Predictably Irrational: Assaying Cognitive Inflexibility in Mouse Models of Schizophrenia

The development of sophisticated, translatable mouse-based assays modeling the behavioral manifestations of neuropsychiatric diseases, such as schizophrenia, has lagged the advances in molecular and genomic techniques. Our laboratory has made efforts to fill this gap by investing in the development of novel assays, including adapting a touchscreen-based method for measuring cognitive and executive functions for use in mice. As part of these efforts, a recent study by Brigman et al. (2009) investigated the effects of subchronic phencyclidine treatment on mouse touchscreen-based pairwise visual discrimination and reversal learning. Here, we summarize the results of that study, and place them in the larger context of ongoing efforts to develop valid mouse “models” of schizophrenia, with a focus on reversal learning and other measures of cognitive flexibility. Touchscreen-based systems could provide a tractable platform for fully utilizing the mouse to elucidate the pathophysiology of cognitive inflexibility in schizophrenia and other neuropsychiatric disorders

Paradoxical reversal learning enhancement by stress or prefrontal cortical damage: rescue with BDNF.

Stress affects various forms of cognition. We found that moderate stress enhanced late reversal learning in a mouse touchscreen-based choice task. Ventromedial prefrontal cortex (vmPFC) lesions mimicked the effect of stress, whereas orbitofrontal and dorsolateral striatal lesions impaired reversal. Stress facilitation of reversal was prevented by BDNF infusion into the vmPFC. These findings suggest a mechanism by which stress-induced vmPFC dysfunction disinhibits learning by alternate (for example, striatal) systems

Strain Differences in Stress Responsivity Are Associated with Divergent Amygdala Gene Expression and Glutamate-Mediated Neuronal Excitability

Stress is a major risk factor for numerous neuropsychiatric diseases. However, susceptibility to stress and the qualitative nature of stress effects on behavior differ markedly among individuals. This is partly because of the moderating influence of genetic factors. Inbred mouse strains provide a relatively stable and restricted range of genetic and environmental variability that is valuable for disentangling gene–stress interactions. Here, we screened a panel of inbred strains for anxiety- and depression-related phenotypes at baseline (trait) and after exposure to repeated restraint. Two strains, DBA/2J and C57BL/6J, differed in trait and restraint-induced anxiety-related behavior (dark/light exploration, elevated plus maze). Gene expression analysis of amygdala, medial prefrontal cortex, and hippocampus revealed divergent expression in DBA/2J and C57BL/6J both at baseline and after repeated restraint. Restraint produced strain-dependent expression alterations in various genes including glutamate receptors (e.g., Grin1, Grik1). To elucidate neuronal correlates of these strain differences, we performed ex vivo analysis of glutamate excitatory neurotransmission in amygdala principal neurons. Repeated restraint augmented amygdala excitatory postsynaptic signaling and altered metaplasticity (temporal summation of NMDA receptor currents) in DBA/2J but not C57BL/6J. Furthermore, we found that the C57BL/6J-like changes in anxiety-related behavior after restraint were absent in null mutants lacking the modulatory NMDA receptor subunit Grin2a, but not the AMPA receptor subunit Gria1. Grin2a null mutants exhibited significant (~30%) loss of dendritic spines on amygdala principal neurons under nonrestraint conditions. Collectively, our data support a model in which genetic variation in glutamatergic neuroplasticity in corticolimbic circuitry underlies phenotypic variation in responsivity to stress

Strain Differences in Stress Responsivity Are Associated with Divergent Amygdala Gene Expression and Glutamate-Mediated Neuronal Excitability

Stress is a major risk factor for numerous neuropsychiatric diseases. However, susceptibility to stress and the qualitative nature of stress effects on behavior differ markedly among individuals. This is partly because of the moderating influence of genetic factors. Inbred mouse strains provide a relatively stable and restricted range of genetic and environmental variability that is valuable for disentangling gene–stress interactions. Here, we screened a panel of inbred strains for anxiety- and depression-related phenotypes at baseline (trait) and after exposure to repeated restraint. Two strains, DBA/2J and C57BL/6J, differed in trait and restraint-induced anxiety-related behavior (dark/light exploration, elevated plus maze). Gene expression analysis of amygdala, medial prefrontal cortex, and hippocampus revealed divergent expression in DBA/2J and C57BL/6J both at baseline and after repeated restraint. Restraint produced strain-dependent expression alterations in various genes including glutamate receptors (e.g., Grin1, Grik1). To elucidate neuronal correlates of these strain differences, we performed ex vivo analysis of glutamate excitatory neurotransmission in amygdala principal neurons. Repeated restraint augmented amygdala excitatory postsynaptic signaling and altered metaplasticity (temporal summation of NMDA receptor currents) in DBA/2J but not C57BL/6J. Furthermore, we found that the C57BL/6J-like changes in anxiety-related behavior after restraint were absent in null mutants lacking the modulatory NMDA receptor subunit Grin2a, but not the AMPA receptor subunit Gria1. Grin2a null mutants exhibited significant (~30%) loss of dendritic spines on amygdala principal neurons under nonrestraint conditions. Collectively, our data support a model in which genetic variation in glutamatergic neuroplasticity in corticolimbic circuitry underlies phenotypic variation in responsivity to stress

