Dirk DeRidder, MD, PhD - Neuromodulation (TMS, tDCS, tRNS, tACS, neurofeedback): Working Mechanisms (K-04_2015)

  • Number of students: 3
  • Released: 2017-11-11 03:36:42
  • Level: Beginner
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Description

Presenter: Dirk DeRidder, MD, PhD

The brain is an information processing machine adjusting itself to the environment. Information processing is performed to reduce uncertainty, which is inherently present in a changing environment. Perception can be seen as Bayesian inference, where an intention driven prediction is actively looked in the environment to update the prediction. The percept itself is an emerging property of network activation, processing the information at different oscillation frequencies for each subnetwork. Brain related symptoms or diseases are associated with both activity, and even more importantly, connectivity changes. Using the brain’s adaptive characteristics can be advantageous in retraining the brain by reshaping its networks. This is the purpose of neurostimulation and neurofeedback. Whereas neurostimulation interferes directly with activity and connectivity, neurofeedback or operant conditioning likely exerts its effect by interfering with the brain’s Bayesian updating mechanisms. A conceptual model of brain functioning can help to  understand mechanisms involved in neurofeedback. This model relates delta oscillations to controlling basic homeostatic activity and a delta can be considered a carrier wave for higher oscillation frequencies, most likely beta activity. Theta is a memory related carrier wave integrating beta3 and gamma activity by theta-beta and theta gamma nesting. Theta oscillations cover short and long range connections, whereas beta3 and gamma oscillations are more locally restricted in widely distributed areas. Alpha oscillations are thalamically driven and can be linked to attentional processes. Delta and beta 1-2 is intermediate in its connectivity range. Theta/beta cross-frequency coupling possibly encodes memory-based predictions of future events/stimuli. In order to update the prediction, alpha is used as scanning frequency sampling the environment for salient information. The prediction error or change is encoded in gamma. Thus correct predictions about the environment will be encoded by beta activity, which therefore represents a status quo, whereas wrong predictions or insufficient input from the environment will be represented by beta/gamma cross-frequency coupling. Thus neurofeedback attempts to modulate these oscillatory networks, thereby normalizing predictions or processing of prediction errors. This results in changing functional and effective connectivity as well as cross-frequency coupling.

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