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Wu FC, Chen CY, Wang YW, You CB, Wang LY, Ruan J, Chou WY, Lai WC, Cheng HL. Modulating Neuromorphic Behavior of Organic Synaptic Electrolyte-Gated Transistors Through Microstructure Engineering and Potential Applications. ACS APPLIED MATERIALS & INTERFACES 2024; 16:41211-41222. [PMID: 39054697 DOI: 10.1021/acsami.4c05966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/27/2024]
Abstract
Organic synaptic transistors are a promising technology for advanced electronic devices with simultaneous computing and memory functions and for the application of artificial neural networks. In this study, the neuromorphic electrical characteristics of organic synaptic electrolyte-gated transistors are correlated with the microstructural and interfacial properties of the active layers. This is accomplished by utilizing a semiconducting/insulating polyblend-based pseudobilayer with embedded source and drain electrodes, referred to as PB-ESD architecture. Three variations of poly(3-hexylthiophene) (P3HT)/poly(methyl methacrylate) (PMMA) PB-ESD-based organic synaptic transistors are fabricated, each exhibiting distinct microstructures and electrical characteristics, thus serving excellent samples for exploring the critical factors influencing neuro-electrical properties. Poor microstructures of P3HT within the active layer and a flat active layer/ion-gel interface correspond to typical neuromorphic behaviors such as potentiated excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and short-term potentiation (STP). Conversely, superior microstructures of P3HT and a rough active layer/ion-gel interface correspond to significantly higher channel conductance and enhanced EPSC and PPF characteristics as well as long-term potentiation behavior. Such devices were further applied to the simulation of neural networks, which produced a good recognition accuracy. However, excessive PMMA penetration into the P3HT conducting channel leads to features of a depressed EPSC and paired-pulse depression, which are uncommon in organic synaptic transistors. The inclusion of a second gate electrode enables the as-prepared organic synaptic transistors to function as two-input synaptic logic gates, performing various logical operations and effectively mimicking neural modulation functions. Microstructure and interface engineering is an effective method to modulate the neuromorphic behavior of organic synaptic transistors and advance the development of bionic artificial neural networks.
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Affiliation(s)
- Fu-Chiao Wu
- Department of Photonics, Meta-nanoPhotonics Center, National Cheng Kung University, Tainan 701, Taiwan
| | - Chun-Yu Chen
- Department of Photonics, Meta-nanoPhotonics Center, National Cheng Kung University, Tainan 701, Taiwan
| | - Yu-Wu Wang
- Institute of Photonics, National Changhua University of Education, Changhua 500, Taiwan
| | - Chun-Bin You
- Department of Photonics, Meta-nanoPhotonics Center, National Cheng Kung University, Tainan 701, Taiwan
| | - Li-Yun Wang
- Department of Photonics, Meta-nanoPhotonics Center, National Cheng Kung University, Tainan 701, Taiwan
| | - Jrjeng Ruan
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 701, Taiwan
| | - Wei-Yang Chou
- Department of Photonics, Meta-nanoPhotonics Center, National Cheng Kung University, Tainan 701, Taiwan
| | - Wei-Chih Lai
- Department of Photonics, Meta-nanoPhotonics Center, National Cheng Kung University, Tainan 701, Taiwan
| | - Horng-Long Cheng
- Department of Photonics, Meta-nanoPhotonics Center, National Cheng Kung University, Tainan 701, Taiwan
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Sawicki J, Berner R, Loos SAM, Anvari M, Bader R, Barfuss W, Botta N, Brede N, Franović I, Gauthier DJ, Goldt S, Hajizadeh A, Hövel P, Karin O, Lorenz-Spreen P, Miehl C, Mölter J, Olmi S, Schöll E, Seif A, Tass PA, Volpe G, Yanchuk S, Kurths J. Perspectives on adaptive dynamical systems. CHAOS (WOODBURY, N.Y.) 2023; 33:071501. [PMID: 37486668 DOI: 10.1063/5.0147231] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 05/24/2023] [Indexed: 07/25/2023]
Abstract
Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches.
