Translational Psychiatry (Nov 2020)

Gamma oscillations predict pro-cognitive and clinical response to auditory-based cognitive training in schizophrenia

  • Juan L. Molina,
  • Michael L. Thomas,
  • Yash B. Joshi,
  • William C. Hochberger,
  • Daisuke Koshiyama,
  • John A. Nungaray,
  • Lauren Cardoso,
  • Joyce Sprock,
  • David L. Braff,
  • Neal R. Swerdlow,
  • Gregory A. Light

DOI
https://doi.org/10.1038/s41398-020-01089-6
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 10

Abstract

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Abstract Cognitive impairments are pervasive and disabling features of schizophrenia. Targeted cognitive training (TCT) is a “bottom-up” cognitive remediation intervention with efficacy for neurocognitive outcomes in schizophrenia, yet individual responses are variable. Gamma oscillatory measures are leading candidate biomarkers in the development of biologically informed pro-cognitive therapeutics. Forty-two schizophrenia patients were recruited from a long-term residential treatment facility. Participants were randomized to receive either 1 h of cognitive training (TCT, n = 21) or computer games (TAU, n = 21). All participants received standard-of-care treatment; the TCT group additionally completed 30 h of cognitive training. The auditory steady-state response paradigm was used to elicit gamma oscillatory power and synchrony during electroencephalogram recordings. Detailed clinical and cognitive assessments were collected at baseline and after completion of the study. Baseline gamma power predicted cognitive gains after a full course of TCT (MCCB, R 2 = 0.31). A change in gamma power after 1-h TCT exposure predicted improvement in both positive (SAPS, R 2 = 0.40) and negative (SANS, R 2 = 0.30) symptoms. These relationships were not observed in the TAU group (MCCB, SAPS, and SANS, all R 2 < 0.06). The results indicate that the capacity to support gamma oscillations, as well as the plasticity of the underlying ASSR circuitry after acute exposure to 1 h of TCT, reflect neural mechanisms underlying the efficacy of TCT, and may be used to predict individualized treatment outcomes. These findings suggest that gamma oscillatory biomarkers applied within the context of experimental medicine designs can be used to personalize individual treatment options for pro-cognitive interventions in patients with schizophrenia.