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Sagalajev B, Zhang T, Abdollahi N, Yousefpour N, Medlock L, Al-Basha D, Ribeiro-da-Silva A, Esteller R, Ratté S, Prescott SA. Absence of paresthesia during high-rate spinal cord stimulation reveals importance of synchrony for sensations evoked by electrical stimulation. Neuron 2024; 112:404-420.e6. [PMID: 37972595 DOI: 10.1016/j.neuron.2023.10.021] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/24/2023] [Accepted: 10/18/2023] [Indexed: 11/19/2023]
Abstract
Electrically activating mechanoreceptive afferents inhibits pain. However, paresthesia evoked by spinal cord stimulation (SCS) at 40-60 Hz becomes uncomfortable at high pulse amplitudes, limiting SCS "dosage." Kilohertz-frequency SCS produces analgesia without paresthesia and is thought, therefore, not to activate afferent axons. We show that paresthesia is absent not because axons do not spike but because they spike asynchronously. In a pain patient, selectively increasing SCS frequency abolished paresthesia and epidurally recorded evoked compound action potentials (ECAPs). Dependence of ECAP amplitude on SCS frequency was reproduced in pigs, rats, and computer simulations and is explained by overdrive desynchronization: spikes desychronize when axons are stimulated faster than their refractory period. Unlike synchronous spikes, asynchronous spikes fail to produce paresthesia because their transmission to somatosensory cortex is blocked by feedforward inhibition. Our results demonstrate how stimulation frequency impacts synchrony based on axon properties and how synchrony impacts sensation based on circuit properties.
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Affiliation(s)
- Boriss Sagalajev
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Tianhe Zhang
- Boston Scientific Neuromodulation, Valencia, CA 25155, USA
| | - Nooshin Abdollahi
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
| | - Noosha Yousefpour
- Department of Pharmacology and Therapeutics, McGill University, Montreal, QC H3G 1Y6, Canada
| | - Laura Medlock
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
| | - Dhekra Al-Basha
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Alfredo Ribeiro-da-Silva
- Department of Pharmacology and Therapeutics, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Anatomy and Cell Biology, McGill University, Montreal, QC H3A 0C7, Canada
| | | | - Stéphanie Ratté
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Steven A Prescott
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada; Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada.
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2
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Christova M, Sylwester V, Gallasch E, Fresnoza S. Reduced Cerebellar Brain Inhibition and Vibrotactile Perception in Response to Mechanical Hand Stimulation at Flutter Frequency. CEREBELLUM (LONDON, ENGLAND) 2024; 23:67-81. [PMID: 36502502 PMCID: PMC10864223 DOI: 10.1007/s12311-022-01502-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/30/2022] [Indexed: 12/14/2022]
Abstract
The cerebellum is traditionally considered a movement control structure because of its established afferent and efferent anatomical and functional connections with the motor cortex. In the last decade, studies also proposed its involvement in perception, particularly somatosensory acquisition and prediction of the sensory consequences of movement. However, compared to its role in motor control, the cerebellum's specific role or modulatory influence on other brain areas involved in sensory perception, specifically the primary sensorimotor cortex, is less clear. In the present study, we explored whether peripherally applied vibrotactile stimuli at flutter frequency affect functional cerebello-cortical connections. In 17 healthy volunteers, changes in cerebellar brain inhibition (CBI) and vibration perception threshold (VPT) were measured before and after a 20-min right hand mechanical stimulation at 25 Hz. 5 Hz mechanical stimulation of the right foot served as an active control condition. Performance in a Grooved Pegboard test (GPT) was also measured to assess stimulation's impact on motor performance. Hand stimulation caused a reduction in CBI (13.16%) and increased VPT but had no specific effect on GPT performance, while foot stimulation had no significant effect on all measures. The result added evidence to the functional connections between the cerebellum and primary motor cortex, as shown by CBI reduction. Meanwhile, the parallel increase in VPT indirectly suggests that the cerebellum influences the processing of vibrotactile stimulus through motor-sensory interactions.
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Affiliation(s)
- Monica Christova
- Otto Loewi Research Center, Physiology Section, Medical University of Graz, Neue Stiftingtalstraße 6/D05, 8010, Graz, Austria.
- Institute of Physiotherapy, University of Applied Sciences FH-Joanneum, Graz, Austria.
| | | | - Eugen Gallasch
- Otto Loewi Research Center, Physiology Section, Medical University of Graz, Neue Stiftingtalstraße 6/D05, 8010, Graz, Austria
| | - Shane Fresnoza
- Institute of Psychology, University of Graz, Graz, Austria
- BioTechMed, Graz, Austria
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3
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Leong F, Rahmani B, Psaltis D, Moser C, Ghezzi D. An actor-model framework for visual sensory encoding. Nat Commun 2024; 15:808. [PMID: 38280912 PMCID: PMC10821921 DOI: 10.1038/s41467-024-45105-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 01/15/2024] [Indexed: 01/29/2024] Open
Abstract
A fundamental challenge in neuroengineering is determining a proper artificial input to a sensory system that yields the desired perception. In neuroprosthetics, this process is known as artificial sensory encoding, and it holds a crucial role in prosthetic devices restoring sensory perception in individuals with disabilities. For example, in visual prostheses, one key aspect of artificial image encoding is to downsample images captured by a camera to a size matching the number of inputs and resolution of the prosthesis. Here, we show that downsampling an image using the inherent computation of the retinal network yields better performance compared to learning-free downsampling methods. We have validated a learning-based approach (actor-model framework) that exploits the signal transformation from photoreceptors to retinal ganglion cells measured in explanted mouse retinas. The actor-model framework generates downsampled images eliciting a neuronal response in-silico and ex-vivo with higher neuronal reliability than the one produced by a learning-free approach. During the learning process, the actor network learns to optimize contrast and the kernel's weights. This methodological approach might guide future artificial image encoding strategies for visual prostheses. Ultimately, this framework could be applicable for encoding strategies in other sensory prostheses such as cochlear or limb.
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Affiliation(s)
- Franklin Leong
- Medtronic Chair in Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Babak Rahmani
- Laboratory of Applied Photonics Devices, Institute of Electrical and Micro Engineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Microsoft Research, Cambridge, UK
| | - Demetri Psaltis
- Optics Laboratory, Institute of Electrical and Micro Engineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Christophe Moser
- Laboratory of Applied Photonics Devices, Institute of Electrical and Micro Engineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Diego Ghezzi
- Medtronic Chair in Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
- Ophthalmic and Neural Technologies Laboratory, Department of Ophthalmology, University of Lausanne, Hôpital ophtalmique Jules-Gonin, Fondation Asile des Aveugles, Lausanne, Switzerland.
