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New Insights into the Nature of Cerebellar-Dependent Eyeblink Conditioning Deficits in Schizophrenia: A Hierarchical Linear Modeling Approach. | LitMetric

AI Article Synopsis

  • Research indicates a link between cerebellar dysfunction and schizophrenia, supported by various studies exploring neuroimaging and behavior, particularly in delay eyeblink conditioning (dEBC).
  • The current study applied hierarchical linear modeling (HLM) to analyze dEBC data from schizophrenia participants and healthy controls, focusing on a specific experimental design involving tone and air puff stimuli.
  • Results showed significant differences between the two groups in learning outcomes, suggesting that while the rate of learning is similar, individuals with schizophrenia start to plateau in associative learning earlier and reach a lower maximum compared to controls.

Article Abstract

Evidence of cerebellar dysfunction in schizophrenia has mounted over the past several decades, emerging from neuroimaging, neuropathological, and behavioral studies. Consistent with these findings, cerebellar-dependent delay eyeblink conditioning (dEBC) deficits have been identified in schizophrenia. While repeated-measures analysis of variance is traditionally used to analyze dEBC data, hierarchical linear modeling (HLM) more reliably describes change over time by accounting for the dependence in repeated-measures data. This analysis approach is well suited to dEBC data analysis because it has less restrictive assumptions and allows unequal variances. The current study examined dEBC measured with electromyography in a single-cue tone paradigm in an age-matched sample of schizophrenia participants and healthy controls (N = 56 per group) using HLM. Subjects participated in 90 trials (10 blocks) of dEBC, during which a 400 ms tone co-terminated with a 50 ms air puff delivered to the left eye. Each block also contained 1 tone-alone trial. The resulting block averages of dEBC data were fitted to a three-parameter logistic model in HLM, revealing significant differences between schizophrenia and control groups on asymptote and inflection point, but not slope. These findings suggest that while the learning rate is not significantly different compared to controls, associative learning begins to level off later and a lower ultimate level of associative learning is achieved in schizophrenia. Given the large sample size in the present study, HLM may provide a more nuanced and definitive analysis of differences between schizophrenia and controls on dEBC.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4725217PMC
http://dx.doi.org/10.3389/fpsyt.2016.00004DOI Listing

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