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Panniello M, Gillon CJ, Maffulli R, Celotto M, Richards BA, Panzeri S, Kohl MM. Stimulus information guides the emergence of behavior-related signals in primary somatosensory cortex during learning. Cell Rep 2024; 43:114244. [PMID: 38796851 DOI: 10.1016/j.celrep.2024.114244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 01/16/2024] [Accepted: 05/02/2024] [Indexed: 05/29/2024] Open
Abstract
Neurons in the primary cortex carry sensory- and behavior-related information, but it remains an open question how this information emerges and intersects together during learning. Current evidence points to two possible learning-related changes: sensory information increases in the primary cortex or sensory information remains stable, but its readout efficiency in association cortices increases. We investigated this question by imaging neuronal activity in mouse primary somatosensory cortex before, during, and after learning of an object localization task. We quantified sensory- and behavior-related information and estimated how much sensory information was used to instruct perceptual choices as learning progressed. We find that sensory information increases from the start of training, while choice information is mostly present in the later stages of learning. Additionally, the readout of sensory information becomes more efficient with learning as early as in the primary sensory cortex. Together, our results highlight the importance of primary cortical neurons in perceptual learning.
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Affiliation(s)
- Mariangela Panniello
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3PT, UK; School of Psychology and Neuroscience, University of Glasgow, Glasgow G12 8QQ, UK; Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Colleen J Gillon
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, ON M1C 1A4, Canada; Department of Cell & Systems Biology, University of Toronto, Toronto, ON M5S 3G5, Canada; Mila, Montréal, QC H2S 3H1, Canada
| | - Roberto Maffulli
- Neural Computation Laboratory, Center for Human Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Marco Celotto
- Neural Computation Laboratory, Center for Human Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy; Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), 20251 Hamburg, Germany; Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy
| | - Blake A Richards
- Mila, Montréal, QC H2S 3H1, Canada; School of Computer Science, McGill University, Montréal, QC H3A 2A7, Canada; Department of Neurology & Neurosurgery, McGill University, Montréal, QC H3A 1A1, Canada; Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, ON M5G 1M1, Canada; Montreal Neurological Institute, Montréal, QC H3A 2B4, Canada
| | - Stefano Panzeri
- Neural Computation Laboratory, Center for Human Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy; Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), 20251 Hamburg, Germany
| | - Michael M Kohl
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3PT, UK; School of Psychology and Neuroscience, University of Glasgow, Glasgow G12 8QQ, UK.
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2
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Hartmann C, Mahajan A, Borges V, Razenberg L, Thönnes Y, Karnani MM. The Switchmaze: an open-design device for measuring motivation and drive switching in mice. PEER COMMUNITY JOURNAL 2024; 4:pcjournal.416. [PMID: 38827787 PMCID: PMC7616052 DOI: 10.1101/2024.01.31.578188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
Animals need to switch between motivated behaviours, like drinking, feeding or social interaction, to meet environmental availability, internal needs and more complex ethological needs such as hiding future actions from competitors. Inflexible, repetitive behaviours are a hallmark of many neuropsychiatric disorders. However, how the brain orchestrates switching between the neural mechanisms controlling motivated behaviours, or drives, is unknown. This is partly due to a lack of appropriate measurement systems. We designed an automated extended home-cage, the Switchmaze, using open-source hardware and software. In this study, we use it to establish a behavioural assay of motivational switching in mice. Individual animals access the Switchmaze from the home-cage and choose between entering one of two chambers containing different goal objects or returning to the home-cage. Motivational switching is measured as a ratio of switching between chambers and continuous exploitation of one chamber. Behavioural transition analysis is used to further dissect altered motivational switching. As proof-of-concept, we show environmental manipulation, and targeted brain manipulation experiments which altered motivational switching without effect on traditional behavioural parameters. Chemogenetic inhibition of the prefrontal-hypothalamic axis increased the rate of motivation switching, highlighting the involvement of this pathway in drive switching. This work demonstrates the utility of open-design in understanding animal behaviour and its neural correlates.