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Affiliation(s)
- Jakub Sawicki
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Rico Berner
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Sarah A M Loos
- DAMTP, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, United Kingdom
| | - Mehrnaz Anvari
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53757 Sankt-Augustin, Germany
| | - Rolf Bader
- Institute of Systematic Musicology, University of Hamburg, Hamburg, Germany
| | - Wolfram Barfuss
- Transdisciplinary Research Area: Sustainable Futures, University of Bonn, 53113 Bonn, Germany
- Center for Development Research (ZEF), University of Bonn, 53113 Bonn, Germany
| | - Nicola Botta
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science and Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Nuria Brede
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science, University of Potsdam, An der Bahn 2, 14476 Potsdam, Germany
| | - Igor Franović
- Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia
| | - Daniel J Gauthier
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Sebastian Goldt
- Department of Physics, International School of Advanced Studies (SISSA), Trieste, Italy
| | - Aida Hajizadeh
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Philipp Hövel
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Omer Karin
- Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom
| | - Philipp Lorenz-Spreen
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
| | - Christoph Miehl
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Jan Mölter
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Boltzmannstraße 3, 85748 Garching bei München, Germany
| | - Simona Olmi
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Eckehard Schöll
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Alireza Seif
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, USA
| | - Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, California 94304, USA
| | - Giovanni Volpe
- Department of Physics, University of Gothenburg, Gothenburg, Sweden
| | - Serhiy Yanchuk
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Jürgen Kurths
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
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3
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Monteverdi A, Di Domenico D, D'Angelo E, Mapelli L. Anisotropy and Frequency Dependence of Signal Propagation in the Cerebellar Circuit Revealed by High-Density Multielectrode Array Recordings. Biomedicines 2023; 11:biomedicines11051475. [PMID: 37239146 DOI: 10.3390/biomedicines11051475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 05/05/2023] [Accepted: 05/12/2023] [Indexed: 05/28/2023] Open
Abstract
The cerebellum is one of the most connected structures of the central nervous system and receives inputs over an extended frequency range. Nevertheless, the frequency dependence of cerebellar cortical processing remains elusive. In this work, we characterized cerebellar cortex responsiveness to mossy fibers activation at different frequencies and reconstructed the spread of activity in the sagittal and coronal planes of acute mouse cerebellar slices using a high-throughput high-density multielectrode array (HD-MEA). The enhanced spatiotemporal resolution of HD-MEA revealed the frequency dependence and spatial anisotropy of cerebellar activation. Mossy fiber inputs reached the Purkinje cell layer even at the lowest frequencies, but the efficiency of transmission increased at higher frequencies. These properties, which are likely to descend from the topographic organization of local inhibition, intrinsic electroresponsiveness, and short-term synaptic plasticity, are critical elements that have to be taken into consideration to define the computational properties of the cerebellar cortex and its pathological alterations.
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Affiliation(s)
- Anita Monteverdi
- Brain Connectivity Center, IRCCS Mondino Foundation, 27100 Pavia, Italy
| | - Danila Di Domenico
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
| | - Egidio D'Angelo
- Brain Connectivity Center, IRCCS Mondino Foundation, 27100 Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
| | - Lisa Mapelli
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
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Munc18-1 Contributes to Hippocampal Injury in Septic Rats Through Regulation of Syntanxin1A and Synaptophysin and Glutamate Levels. Neurochem Res 2023; 48:791-803. [PMID: 36335177 PMCID: PMC9638283 DOI: 10.1007/s11064-022-03806-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/07/2022] [Accepted: 10/20/2022] [Indexed: 11/06/2022]
Abstract
Sepsis-associated encephalopathy (SAE) is a diffuse brain dysfunction closely associated with mortality in the acute phase of sepsis. Abnormal neurotransmitters release, such as glutamate, plays a crucial role in the pathological mechanism of SAE. Munc18-1 is a key protein regulating neurotransmission. However, whether Munc18-1 plays a role in SAE by regulating glutamate transmission is still unclear. In this study, a septic rat model was established by the cecal ligation and perforation. We found an increase in the content of glutamate in the hippocampus of septic rat, the number of synaptic vesicles in the synaptic active area and the expression of the glutamate receptor NMDAR1. Meanwhile, it was found that the expressions of Munc18-1, Syntaxin1A and Synaptophysin increased, which are involved in neurotransmission. The expression levels of Syntaxin1A and Synaptophysin in hippocampus of septic rats decreased after interference using Munc18-1siRNA. We observed a decrease in the content of glutamate in the hippocampus of septic rats, the number of synaptic vesicles in the synaptic activity area and the expression of NMDAR1. Interestingly, it was also found that the down-regulation of Munc18-1 improved the vital signs of septic rats. This study shows that CLP induced the increased levels of glutamate in rat hippocampus, and Munc18-1 may participate in the process of hippocampal injury in septic rats by affecting the levels of glutamate via regulating Syntaxin1A and Synaptophysin. Munc18-1 may serve as a potential target for SAE therapy.