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4
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Ordás CM, Alonso-Frech F. The neural basis of somatosensory temporal discrimination threshold as a paradigm for time processing in the sub-second range: An updated review. Neurosci Biobehav Rev 2024; 156:105486. [PMID: 38040074 DOI: 10.1016/j.neubiorev.2023.105486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 11/20/2023] [Accepted: 11/27/2023] [Indexed: 12/03/2023]
Abstract
BACKGROUND AND OBJECTIVE The temporal aspect of somesthesia is a feature of any somatosensory process and a pre-requisite for the elaboration of proper behavior. Time processing in the milliseconds range is crucial for most of behaviors in everyday life. The somatosensory temporal discrimination threshold (STDT) is the ability to perceive two successive stimuli as separate in time, and deals with time processing in this temporal range. Herein, we focus on the physiology of STDT, on a background of the anatomophysiology of somesthesia and the neurobiological substrates of timing. METHODS A review of the literature through PubMed & Cochrane databases until March 2023 was performed with inclusion and exclusion criteria following PRISMA recommendations. RESULTS 1151 abstracts were identified. 4 duplicate records were discarded before screening. 957 abstracts were excluded because of redundancy, less relevant content or not English-written. 4 were added after revision. Eventually, 194 articles were included. CONCLUSIONS STDT encoding relies on intracortical inhibitory S1 function and is modulated by the basal ganglia-thalamic-cortical interplay through circuits involving the nigrostriatal dopaminergic pathway and probably the superior colliculus.
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Affiliation(s)
- Carlos M Ordás
- Universidad Rey Juan Carlos, Móstoles, Madrid, Spain; Department of Neurology, Hospital Rey Juan Carlos, Móstoles, Madrid, Spain.
| | - Fernando Alonso-Frech
- Department of Neurology, Hospital Clínico San Carlos, Universidad Complutense de Madrid, Spain
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5
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Rezaei MR, Saadati Fard R, Popovic MR, Prescott SA, Lankarany M. Synchrony-Division Neural Multiplexing: An Encoding Model. ENTROPY (BASEL, SWITZERLAND) 2023; 25:e25040589. [PMID: 37190377 PMCID: PMC10137806 DOI: 10.3390/e25040589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/15/2023] [Accepted: 03/22/2023] [Indexed: 05/17/2023]
Abstract
Cortical neurons receive mixed information from the collective spiking activities of primary sensory neurons in response to a sensory stimulus. A recent study demonstrated an abrupt increase or decrease in stimulus intensity and the stimulus intensity itself can be respectively represented by the synchronous and asynchronous spikes of S1 neurons in rats. This evidence capitalized on the ability of an ensemble of homogeneous neurons to multiplex, a coding strategy that was referred to as synchrony-division multiplexing (SDM). Although neural multiplexing can be conceived by distinct functions of individual neurons in a heterogeneous neural ensemble, the extent to which nearly identical neurons in a homogeneous neural ensemble encode multiple features of a mixed stimulus remains unknown. Here, we present a computational framework to provide a system-level understanding on how an ensemble of homogeneous neurons enable SDM. First, we simulate SDM with an ensemble of homogeneous conductance-based model neurons receiving a mixed stimulus comprising slow and fast features. Using feature-estimation techniques, we show that both features of the stimulus can be inferred from the generated spikes. Second, we utilize linear nonlinear (LNL) cascade models and calculate temporal filters and static nonlinearities of differentially synchronized spikes. We demonstrate that these filters and nonlinearities are distinct for synchronous and asynchronous spikes. Finally, we develop an augmented LNL cascade model as an encoding model for the SDM by combining individual LNLs calculated for each type of spike. The augmented LNL model reveals that a homogeneous neural ensemble model can perform two different functions, namely, temporal- and rate-coding, simultaneously.
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Affiliation(s)
- Mohammad R Rezaei
- Krembil Research Institute, University Health Network (UHN), Toronto, ON M5T 0S8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network (UHN), Toronto, ON M5G 2A2, Canada
| | - Reza Saadati Fard
- Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA 01609, USA
| | - Milos R Popovic
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network (UHN), Toronto, ON M5G 2A2, Canada
| | - Steven A Prescott
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
- Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada
- Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Milad Lankarany
- Krembil Research Institute, University Health Network (UHN), Toronto, ON M5T 0S8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network (UHN), Toronto, ON M5G 2A2, Canada
- Department of Physiology, University of Toronto, Toronto, ON M5S 1A8, Canada
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6
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Physiological noise facilitates multiplexed coding of vibrotactile-like signals in somatosensory cortex. Proc Natl Acad Sci U S A 2022; 119:e2118163119. [PMID: 36067307 PMCID: PMC9478643 DOI: 10.1073/pnas.2118163119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Neurons can use different aspects of their spiking to simultaneously represent (multiplex) different features of a stimulus. For example, some pyramidal neurons in primary somatosensory cortex (S1) use the rate and timing of their spikes to, respectively, encode the intensity and frequency of vibrotactile stimuli. Doing so has several requirements. Because they fire at low rates, pyramidal neurons cannot entrain 1:1 with high-frequency (100 to 600 Hz) inputs and, instead, must skip (i.e., not respond to) some stimulus cycles. The proportion of skipped cycles must vary inversely with stimulus intensity for firing rate to encode stimulus intensity. Spikes must phase-lock to the stimulus for spike times (intervals) to encode stimulus frequency, but, in addition, skipping must occur irregularly to avoid aliasing. Using simulations and in vitro experiments in which mouse S1 pyramidal neurons were stimulated with inputs emulating those induced by vibrotactile stimuli, we show that fewer cycles are skipped as stimulus intensity increases, as required for rate coding, and that intrinsic or synaptic noise can induce irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because noise can modulate the reliability without disrupting the precision of spikes evoked by small-amplitude, fast-onset signals. Specifically, in the fluctuation-driven regime associated with sparse spiking, rate and temporal coding are both paradoxically improved by the strong synaptic noise characteristic of the intact cortex. Our results demonstrate that multiplexed coding by S1 pyramidal neurons is not only feasible under in vivo conditions, but that background synaptic noise is actually beneficial.
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7
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Lieber JD, Bensmaia SJ. The neural basis of tactile texture perception. Curr Opin Neurobiol 2022; 76:102621. [PMID: 36027737 DOI: 10.1016/j.conb.2022.102621] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 06/23/2022] [Accepted: 07/05/2022] [Indexed: 12/15/2022]
Abstract
Running our fingers across a textured surface gives rise to two types of skin deformations, each transduced by different tactile nerve fibers. Coarse features produce large-scale skin deformations whose spatial configuration is reflected in the spatial pattern of activation of some tactile fibers. Scanning a finely textured surface elicits vibrations in the skin, which in turn evoked temporally patterned responses in other fibers. These two neural codes-spatial and temporal-drive a spectrum of neural response properties in somatosensory cortex: At one extreme, neurons are sensitive to spatial patterns and encode coarse features; at the other extreme, neurons are sensitive to vibrations and encode fine features. While the texture responses of nerve fibers are dependent on scanning speed, those of cortical neurons are less so, giving rise to a speed invariant texture percept. Neurons in high-level somatosensory cortices combine information about texture with information about task variables.
