A low-cost open-source 5-choice operant box system optimized for electrophysiology and optophysiology in mice

GoFish: A low-cost, open-source platform for closed-loop behavioural experiments on fish

Fish are the most species-rich vertebrate group, displaying vast ecological, anatomical and behavioural diversity, and therefore are of major interest for the study of behaviour and its evolution. However, with respect to other vertebrates, fish are relatively underrepresented in psychological and cognitive research. A greater availability of easily accessible, flexible, open-source experimental platforms that facilitate the automation of task control and data acquisition may help to reduce this bias and improve the scalability and refinement of behavioural experiments in a range of different fish species. Here we present GoFish, a fully automated platform for behavioural experiments in aquatic species. GoFish includes real-time video tracking of subjects, presentation of stimuli in a computer screen, an automatic feeder device, and closed-loop control of task contingencies and data acquisition. The design and software components of the platform are freely available, while the hardware is open-source and relatively inexpensive. The control software, Bonsai, is designed to facilitate rapid development of task workflows and is supported by a growing community of users. As an illustration and test of its use, we present the results of two experiments on discrimination learning, reversal, and choice in goldfish (Carassius auratus). GoFish facilitates the automation of high-throughput protocols and the acquisition of rich behavioural data. Our platform has the potential to become a widely used tool that facilitates complex behavioural experiments in aquatic species.

Control of sustained attention and impulsivity by Gq-protein signalling in parvalbumin interneurons of the anterior cingulate cortex

The anterior cingulate cortex (ACC) has been implicated in attention deficit hyperactivity disorder (ADHD). More specifically, an appropriate balance of excitatory and inhibitory activity in the ACC may be critical for the control of impulsivity, hyperactivity, and sustained attention which are centrally affected in ADHD. Hence, pharmacological augmentation of parvalbumin- (PV) or somatostatin-positive (Sst) inhibitory ACC interneurons could be a potential treatment strategy. We, therefore, tested whether stimulation of G_q-protein-coupled receptors (G_qPCRs) in these interneurons could improve attention or impulsivity assessed with the 5-choice-serial reaction-time task in male mice. When challenging impulse control behaviourally or pharmacologically, activation of the chemogenetic G_qPCR hM3Dq in ACC PV-cells caused a selective decrease of active erroneous-i.e. incorrect and premature-responses, indicating improved attentional and impulse control. When challenging attention, in contrast, omissions were increased, albeit without extension of reward latencies or decreases of attentional accuracy. These effects largely resembled those of the ADHD medication atomoxetine. Additionally, they were mostly independent of each other within individual animals. G_qPCR activation in ACC PV-cells also reduced hyperactivity. In contrast, if hM3Dq was activated in Sst-interneurons, no improvement of impulse control was observed, and a reduction of incorrect responses was only induced at high agonist levels and accompanied by reduced motivational drive. These results suggest that the activation of G_qPCRs expressed specifically in PV-cells of the ACC may be a viable strategy to improve certain aspects of sustained attention, impulsivity and hyperactivity in ADHD.

Chronic N-acetylcysteine treatment improves anhedonia and cognition in a mouse model of the schizophrenia prodrome

Schizophrenia is a severe psychiatric disorder whose neurodevelopmental pathogenesis includes a prodromal phase before its diagnostically decisive—namely psychotic—symptoms are present. This prodrome is characterized by cognitive and affective deficits, and it may constitute a critical time period for an early therapeutic intervention to improve or even prevent further disease development. N-acetylcysteine (NAC) is an easily repurposable compound that has recently shown promise in improving non-psychotic symptoms in patients with established schizophrenia. Its therapeutic mechanism may involve the amelioration of circuit abnormalities like a hyper-glutamatergic state and oxidative stress in cortex which have been proposed to drive the pathogenesis of this disease. However, it is currently unknown to what extent NAC can actually improve prodromal aberrations. To investigate this preclinically, we deployed the cyclin-D2 knockout mouse model (CD2-KO) that shares physiological and behavioral abnormalities with the schizophrenia prodrome, including a hyperactive CA1 region, and cognitive and affective deficits. Applying NAC chronically in drinking water (0.9 g/l) during development (∼P22–P70), we found that excessive novelty-induced hyperlocomotion was neither ameliorated during (∼P68) nor after (∼P75) treatment; similarly, T-maze working memory (tested after treatment; ∼P84) was unaffected. However, once chronic NAC treatment was resumed (at approximately P134) in those mice that had received it before, working memory, cognitive flexibility (tested under NAC), and anhedonia (sucrose-preference, tested 1 day after NAC-treatment stopped) were improved in CD2-KO mice. This suggests that chronic NAC treatment may be a therapeutic strategy to improve some cognitive and affective dysfunctions in the schizophrenia prodrome.

Distinct contributions of GluA1-containing AMPA receptors of different hippocampal subfields to salience processing, memory and impulse control

Schizophrenia is associated with a broad range of severe and currently pharmacoresistant cognitive deficits. Prior evidence suggests that hypofunction of AMPA-type glutamate receptors (AMPARs) containing the subunit GLUA1, encoded by GRIA1, might be causally related to impairments of selective attention and memory in this disorder, at least in some patients. In order to clarify the roles of GluA1 in distinct cell populations, we investigated behavioural consequences of selective Gria1-knockout in excitatory neurons of subdivisions of the prefrontal cortex and the hippocampus, assessing sustained attention, impulsivity, cognitive flexibility, anxiety, sociability, hyperactivity, and various forms of short-term memory in mice. We found that virally induced reduction of GluA1 across multiple hippocampal subfields impaired spatial working memory. Transgene-mediated ablation of GluA1 from excitatory cells of CA2 impaired short-term memory for conspecifics and objects. Gria1 knockout in CA3 pyramidal cells caused mild impairments of object-related and spatial short-term memory, but appeared to partially increase social interaction and sustained attention and to reduce motor impulsivity. Our data suggest that reduced hippocampal GluA1 expression-as seen in some patients with schizophrenia-may be a central cause particularly for several short-term memory deficits. However, as impulse control and sustained attention actually appeared to improve with GluA1 ablation in CA3, strategies of enhancement of AMPAR signalling likely require a fine balance to be therapeutically effective across the broad symptom spectrum of schizophrenia.

Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments

Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends, we developed pyControl, a system of open-source hardware and software for controlling behavioural experiments comprising a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high-throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier, and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features. Here, we outline the system's design and rationale, present validation experiments characterising system performance, and demonstrate example applications in freely moving and head-fixed mouse behaviour.