2015
DOI: 10.1016/j.conb.2014.05.004
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LFP and oscillations—what do they tell us?

Abstract: HighlightsA brief treatment of dynamic coordination in terms of predictive coding.Understanding synchronous message passing in terms of hierarchical predictive coding.Characterising cortical gain control with the dynamic causal modelling of neural fields.Characterising pathophysiological oscillations with dynamic causal modelling of neural masses.

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Cited by 172 publications
(147 citation statements)
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“…Theoretical models have associated top-down processes with oscillations in the 8 to 14Hz range (Bastos et al, 2012;Friston, Bastos, Pinotsis, & Litvak, 2014) and recent neurophysiological findings suggest that occipital alpha oscillations primarily propagate in a top-down fashion (van Kerkoerle et al, 2014), supporting the notion that alpha power is intimately related to top-down control (Klimesch, Sauseng, & Hanslmayr, 2007;Mathewson et al, 2012;Palva & Palva, 2007). Recent work has revealed that the phase (in addition to power) of prestimulus alpha oscillations also predicts various components of perception.…”
mentioning
confidence: 79%
“…Theoretical models have associated top-down processes with oscillations in the 8 to 14Hz range (Bastos et al, 2012;Friston, Bastos, Pinotsis, & Litvak, 2014) and recent neurophysiological findings suggest that occipital alpha oscillations primarily propagate in a top-down fashion (van Kerkoerle et al, 2014), supporting the notion that alpha power is intimately related to top-down control (Klimesch, Sauseng, & Hanslmayr, 2007;Mathewson et al, 2012;Palva & Palva, 2007). Recent work has revealed that the phase (in addition to power) of prestimulus alpha oscillations also predicts various components of perception.…”
mentioning
confidence: 79%
“…From a predictive coding perspective, topdown information (conveyed by feedback connections) provides context for lower-level processing over slower time scales (beta oscillations), while bottom-up information (conveyed by feedforward connections) works on faster time scales (gamma oscillations) propagating prediction errors up the hierarchy in order to rapidly adapt predictions at these higher levels. This implies that oscillatory activity in the beta frequency range might be a proxy for top-down predictions about activity at lower hierarchical levels within a cortical hierarchy, while gamma oscillations might be an indication of the forward propagation of prediction errors to higher cortical levels in order to update predictions (Bastos et al, 2012;Friston, Bastos, Pinotsis, & Litvak, 2015). Bressler and Richter (2015) propose that cortical areas recruited under task-specific conditions may be linked by inter-areal beta synchrony to form NeuroCognitive Networks (NCNs e self-organizing, large-scale distributed cortical networks) at the highest hierarchical levels.…”
Section: 1mentioning
confidence: 99%
“…Fourth, there may be a central role for AA in free energy theory because it could provide an intracellular mechanism for the control of gain, precision, or confidence that is central to the theory (Brown, Adams, Parees, Edwards, & Friston, 2013;Clark, 2013aClark, , 2013bFriston, 2010;Friston, Bastos, Pinotsis, & Litvak, 2015). From its early days free energy theory has been primarily concerned with analyzing the macroscopic dynamics of whole neural systems adapting to and operating within an environment.…”
Section: The Bayesian Brain Predictive Coding and Free Energy Minimimentioning
confidence: 99%
“…From its early days free energy theory has been primarily concerned with analyzing the macroscopic dynamics of whole neural systems adapting to and operating within an environment. Therefore, as Friston et al (2015) say, a long road ahead faces attempts to test and develop it in terms of intracellular processes. Consideration of the evidence for AA may provide some early steps along that road, and supports the free energy theory in several ways.…”
Section: The Bayesian Brain Predictive Coding and Free Energy Minimimentioning
confidence: 99%