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Affiliation(s)
- Justin D Lieber
- Center for Neural Science, New York University, New York, NY, USA. https://twitter.com/jdlieber
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA; Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA; Neuroscience Institute, University of Chicago, Chicago, IL, USA.
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8
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van Ackooij M, Paul JM, van der Zwaag W, van der Stoep N, Harvey BM. Auditory timing-tuned neural responses in the human auditory cortices. Neuroimage 2022; 258:119366. [PMID: 35690255 DOI: 10.1016/j.neuroimage.2022.119366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 05/25/2022] [Accepted: 06/08/2022] [Indexed: 11/27/2022] Open
Abstract
Perception of sub-second auditory event timing supports multisensory integration, and speech and music perception and production. Neural populations tuned for the timing (duration and rate) of visual events were recently described in several human extrastriate visual areas. Here we ask whether the brain also contains neural populations tuned for auditory event timing, and whether these are shared with visual timing. Using 7T fMRI, we measured responses to white noise bursts of changing duration and rate. We analyzed these responses using neural response models describing different parametric relationships between event timing and neural response amplitude. This revealed auditory timing-tuned responses in the primary auditory cortex, and auditory association areas of the belt, parabelt and premotor cortex. While these areas also showed tonotopic tuning for auditory pitch, pitch and timing preferences were not consistently correlated. Auditory timing-tuned response functions differed between these areas, though without clear hierarchical integration of responses. The similarity of auditory and visual timing tuned responses, together with the lack of overlap between the areas showing these responses for each modality, suggests modality-specific responses to event timing are computed similarly but from different sensory inputs, and then transformed differently to suit the needs of each modality.
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Affiliation(s)
- Martijn van Ackooij
- Experimental Psychology, Helmholtz Institute, Utrecht University, Heidelberglaan 1, Utrecht 3584 CS, the Netherlands
| | - Jacob M Paul
- Experimental Psychology, Helmholtz Institute, Utrecht University, Heidelberglaan 1, Utrecht 3584 CS, the Netherlands; Melbourne School of Psychological Sciences, University of Melbourne, Redmond Barry Building, Parkville 3010, Victoria, Australia
| | | | - Nathan van der Stoep
- Experimental Psychology, Helmholtz Institute, Utrecht University, Heidelberglaan 1, Utrecht 3584 CS, the Netherlands
| | - Ben M Harvey
- Experimental Psychology, Helmholtz Institute, Utrecht University, Heidelberglaan 1, Utrecht 3584 CS, the Netherlands.
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9
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Wesselink DB, Sanders ZB, Edmondson LR, Dempsey-Jones H, Kieliba P, Kikkert S, Themistocleous AC, Emir U, Diedrichsen J, Saal HP, Makin TR. Malleability of the cortical hand map following a finger nerve block. SCIENCE ADVANCES 2022; 8:eabk2393. [PMID: 35452294 PMCID: PMC9032959 DOI: 10.1126/sciadv.abk2393] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Electrophysiological studies in monkeys show that finger amputation triggers local remapping within the deprived primary somatosensory cortex (S1). Human neuroimaging research, however, shows persistent S1 representation of the missing hand's fingers, even decades after amputation. Here, we explore whether this apparent contradiction stems from underestimating the distributed peripheral and central representation of fingers in the hand map. Using pharmacological single-finger nerve block and 7-tesla neuroimaging, we first replicated previous accounts (electrophysiological and other) of local S1 remapping. Local blocking also triggered activity changes to nonblocked fingers across the entire hand area. Using methods exploiting interfinger representational overlap, however, we also show that the blocked finger representation remained persistent despite input loss. Computational modeling suggests that both local stability and global reorganization are driven by distributed processing underlying the topographic map, combined with homeostatic mechanisms. Our findings reveal complex interfinger representational features that play a key role in brain (re)organization, beyond (re)mapping.
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Affiliation(s)
- Daan B. Wesselink
- Institute of Cognitive Neuroscience, University College London, London, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Corresponding author.
| | - Zeena-Britt Sanders
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Laura R. Edmondson
- Active Touch Laboratory, Department of Psychology, The University of Sheffield, Sheffield, UK
| | - Harriet Dempsey-Jones
- Institute of Cognitive Neuroscience, University College London, London, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- School of Psychology, University of Queensland, Brisbane, Australia
| | - Paulina Kieliba
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Sanne Kikkert
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Andreas C. Themistocleous
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Brain Function Research Group, University of the Witwatersrand, Johannesburg, South Africa
| | - Uzay Emir
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Jörn Diedrichsen
- Brain and Mind Institute, University of Western Ontario, London, Canada
| | - Hannes P. Saal
- Active Touch Laboratory, Department of Psychology, The University of Sheffield, Sheffield, UK
| | - Tamar R. Makin
- Institute of Cognitive Neuroscience, University College London, London, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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10
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Texture is encoded in precise temporal spiking patterns in primate somatosensory cortex. Nat Commun 2022; 13:1311. [PMID: 35288570 PMCID: PMC8921276 DOI: 10.1038/s41467-022-28873-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 01/31/2022] [Indexed: 11/24/2022] Open
Abstract
Humans are exquisitely sensitive to the microstructure and material properties of surfaces. In the peripheral nerves, texture information is conveyed via two mechanisms: coarse textural features are encoded in spatial patterns of activation that reflect their spatial layout, and fine features are encoded in highly repeatable, texture-specific temporal spiking patterns evoked as the skin moves across the surface. Here, we examined whether this temporal code is preserved in the responses of neurons in somatosensory cortex. We scanned a diverse set of everyday textures across the fingertip of awake macaques while recording the responses evoked in individual cortical neurons. We found that temporal spiking patterns are highly repeatable across multiple presentations of the same texture, with millisecond precision. As a result, texture identity can be reliably decoded from the temporal patterns themselves, even after information carried in the spike rates is eliminated. However, the combination of rate and timing is more informative than either code in isolation. The temporal precision of the texture response is heterogenous across cortical neurons and depends on the submodality composition of their input and on their location along the somatosensory neuraxis. Furthermore, temporal spiking patterns in cortex dilate and contract with decreases and increases in scanning speed, respectively, and this systematic relationship between speed and patterning may contribute to the observed perceptual invariance to speed. Finally, we find that the quality of a texture percept can be better predicted when these temporal patterns are taken into consideration. We conclude that high-precision spike timing complements rate-based signals to encode texture in somatosensory cortex. Neuroscientists seek to understand how neuronal signals carry information and drive perception. Here, the authors show that millisecond-level spike timing in somatosensory cortex is informative about texture and shapes the evoked sensory experience.
