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Rationale Continuous performance tests (CPTs) are widely used to assess attentional processes in a variety of disorders including Alzheimer’s disease and schizophrenia. Common human CPTs require discrimination of sequentially presented, visually patterned ‘target’ and ‘non-target’ stimuli at a single location. Objectives The aims of this study were to evaluate the performance of three popular mouse strains on a novel rodent touchscreen test (rCPT) designed to be analogous to common human CPT variants and to investigate the effects of donepezil, a cholinesterase inhibitor and putative cognitive enhancer. Methods C57BL/6J, DBA/2J and CD1 mice ( n  = 15–16/strain) were trained to baseline performance using four rCPT training stages. Then, probe tests assessed the effects of parameter changes on task performance: stimulus size, duration, contrast, probability, inter-trial interval or inclusion of flanker distractors. rCPT performance was also evaluated following acute administration of donepezil (0–3 mg/kg, i.p.). Results C57BL/6J and DBA/2J mice showed similar acquisition rates and final baseline performance following rCPT training. On probe tests, rCPT performance of both strains was sensitive to alteration of visual and/or attentional demands (stimulus size, duration, contrast, rate, flanker distraction). Relative to C57BL/6J, DBA/2J mice exhibited (1) decreasing sensitivity ( d ′) across the 45-min session, (2) reduced performance on probes where the appearance of stimuli or adjacent areas were changed (size, contrast, flanking distractors) and (3) larger dose- and stimulus duration-dependent changes in performance following donepezil administration. In contrast, CD1 mice failed to acquire rCPT (stage 3) and pairwise visual discrimination tasks. Conclusions rCPT is a potentially useful translational tool for assessing attention in mice and for detecting the effects of nootropic drugs.

Impaired cognitive flexibility in visual reversal-learning tasks has been observed in a wide range of neurological and neuropsychiatric disorders. Although both human and animal studies have implicated striatal D2-like and D1-like receptors (D2R; D1R) in this form of flexibility, less is known about the contribution they make within distinct sub-regions of the striatum and the different phases of visual reversal learning. The present study investigated the involvement of D2R and D1R during the early (perseverative) phase of reversal learning as well as in the intermediate and late stages (new learning) after microinfusions of D2R and D1R antagonists into the nucleus accumbens core and shell (NAcC; NAcS), the anterior and posterior dorsomedial striatum (DMS) and the dorsolateral striatum (DLS) on a touchscreen visual serial reversal-learning task. Reversal learning was improved after dopamine receptor blockade in the nucleus accumbens; the D1R antagonist, SCH23390, in the NAcS and the D2R antagonist, raclopride, in the NAcC selectively reduced early, perseverative errors. In contrast, reversal learning was impaired by D2R antagonism, but not D1R antagonism, in the dorsal striatum: raclopride increased errors in the intermediate phase after DMS infusions, and increased errors across phases after DLS infusions. These findings indicate that D1R and D2R modulate different stages of reversal learning through effects localised to different sub-regions of the striatum. Thus, deficits in behavioral flexibility observed in disorders linked to dopamine perturbations may be attributable to specific D1R and D2R dysfunction in distinct striatal sub-regions.

Rationale A microdeletion at locus 15q13.3 is associated with high incidence rates of psychopathology, including schizophrenia. A mouse model of the 15q13.3 microdeletion syndrome has been generated (Df[h15q13]/+) with translational utility for modelling schizophrenia-like pathology. Among other deficits, schizophrenia is characterised by dysfunctions in prefrontal cortical (PFC) inhibitory circuitry and attention. Objectives The objective of this study is to assess PFC-dependent functioning in the Df(h15q13)/+ mouse using electrophysiological, pharmacological, and behavioural assays. Method Experiments 1–2 investigated baseline firing and auditory-evoked responses of PFC interneurons and pyramidal neurons. Experiment 3 measured pyramidal firing in response to intra-PFC GABA A receptor antagonism. Experiments 4–6 assessed PFC-dependent attentional functioning through the touchscreen 5-choice serial reaction time task (5-CSRTT). Experiments 7–12 assessed reversal learning, paired-associate learning, extinction learning, progressive ratio, trial-unique non-match to sample, and object recognition. Results In experiments 1–3, the Df(h15q13)/+ mouse showed reduced baseline firing rate of fast-spiking interneurons and in the ability of the GABA A receptor antagonist gabazine to increase the firing rate of pyramidal neurons. In assays of auditory-evoked responses, PFC interneurons in the Df(h15q13)/+ mouse had reduced detection amplitudes and increased detection latencies, while pyramidal neurons showed increased detection latencies. In experiments 4–6, the Df(h15q13)/+ mouse showed a stimulus duration-dependent decrease in percent accuracy in the 5-CSRTT. The impairment was insensitive to treatment with the partial α 7 nAChR agonist EVP-6124. The Df(h15q13)/+ mouse showed no cognitive impairments in experiments 7–12. Conclusion The Df(h15q13)/+ mouse has multiple dysfunctions converging on disrupted PFC processing as measured by several independent assays of inhibitory transmission and attentional function.

