Set shifting and reversal learning in patients with bipolar disorder or schizophrenia

Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.
Psychological Medicine (Impact Factor: 5.43). 08/2009; 39(8):1289-93. DOI: 10.1017/S0033291708004935
Source: PubMed

ABSTRACT Bipolar disorder and schizophrenia have both been associated with deficits in extra-dimensional set shifting (EDS). Deficits in reversal learning (RL) have also been shown in schizophrenia but not in bipolar disorder. This study sought to assess the specificity of these findings in a direct comparison of clinically stable patients with each disorder.
The intra-dimensional/extra-dimensional (IDED) set-shifting task, part of the Cambridge Neuropsychological Test Automated Battery (CANTAB), was administered to 30 patients with schizophrenia, 47 with bipolar disorder and a group of 44 unaffected controls. EDS and RL errors were compared between the groups and related to measures of current and past psychiatric symptoms and medication.
Both groups of patients with schizophrenia or bipolar disorder made more EDS and RL errors than controls. Neither measure separated the two disorders, even when the analysis was restricted to euthymic patients. No relationship was found with prescribed medication.
Patients with bipolar disorder or schizophrenia show common deficits in EDS and RL. These deficits do not seem to be attributable to current symptoms and are consistent with disrupted networks involving the ventral prefrontal cortex.


Available from: Andrew Mark Mcintosh, May 29, 2015
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Executive functions consist of multiple high-level cognitive processes that drive rule generation and behavioral selection. An emergent property of these processes is the ability to adjust behavior in response to changes in one's environment (i.e., behavioral flexibility). These processes are essential to normal human behavior, and may be disrupted in diverse neuropsychiatric conditions, including schizophrenia, alcoholism, depression, stroke, and Alzheimer's disease. Understanding of the neurobiology of executive functions has been greatly advanced by the availability of animal tasks for assessing discrete components of behavioral flexibility, particularly strategy shifting and reversal learning. While several types of tasks have been developed, most are non-automated, labor intensive, and allow testing of only one animal at a time. The recent development of automated, operant-based tasks for assessing behavioral flexibility streamlines testing, standardizes stimulus presentation and data recording, and dramatically improves throughput. Here, we describe automated strategy shifting and reversal tasks, using operant chambers controlled by custom written software programs. Using these tasks, we have shown that the medial prefrontal cortex governs strategy shifting but not reversal learning in the rat, similar to the dissociation observed in humans. Moreover, animals with a neonatal hippocampal lesion, a neurodevelopmental model of schizophrenia, are selectively impaired on the strategy shifting task but not the reversal task. The strategy shifting task also allows the identification of separate types of performance errors, each of which is attributable to distinct neural substrates. The availability of these automated tasks, and the evidence supporting the dissociable contributions of separate prefrontal areas, makes them particularly well-suited assays for the investigation of basic neurobiological processes as well as drug discovery and screening in disease models.
    Journal of Visualized Experiments 02/2015; DOI:10.3791/52387
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Objectives Genetic markers in the genes encoding ankyrin 3 (ANK3) and the α-calcium channel subunit (CACNA1C) are associated with bipolar disorder (BP). The associated variants in the CACNA1C gene are mainly within intron 3 of the gene. ANK3 BP-associated variants are in two distinct clusters at the ends of the gene, indicating disease allele heterogeneity.Methods In order to screen both coding and non-coding regions to identify potential aetiological variants, we used whole-genome sequencing in 99 BP cases. Variants with markedly different allele frequencies in the BP samples and the 1,000 genomes project European data were genotyped in 1,510 BP cases and 1,095 controls.ResultsWe found that the CACNA1C intron 3 variant, rs79398153, potentially affecting an ENCyclopedia of DNA Elements (ENCODE)-defined region, showed an association with BP (p = 0.015). We also found the ANK3 BP-associated variant rs139972937, responsible for an asparagine to serine change (p = 0.042). However, a previous study had not found support for an association between rs139972937 and BP. The variants at ANK3 and CACNA1C previously known to be associated with BP were not in linkage disequilibrium with either of the two variants that we identified and these are therefore independent of the previous haplotypes implicated by genome-wide association.Conclusions Sequencing in additional BP samples is needed to find the molecular pathology that explains the previous association findings. If changes similar to those we have found can be shown to have an effect on the expression and function of ANK3 and CACNA1C, they might help to explain the so-called ‘missing heritability’ of BP.
    Bipolar Disorders 04/2014; 16(6). DOI:10.1111/bdi.12203 · 4.89 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cerebral cortical gamma-aminobutyric acidergic interneuron dysfunction is hypothesized to lead to cognitive deficits comorbid with human neuropsychiatric disorders, including schizophrenia, autism, and epilepsy. We have previously shown that mice that harbor mutations in the Plaur gene, which is associated with schizophrenia, have deficits in frontal cortical parvalbumin-expressing interneurons. Plaur mice have impaired reversal learning, similar to deficits observed in patients with schizophrenia.
    Biological Psychiatry 08/2014; 77(5). DOI:10.1016/j.biopsych.2014.07.023 · 9.47 Impact Factor