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Hajizadeh A, Matysiak A, Wolfrum M, May PJC, König R. Auditory cortex modelled as a dynamical network of oscillators: understanding event-related fields and their adaptation. BIOLOGICAL CYBERNETICS 2022; 116:475-499. [PMID: 35718809 PMCID: PMC9287241 DOI: 10.1007/s00422-022-00936-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 05/07/2022] [Indexed: 06/15/2023]
Abstract
Adaptation, the reduction of neuronal responses by repetitive stimulation, is a ubiquitous feature of auditory cortex (AC). It is not clear what causes adaptation, but short-term synaptic depression (STSD) is a potential candidate for the underlying mechanism. In such a case, adaptation can be directly linked with the way AC produces context-sensitive responses such as mismatch negativity and stimulus-specific adaptation observed on the single-unit level. We examined this hypothesis via a computational model based on AC anatomy, which includes serially connected core, belt, and parabelt areas. The model replicates the event-related field (ERF) of the magnetoencephalogram as well as ERF adaptation. The model dynamics are described by excitatory and inhibitory state variables of cell populations, with the excitatory connections modulated by STSD. We analysed the system dynamics by linearising the firing rates and solving the STSD equation using time-scale separation. This allows for characterisation of AC dynamics as a superposition of damped harmonic oscillators, so-called normal modes. We show that repetition suppression of the N1m is due to a mixture of causes, with stimulus repetition modifying both the amplitudes and the frequencies of the normal modes. In this view, adaptation results from a complete reorganisation of AC dynamics rather than a reduction of activity in discrete sources. Further, both the network structure and the balance between excitation and inhibition contribute significantly to the rate with which AC recovers from adaptation. This lifetime of adaptation is longer in the belt and parabelt than in the core area, despite the time constants of STSD being spatially homogeneous. Finally, we critically evaluate the use of a single exponential function to describe recovery from adaptation.
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Affiliation(s)
- Aida Hajizadeh
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
| | - Artur Matysiak
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
| | - Matthias Wolfrum
- Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstraße 39, 10117 Berlin, Germany
| | - Patrick J. C. May
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
- Department of Psychology, Lancaster University, Lancaster, LA1 4YF UK
| | - Reinhard König
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
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6
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Lin CY, Chen J, Chen PH, Chang TC, Wu Y, Eshraghian JK, Moon J, Yoo S, Wang YH, Chen WC, Wang ZY, Huang HC, Li Y, Miao X, Lu WD, Sze SM. Adaptive Synaptic Memory via Lithium Ion Modulation in RRAM Devices. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e2003964. [PMID: 32996256 DOI: 10.1002/smll.202003964] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 08/12/2020] [Indexed: 06/11/2023]
Abstract
Biologically plausible computing systems require fine-grain tuning of analog synaptic characteristics. In this study, lithium-doped silicate resistive random access memory with a titanium nitride (TiN) electrode mimicking biological synapses is demonstrated. Biological plausibility of this RRAM device is thought to occur due to the low ionization energy of lithium ions, which enables controllable forming and filamentary retraction spontaneously or under an applied voltage. The TiN electrode can effectively store lithium ions, a principle widely adopted from battery construction, and allows state-dependent decay to be reliably achieved. As a result, this device offers multi-bit functionality and synaptic plasticity for simulating various strengths in neuronal connections. Both short-term memory and long-term memory are emulated across dynamical timescales. Spike-timing-dependent plasticity and paired-pulse facilitation are also demonstrated. These mechanisms are capable of self-pruning to generate efficient neural networks. Time-dependent resistance decay is observed for different conductance values, which mimics both biological and artificial memory pruning and conforms to the trend of the biological brain that prunes weak synaptic connections. By faithfully emulating learning rules that exist in human's higher cortical areas from STDP to synaptic pruning, the device has the capacity to drive forward the development of highly efficient neuromorphic computing systems.