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11
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Graczyk EL, Christie BP, He Q, Tyler DJ, Bensmaia SJ. Frequency Shapes the Quality of Tactile Percepts Evoked through Electrical Stimulation of the Nerves. J Neurosci 2022; 42:2052-2064. [PMID: 35074865 PMCID: PMC8916769 DOI: 10.1523/jneurosci.1494-21.2021] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 09/29/2021] [Accepted: 11/22/2021] [Indexed: 11/21/2022] Open
Abstract
Electrical stimulation of the peripheral nerves of human participants provides a unique opportunity to study the neural determinants of perceptual quality using a causal manipulation. A major challenge in the study of neural coding of touch has been to isolate the role of spike timing-at the scale of milliseconds or tens of milliseconds-in shaping the sensory experience. In the present study, we address this question by systematically varying the pulse frequency (PF) of electrical stimulation pulse trains delivered to the peripheral nerves of seven participants with upper and lower extremity limb loss via chronically implanted neural interfaces. We find that increases in PF lead to systematic increases in perceived frequency, up to ∼50 Hz, at which point further changes in PF have little to no impact on sensory quality. Above this transition frequency, ratings of perceived frequency level off, the ability to discriminate changes in PF is abolished, and verbal descriptors selected to characterize the sensation change abruptly. We conclude that sensation quality is shaped by temporal patterns of neural activation, even if these patterns are imposed on a fixed neural population, but this temporal patterning can only be resolved up to ∼50 Hz. These findings highlight the importance of spike timing in shaping the quality of a sensation and will contribute to the development of encoding strategies for conveying touch feedback through bionic hands and feet.SIGNIFICANCE STATEMENT A major challenge in the study of neural coding of touch has been to understand how temporal patterns in neuronal responses shape the sensory experience. We address this question by varying the pulse frequency (PF) of electrical pulse trains delivered through implanted nerve interfaces in seven amputees. We concomitantly vary pulse width to separate the effect of changing PF on sensory quality from its effect on perceived magnitude. We find that increases in PF lead to increases in perceived frequency, a qualitative dimension, up to ∼50 Hz, beyond which changes in PF have little impact on quality. We conclude that temporal patterning in the neuronal response can shape quality and discuss the implications for restoring touch via neural interfaces.
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Affiliation(s)
- Emily L Graczyk
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio 44106
| | - Breanne P Christie
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106
- Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland 20723
| | - Qinpu He
- Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois 60637
| | - Dustin J Tyler
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio 44106
| | - Sliman J Bensmaia
- Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois 60637
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois 60637
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12
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Metzger A, Toscani M. Unsupervised learning of haptic material properties. eLife 2022; 11:64876. [PMID: 35195520 PMCID: PMC8865843 DOI: 10.7554/elife.64876] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 12/09/2021] [Indexed: 11/18/2022] Open
Abstract
When touching the surface of an object, its spatial structure translates into a vibration on the skin. The perceptual system evolved to translate this pattern into a representation that allows to distinguish between different materials. Here, we show that perceptual haptic representation of materials emerges from efficient encoding of vibratory patterns elicited by the interaction with materials. We trained a deep neural network with unsupervised learning (Autoencoder) to reconstruct vibratory patterns elicited by human haptic exploration of different materials. The learned compressed representation (i.e., latent space) allows for classification of material categories (i.e., plastic, stone, wood, fabric, leather/wool, paper, and metal). More importantly, classification performance is higher with perceptual category labels as compared to ground truth ones, and distances between categories in the latent space resemble perceptual distances, suggesting a similar coding. Crucially, the classification performance and the similarity between the perceptual and the latent space decrease with decreasing compression level. We could further show that the temporal tuning of the emergent latent dimensions is similar to properties of human tactile receptors.
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Affiliation(s)
- Anna Metzger
- Department of Psychology, Bournemouth University, Bournemouth, United Kingdom.,Department of Psychology, Justus-Liebig University, Giessen, Germany
| | - Matteo Toscani
- Department of Psychology, Bournemouth University, Bournemouth, United Kingdom.,Department of Psychology, Justus-Liebig University, Giessen, Germany
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13
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Ng KKW, Tee X, Vickery RM, Birznieks I. The Relationship Between Tactile Intensity Perception and Afferent Spike Count is Moderated by a Function of Frequency. IEEE TRANSACTIONS ON HAPTICS 2022; 15:14-19. [PMID: 34990370 DOI: 10.1109/toh.2022.3140877] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
It has been suggested that tactile intensity perception can be explained by a linear function of spike rate weighted by afferent type. Other than relying on mathematical models, verifying this experimentally is difficult due to the frequency tuning of different afferent types and changes in population recruitment patterns with vibrotactile frequency. To overcome these complexities, we used pulsatile mechanical stimuli which activate the same afferent population regardless of the repetition rate (frequency), generating one action potential per pulse. We used trains of different frequencies (20-200 Hz) to investigate perceived intensity. Subjects' magnitude ratings increased with pulse rate up to ∼100 Hz and plateaued beyond this frequency. This was true regardless of pulse amplitude, from small pulses that exclusively activated Pacinian (PC) afferents, to pulses large enough to activate other afferents including slowly adapting. Electrical stimulation, which activates afferents indiscriminately, plateaued at a similar frequency, although not in all subjects. As the plateauing did not depend on indentation magnitude and hence on afferent weights, we propose that the contribution of spike count to intensity perception is weighted by a function of frequency. This may explain why fine textures evoking high frequency vibrations of a small magnitude do not feel disproportionally intense.
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14
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Suresh AK, Greenspon CM, He Q, Rosenow JM, Miller LE, Bensmaia SJ. Sensory computations in the cuneate nucleus of macaques. Proc Natl Acad Sci U S A 2021; 118:e2115772118. [PMID: 34853173 PMCID: PMC8670430 DOI: 10.1073/pnas.2115772118] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Accepted: 10/25/2021] [Indexed: 12/15/2022] Open
Abstract
Tactile nerve fibers fall into a few classes that can be readily distinguished based on their spatiotemporal response properties. Because nerve fibers reflect local skin deformations, they individually carry ambiguous signals about object features. In contrast, cortical neurons exhibit heterogeneous response properties that reflect computations applied to convergent input from multiple classes of afferents, which confer to them a selectivity for behaviorally relevant features of objects. The conventional view is that these complex response properties arise within the cortex itself, implying that sensory signals are not processed to any significant extent in the two intervening structures-the cuneate nucleus (CN) and the thalamus. To test this hypothesis, we recorded the responses evoked in the CN to a battery of stimuli that have been extensively used to characterize tactile coding in both the periphery and cortex, including skin indentations, vibrations, random dot patterns, and scanned edges. We found that CN responses are more similar to their cortical counterparts than they are to their inputs: CN neurons receive input from multiple classes of nerve fibers, they have spatially complex receptive fields, and they exhibit selectivity for object features. Contrary to consensus, then, the CN plays a key role in processing tactile information.