The study of complex behaviors is often challenging when using manual annotation due to the absence of quantifiable behavioral definitions and the subjective nature of behavioral annotation. Integration of supervised machine learning approaches mitigates some of these issues through the inclusion of accessible and explainable model interpretation. To decrease barriers to access, and with an emphasis on accessible model explainability, we developed the open-source Simple Behavioral Analysis (SimBA) platform for behavioral neuroscientists. SimBA introduces several machine learning interpretability tools, including SHapley Additive exPlanation (SHAP) scores, that aid in creating explainable and transparent behavioral classifiers. Here we show how the addition of explainability metrics allows for quantifiable comparisons of aggressive social behavior across research groups and species, reconceptualizing behavior as a sharable reagent and providing an open-source framework. We provide an open-source, graphical user interface (GUI)-driven, well-documented package to facilitate the movement toward improved automation and sharing of behavioral classification tools across laboratories. This paper presents Simple Behavioral Analysis (SimBA), an open-source platform for automated, explainable machine learning analysis of behavior. SimBA comes with extensive documentation, a graphical interface and an active community and works with any organism tracked by pose estimation.

Rationale Impairments in attention and inhibitory control are endophenotypic markers of neuropsychiatric disorders such as schizophrenia and represent key targets for therapeutic management. Robust preclinical models and assays sensitive to clinically relevant treatments are crucial for improving cognitive enhancement strategies. Objectives We assessed a rodent model with neural and behavioral features relevant to schizophrenia (gestational day 17 methylazoxymethanol acetate treatment (MAM-E17)) on a novel test of attention and executive function, and examined the impact of putative nootropic drugs. Methods MAM-E17 and sham control rats were trained on a novel touchscreen-based rodent continuous performance test (rCPT) designed to closely mimic the human CPT paradigm. Performance following acute, systemic treatment with an array of pharmacological compounds was investigated. Results Two cohorts of MAM-E17 rats were impaired on rCPT performance including deficits in sensitivity ( d ′) and increased false alarm rates (FARs). Sulpiride (0–30 mg/kg) dose-dependently reduced elevated FAR in MAM-E17 rats whereas low-dose modafinil (8 mg/kg) only improved d ′ in sham controls. ABT-594 (5.9–19.4 μg/kg) and modafinil (64 mg/kg) showed expected stimulant-like effects, while LSN2463359 (5 mg/kg), RO493858 (10 mg/kg), atomoxetine (0.3–1 mg/kg), and sulpiride (30 mg/kg) showed expected suppressant effects on performance across all animals. Donepezil (0.1–1 mg/kg) showed near-significant enhancements in d ′, and EVP-6124 (0.3–3 mg/kg) exerted no effects in the rCPT paradigm. Conclusion The MAM-E17 model exhibits robust and replicable impairments in rCPT performance that resemble attention and inhibitory control deficits seen in schizophrenia. Pharmacological profiles were highly consistent with known drug effects on cognition in preclinical and clinical studies. The rCPT is a sensitive and reliable tool with high translational potential for understanding the etiology and treatment of disorders affecting attention and executive dysfunction.

