Spatial cognition in a virtual reality home-cage extension for freely moving rodents

Development of an IntelliCage-based cognitive bias test for mice

The cognitive bias test is used to measure the emotional state of animals with regard to future expectations. Thus, the test offers a unique possibility to assess animal welfare with regard to housing and testing conditions of laboratory animals. So far, however, performing such a test is time-consuming and requires the presence of an experimenter. Therefore, we developed an automated and home-cage based cognitive bias test based on the IntelliCage system. We present several developmental steps to improve the experimental design leading to a successful measurement of cognitive bias in group-housed female C57BL/6J mice. The automated and home-cage based test design allows to obtain individual data from group-housed mice, to test the mice in their familiar environment, and during their active phase. By connecting the test-cage to the home-cage via a gating system, the mice participated in the test on a self-chosen schedule, indicating high motivation to actively participate in the experiment. We propose that this should have a positive effect on the animals themselves as well as on the data. Unexpectedly, the mice showed an optimistic cognitive bias after enrichment was removed and additional restraining. An optimistic expectation of the future as a consequence of worsening environmental conditions, however, can also be interpreted as an active coping strategy in which a potential profit is sought to be maximized through a higher willingness to take risks.

Development of an IntelliCage-based cognitive bias test for mice

The cognitive bias test is used to measure the emotional state of animals with regard to future expectations. Thus, the test offers a unique possibility to assess animal welfare with regard to housing and testing conditions of laboratory animals. So far, however, performing such a test is time-consuming and requires the presence of an experimenter. Therefore, we developed an automated and home-cage based cognitive bias test based on the IntelliCage system. We present several developmental steps to improve the experimental design leading to a successful measurement of cognitive bias in group-housed female C57BL/6J mice. The automated and home-cage based test design allows to obtain individual data from group-housed mice, to test the mice in their familiar environment, and during their active phase. By connecting the test-cage to the home-cage via a gating system, the mice participated in the test on a self-chosen schedule, indicating high motivation to actively participate in the experiment. We propose that this should have a positive effect on the animals themselves as well as on the data. Unexpectedly, the mice showed an optimistic cognitive bias after enrichment was removed and additional restraining. An optimistic expectation of the future as a consequence of worsening environmental conditions, however, can also be interpreted as an active coping strategy in which a potential profit is sought to be maximized through a higher willingness to take risks.

Determining the value of preferred goods based on consumer demand in a home-cage based test for mice

From the preference of one good over another, the strength of the preference cannot automatically be inferred. While money is the common denominator to assess the value of goods in humans, it appears difficult at first glance to put a price tag on the decisions of laboratory animals. Here we used consumer demand tests to measure how much work female mice expend to obtain access to different liquids. The mice could each choose between two liquids, one of which was free. The amount of work required to access the other liquid, by contrast, increased daily. In this way, the value of the liquid can be determined from a mouse's microeconomic perspective. The unique feature is that our test was carried out in a home-cage based setup. The mice lived in a group but could individually access the test-cage, which was connected to the home-cage via a gate. Thereby the mice were able to perform their task undisturbed by group members and on a self-chosen schedule with minimal influence by the experimenter. Our results show that the maximum number of nosepokes depends on the liquids presented. Mice worked incredibly hard for access to water while a bitter-tasting solution was offered for free whereas they made less nosepokes for sweetened liquids while water was offered for free. The results demonstrate that it is possible to perform automated and home-cage based consumer demand tests in order to ask the mice not only what they like best but also how strong their preference is.

Naturalistic neuroscience and virtual reality

Virtual reality (VR) is one of the techniques that became particularly popular in neuroscience over the past few decades. VR experiments feature a closed-loop between sensory stimulation and behavior. Participants interact with the stimuli and not just passively perceive them. Several senses can be stimulated at once, large-scale environments can be simulated as well as social interactions. All of this makes VR experiences more natural than those in traditional lab paradigms. Compared to the situation in field research, a VR simulation is highly controllable and reproducible, as required of a laboratory technique used in the search for neural correlates of perception and behavior. VR is therefore considered a middle ground between ecological validity and experimental control. In this review, I explore the potential of VR in eliciting naturalistic perception and behavior in humans and non-human animals. In this context, I give an overview of recent virtual reality approaches used in neuroscientific research.

Driving singing behaviour in songbirds using a multi-modal, multi-agent virtual environment

Interactive biorobotics provides unique experimental potential to study the mechanisms underlying social communication but is limited by our ability to build expressive robots that exhibit the complex behaviours of birds and small mammals. An alternative to physical robots is to use virtual environments. Here, we designed and built a modular, audio-visual 2D virtual environment that allows multi-modal, multi-agent interaction to study mechanisms underlying social communication. The strength of the system is an implementation based on event processing that allows for complex computation. We tested this system in songbirds, which provide an exceptionally powerful and tractable model system to study social communication. We show that pair-bonded zebra finches (Taeniopygia guttata) communicating through the virtual environment exhibit normal call timing behaviour, males sing female directed song and both males and females display high-intensity courtship behaviours to their mates. These results suggest that the environment provided is sufficiently natural to elicit these behavioral responses. Furthermore, as an example of complex behavioral annotation, we developed a fully unsupervised song motif detector and used it to manipulate the virtual social environment of male zebra finches based on the number of motifs sung. Our virtual environment represents a first step in real-time automatic behaviour annotation and animal–computer interaction using higher level behaviours such as song. Our unsupervised acoustic analysis eliminates the need for annotated training data thus reducing labour investment and experimenter bias.