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Affiliation(s)
- Chih-Yang Lin
- Department of Physics, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan
| | - Jia Chen
- Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, No.1037 Luoyu Road, Wuhan, 430074, China
| | - Po-Hsun Chen
- Department of Applied Science, R.O.C. Naval Academy, No.669 Junxiao Road, Kaohsiung, 81345, Taiwan
- Center for Nanoscience and Nanotechnology, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan
| | - Ting-Chang Chang
- Department of Physics, The Center of Crystal Research, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan
| | - Yuting Wu
- Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA
| | - Jason K Eshraghian
- Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA
| | - John Moon
- Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA
| | - Sangmin Yoo
- Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA
| | - Yu-Hsun Wang
- Department of Electronics Engineering and Institute of Electronics, National Chiao Tung University, No.1001 University Road, Hsinchu, 30010, Taiwan
| | - Wen-Chung Chen
- Department of Materials and Optoelectronic Science, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan
| | - Zhi-Yang Wang
- Department of Materials and Optoelectronic Science, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan
| | - Hui-Chun Huang
- Department of Materials and Optoelectronic Science, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan
| | - Yi Li
- Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, No.1037 Luoyu Road, Wuhan, 430074, China
| | - Xiangshui Miao
- Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, No.1037 Luoyu Road, Wuhan, 430074, China
| | - Wei D Lu
- Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA
| | - Simon M Sze
- Department of Electronics Engineering and Institute of Electronics, National Chiao Tung University, No.1001 University Road, Hsinchu, 30010, Taiwan
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Local Design Principles at Hippocampal Synapses Revealed by an Energy-Information Trade-Off. eNeuro 2020; 7:ENEURO.0521-19.2020. [PMID: 32847867 PMCID: PMC7540928 DOI: 10.1523/eneuro.0521-19.2020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 03/16/2020] [Accepted: 03/17/2020] [Indexed: 12/01/2022] Open
Abstract
Synapses across different brain regions display distinct structure-function relationships. We investigated the interplay of fundamental design constraints that shape the transmission properties of the excitatory CA3-CA1 pyramidal cell connection, a prototypic synapse for studying the mechanisms of learning in the mammalian hippocampus. This small synapse is characterized by probabilistic release of transmitter, which is markedly facilitated in response to naturally occurring trains of action potentials. Based on a physiologically motivated computational model of the rat CA3 presynaptic terminal, we show how unreliability and short-term dynamics of vesicular release work together to regulate the trade-off of information transfer versus energy use. We propose that individual CA3-CA1 synapses are designed to operate near the maximum possible capacity of information transmission in an efficient manner. Experimental measurements reveal a wide range of vesicular release probabilities at hippocampal synapses, which may be a necessary consequence of long-term plasticity and homeostatic mechanisms that manifest as presynaptic modifications of the release probability. We show that the timescales and magnitude of short-term plasticity (STP) render synaptic information transfer nearly independent of differences in release probability. Thus, individual synapses transmit optimally while maintaining a heterogeneous distribution of presynaptic strengths indicative of synaptically-encoded memory representations. Our results support the view that organizing principles that are evident on higher scales of neural organization percolate down to the design of an individual synapse.
