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Quansah Amissah R, Albeely AM, Bragg EM, Perreault ML, Doucette WT, Khokhar JY. A Simple, Lightweight, and Low-Cost Customizable Multielectrode Array for Local Field Potential Recordings. eNeuro 2023; 10:ENEURO.0212-23.2023. [PMID: 37643859 PMCID: PMC10467017 DOI: 10.1523/eneuro.0212-23.2023] [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: 06/19/2023] [Revised: 08/01/2023] [Accepted: 08/03/2023] [Indexed: 08/31/2023] Open
Abstract
Local field potential (LFP) recording is a valuable method for assessing brain systems communication. Multiple methods have been developed to collect LFP data to study the rhythmic activity of the brain. These methods range from the use of single or bundled metal electrodes to electrode arrays that can target multiple brain regions. Although these electrodes are efficient in collecting LFP activity, they can be expensive, difficult to build, and less adaptable to different applications, which may include targeting multiple brain regions simultaneously. Here, the building process for a 16-channel customizable multielectrode array (CMEA) that can be used to collect LFP data from different brain regions simultaneously in rats is described. These CMEA electrode arrays are lightweight (<1 g), take little time to build (<1 h), and are affordable ($15 Canadian). The CMEA can also be modified to record single-unit and multiunit activity in addition to LFP activity using both wired and wireless neural data acquisition systems. Moreover, these CMEAs can be used to explore neural activity (LFP and single-unit/multiunit activity) in preliminary studies, before purchasing more expensive electrodes for targeted studies. Together, these characteristics make the described CMEA a competitive alternative to the commercially available multielectrode arrays for its simplicity, low cost, and efficiency in collecting LFP data in freely behaving animals.
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Affiliation(s)
- Richard Quansah Amissah
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Abdalla M Albeely
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 5C1, Canada
| | - Elise M Bragg
- Department of Psychiatry, Dartmouth Hitchcock Medical Center, Lebanon, New Hampshire 03756
- Geisel School of Medicine at Dartmouth, Hanover, New Hampshire 03755-1404
| | - Melissa L Perreault
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Wilder T Doucette
- Department of Psychiatry, Dartmouth Hitchcock Medical Center, Lebanon, New Hampshire 03756
- Geisel School of Medicine at Dartmouth, Hanover, New Hampshire 03755-1404
| | - Jibran Y Khokhar
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, Ontario N1G 2W1, Canada
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 5C1, Canada
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Bod RB, Rokai J, Meszéna D, Fiáth R, Ulbert I, Márton G. From End to End: Gaining, Sorting, and Employing High-Density Neural Single Unit Recordings. Front Neuroinform 2022; 16:851024. [PMID: 35769832 PMCID: PMC9236662 DOI: 10.3389/fninf.2022.851024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 05/06/2022] [Indexed: 11/15/2022] Open
Abstract
The meaning behind neural single unit activity has constantly been a challenge, so it will persist in the foreseeable future. As one of the most sourced strategies, detecting neural activity in high-resolution neural sensor recordings and then attributing them to their corresponding source neurons correctly, namely the process of spike sorting, has been prevailing so far. Support from ever-improving recording techniques and sophisticated algorithms for extracting worthwhile information and abundance in clustering procedures turned spike sorting into an indispensable tool in electrophysiological analysis. This review attempts to illustrate that in all stages of spike sorting algorithms, the past 5 years innovations' brought about concepts, results, and questions worth sharing with even the non-expert user community. By thoroughly inspecting latest innovations in the field of neural sensors, recording procedures, and various spike sorting strategies, a skeletonization of relevant knowledge lays here, with an initiative to get one step closer to the original objective: deciphering and building in the sense of neural transcript.
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Affiliation(s)
- Réka Barbara Bod
- Laboratory of Experimental Neurophysiology, Department of Physiology, Faculty of Medicine, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureş, Târgu Mureş, Romania
| | - János Rokai
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- School of PhD Studies, Semmelweis University, Budapest, Hungary
| | - Domokos Meszéna
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Richárd Fiáth
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - István Ulbert
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Gergely Márton
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
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