Literature DB >> 23663509

Grounding predictive coding models in empirical neuroscience research.

Tobias Egner1, Christopher Summerfield.   

Abstract

Clark makes a convincing case for the merits of conceptualizing brains as hierarchical prediction machines. This perspective has the potential to provide an elegant and powerful general theory of brain function, but it will ultimately stand or fall with evidence from basic neuroscience research. Here, we characterize the status quo of that evidence and highlight important avenues for future investigations.

Mesh:

Year:  2013        PMID: 23663509     DOI: 10.1017/S0140525X1200218X

Source DB:  PubMed          Journal:  Behav Brain Sci        ISSN: 0140-525X            Impact factor:   12.579


  6 in total

Review 1.  Computational psychiatry: from synapses to sentience.

Authors:  Karl Friston
Journal:  Mol Psychiatry       Date:  2022-09-02       Impact factor: 13.437

2.  Threat Prediction from Schemas as a Source of Bias in Pain Perception.

Authors:  Manyoel Lim; Christopher O'Grady; Douglas Cane; Amita Goyal; Mary Lynch; Steven Beyea; Javeria Ali Hashmi
Journal:  J Neurosci       Date:  2020-01-02       Impact factor: 6.167

Review 3.  A Duet for one.

Authors:  Karl Friston; Christopher Frith
Journal:  Conscious Cogn       Date:  2015-01-03

Review 4.  Active inference, communication and hermeneutics.

Authors:  Karl J Friston; Christopher D Frith
Journal:  Cortex       Date:  2015-04-15       Impact factor: 4.027

5.  The basal ganglia select the expected sensory input used for predictive coding.

Authors:  Brian Colder
Journal:  Front Comput Neurosci       Date:  2015-09-23       Impact factor: 2.380

Review 6.  Evaluating the neurophysiological evidence for predictive processing as a model of perception.

Authors:  Kevin S Walsh; David P McGovern; Andy Clark; Redmond G O'Connell
Journal:  Ann N Y Acad Sci       Date:  2020-03-08       Impact factor: 5.691

  6 in total

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