• Nature communications · Mar 2018

    Thalamocortical dysrhythmia detected by machine learning.

    • Sven Vanneste, Jae-Jin Song, and Dirk De Ridder.
    • School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, 75080, USA. sven.vanneste@utdallas.edu.
    • Nat Commun. 2018 Mar 16; 9 (1): 1103.

    AbstractThalamocortical dysrhythmia (TCD) is a model proposed to explain divergent neurological disorders. It is characterized by a common oscillatory pattern in which resting-state alpha activity is replaced by cross-frequency coupling of low- and high-frequency oscillations. We undertook a data-driven approach using support vector machine learning for analyzing resting-state electroencephalography oscillatory patterns in patients with Parkinson's disease, neuropathic pain, tinnitus, and depression. We show a spectrally equivalent but spatially distinct form of TCD that depends on the specific disorder. However, we also identify brain areas that are common to the pathology of Parkinson's disease, pain, tinnitus, and depression. This study therefore supports the validity of TCD as an oscillatory mechanism underlying diverse neurological disorders.

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