Cognitive control network connectivity differentially disrupted in treatment resistant schizophrenia: Impaired cognitive control connectivity in treatment-resistant schizophrenia

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Abstract

Antipsychotic treatment resistance affects a third of people with schizophrenia and the
underlying mechanism remains unclear. We used an fMRI emotion-yoked reward learning
task, allied to prefrontal cortical glutamate levels, to explain the role of cognitive control in
differentiating treatment-resistant from responsive patients. We investigated how reward
learning is disrupted at the network level in 21 medicated treatment-responsive and 20
medicated treatment-resistant patients with schizophrenia compared with 24 healthy controls
(HC). Dynamic Causal Modelling assessed how effective connectivity between regions in a
cortico-striatal-limbic network is disrupted in each patient group compared to HC.
Connectivity was also examined with respect to symptoms, salience and anterior cingulate
(ACC) glutamate levels measured from the same region of the ACC. We found that ACC
connectivity differentiated these patient groups, with responsive patients exhibiting increased
top-down connectivity from ACC to sensory regions and reduced ACC drive to the striatum,
while resistant patients showed altered connectivity within the ACC itself. In these resistant
patients, the ACC drive to striatum was positively correlated with their symptom severity. ACC
glutamate levels were found to correlate with ACC control over sensory regions in responsive
patients but not in resistant patients. We suggest a central non-dopaminergic impairment that
impacts cognitive control networks in treatment-resistant schizophrenia. This impairment was
associated with disrupted reward learning and could be underpinned by aberrant glutamate
function. These findings should form the focus of future treatment strategies (e.g.
glutamatergic targets and giving clozapine earlier) in resistant patients.
Original languageEnglish
JournalNeuroImage: Clinical
Early online date24 Mar 2021
Publication statusE-pub ahead of print - 24 Mar 2021

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