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Rizzello E, Martin SK, Rouine J, Callaghan C, Mathiasen ML, O'Mara SM. Place Cells in the Claustrum Remap Under NMDA Receptor Control. Eur J Neurosci 2022; 56:3825-3838. [PMID: 35658087 PMCID: PMC9543514 DOI: 10.1111/ejn.15726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 05/18/2022] [Indexed: 11/29/2022]
Abstract
Place cells are cells that exhibit location‐dependent responses; they have mostly been studied in the hippocampus. Place cells have also been reported in the rat claustrum, an underexplored paracortical region with extensive corto‐cortical connectivity. It has been hypothesised that claustral neuronal responses are anchored to cortical visual inputs. We show rat claustral place cells remap when visual inputs are eliminated from the environment, and that this remapping is NMDA‐receptor‐dependent. Eliminating visual input decreases claustral delta‐band oscillatory activity, increases theta‐band oscillatory activity, and increases simultaneously recorded visual cortical activity. We conclude that, like the hippocampus, claustral place field remapping might be mediated by NMDA receptor activity, and is modulated by visual cortical inputs.
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Affiliation(s)
- Emanuela Rizzello
- School of Psychology and Institute of Neuroscience, Trinity College, Dublin - the University of Dublin, College Green, Ireland
| | - Seán K Martin
- School of Psychology and Institute of Neuroscience, Trinity College, Dublin - the University of Dublin, College Green, Ireland
| | - Jennifer Rouine
- School of Psychology and Institute of Neuroscience, Trinity College, Dublin - the University of Dublin, College Green, Ireland
| | - Charlotte Callaghan
- School of Psychology and Institute of Neuroscience, Trinity College, Dublin - the University of Dublin, College Green, Ireland
| | - Mathias L Mathiasen
- School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom.,Current address: Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Shane M O'Mara
- School of Psychology and Institute of Neuroscience, Trinity College, Dublin - the University of Dublin, College Green, Ireland
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Frost BE, Martin SK, Cafalchio M, Islam MN, Aggleton JP, O'Mara SM. Anterior Thalamic Inputs Are Required for Subiculum Spatial Coding, with Associated Consequences for Hippocampal Spatial Memory. J Neurosci 2021; 41:6511-6525. [PMID: 34131030 PMCID: PMC8318085 DOI: 10.1523/jneurosci.2868-20.2021] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 03/24/2021] [Accepted: 03/28/2021] [Indexed: 11/21/2022] Open
Abstract
Just as hippocampal lesions are principally responsible for "temporal lobe" amnesia, lesions affecting the anterior thalamic nuclei seem principally responsible for a similar loss of memory, "diencephalic" amnesia. Compared with the former, the causes of diencephalic amnesia have remained elusive. A potential clue comes from how the two sites are interconnected, as within the hippocampal formation, only the subiculum has direct, reciprocal connections with the anterior thalamic nuclei. We found that both permanent and reversible anterior thalamic nuclei lesions in male rats cause a cessation of subicular spatial signaling, reduce spatial memory performance to chance, but leave hippocampal CA1 place cells largely unaffected. We suggest that a core element of diencephalic amnesia stems from the information loss in hippocampal output regions following anterior thalamic pathology.SIGNIFICANCE STATEMENT At present, we know little about interactions between temporal lobe and diencephalic memory systems. Here, we focused on the subiculum, as the sole hippocampal formation region directly interconnected with the anterior thalamic nuclei. We combined reversible and permanent lesions of the anterior thalamic nuclei, electrophysiological recordings of the subiculum, and behavioral analyses. Our results were striking and clear: following permanent thalamic lesions, the diverse spatial signals normally found in the subiculum (including place cells, grid cells, and head-direction cells) all disappeared. Anterior thalamic lesions had no discernible impact on hippocampal CA1 place fields. Thus, spatial firing activity within the subiculum requires anterior thalamic function, as does successful spatial memory performance. Our findings provide a key missing part of the much bigger puzzle concerning why anterior thalamic damage is so catastrophic for spatial memory in rodents and episodic memory in humans.