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Affiliation(s)
- Aneesha K Suresh
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL 60637
| | - Charles M Greenspon
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL 60637
| | - Qinpu He
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL 60637
| | - Joshua M Rosenow
- Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611
| | - Lee E Miller
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611
- Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL 60208
- Shirley Ryan AbilityLab, Chicago, IL 60611
| | - Sliman J Bensmaia
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL 60637;
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL 60637
- Grossman Institute for Neuroscience, Quantitative Biology, and Human Behavior, University of Chicago, Chicago, IL 60637
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15
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Sobinov AR, Bensmaia SJ. The neural mechanisms of manual dexterity. Nat Rev Neurosci 2021; 22:741-757. [PMID: 34711956 DOI: 10.1038/s41583-021-00528-7] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2021] [Indexed: 01/22/2023]
Abstract
The hand endows us with unparalleled precision and versatility in our interactions with objects, from mundane activities such as grasping to extraordinary ones such as virtuoso pianism. The complex anatomy of the human hand combined with expansive and specialized neuronal control circuits allows a wide range of precise manual behaviours. To support these behaviours, an exquisite sensory apparatus, spanning the modalities of touch and proprioception, conveys detailed and timely information about our interactions with objects and about the objects themselves. The study of manual dexterity provides a unique lens into the sensorimotor mechanisms that endow the nervous system with the ability to flexibly generate complex behaviour.
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Affiliation(s)
- Anton R Sobinov
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA.,Neuroscience Institute, University of Chicago, Chicago, IL, USA
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA. .,Neuroscience Institute, University of Chicago, Chicago, IL, USA. .,Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA.
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16
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Schellekens W, Thio M, Badde S, Winawer J, Ramsey N, Petridou N. A touch of hierarchy: population receptive fields reveal fingertip integration in Brodmann areas in human primary somatosensory cortex. Brain Struct Funct 2021; 226:2099-2112. [PMID: 34091731 PMCID: PMC8354965 DOI: 10.1007/s00429-021-02309-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 05/26/2021] [Indexed: 12/03/2022]
Abstract
Several neuroimaging studies have shown the somatotopy of body part representations in primary somatosensory cortex (S1), but the functional hierarchy of distinct subregions in human S1 has not been adequately addressed. The current study investigates the functional hierarchy of cyto-architectonically distinct regions, Brodmann areas BA3, BA1, and BA2, in human S1. During functional MRI experiments, we presented participants with vibrotactile stimulation of the fingertips at three different vibration frequencies. Using population Receptive Field (pRF) modeling of the fMRI BOLD activity, we identified the hand region in S1 and the somatotopy of the fingertips. For each voxel, the pRF center indicates the finger that most effectively drives the BOLD signal, and the pRF size measures the spatial somatic pooling of fingertips. We find a systematic relationship of pRF sizes from lower-order areas to higher-order areas. Specifically, we found that pRF sizes are smallest in BA3, increase slightly towards BA1, and are largest in BA2, paralleling the increase in visual receptive field size as one ascends the visual hierarchy. Additionally, we find that the time-to-peak of the hemodynamic response in BA3 is roughly 0.5 s earlier compared to BA1 and BA2, further supporting the notion of a functional hierarchy of subregions in S1. These results were obtained during stimulation of different mechanoreceptors, suggesting that different afferent fibers leading up to S1 feed into the same cortical hierarchy.
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Affiliation(s)
- W Schellekens
- Department of Radiology, Center for Image Sciences, UMC Utrecht, Q101.132, P.O.Box 85500, 3508 GA, Utrecht, The Netherlands.
| | - M Thio
- Department of Radiology, Center for Image Sciences, UMC Utrecht, Q101.132, P.O.Box 85500, 3508 GA, Utrecht, The Netherlands
| | - S Badde
- Department of Psychology and Center of Neural Science, NYU, New York, USA
| | - J Winawer
- Department of Psychology and Center of Neural Science, NYU, New York, USA
| | - N Ramsey
- Department of Neurology and Neurosurgery, UMC Utrecht, Utrecht, The Netherlands
| | - N Petridou
- Department of Radiology, Center for Image Sciences, UMC Utrecht, Q101.132, P.O.Box 85500, 3508 GA, Utrecht, The Netherlands
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17
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Computational approach to understand temporal and spatial tactile transmission processes from mechanical stimuli of the index fingertip to the primary somatosensory cortex. J Neurosci Methods 2021; 359:109215. [PMID: 33957157 DOI: 10.1016/j.jneumeth.2021.109215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 04/15/2021] [Accepted: 04/29/2021] [Indexed: 11/23/2022]
Abstract
Mechanisms of information transmission using tactile sense are one of major concerns in producing simulated experience in virtual or augmented reality as well as in compensating elderly or impaired people with diminished tactile sensory function. However, important mechanism of the difference of peak latency in the primary somatosensory cortex (SI) between electrical and mechanical stimulations of finger skin is not fully understood. We propose a computational approach to fuse a computational model to simulate temporal and spatial transmission processes from mechanical stimuli to the SI and experimental method using a magnetoencephalograph (MEG). In our model, a tactile model that combined a three-dimensional mechanical model of fingertip skin and a neurophysiological model of a slowly adapting type 1 (SA1) mechanoreceptor was integrated with a somatosensory evoked field (SEF) response model. Electrical and mechanical stimulations were applied to the same locations of the right or left index fingertips of three subjects using a MEG. By identifying parameters of the SEF response model using the electrical stimulation test data, predicted first peak latency due to a mechanical stimulus was identical to its average value obtained from the mechanical stimulation test data, while the spatial map predicted at the multiple SA1 receptors qualitatively corresponded to the MEG image map in the timings of peak latency. This suggests that mechanical change in the skin and neurophysiological responses generate the difference of peak latency in SI between electrical and mechanical stimulations. The computational approach has the potential for detailed investigation of mechanisms of tactile information transmission.
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18
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Iyer LR, Chua Y, Li H. Is Neuromorphic MNIST Neuromorphic? Analyzing the Discriminative Power of Neuromorphic Datasets in the Time Domain. Front Neurosci 2021; 15:608567. [PMID: 33841072 PMCID: PMC8027306 DOI: 10.3389/fnins.2021.608567] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 03/01/2021] [Indexed: 11/26/2022] Open
Abstract
A major characteristic of spiking neural networks (SNNs) over conventional artificial neural networks (ANNs) is their ability to spike, enabling them to use spike timing for coding and efficient computing. In this paper, we assess if neuromorphic datasets recorded from static images are able to evaluate the ability of SNNs to use spike timings in their calculations. We have analyzed N-MNIST, N-Caltech101 and DvsGesture along these lines, but focus our study on N-MNIST. First we evaluate if additional information is encoded in the time domain in a neuromorphic dataset. We show that an ANN trained with backpropagation on frame-based versions of N-MNIST and N-Caltech101 images achieve 99.23 and 78.01% accuracy. These are comparable to the state of the art-showing that an algorithm that purely works on spatial data can classify these datasets. Second we compare N-MNIST and DvsGesture on two STDP algorithms, RD-STDP, that can classify only spatial data, and STDP-tempotron that classifies spatiotemporal data. We demonstrate that RD-STDP performs very well on N-MNIST, while STDP-tempotron performs better on DvsGesture. Since DvsGesture has a temporal dimension, it requires STDP-tempotron, while N-MNIST can be adequately classified by an algorithm that works on spatial data alone. This shows that precise spike timings are not important in N-MNIST. N-MNIST does not, therefore, highlight the ability of SNNs to classify temporal data. The conclusions of this paper open the question-what dataset can evaluate SNN ability to classify temporal data?