The zebrafish lateral line is an established model for hair cell organ damage, yet few studies link mechanistic disruptions to changes in biologically relevant behavior. We used larval zebrafish to determine how damage via ototoxic compounds impact rheotaxis. Larvae were treated with CuSO 4 or neomycin to disrupt lateral line function then exposed to water flow stimuli. Their swimming behavior was recorded on video then DeepLabCut and SimBA software were used to track movements and classify rheotaxis behavior, respectively. Lateral line-disrupted fish performed rheotaxis, but they swam greater distances, for shorter durations, and with greater angular variance than controls. Furthermore, spectral decomposition analyses confirmed that lesioned fish exhibited ototoxic compound-specific behavioral profiles with distinct changes in the magnitude, frequency, and cross-correlation between fluctuations in linear and angular movements. Our observations demonstrate that lateral line input is needed for fish to hold their station in flow efficiently and reveals that commonly used lesion methods have unique effects on rheotaxis behavior. Larval zebrafish are subjected to ototoxic compounds to evaluate their impact on rheotaxis, and compound-specific behaviour profiles reveal unique effects on zebrafish rheotaxis behavior.

An increasingly popular method of assessing cognitive functions in rodents is the automated touchscreen platform, on which a number of different cognitive tests can be run in a manner very similar to touchscreen methods currently used to test human subjects. This methodology is low stress (using appetitive rather than aversive reinforcement), has high translational potential and lends itself to a high degree of standardization and throughput. Applications include the study of cognition in rodent models of psychiatric and neurodegenerative diseases (e.g., Alzheimer's disease, schizophrenia, Huntington's disease, frontotemporal dementia), as well as the characterization of the role of select brain regions, neurotransmitter systems and genes in rodents. This protocol describes how to perform four touchscreen assays of learning and memory: visual discrimination, object-location paired-associates learning, visuomotor conditional learning and autoshaping. It is accompanied by two further protocols (also published in this issue) that use the touchscreen platform to assess executive function, working memory and pattern separation.

This protocol details a subset of assays developed within the touchscreen platform to measure various aspects of executive function in rodents. Three main procedures are included: extinction, measuring the rate and extent of curtailing a response that was previously, but is no longer, associated with reward; reversal learning, measuring the rate and extent of switching a response toward a visual stimulus that was previously not, but has become, associated with reward (and away from a visual stimulus that was previously, but is no longer, rewarded); and the 5-choice serial reaction time (5-CSRT) task, gauging the ability to selectively detect and appropriately respond to briefly presented, spatially unpredictable visual stimuli. These protocols were designed to assess both complementary and overlapping constructs including selective and divided visual attention, inhibitory control, flexibility, impulsivity and compulsivity. The procedures comprise part of a wider touchscreen test battery assessing cognition in rodents with high potential for translation to human studies.

RationaleAggression, comorbid with neuropsychiatric disorders, exhibits with diverse clinical presentations and places a significant burden on patients, caregivers, and society. This diversity is observed because aggression is a complex behavior that can be ethologically demarcated as either appetitive (rewarding) or reactive (defensive), each with its own behavioral characteristics, functionality, and neural basis that may transition from adaptive to maladaptive depending on genetic and environmental factors. There has been a recent surge in the development of preclinical animal models for studying appetitive aggression-related behaviors and identifying the neural mechanisms guiding their progression and expression. However, adoption of these procedures is often impeded by the arduous task of manually scoring complex social interactions. Manual observations are generally susceptible to observer drift, long analysis times, and poor inter-rater reliability, and are further incompatible with the sampling frequencies required of modern neuroscience methods.ObjectivesIn this review, we discuss recent advances in the preclinical study of appetitive aggression in mice, paired with our perspective on the potential for machine learning techniques in producing automated, robust scoring of aggressive social behavior. We discuss critical considerations for implementing valid computer classifications within behavioral pharmacological studies.Key resultsOpen-source automated classification platforms can match or exceed the performance of human observers while removing the confounds of observer drift, bias, and inter-rater reliability. Furthermore, unsupervised approaches can identify previously uncharacterized aggression-related behavioral repertoires in model species.Discussion and conclusionsAdvances in open-source computational approaches hold promise for overcoming current manual annotation caveats while also introducing and generalizing computational neuroethology to the greater behavioral neuroscience community. We propose that currently available open-source approaches are sufficient for overcoming the main limitations preventing wide adoption of machine learning within the context of preclinical aggression behavioral research.