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Affiliation(s)
- Bethany E Frost
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - Sean K Martin
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - Matheus Cafalchio
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - Md Nurul Islam
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - John P Aggleton
- School of Psychology, Cardiff University, Cardiff, CF10 3AS, United Kingdom
| | - Shane M O'Mara
- School of Psychology and Institute of Neuroscience, Trinity College Dublin, Dublin, D02 PN40, Ireland
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Fabietti M, Mahmud M, Lotfi A, Kaiser MS, Averna A, Guggenmos DJ, Nudo RJ, Chiappalone M, Chen J. SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals. Brain Inform 2021; 8:14. [PMID: 34283328 PMCID: PMC8292498 DOI: 10.1186/s40708-021-00135-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 06/29/2021] [Indexed: 12/11/2022] Open
Abstract
Neuronal signals generally represent activation of the neuronal networks and give insights into brain functionalities. They are considered as fingerprints of actions and their processing across different structures of the brain. These recordings generate a large volume of data that are susceptible to noise and artifacts. Therefore, the review of these data to ensure high quality by automatically detecting and removing the artifacts is imperative. Toward this aim, this work proposes a custom-developed automatic artifact removal toolbox named, SANTIA (SigMate Advanced: a Novel Tool for Identification of Artifacts in Neuronal Signals). Developed in Matlab, SANTIA is an open-source toolbox that applies neural network-based machine learning techniques to label and train models to detect artifacts from the invasive neuronal signals known as local field potentials.
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Affiliation(s)
- Marcos Fabietti
- Department of Computer Science, Nottingham Trent University, Clifton Lane, Nottingham, NG11 8NS, UK
| | - Mufti Mahmud
- Department of Computer Science, Nottingham Trent University, Clifton Lane, Nottingham, NG11 8NS, UK.
- Medical Technologies Innovation Facility, Nottingham Trent University, Clifton Lane, Nottingham, NG11 8NS, UK.
- Computing and Informatics Research Centre, Nottingham Trent University, Clifton Lane, Nottingham, NG11 8NS, UK.
| | - Ahmad Lotfi
- Department of Computer Science, Nottingham Trent University, Clifton Lane, Nottingham, NG11 8NS, UK
| | - M Shamim Kaiser
- Institute of Information Technology, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh
| | - Alberto Averna
- Department of Health Sciences, University of Milan, Via di Rudinì, 8, 20142, Milan, Italy
| | - David J Guggenmos
- Department of Physical Medicine and Rehabilitation, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, 66160, USA
| | - Randolph J Nudo
- Department of Physical Medicine and Rehabilitation, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, 66160, USA
| | - Michela Chiappalone
- Department of informatics, Bioengineering, Robotics and System Engineering-DIBRIS, University of Genova, Via All'Opera Pia, 13, 16145, Genoa, Italy
| | - Jianhui Chen
- Faculty of Information Technology, International WIC Institute, Beijing University of Technology, Beijing, 100124, China
- Beijing International Collaboration Base on Brain Informatics and Wisdom Services, Beijing, 100124, China
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Fabietti M, Mahmud M, Lotfi A. A Matlab-Based Open-Source Toolbox for Artefact Removal from Extracellular Neuronal Signals. Brain Inform 2021. [DOI: 10.1007/978-3-030-86993-9_32] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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neurotic: Neuroscience Tool for Interactive Characterization. eNeuro 2020; 7:ENEURO.0085-20.2020. [PMID: 32332078 PMCID: PMC7215586 DOI: 10.1523/eneuro.0085-20.2020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 04/15/2020] [Accepted: 04/16/2020] [Indexed: 12/26/2022] Open
Abstract
A software tool for synchronization of video with signals would be of broad general use to behavioral neuroscientists. A new program, called neurotic (NEUROscience Tool for Interactive Characterization), allows users to review and annotate signal data synchronized with video, performs simple initial analyses including signal filtering and spike detection, is easy to use, and supports a variety of file formats. The program also facilitates collaborations by using a portable specification for loading and processing data and retrieving data files from online sources. Two examples are shown in which the software is used to explore experimental datasets with extracellular nerve or muscle recordings and simultaneous video of behavior. The configuration specification for controlling how data are located, loaded, processed, and plotted is also summarized. Algorithms for spike detection and burst detection are demonstrated. This new program could be used in many applications in which behavior and signals need to be analyzed together.
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