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Affiliation(s)
- Clara Hartmann
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
| | - Ambika Mahajan
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
| | - Vinicius Borges
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
| | - Lotte Razenberg
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
| | - Yves Thönnes
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
| | - Mahesh M Karnani
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
- Institute for Neuroscience and Cardiovascular Research, Centre for Discovery Brain Sciences, University of Edinburgh, 1 George Square, Edinburgh EH8 9JZ, UK
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Bowler JC, Zakka G, Yong HC, Li W, Rao B, Liao Z, Priestley JB, Losonczy A. behaviorMate: An Intranet of Things Approach for Adaptable Control of Behavioral and Navigation-Based Experiments. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.04.569989. [PMID: 38116032 PMCID: PMC10729741 DOI: 10.1101/2023.12.04.569989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Investigators conducting behavioral experiments often need precise control over the timing of the delivery of stimuli to subjects and to collect the precise times of the subsequent behavioral responses. Furthermore, investigators want fine-tuned control over how various multi-modal cues are presented. behaviorMate takes an "Intranet of Things" approach, using a networked system of hardware and software components for achieving these goals. The system outputs a file with integrated timestamp-event pairs that investigators can then format and process using their own analysis pipelines. We present an overview of the electronic components and GUI application that make up behaviorMate as well as mechanical designs for compatible experimental rigs to provide the reader with the ability to set up their own system. A wide variety of paradigms are supported, including goal-oriented learning, random foraging, and context switching. We demonstrate behaviorMate's utility and reliability with a range of use cases from several published studies and benchmark tests. Finally, we present experimental validation demonstrating different modalities of hippocampal place field studies. Both treadmill with burlap belt and virtual reality with running wheel paradigms were performed to confirm the efficacy and flexibility of the approach. Previous solutions rely on proprietary systems that may have large upfront costs or present frameworks that require customized software to be developed. behaviorMate uses open-source software and a flexible configuration system to mitigate both concerns. behaviorMate has a proven record for head-fixed imaging experiments and could be easily adopted for task control in a variety of experimental situations.
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Affiliation(s)
- John C. Bowler
- Department of Neuroscience
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
- Department of Neurobiology University of Utah, Salt Lake City, UT 84112, USA
| | - George Zakka
- Department of Neuroscience
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
| | - Hyun Choong Yong
- Department of Neuroscience
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
| | - Wenke Li
- Aquabyte, San Francisco, CA 94111
| | - Bovey Rao
- Department of Neuroscience
- Doctoral Program in Neurobiology and Behavior
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
| | - Zhenrui Liao
- Department of Neuroscience
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
| | | | - Attila Losonczy
- Department of Neuroscience
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
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4
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Zhou M, Wu B, Jeong H, Burke DA, Namboodiri VMK. An open-source behavior controller for associative learning and memory (B-CALM). Behav Res Methods 2024; 56:2695-2710. [PMID: 37464151 PMCID: PMC10898869 DOI: 10.3758/s13428-023-02182-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/23/2023] [Indexed: 07/20/2023]
Abstract
Associative learning and memory, i.e., learning and remembering the associations between environmental stimuli, self-generated actions, and outcomes such as rewards or punishments, are critical for the well-being of animals. Hence, the neural mechanisms underlying these processes are extensively studied using behavioral tasks in laboratory animals. Traditionally, these tasks have been controlled using commercial hardware and software, which limits scalability and accessibility due to their cost. More recently, due to the revolution in microcontrollers or microcomputers, several general-purpose and open-source solutions have been advanced for controlling neuroscientific behavioral tasks. While these solutions have great strength due to their flexibility and general-purpose nature, for the same reasons, they suffer from some disadvantages including the need for considerable programming expertise, limited online visualization, or slower than optimal response latencies for any specific task. Here, to mitigate these concerns, we present an open-source behavior controller for associative learning and memory (B-CALM). B-CALM provides an integrated suite that can control a host of associative learning and memory behaviors. As proof of principle for its applicability, we show data from head-fixed mice learning Pavlovian conditioning, operant conditioning, discrimination learning, as well as a timing task and a choice task. These can be run directly from a user-friendly graphical user interface (GUI) written in MATLAB that controls many independently running Arduino Mega microcontrollers in parallel (one per behavior box). In sum, B-CALM will enable researchers to execute a wide variety of associative learning and memory tasks in a scalable, accurate, and user-friendly manner.