Multimodal Functional Analysis Platform: 3. Spherical Treadmill System for Small Animals

In the application of advanced neuroscience techniques including optogenetics to small awake animals, it is often necessary to restrict the animal's movements. A spherical treadmill is a beneficial option that enables virtual locomotion of body- or head-restrained small animals. Besides, it has a wide application range, including virtual reality experiments. This chapter describes the fundamentals of a spherical treadmill for researchers who want to start experiments with it. First, we describe the physical aspect of a spherical treadmill based on the simple mechanical analysis. Next, we explain the basics of data logging and preprocessing for behavioral analysis. We also provide simple computer programs that work for the purpose.

Habit learning in hierarchical cortex-basal ganglia loops

How do the multiple cortico-basal ganglia-thalamo-cortical loops interact? Are they parallel and fully independent or controlled by an arbitrator, or are they hierarchically organized? We introduce here a set of four key concepts, integrated and evaluated by means of a neuro-computational model, that bring together current ideas regarding cortex-basal ganglia interactions in the context of habit learning. According to key concept 1, each loop learns to select an intermediate objective at a different abstraction level, moving from goals in the ventral striatum to motor in the putamen. Key concept 2 proposes that the cortex integrates the basal ganglia selection with environmental information regarding the achieved objective. Key concept 3 claims shortcuts between loops, and key concept 4 predicts that loops compute their own prediction error signal for learning. Computational benefits of the key concepts are demonstrated. Contrasting with former concepts of habit learning, the loops collaborate to select goal-directed actions while training slower shortcuts develops habitual responses.

Current approaches to modeling the virtual reality in rodents for the assessment of brain plasticity and behavior

Virtual reality (VR) and augmented reality (AR) have become valuable tools to study brains and behaviors resulting in development of new methods of diagnostics and treatment. Neurodegenerаtion is one of the best examples demonstrating efficacy of VR/АR technologies in modern neurology. Development of novel VR systems for rodents and combination of VR tools with up-to-date imaging techniques (i.e. MRI, imaging of neural networks etc.), brain electrophysiology (EEG, patch-clamp), precise analytics (microdialysis) allowed implementing of VR protocols into the animal neurobiology to study brain plasticity, sensorimotor integration, spatial navigation, memory, and decision-making. VR/AR for rodents is а young field of experimental neuroscience and has already provided more consistent testing conditions, less human-animal interaction, opportunities to use a wider variety of experimental parameters. Here we discuss present and future perspectives of using VR/AR to assess brain plasticity, neurogenesis and complex behavior in rodent and human study, and their advantages for translational neuroscience.

Cholinergic modulation of spatial learning, memory and navigation

Spatial learning, including encoding and retrieval of spatial memories as well as holding spatial information in working memory generally serving navigation under a broad range of circumstances, relies on a network of structures. While central to this network are medial temporal lobe structures with a widely appreciated crucial function of the hippocampus, neocortical areas such as the posterior parietal cortex and the retrosplenial cortex also play essential roles. Since the hippocampus receives its main subcortical input from the medial septum of the basal forebrain (BF) cholinergic system, it is not surprising that the potential role of the septo-hippocampal pathway in spatial navigation has been investigated in many studies. Much less is known of the involvement in spatial cognition of the parallel projection system linking the posterior BF with neocortical areas. Here we review the current state of the art of the division of labour within this complex 'navigation system', with special focus on how subcortical cholinergic inputs may regulate various aspects of spatial learning, memory and navigation.

Structural modularity and grid activity in the medial entorhinal cortex

Following the groundbreaking discovery of grid cells, the medial entorhinal cortex (MEC) has become the focus of intense anatomical, physiological, and computational investigations. Whether and how grid activity maps onto cell types and cortical architecture is still an open question. Fundamental similarities in microcircuits, function, and connectivity suggest a homology between rodent MEC and human posteromedial entorhinal cortex. Both are specialized for spatial processing and display similar cellular organization, consisting of layer 2 pyramidal/calbindin cell patches superimposed on scattered stellate neurons. Recent data indicate the existence of a further nonoverlapping modular system (zinc patches) within the superficial MEC layers. Zinc and calbindin patches have been shown to receive largely segregated inputs from the presubiculum and parasubiculum. Grid cells are also clustered in the MEC, and we discuss possible structure-function schemes on how grid activity could map onto cortical patch systems. We hypothesize that in the superficial layers of the MEC, anatomical location can be predictive of function; thus relating functional properties and neuronal morphologies to the cortical modules will be necessary for resolving how grid activity maps onto cortical architecture. Imaging or cell identification approaches in freely moving animals will be required for testing this hypothesis.