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Affiliation(s)
- Laxmi R. Iyer
- Neuromorphic Computing, Institute of Infocomms Research, A*Star, Singapore, Singapore
| | - Yansong Chua
- Neuromorphic Computing, Institute of Infocomms Research, A*Star, Singapore, Singapore
| | - Haizhou Li
- Neuromorphic Computing, Institute of Infocomms Research, A*Star, Singapore, Singapore
- Huawei Technologies Co., Ltd., Shenzhen, China
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19
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Kawashima Y, Li R, Chen SCY, Vickery RM, Morley JW, Tsuchiya N. Steady state evoked potential (SSEP) responses in the primary and secondary somatosensory cortices of anesthetized cats: Nonlinearity characterized by harmonic and intermodulation frequencies. PLoS One 2021; 16:e0240147. [PMID: 33690648 PMCID: PMC7943005 DOI: 10.1371/journal.pone.0240147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 02/10/2021] [Indexed: 11/23/2022] Open
Abstract
When presented with an oscillatory sensory input at a particular frequency, F [Hz], neural systems respond with the corresponding frequency, f [Hz], and its multiples. When the input includes two frequencies (F1 and F2) and they are nonlinearly integrated in the system, responses at intermodulation frequencies (i.e., n1*f1+n2*f2 [Hz], where n1 and n2 are non-zero integers) emerge. Utilizing these properties, the steady state evoked potential (SSEP) paradigm allows us to characterize linear and nonlinear neural computation performed in cortical neurocircuitry. Here, we analyzed the steady state evoked local field potentials (LFPs) recorded from the primary (S1) and secondary (S2) somatosensory cortex of anesthetized cats (maintained with alfaxalone) while we presented slow (F1 = 23Hz) and fast (F2 = 200Hz) somatosensory vibration to the contralateral paw pads and digits. Over 9 experimental sessions, we recorded LFPs from N = 1620 and N = 1008 bipolar-referenced sites in S1 and S2 using electrode arrays. Power spectral analyses revealed strong responses at 1) the fundamental (f1, f2), 2) its harmonic, 3) the intermodulation frequencies, and 4) broadband frequencies (50-150Hz). To compare the computational architecture in S1 and S2, we employed simple computational modeling. Our modeling results necessitate nonlinear computation to explain SSEP in S2 more than S1. Combined with our current analysis of LFPs, our paradigm offers a rare opportunity to constrain the computational architecture of hierarchical organization of S1 and S2 and to reveal how a large-scale SSEP can emerge from local neural population activities.
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Affiliation(s)
- Yota Kawashima
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
| | - Rannee Li
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
| | - Spencer Chin-Yu Chen
- Department of Neurosurgery, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, United States of America
| | | | - John W. Morley
- School of Medicine, Western Sydney University, Penrith, New South Wales, Australia
| | - Naotsugu Tsuchiya
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Suita, Osaka, Japan
- Advanced Telecommunications Research Computational Neuroscience Laboratories, Soraku-gun, Kyoto, Japan
- * E-mail:
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20
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Cataldo A, Hagura N, Hyder Y, Haggard P. Touch inhibits touch: sanshool-induced paradoxical tingling reveals perceptual interaction between somatosensory submodalities. Proc Biol Sci 2021; 288:20202914. [PMID: 33499781 PMCID: PMC7893281 DOI: 10.1098/rspb.2020.2914] [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] [Indexed: 11/21/2022] Open
Abstract
Human perception of touch is mediated by inputs from multiple channels. Classical theories postulate independent contributions of each channel to each tactile feature, with little or no interaction between channels. In contrast to this view, we show that inputs from two sub-modalities of mechanical input channels interact to determine tactile perception. The flutter-range vibration channel was activated anomalously using hydroxy-α-sanshool, a bioactive compound of Szechuan pepper, which chemically induces vibration-like tingling sensations. We tested whether this tingling sensation on the lips was modulated by sustained mechanical pressure. Across four experiments, we show that sustained touch inhibits sanshool tingling sensations in a location-specific, pressure-level and time-dependent manner. Additional experiments ruled out the mediation of this interaction by nociceptive or affective (C-tactile) channels. These results reveal novel inhibitory influence from steady pressure onto flutter-range tactile perceptual channels, consistent with early-stage interactions between mechanoreceptor inputs within the somatosensory pathway.
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Affiliation(s)
- Antonio Cataldo
- Institute of Cognitive Neuroscience, University College London, Alexandra House 17 Queen Square, London WC1N 3AZ, UK.,Institute of Philosophy, School of Advanced Study - University of London, Senate House, Malet Street, London WC1E 7HU, UK.,Cognition, Values and Behaviour, Ludwig Maximilian University, Gabelsbergerstraße 62, 80333 München, Germany
| | - Nobuhiro Hagura
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, 1-4 Yamadaoka, Suita City, Osaka 565-0871, Japan.,Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
| | - Yousef Hyder
- Institute of Cognitive Neuroscience, University College London, Alexandra House 17 Queen Square, London WC1N 3AZ, UK.,Center for Information and Neural Networks, National Institute of Information and Communications Technology, 1-4 Yamadaoka, Suita City, Osaka 565-0871, Japan
| | - Patrick Haggard
- Institute of Cognitive Neuroscience, University College London, Alexandra House 17 Queen Square, London WC1N 3AZ, UK.,Institute of Philosophy, School of Advanced Study - University of London, Senate House, Malet Street, London WC1E 7HU, UK
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21
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Parvizi-Fard A, Amiri M, Kumar D, Iskarous MM, Thakor NV. A functional spiking neuronal network for tactile sensing pathway to process edge orientation. Sci Rep 2021; 11:1320. [PMID: 33446742 PMCID: PMC7809061 DOI: 10.1038/s41598-020-80132-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 12/17/2020] [Indexed: 01/24/2023] Open
Abstract
To obtain deeper insights into the tactile processing pathway from a population-level point of view, we have modeled three stages of the tactile pathway from the periphery to the cortex in response to indentation and scanned edge stimuli at different orientations. Three stages in the tactile pathway are, (1) the first-order neurons which innervate the cutaneous mechanoreceptors, (2) the cuneate nucleus in the midbrain and (3) the cortical neurons of the somatosensory area. In the proposed network, the first layer mimics the spiking patterns generated by the primary afferents. These afferents have complex skin receptive fields. In the second layer, the role of lateral inhibition on projection neurons in the cuneate nucleus is investigated. The third layer acts as a biomimetic decoder consisting of pyramidal and cortical interneurons that correspond to heterogeneous receptive fields with excitatory and inhibitory sub-regions on the skin. In this way, the activity of pyramidal neurons is tuned to the specific edge orientations. By modifying afferent receptive field size, it is observed that the larger receptive fields convey more information about edge orientation in the first spikes of cortical neurons when edge orientation stimuli move across the patch of skin. In addition, the proposed spiking neural model can detect edge orientation at any location on the simulated mechanoreceptor grid with high accuracy. The results of this research advance our knowledge about tactile information processing and can be employed in prosthetic and bio-robotic applications.
