connections that are most likely to be modulated by noisy visual motion are shown in Fig. 7. The winning model is Model 5, which allowed for changes in lower level recurrent self-inhibitory (precision) and forward connections. The evidence for Model 9, which allowed changes in lower level forward and higher level self-inhibitory connections, was 135 times less, which reflects ‘decisive’ evidence for Model 5.


Dynamic causal modelling of eye movements during pursuit: Confirming precision-encoding in V1 using MEG.

Adams RA, Bauer M, Pinotsis D, Friston KJ - Neuroimage (2016)

DCM results.This graph plots the log model evidences for each combination of two factors: connection type (precision, i.e. self-inhibitory, and forward) and hierarchical level (low, i.e. V1/2 and high, i.e. V5). Model 5 — in which only lower connections (both forward and self-inhibitory) are modulated by stimulus noise — is the clear winner, with > 100 times the evidence of the runner up.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862965&req=5

f0045: DCM results.This graph plots the log model evidences for each combination of two factors: connection type (precision, i.e. self-inhibitory, and forward) and hierarchical level (low, i.e. V1/2 and high, i.e. V5). Model 5 — in which only lower connections (both forward and self-inhibitory) are modulated by stimulus noise — is the clear winner, with > 100 times the evidence of the runner up.
Mentions: The results of the DCM analysis of connections that are most likely to be modulated by noisy visual motion are shown in Fig. 7. The winning model is Model 5, which allowed for changes in lower level recurrent self-inhibitory (precision) and forward connections. The evidence for Model 9, which allowed changes in lower level forward and higher level self-inhibitory connections, was 135 times less, which reflects ‘decisive’ evidence for Model 5.

Bottom Line: We compared (noisy motion-induced) changes in the synaptic gain based on the modelling of MEG data to changes in subjective precision estimated using the pursuit data.Furthermore, increases in sensory precision - inferred by our behavioural DCM - correlate with the increase in gain in V1, across subjects.This is a step towards a fully integrated model of brain computations, cortical responses and behaviour that may provide a useful clinical tool in conditions like schizophrenia.

View Article: PubMed Central - PubMed

Affiliation: The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK. Electronic address: rick.adams@ucl.ac.uk.

No MeSH data available.


Related in: MedlinePlus