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Affiliation(s)
- Mingkang Zhou
- Department of Neurology, University of California, San Francisco, CA, USA
- Neuroscience Graduate Program, University of California, San Francisco, CA, USA
| | - Brenda Wu
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Huijeong Jeong
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Dennis A Burke
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Vijay Mohan K Namboodiri
- Department of Neurology, University of California, San Francisco, CA, USA.
- Neuroscience Graduate Program, University of California, San Francisco, CA, USA.
- Weill Institute for Neuroscience, Kavli Institute for Fundamental Neuroscience, Center for Integrative Neuroscience, University of California, San Francisco, CA, USA.
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5
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Neville V, Mendl M, Paul ES, Seriès P, Dayan P. A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2024; 24:370-383. [PMID: 38036937 PMCID: PMC11039423 DOI: 10.3758/s13415-023-01137-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/30/2023] [Indexed: 12/02/2023]
Abstract
Objective measures of animal emotion-like and mood-like states are essential for preclinical studies of affective disorders and for assessing the welfare of laboratory and other animals. However, the development and validation of measures of these affective states poses a challenge partly because the relationships between affect and its behavioural, physiological and cognitive signatures are complex. Here, we suggest that the crisp characterisations offered by computational modelling of the underlying, but unobservable, processes that mediate these signatures should provide better insights. Although this computational psychiatry approach has been widely used in human research in both health and disease, translational computational psychiatry studies remain few and far between. We explain how building computational models with data from animal studies could play a pivotal role in furthering our understanding of the aetiology of affective disorders, associated affective states and the likely underlying cognitive processes involved. We end by outlining the basic steps involved in a simple computational analysis.
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Affiliation(s)
- Vikki Neville
- Bristol Veterinary School, University of Bristol, Langford, UK.
| | - Michael Mendl
- Bristol Veterinary School, University of Bristol, Langford, UK
| | | | - Peggy Seriès
- Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, UK
| | - Peter Dayan
- Max Planck Institute for Biological Cybernetics & University of Tübingen, Tübingen, Germany
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6
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Blanco-Pozo M, Akam T, Walton ME. Dopamine-independent effect of rewards on choices through hidden-state inference. Nat Neurosci 2024; 27:286-297. [PMID: 38216649 PMCID: PMC10849965 DOI: 10.1038/s41593-023-01542-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 12/01/2023] [Indexed: 01/14/2024]
Abstract
Dopamine is implicated in adaptive behavior through reward prediction error (RPE) signals that update value estimates. There is also accumulating evidence that animals in structured environments can use inference processes to facilitate behavioral flexibility. However, it is unclear how these two accounts of reward-guided decision-making should be integrated. Using a two-step task for mice, we show that dopamine reports RPEs using value information inferred from task structure knowledge, alongside information about reward rate and movement. Nonetheless, although rewards strongly influenced choices and dopamine activity, neither activating nor inhibiting dopamine neurons at trial outcome affected future choice. These data were recapitulated by a neural network model where cortex learned to track hidden task states by predicting observations, while basal ganglia learned values and actions via RPEs. This shows that the influence of rewards on choices can stem from dopamine-independent information they convey about the world's state, not the dopaminergic RPEs they produce.
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Affiliation(s)
- Marta Blanco-Pozo
- Department of Experimental Psychology, Oxford University, Oxford, UK.
- Wellcome Centre for Integrative Neuroimaging, Oxford University, Oxford, UK.
| | - Thomas Akam
- Department of Experimental Psychology, Oxford University, Oxford, UK.
