1
|
Fortuna L, Buscarino A. Spiking Neuron Mathematical Models: A Compact Overview. Bioengineering (Basel) 2023; 10:bioengineering10020174. [PMID: 36829668 PMCID: PMC9952045 DOI: 10.3390/bioengineering10020174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/13/2023] [Accepted: 01/23/2023] [Indexed: 01/31/2023] Open
Abstract
The features of the main models of spiking neurons are discussed in this review. We focus on the dynamical behaviors of five paradigmatic spiking neuron models and present recent literature studies on the topic, classifying the contributions based on the most-studied items. The aim of this review is to provide the reader with fundamental details related to spiking neurons from a dynamical systems point-of-view.
Collapse
Affiliation(s)
- Luigi Fortuna
- Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, 95125 Catania, Italy
- IASI, Consiglio Nazionale delle Ricerche (CNR), 00185 Roma, Italy
- Correspondence: (L.F.); (A.B.)
| | - Arturo Buscarino
- Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, 95125 Catania, Italy
- IASI, Consiglio Nazionale delle Ricerche (CNR), 00185 Roma, Italy
- Correspondence: (L.F.); (A.B.)
| |
Collapse
|
2
|
Chiappalone M, Cota VR, Carè M, Di Florio M, Beaubois R, Buccelli S, Barban F, Brofiga M, Averna A, Bonacini F, Guggenmos DJ, Bornat Y, Massobrio P, Bonifazi P, Levi T. Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering. Brain Sci 2022; 12:1578. [PMID: 36421904 PMCID: PMC9688667 DOI: 10.3390/brainsci12111578] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/09/2022] [Accepted: 11/17/2022] [Indexed: 08/27/2023] Open
Abstract
Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system.
Collapse
Affiliation(s)
- Michela Chiappalone
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Vinicius R. Cota
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Marta Carè
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Mattia Di Florio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Romain Beaubois
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Stefano Buccelli
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Federico Barban
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Martina Brofiga
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Alberto Averna
- Department of Neurology, Bern University Hospital, University of Bern, 3012 Bern, Switzerland
| | - Francesco Bonacini
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - David J. Guggenmos
- Department of Rehabilitation Medicine, University of Kansas Medical Center, Kansas City, KS 66103, USA
- Landon Center on Aging, University of Kansas Medical Center, Kansas City, KS 66103, USA
| | - Yannick Bornat
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Paolo Massobrio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- National Institute for Nuclear Physics (INFN), 16146 Genova, Italy
| | - Paolo Bonifazi
- IKERBASQUE, The Basque Fundation, 48009 Bilbao, Spain
- Biocruces Health Research Institute, 48903 Barakaldo, Spain
| | - Timothée Levi
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| |
Collapse
|