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Front Hum Neurosci. 2014 Dec 18;8:1008. doi: 10.3389/fnhum.2014.01008. eCollection 2014.

Tuning pathological brain oscillations with neurofeedback: a systems neuroscience framework.

Author information

1
Laboratory for Neurology and Imaging of Cognition, Department of Neurosciences, University of Geneva Geneva, Switzerland.
2
Theoretical Neurobiology, The Neurosciences Institute La Jolla, CA, USA.
3
Department of Psychiatry, University of Western Ontario London, ON, Canada.

Abstract

Neurofeedback (NFB) is emerging as a promising technique that enables self-regulation of ongoing brain oscillations. However, despite a rise in empirical evidence attesting to its clinical benefits, a solid theoretical basis is still lacking on the manner in which NFB is able to achieve these outcomes. The present work attempts to bring together various concepts from neurobiology, engineering, and dynamical systems so as to propose a contemporary theoretical framework for the mechanistic effects of NFB. The objective is to provide a firmly neurophysiological account of NFB, which goes beyond traditional behaviorist interpretations that attempt to explain psychological processes solely from a descriptive standpoint whilst treating the brain as a "black box". To this end, we interlink evidence from experimental findings that encompass a broad range of intrinsic brain phenomena: starting from "bottom-up" mechanisms of neural synchronization, followed by "top-down" regulation of internal brain states, moving to dynamical systems plus control-theoretic principles, and concluding with activity-dependent as well as homeostatic forms of brain plasticity. In support of our framework, we examine the effects of NFB in several brain disorders, including attention-deficit hyperactivity (ADHD) and post-traumatic stress disorder (PTSD). In sum, it is argued that pathological oscillations emerge from an abnormal formation of brain-state attractor landscape(s). The central thesis put forward is that NFB tunes brain oscillations toward a homeostatic set-point which affords an optimal balance between network flexibility and stability (i.e., self-organised criticality (SOC)).

KEYWORDS:

brain computer interface (BCI); brain disorders; brain plasticity; criticality; electroencephalography (EEG); magnetoencephalography (MEG); neurofeedback; neuromodulation

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