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Rusakov DA, Savtchenko LP, Latham PE. Noisy Synaptic Conductance: Bug or a Feature? Trends Neurosci 2020; 43:363-372. [PMID: 32459990 PMCID: PMC7902755 DOI: 10.1016/j.tins.2020.03.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Revised: 03/10/2020] [Accepted: 03/23/2020] [Indexed: 12/31/2022]
Abstract
More often than not, action potentials fail to trigger neurotransmitter release. And even when neurotransmitter is released, the resulting change in synaptic conductance is highly variable. Given the energetic cost of generating and propagating action potentials, and the importance of information transmission across synapses, this seems both wasteful and inefficient. However, synaptic noise arising from variable transmission can improve, in certain restricted conditions, information transmission. Under broader conditions, it can improve information transmission per release, a quantity that is relevant given the energetic constraints on computing in the brain. Here we discuss the role, both positive and negative, synaptic noise plays in information transmission and computation in the brain.
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Affiliation(s)
- Dmitri A Rusakov
- Queen Square UCL Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.
| | - Leonid P Savtchenko
- Queen Square UCL Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.
| | - Peter E Latham
- Gatsby Computational Neuroscience Unit, University College London, 25 Howland Street, London, W1T 4JG, UK.
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Salmasi M, Stemmler M, Glasauer S, Loebel A. Synaptic Information Transmission in a Two-State Model of Short-Term Facilitation. ENTROPY 2019; 21:e21080756. [PMID: 33267470 PMCID: PMC7515285 DOI: 10.3390/e21080756] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 07/24/2019] [Accepted: 07/31/2019] [Indexed: 11/16/2022]
Abstract
Action potentials (spikes) can trigger the release of a neurotransmitter at chemical synapses between neurons. Such release is uncertain, as it occurs only with a certain probability. Moreover, synaptic release can occur independently of an action potential (asynchronous release) and depends on the history of synaptic activity. We focus here on short-term synaptic facilitation, in which a sequence of action potentials can temporarily increase the release probability of the synapse. In contrast to the phenomenon of short-term depression, quantifying the information transmission in facilitating synapses remains to be done. We find rigorous lower and upper bounds for the rate of information transmission in a model of synaptic facilitation. We treat the synapse as a two-state binary asymmetric channel, in which the arrival of an action potential shifts the synapse to a facilitated state, while in the absence of a spike, the synapse returns to its baseline state. The information bounds are functions of both the asynchronous and synchronous release parameters. If synchronous release facilitates more than asynchronous release, the mutual information rate increases. In contrast, short-term facilitation degrades information transmission when the synchronous release probability is intrinsically high. As synaptic release is energetically expensive, we exploit the information bounds to determine the energy-information trade-off in facilitating synapses. We show that unlike information rate, the energy-normalized information rate is robust with respect to variations in the strength of facilitation.
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Affiliation(s)
- Mehrdad Salmasi
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, 82152 Planegg-Martinsried, Germany
- Bernstein Center for Computational Neuroscience Munich, 82152 Planegg-Martinsried, Germany
- German Center for Vertigo and Balance Disorders, Ludwig-Maximilians-Universität, 81377 Munich, Germany
- Correspondence:
| | - Martin Stemmler
- Bernstein Center for Computational Neuroscience Munich, 82152 Planegg-Martinsried, Germany
- Department of Biology II, Ludwig-Maximilians-Universität München, 82152 Planegg-Martinsried, Germany
| | - Stefan Glasauer
- Bernstein Center for Computational Neuroscience Munich, 82152 Planegg-Martinsried, Germany
- German Center for Vertigo and Balance Disorders, Ludwig-Maximilians-Universität, 81377 Munich, Germany
- Computational Neuroscience, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany
| | - Alex Loebel
- Bernstein Center for Computational Neuroscience Munich, 82152 Planegg-Martinsried, Germany
- Department of Biology II, Ludwig-Maximilians-Universität München, 82152 Planegg-Martinsried, Germany
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