Common and distinct neural effects of risperidone and olanzapine during procedural learning in schizophrenia: a randomised longitudinal fMRI study.

RATIONALE: Most cognitive domains show only minimal improvement following typical or atypical antipsychotic treatments in schizophrenia, and some may even worsen. One domain that may worsen is procedural learning, an implicit memory function relying mainly on the integrity of the fronto-striatal system. OBJECTIVES: We investigated whether switching to atypical antipsychotics would improve procedural learning and task-related neural activation in patients on typical antipsychotics. Furthermore, we explored the differential effects of the atypical antipsychotics risperidone and olanzapine. METHODS: Thirty schizophrenia patients underwent functional magnetic resonance imaging during a 5-min procedural (sequence) learning task on two occasions: at baseline and 7-8 weeks later. Of 30 patients, 10 remained on typical antipsychotics, and 20 were switched randomly in equal numbers to receive either olanzapine (10-20 mg) or risperidone (4-8 mg) for 7-8 weeks. RESULTS: At baseline, patients (all on typical antipsychotics) showed no procedural learning. At follow-up, patients who remained on typical antipsychotics continued to show a lack of procedural learning, whereas those switched to atypical antipsychotics displayed significant procedural learning (p = 0.001) and increased activation in the superior-middle frontal gyrus, anterior cingulate and striatum (cluster-corrected p < 0.05). These neural effects were present as a linear increase over five successive 30-s blocks of sequenced trials. A switch to either risperidone or olanzapine resulted in comparable performance but with both overlapping and distinct task-related activations. CONCLUSIONS: Atypical antipsychotics restore procedural learning deficits and associated neural activity in schizophrenia. Furthermore, different atypical antipsychotics produce idiosyncratic task-related neural activations, and this specificity may contribute to their differential long-term clinical profiles.

Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses - the case of behavioral variant frontotemporal dementia.

INTRODUCTION: Uniform coordinate systems in neuroimaging research have enabled comprehensive systematic and quantitative meta-analyses. Such approaches are particularly relevant for neuropsychiatric diseases, the understanding of their symptoms, prediction and treatment. Behavioral variant frontotemporal dementia (bvFTD), a common neurodegenerative syndrome, is characterized by deep alterations in behavior and personality. Investigating this 'nexopathy' elucidates the healthy social and emotional brain. METHODS: Here, we combine three multimodal meta-analyses approaches - anatomical and activation likelihood estimates and behavioral domain profiles - to identify neural correlates of bvFTD in 417 patients and 406 control subjects and to extract mental functions associated with this disease by meta-analyzing functional activation studies in the comprehensive probabilistic functional brain atlas of the BrainMap database. RESULTS: The analyses identify the frontomedian cortex, basal ganglia, anterior insulae and thalamus as most relevant hubs, with a regional dissociation between atrophy and hypometabolism. Neural networks affected by bvFTD were associated with emotion and reward processing, empathy and executive functions (mainly inhibition), suggesting these functions as core domains affected by the disease and finally leading to its clinical symptoms. In contrast, changes in theory of mind or mentalizing abilities seem to be secondary phenomena of executive dysfunctions. CONCLUSIONS: The study creates a novel conceptual framework to understand neuropsychiatric diseases by powerful data-driven meta-analytic approaches that shall be extended to the whole neuropsychiatric spectrum in the future.