- Wellcome Centre for Integrative Neuroimaging, Oxford University, Oxford, UK.
| | - Mark E Walton
- Department of Experimental Psychology, Oxford University, Oxford, UK.
- Wellcome Centre for Integrative Neuroimaging, Oxford University, Oxford, UK.
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7
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Ly R, Avaylon M, Wulf M, Kepecs A, Rübel O. Structured behavioral data format: An NWB extension standard for task-based behavioral neuroscience experiments. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.08.574597. [PMID: 38260593 PMCID: PMC10802442 DOI: 10.1101/2024.01.08.574597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Understanding brain function necessitates linking neural activity with corresponding behavior. Structured behavioral experiments are crucial for probing the neural computations and dynamics underlying behavior; however, adequately representing their complex data is a significant challenge. Currently, a comprehensive data standard that fully encapsulates task-based experiments, integrating neural activity with the richness of behavioral context, is lacking. We designed a data model, as an extension to the NWB neurophysiology data standard, to represent structured behavioral neuroscience experiments, spanning stimulus delivery, timestamped events and responses, and simultaneous neural recordings. This data format is validated through its application to a variety of experimental designs, showcasing its potential to advance integrative analyses of neural circuits and complex behaviors. This work introduces a comprehensive data standard designed to capture and store a spectrum of behavioral data, encapsulating the multifaceted nature of modern neuroscience experiments.
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8
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Nadtochiy A, Luu P, Fraser SE, Truong TV. VoDEx: a Python library for time annotation and management of volumetric functional imaging data. Bioinformatics 2023; 39:btad568. [PMID: 37699009 PMCID: PMC10562951 DOI: 10.1093/bioinformatics/btad568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 08/30/2023] [Accepted: 09/11/2023] [Indexed: 09/14/2023] Open
Abstract
SUMMARY In functional imaging studies, accurately synchronizing the time course of experimental manipulations and stimulus presentations with resulting imaging data is crucial for analysis. Current software tools lack such functionality, requiring manual processing of the experimental and imaging data, which is error-prone and potentially non-reproducible. We present VoDEx, an open-source Python library that streamlines the data management and analysis of functional imaging data. VoDEx synchronizes the experimental timeline and events (e.g. presented stimuli, recorded behavior) with imaging data. VoDEx provides tools for logging and storing the timeline annotation, and enables retrieval of imaging data based on specific time-based and manipulation-based experimental conditions. AVAILABILITY AND IMPLEMENTATION VoDEx is an open-source Python library and can be installed via the "pip install" command. It is released under a BSD license, and its source code is publicly accessible on GitHub (https://github.com/LemonJust/vodex). A graphical interface is available as a napari-vodex plugin, which can be installed through the napari plugins menu or using "pip install." The source code for the napari plugin is available on GitHub (https://github.com/LemonJust/napari-vodex). The software version at the time of submission is archived at Zenodo (version v1.0.18, https://zenodo.org/record/8061531).
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Affiliation(s)
- Anna Nadtochiy
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, United States
- Translational Imaging Center, University of Southern California, Los Angeles, CA 90089, United States
| | - Peter Luu
- Translational Imaging Center, University of Southern California, Los Angeles, CA 90089, United States
- Division of Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, United States
| | - Scott E Fraser
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, United States
- Translational Imaging Center, University of Southern California, Los Angeles, CA 90089, United States
- Division of Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, United States
| | - Thai V Truong
- Translational Imaging Center, University of Southern California, Los Angeles, CA 90089, United States
- Division of Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, United States
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9
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Rowland JM, van der Plas TL, Loidolt M, Lees RM, Keeling J, Dehning J, Akam T, Priesemann V, Packer AM. Propagation of activity through the cortical hierarchy and perception are determined by neural variability. Nat Neurosci 2023; 26:1584-1594. [PMID: 37640911 PMCID: PMC10471496 DOI: 10.1038/s41593-023-01413-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 07/18/2023] [Indexed: 08/31/2023]
Abstract
Brains are composed of anatomically and functionally distinct regions performing specialized tasks, but regions do not operate in isolation. Orchestration of complex behaviors requires communication between brain regions, but how neural dynamics are organized to facilitate reliable transmission is not well understood. Here we studied this process directly by generating neural activity that propagates between brain regions and drives behavior, assessing how neural populations in sensory cortex cooperate to transmit information. We achieved this by imaging two densely interconnected regions-the primary and secondary somatosensory cortex (S1 and S2)-in mice while performing two-photon photostimulation of S1 neurons and assigning behavioral salience to the photostimulation. We found that the probability of perception is determined not only by the strength of the photostimulation but also by the variability of S1 neural activity. Therefore, maximizing the signal-to-noise ratio of the stimulus representation in cortex relative to the noise or variability is critical to facilitate activity propagation and perception.