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Affiliation(s)
- Adel Parvizi-Fard
- Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mahmood Amiri
- Medical Technology Research Center, Institute of Health Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran.
| | - Deepesh Kumar
- SINAPSE Laboratory, National University of Singapore, Singapore, Singapore
| | - Mark M Iskarous
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nitish V Thakor
- SINAPSE Laboratory, National University of Singapore, Singapore, Singapore.
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
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22
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Chivukula S, Zhang CY, Aflalo T, Jafari M, Pejsa K, Pouratian N, Andersen RA. Neural encoding of actual and imagined touch within human posterior parietal cortex. eLife 2021; 10:61646. [PMID: 33647233 PMCID: PMC7924956 DOI: 10.7554/elife.61646] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 02/08/2021] [Indexed: 12/27/2022] Open
Abstract
In the human posterior parietal cortex (PPC), single units encode high-dimensional information with partially mixed representations that enable small populations of neurons to encode many variables relevant to movement planning, execution, cognition, and perception. Here, we test whether a PPC neuronal population previously demonstrated to encode visual and motor information is similarly engaged in the somatosensory domain. We recorded neurons within the PPC of a human clinical trial participant during actual touch presentation and during a tactile imagery task. Neurons encoded actual touch at short latency with bilateral receptive fields, organized by body part, and covered all tested regions. The tactile imagery task evoked body part-specific responses that shared a neural substrate with actual touch. Our results are the first neuron-level evidence of touch encoding in human PPC and its cognitive engagement during a tactile imagery task, which may reflect semantic processing, attention, sensory anticipation, or imagined touch.
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Affiliation(s)
- Srinivas Chivukula
- Department of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of TechnologyPasadenaUnited States,Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Carey Y Zhang
- Department of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of TechnologyPasadenaUnited States
| | - Tyson Aflalo
- Department of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of TechnologyPasadenaUnited States
| | - Matiar Jafari
- Department of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of TechnologyPasadenaUnited States,Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Kelsie Pejsa
- Department of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of TechnologyPasadenaUnited States
| | - Nader Pouratian
- Department of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of TechnologyPasadenaUnited States,Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Richard A Andersen
- Department of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of TechnologyPasadenaUnited States
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23
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Kim YR, Kim CE, Yoon H, Kim SK, Kim SJ. Multiplexed Processing of Vibrotactile Information in the Mouse Primary Somatosensory Cortex. Exp Neurobiol 2020; 29:425-432. [PMID: 33372168 PMCID: PMC7788311 DOI: 10.5607/en20041] [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: 08/31/2020] [Revised: 10/24/2020] [Accepted: 10/26/2020] [Indexed: 11/25/2022] Open
Abstract
The primary somatosensory (S1) cortex plays a key role in distinguishing different sensory stimuli. Vibrotactile touch information is conveyed from the periphery to the S1 cortex through three major classes of mechanoreceptors: slowly adapting type 1 (SA1), rapidly adapting (RA), and Pacinian (PC) afferents. It has been a long-standing question whether specific populations in the S1 cortex preserve the peripheral segregation by the afferent submodalities. Here, we investigated whether S1 neurons exhibit specific responses to two distinct vibrotactile stimuli, which excite different types of mechanoreceptors (e.g., SA1 and PC afferents). Using in vivo two-photon microscopy and genetically encoded calcium indicator, GCaMP6s, we recorded calcium activities of S1 L2/3 neurons. At the same time, static (<1 Hz) and dynamic (150 Hz) vibrotactile stimuli, which are known to excite SA1 and PC, respectively, were pseudorandomly applied to the right hind paw in lightly anesthetized mice. We found that most active S1 neurons responded to both static and dynamic stimuli, but more than half of them showed preferred responses to either type of stimulus. Only a small fraction of the active neurons exhibited specific responses to either static or dynamic stimuli. However, the S1 population activity patterns by the two stimuli were markedly distinguished. These results indicate that the vibrotactile inputs driven by excitation of distinct submodalities are converged on the single cells of the S1 cortex, but are well discriminated by population activity patterns composed of neurons that have a weighted preference for each type of stimulus.
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Affiliation(s)
- Yoo Rim Kim
- Department of Physiology, Seoul National University College of Medicine, Seoul 08826, Korea.,Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 08826, Korea.,Neuroscience Research Institute, Seoul National University College of Medicine, Seoul 08826, Korea
| | - Chang-Eop Kim
- Department of Physiology, Seoul National University College of Medicine, Seoul 08826, Korea.,Department of Physiology, College of Korean Medicine, Gachon University, Seongnam 13120, Korea
| | - Heera Yoon
- Department of Science in Korean Medicine, Graduate School, Kyung Hee University, Seoul 02447, Korea
| | - Sun Kwang Kim
- Department of Science in Korean Medicine, Graduate School, Kyung Hee University, Seoul 02447, Korea.,Department of Physiology, College of Korean Medicine, Kyung Hee University, Seoul 02447, Korea
| | - Sang Jeong Kim
- Department of Physiology, Seoul National University College of Medicine, Seoul 08826, Korea.,Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 08826, Korea.,Neuroscience Research Institute, Seoul National University College of Medicine, Seoul 08826, Korea
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24
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Callier T, Suresh AK, Bensmaia SJ. Neural Coding of Contact Events in Somatosensory Cortex. Cereb Cortex 2020; 29:4613-4627. [PMID: 30668644 DOI: 10.1093/cercor/bhy337] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 12/07/2018] [Accepted: 12/17/2018] [Indexed: 01/22/2023] Open
Abstract
Manual interactions with objects require precise and rapid feedback about contact events. These tactile signals are integrated with motor plans throughout the neuraxis to achieve dexterous object manipulation. To better understand the role of somatosensory cortex in interactions with objects, we measured, using chronically implanted arrays of electrodes, the responses of populations of somatosensory neurons to skin indentations designed to simulate the initiation, maintenance, and termination of contact with an object. First, we find that the responses of somatosensory neurons to contact onset and offset dwarf their responses to maintenance of contact. Second, we show that these responses rapidly and reliably encode features of the simulated contact events-their timing, location, and strength-and can account for the animals' performance in an amplitude discrimination task. Third, we demonstrate that the spatiotemporal dynamics of the population response in cortex mirror those of the population response in the nerves. We conclude that the responses of populations of somatosensory neurons are well suited to encode contact transients and are consistent with a role of somatosensory cortex in signaling transitions between task subgoals.