Strains and stressors: an analysis of touchscreen learning in genetically diverse mouse strains.

Touchscreen-based systems are growing in popularity as a tractable, translational approach for studying learning and cognition in rodents. However, while mouse strains are well known to differ in learning across various settings, performance variation between strains in touchscreen learning has not been well described. The selection of appropriate genetic strains and backgrounds is critical to the design of touchscreen-based studies and provides a basis for elucidating genetic factors moderating behavior. Here we provide a quantitative foundation for visual discrimination and reversal learning using touchscreen assays across a total of 35 genotypes. We found significant differences in operant performance and learning, including faster reversal learning in DBA/2J compared to C57BL/6J mice. We then assessed DBA/2J and C57BL/6J for differential sensitivity to an environmental insult by testing for alterations in reversal learning following exposure to repeated swim stress. Stress facilitated reversal learning (selectively during the late stage of reversal) in C57BL/6J, but did not affect learning in DBA/2J. To dissect genetic factors underlying these differences, we phenotyped a family of 27 BXD strains generated by crossing C57BL/6J and DBA/2J. There was marked variation in discrimination, reversal and extinction learning across the BXD strains, suggesting this task may be useful for identifying underlying genetic differences. Moreover, different measures of touchscreen learning were only modestly correlated in the BXD strains, indicating that these processes are comparatively independent at both genetic and phenotypic levels. Finally, we examined the behavioral structure of learning via principal component analysis of the current data, plus an archival dataset, totaling 765 mice. This revealed 5 independent factors suggestive of "reversal learning," "motivation-related late reversal learning," "discrimination learning," "speed to respond," and "motivation during discrimination." Together, these findings provide a valuable reference to inform the choice of strains and genetic backgrounds in future studies using touchscreen-based tasks

Association of Mouse Dlg4 (PSD-95) Gene Deletion and Human DLG4 Gene Variation With Phenotypes Relevant to Autism Spectrum Disorders and Williams' Syndrome

OBJECTIVE: Research is increasingly linking autism spectrum disorders and other neurodevelopmental disorders to synaptic abnormalities (“synaptopathies”). PSD-95 (postsynaptic density-95, DLG4) orchestrates protein-protein interactions at excitatory synapses and is a major functional bridge interconnecting a neurexin-neuroligin-SHANK pathway implicated in autism spectrum disorders. METHOD: The authors characterized behavioral, dendritic, and molecular phenotypic abnormalities relevant to autism spectrum disorders in mice with PSD-95 deletion (Dlg4(−/−)). The data from mice led to the identification of single-nucleotide polymorphisms (SNPs) in human DLG4 and the examination of associations between these variants and neural signatures of Williams’ syndrome in a normal population, using functional and structural neuroimaging. RESULTS: Dlg4(−/−) showed increased repetitive behaviors, abnormal communication and social behaviors, impaired motor coordination, and increased stress reactivity and anxiety-related responses. Dlg4(−/−) had subtle dysmorphology of amygdala dendritic spines and altered forebrain expression of various synaptic genes, including Cyln2, which regulates cytoskeletal dynamics and is a candidate gene for Williams’ syndrome. A significant association was observed between variations in two human DLG4 SNPs and reduced intraparietal sulcus volume and abnormal cortico-amygdala coupling, both of which characterize Williams’ syndrome. CONCLUSIONS: These findings demonstrate that Dlg4 gene disruption in mice produces a complex range of behavioral and molecular abnormalities relevant to autism spectrum disorders and Williams’ syndrome. The study provides an initial link between human DLG4 gene variation and key neural endophenotypes of Williams’ syndrome and perhaps cortico-amygdala regulation of emotional and social processes more generally

BXD-RI strain differences in training performance, and in discrimination and reversal learning.

<p>(<b>A</b>) Sessions to autoshaping, touch and punish criterion. (<b>B</b>) Sessions to discrimination, reversal and extinction criterion. Errors (<b>C</b>) and correction errors (<b>D</b>) to discrimination criterion. n = 1–16 per strain. Data are Means ± SEM.</p