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Affiliation(s)
- James M Rowland
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Thijs L van der Plas
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Matthias Loidolt
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Laboratory for Molecular Cell Biology, University College London, London, UK
| | - Robert M Lees
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
- Science and Technology Facilities Council, Octopus Imaging Facility, Research Complex at Harwell, Harwell Campus, Oxfordshire, UK
| | - Joshua Keeling
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Jonas Dehning
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - Thomas Akam
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Viola Priesemann
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany
| | - Adam M Packer
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK.
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10
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Jankowski MM, Polterovich A, Kazakov A, Niediek J, Nelken I. An automated, low-latency environment for studying the neural basis of behavior in freely moving rats. BMC Biol 2023; 21:172. [PMID: 37568111 PMCID: PMC10416379 DOI: 10.1186/s12915-023-01660-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 07/10/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes). RESULTS To overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding areas, multiple sound sources, high-resolution behavioral tracking, and simultaneous electrophysiological recordings. The paper provides detailed information about the construction of the RIFF and the software used to control it. To illustrate the flexibility of the RIFF, we describe two complex tasks implemented in the RIFF, a foraging task and a sound localization task. Rats quickly learned to obtain rewards in both tasks. Neurons in the auditory cortex as well as neurons in the auditory field in the posterior insula had sound-driven activity during behavior. Remarkably, neurons in both structures also showed sensitivity to non-auditory parameters such as location in the arena and head-to-body angle. CONCLUSIONS The RIFF provides insights into the cognitive capabilities and learning mechanisms of rats and opens the way to a better understanding of how brains control behavior. The ability to do so depends crucially on the combination of wireless electrophysiology and detailed behavioral documentation available in the RIFF.
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Affiliation(s)
- Maciej M Jankowski
- The Edmond and Lily Safra Center for Brain Sciences and the Department of Neurobiology, Silberman Institute of Life Sciences, the Hebrew University of Jerusalem, Jerusalem, Israel
- BioTechMed Center, Multimedia Systems Department, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland
| | - Ana Polterovich
- The Edmond and Lily Safra Center for Brain Sciences and the Department of Neurobiology, Silberman Institute of Life Sciences, the Hebrew University of Jerusalem, Jerusalem, Israel
| | - Alex Kazakov
- The Edmond and Lily Safra Center for Brain Sciences and the Department of Neurobiology, Silberman Institute of Life Sciences, the Hebrew University of Jerusalem, Jerusalem, Israel
| | - Johannes Niediek
- The Edmond and Lily Safra Center for Brain Sciences and the Department of Neurobiology, Silberman Institute of Life Sciences, the Hebrew University of Jerusalem, Jerusalem, Israel
| | - Israel Nelken
- The Edmond and Lily Safra Center for Brain Sciences and the Department of Neurobiology, Silberman Institute of Life Sciences, the Hebrew University of Jerusalem, Jerusalem, Israel.
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11
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Jendryka MM, Lewin U, van der Veen B, Kapanaiah SKT, Prex V, Strahnen D, Akam T, Liss B, Pekcec A, Nissen W, Kätzel D. Control of sustained attention and impulsivity by G q-protein signalling in parvalbumin interneurons of the anterior cingulate cortex. Transl Psychiatry 2023; 13:243. [PMID: 37407615 DOI: 10.1038/s41398-023-02541-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 06/19/2023] [Accepted: 06/23/2023] [Indexed: 07/07/2023] Open
Abstract
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 Gq-protein-coupled receptors (GqPCRs) 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 GqPCR 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. GqPCR 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 GqPCRs 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.
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Affiliation(s)
- Martin M Jendryka
- Institute of Applied Physiology, Ulm University, Ulm, Germany
- Boehringer Ingelheim Pharma GmbH & Co. KG, Div. Research Germany, Biberach an der Riss, Germany
| | - Uwe Lewin
- Institute of Applied Physiology, Ulm University, Ulm, Germany
| | | | | | - Vivien Prex
- Institute of Applied Physiology, Ulm University, Ulm, Germany
| | - Daniel Strahnen
- Institute of Applied Physiology, Ulm University, Ulm, Germany
| | - Thomas Akam
- Department of Experimental Psychology and Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Birgit Liss
- Institute of Applied Physiology, Ulm University, Ulm, Germany
- Linacre College and New College, University of Oxford, Oxford, UK
| | - Anton Pekcec
- Boehringer Ingelheim Pharma GmbH & Co. KG, Div. Research Germany, Biberach an der Riss, Germany
| | - Wiebke Nissen
- Boehringer Ingelheim Pharma GmbH & Co. KG, Div. Research Germany, Biberach an der Riss, Germany
| | - Dennis Kätzel
- Institute of Applied Physiology, Ulm University, Ulm, Germany.
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12
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Nadtochiy A, Luu P, Fraser SE, Truong TV. VoDEx: a Python library for time annotation and management of volumetric functional imaging data. ARXIV 2023:arXiv:2305.07438v1. [PMID: 37214133 PMCID: PMC10197724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
In functional imaging studies, accurately synchronizing the time course of experimental manipulations and stimulus presentations with resulting imaging data is crucial for analysis. Current software tools lack such functionality, requiring manual processing of the experimental and imaging data, which is error-prone and potentially non-reproducible. We present VoDEx, an open-source Python library that streamlines the data management and analysis of functional imaging data. VoDEx synchronizes the experimental timeline and events (eg. presented stimuli, recorded behavior) with imaging data. VoDEx provides tools for logging and storing the timeline annotation, and enables retrieval of imaging data based on specific time-based and manipulation-based experimental conditions. Availability and Implementation: VoDEx is an open-source Python library and can be installed via the "pip install" command. It is released under a BSD license, and its source code is publicly accessible on GitHub https://github.com/LemonJust/vodex. A graphical interface is available as a napari-vodex plugin, which can be installed through the napari plugins menu or using "pip install." The source code for the napari plugin is available on GitHub https://github.com/LemonJust/napari-vodex.
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Affiliation(s)
- Anna Nadtochiy
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
- Translational Imaging Center, University of Southern California, Los Angeles, CA, 90089, USA
| | - Peter Luu
- Department of Biological Sciences, Division of Molecular and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
- Translational Imaging Center, University of Southern California, Los Angeles, CA, 90089, USA
| | - Scott E. Fraser
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Biological Sciences, Division of Molecular and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
- Translational Imaging Center, University of Southern California, Los Angeles, CA, 90089, USA
| | - Thai V. Truong
- Department of Biological Sciences, Division of Molecular and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA
- Translational Imaging Center, University of Southern California, Los Angeles, CA, 90089, USA
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Wong K, Wang ZC, Patarino M, Baskin B, Lee SJ, Schindler AG. Socially Integrated Polysubstance (SIP) system: An open-source solution for continuous monitoring of polysubstance fluid intake in group housed mice. ADDICTION NEUROSCIENCE 2023; 7:10.1016/j.addicn.2023.100101. [PMID: 37560335 PMCID: PMC10411158 DOI: 10.1016/j.addicn.2023.100101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
Despite impressive results from neuroscience research using rodent models, there is a paucity of successful translation from preclinical findings to effective pharmacological interventions for treatment of substance use disorder (SUD) in humans. One potential reason for lack of translation from animal models is difficulty in accurately replicating the lived experience of people who use drugs. Aspects of substance use in humans that are often not modeled in animal research include but are not limited to 1) voluntary timing and frequency of substance intake, 2) social environment during substance use, and 3) access to multiple substances and multiple concentrations of each substance. Critically, existing commercial equipment that allows for social housing and voluntary polysubstance use (e.g., home cage monitoring system) is prohibitively expensive and no open-source solutions exist. With these goals in mind, here we detail development of the Socially Integrated Polysubstance (SIP) system, an open-source and lower cost solution that allows for group housed rodents to self-administer multiple substances with continuous monitoring and measurement. In our current setup, each SIP cage contains four drinking stations, and each station is equipped with a RFID sensor and sipper tube connected to a unique fluid reservoir. Using this system, we can track which animal (implanted with unique RFID transponder) visits which drinking location and the amount they drink during each visit (in 20 ul increments). Using four flavors of Kool-Aid, here we demonstrate that the SIP system is reliable and accurate with high temporal resolution for long term monitoring of substance intake and behavior tracking in a social environment. The SIP cage system is a first step towards designing an accessible and flexible rodent model of substance use that more closely resembles the experience of people who use drugs.
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Affiliation(s)
- Katrina Wong
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA 98195
- VA Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA
| | - Ziheng Christina Wang
- VA Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA
| | - Makenzie Patarino
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA 98195
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, USA 98195
- VA Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA
| | - Britahny Baskin
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA 98195
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, USA 98195
- VA Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA
| | - Suhjung Janet Lee
- VA Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA
| | - Abigail G. Schindler
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA 98195
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, USA 98195
- VA Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA
- VA Northwest Mental Illness Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
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Eleftheriou C, Clarke T, Poon V, Zechner M, Duguid I. Visiomode: An open-source platform for building rodent touchscreen-based behavioral assays. J Neurosci Methods 2023; 386:109779. [PMID: 36621552 PMCID: PMC10375831 DOI: 10.1016/j.jneumeth.2022.109779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 12/22/2022] [Accepted: 12/23/2022] [Indexed: 01/06/2023]
Abstract
BACKGROUND Touchscreen-based behavioral assays provide a robust method for assessing cognitive behavior in rodents, offering great flexibility and translational potential. The development of touchscreen assays presents a significant programming and mechanical engineering challenge, where commercial solutions can be prohibitively expensive and open-source solutions are underdeveloped, with limited adaptability. NEW METHOD Here, we present Visiomode (www.visiomode.org), an open-source platform for building rodent touchscreen-based behavioral tasks. Visiomode leverages the inherent flexibility of touchscreens to offer a simple yet adaptable software and hardware platform. The platform is built on the Raspberry Pi computer combining a web-based interface and powerful plug-in system with an operant chamber that can be adapted to generate a wide range of behavioral tasks. RESULTS As a proof of concept, we use Visiomode to build both simple stimulus-response and more complex visual discrimination tasks, showing that mice display rapid sensorimotor learning including switching between different motor responses (i.e., nose poke versus reaching). COMPARISON WITH EXISTING METHODS Commercial solutions are the 'go to' for rodent touchscreen behaviors, but the associated costs can be prohibitive, limiting their uptake by the wider neuroscience community. While several open-source solutions have been developed, efforts so far have focused on reducing the cost, rather than promoting ease of use and adaptability. Visiomode addresses these unmet needs providing a low-cost, extensible platform for creating touchscreen tasks. CONCLUSIONS Developing an open-source, rapidly scalable and low-cost platform for building touchscreen-based behavioral assays should increase uptake across the science community and accelerate the investigation of cognition, decision-making and sensorimotor behaviors both in health and disease.
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Affiliation(s)
- Constantinos Eleftheriou
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh EH8 9XD, UK; Centre for Discovery Brain Sciences and Patrick Wild Centre, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK.
| | - Thomas Clarke
- Centre for Discovery Brain Sciences and Patrick Wild Centre, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK
| | - V Poon
- Centre for Discovery Brain Sciences and Patrick Wild Centre, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK
| | - Marie Zechner
- The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, Scotland, UK
| | - Ian Duguid
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh EH8 9XD, UK; Centre for Discovery Brain Sciences and Patrick Wild Centre, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK.
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15
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Samborska V, Butler JL, Walton ME, Behrens TEJ, Akam T. Complementary task representations in hippocampus and prefrontal cortex for generalizing the structure of problems. Nat Neurosci 2022; 25:1314-1326. [PMID: 36171429 PMCID: PMC9534768 DOI: 10.1038/s41593-022-01149-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 07/19/2022] [Indexed: 11/16/2022]
Abstract
Humans and other animals effortlessly generalize prior knowledge to solve novel problems, by abstracting common structure and mapping it onto new sensorimotor specifics. To investigate how the brain achieves this, in this study, we trained mice on a series of reversal learning problems that shared the same structure but had different physical implementations. Performance improved across problems, indicating transfer of knowledge. Neurons in medial prefrontal cortex (mPFC) maintained similar representations across problems despite their different sensorimotor correlates, whereas hippocampal (dCA1) representations were more strongly influenced by the specifics of each problem. This was true for both representations of the events that comprised each trial and those that integrated choices and outcomes over multiple trials to guide an animal’s decisions. These data suggest that prefrontal cortex and hippocampus play complementary roles in generalization of knowledge: PFC abstracts the common structure among related problems, and hippocampus maps this structure onto the specifics of the current situation. Samborska et al. trained mice on a set of problems with the same structure but different physical layouts to study generalization. Neurons in prefrontal cortex generalized across problems, whereas those in hippocampus were more problem specific.
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Affiliation(s)
- Veronika Samborska
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
| | - James L Butler
- Department of Clinical and Movement Neurosciences, University College London, London, UK.,Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Mark E Walton
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Timothy E J Behrens
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK. .,Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK. .,Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Thomas Akam
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
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Kilonzo K, Strahnen D, Prex V, Gems J, van der Veen B, Kapanaiah SKT, Murthy BKB, Schulz S, Sprengel R, Bannerman D, Kätzel D. Distinct contributions of GluA1-containing AMPA receptors of different hippocampal subfields to salience processing, memory and impulse control. Transl Psychiatry 2022; 12:102. [PMID: 35288531 PMCID: PMC8921206 DOI: 10.1038/s41398-022-01863-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 02/19/2022] [Accepted: 02/21/2022] [Indexed: 12/29/2022] Open
Abstract
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.
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Affiliation(s)
- Kasyoka Kilonzo
- grid.6582.90000 0004 1936 9748Institute of Applied Physiology, Ulm University, Ulm, Germany
| | - Daniel Strahnen
- grid.6582.90000 0004 1936 9748Institute of Applied Physiology, Ulm University, Ulm, Germany
| | - Vivien Prex
- grid.6582.90000 0004 1936 9748Institute of Applied Physiology, Ulm University, Ulm, Germany
| | - John Gems
- grid.6582.90000 0004 1936 9748Institute of Applied Physiology, Ulm University, Ulm, Germany
| | - Bastiaan van der Veen
- grid.6582.90000 0004 1936 9748Institute of Applied Physiology, Ulm University, Ulm, Germany
| | | | - Bhargavi K. B. Murthy
- grid.6582.90000 0004 1936 9748Institute of Applied Physiology, Ulm University, Ulm, Germany
| | - Stefanie Schulz
- grid.6582.90000 0004 1936 9748Institute of Applied Physiology, Ulm University, Ulm, Germany
| | - Rolf Sprengel
- grid.414703.50000 0001 2202 0959Max Planck Institute for Medical Research, Heidelberg, Germany
| | - David Bannerman
- grid.4991.50000 0004 1936 8948Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Dennis Kätzel
- Institute of Applied Physiology, Ulm University, Ulm, Germany.
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