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Affiliation(s)
- Thierri Callier
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA
| | - Aneesha K Suresh
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA
| | - Sliman J Bensmaia
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA.,Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
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25
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Kumaravelu K, Tomlinson T, Callier T, Sombeck J, Bensmaia SJ, Miller LE, Grill WM. A comprehensive model-based framework for optimal design of biomimetic patterns of electrical stimulation for prosthetic sensation. J Neural Eng 2020; 17:046045. [PMID: 32759488 PMCID: PMC8559728 DOI: 10.1088/1741-2552/abacd8] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
OBJECTIVE Touch and proprioception are essential to motor function as shown by the movement deficits that result from the loss of these senses, e.g. due to neuropathy of sensory nerves. To achieve a high-performance brain-controlled prosthetic arm/hand thus requires the restoration of somatosensation, perhaps through intracortical microstimulation (ICMS) of somatosensory cortex (S1). The challenge is to generate patterns of neuronal activation that evoke interpretable percepts. We present a framework to design optimal spatiotemporal patterns of ICMS (STIM) that evoke naturalistic patterns of neuronal activity and demonstrate performance superior to four previous approaches. APPROACH We recorded multiunit activity from S1 during a center-out reach task (from proprioceptive neurons in Brodmann's area 2) and during application of skin indentations (from cutaneous neurons in Brodmann's area 1). We implemented a computational model of a cortical hypercolumn and used a genetic algorithm to design STIM that evoked patterns of model neuron activity that mimicked their experimentally-measured counterparts. Finally, from the ICMS patterns, the evoked neuronal activity, and the stimulus parameters that gave rise to it, we trained a recurrent neural network (RNN) to learn the mapping function between the physical stimulus and the biomimetic stimulation pattern, i.e. the sensory encoder to be integrated into a neuroprosthetic device. MAIN RESULTS We identified ICMS patterns that evoked simulated responses that closely approximated the measured responses for neurons within 50 µm of the electrode tip. The RNN-based sensory encoder generalized well to untrained limb movements or skin indentations. STIM designed using the model-based optimization approach outperformed STIM designed using existing linear and nonlinear mappings. SIGNIFICANCE The proposed framework produces an encoder that converts limb state or patterns of pressure exerted onto the prosthetic hand into STIM that evoke naturalistic patterns of neuronal activation.
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Affiliation(s)
| | | | - Thierri Callier
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Joseph Sombeck
- Department of Biomedical Engineering, Northwestern University, Chicago, IL
| | - Sliman J. Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Lee E. Miller
- Department of Biomedical Engineering, Northwestern University, Chicago, IL
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL
- Deptartment of Physiology, Northwestern University, Chicago, IL
| | - Warren M. Grill
- Department of Biomedical Engineering, Duke University, Durham, NC
- Department of Electrical and Computer Engineering, Duke University, Durham, NC
- Department of Neurobiology, Duke University, Durham, NC
- Department of Neurosurgery, Duke University, Durham, NC
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26
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Vickery RM, Ng KKW, Potas JR, Shivdasani MN, McIntyre S, Nagi SS, Birznieks I. Tapping Into the Language of Touch: Using Non-invasive Stimulation to Specify Tactile Afferent Firing Patterns. Front Neurosci 2020; 14:500. [PMID: 32508581 PMCID: PMC7248323 DOI: 10.3389/fnins.2020.00500] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Accepted: 04/21/2020] [Indexed: 12/12/2022] Open
Abstract
The temporal pattern of action potentials can convey rich information in a variety of sensory systems. We describe a new non-invasive technique that enables precise, reliable generation of action potential patterns in tactile peripheral afferent neurons by brief taps on the skin. Using this technique, we demonstrate sophisticated coding of temporal information in the somatosensory system, that shows that perceived vibration frequency is not encoded in peripheral afferents as was expected by either their firing rate or the underlying periodicity of the stimulus. Instead, a burst gap or silent gap between trains of action potentials conveys frequency information. This opens the possibility of new encoding strategies that could be deployed to convey sensory information using mechanical or electrical stimulation in neural prostheses and brain-machine interfaces, and may extend to senses beyond artificial encoding of aspects of touch. We argue that a focus on appropriate use of effective temporal coding offers more prospects for rapid improvement in the function of these interfaces than attempts to scale-up existing devices.
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Affiliation(s)
- Richard M. Vickery
- School of Medical Sciences, UNSW Sydney, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Kevin K. W. Ng
- School of Medical Sciences, UNSW Sydney, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Jason R. Potas
- School of Medical Sciences, UNSW Sydney, Sydney, NSW, Australia
| | - Mohit N. Shivdasani
- Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, Australia
| | - Sarah McIntyre
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Saad S. Nagi
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Ingvars Birznieks
- School of Medical Sciences, UNSW Sydney, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
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27
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Lieber JD, Bensmaia SJ. Emergence of an Invariant Representation of Texture in Primate Somatosensory Cortex. Cereb Cortex 2019; 30:3228-3239. [PMID: 31813989 PMCID: PMC7197205 DOI: 10.1093/cercor/bhz305] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 11/08/2019] [Accepted: 11/12/2019] [Indexed: 01/13/2023] Open
Abstract
A major function of sensory processing is to achieve neural representations of objects that are stable across changes in context and perspective. Small changes in exploratory behavior can lead to large changes in signals at the sensory periphery, thus resulting in ambiguous neural representations of objects. Overcoming this ambiguity is a hallmark of human object recognition across sensory modalities. Here, we investigate how the perception of tactile texture remains stable across exploratory movements of the hand, including changes in scanning speed, despite the concomitant changes in afferent responses. To this end, we scanned a wide range of everyday textures across the fingertips of rhesus macaques at multiple speeds and recorded the responses evoked in tactile nerve fibers and somatosensory cortical neurons (from Brodmann areas 3b, 1, and 2). We found that individual cortical neurons exhibit a wider range of speed-sensitivities than do nerve fibers. The resulting representations of speed and texture in cortex are more independent than are their counterparts in the nerve and account for speed-invariant perception of texture. We demonstrate that this separation of speed and texture information is a natural consequence of previously described cortical computations.
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Affiliation(s)
- Justin D Lieber
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Sliman J Bensmaia
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, 60637, USA.,Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, 60637, USA
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28
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Birznieks I, McIntyre S, Nilsson HM, Nagi SS, Macefield VG, Mahns DA, Vickery RM. Tactile sensory channels over-ruled by frequency decoding system that utilizes spike pattern regardless of receptor type. eLife 2019; 8:46510. [PMID: 31383258 PMCID: PMC6684274 DOI: 10.7554/elife.46510] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 07/19/2019] [Indexed: 12/16/2022] Open
Abstract
The established view is that vibrotactile stimuli evoke two qualitatively distinctive cutaneous sensations, flutter (frequencies < 60 Hz) and vibratory hum (frequencies > 60 Hz), subserved by two distinct receptor types (Meissner’s and Pacinian corpuscle, respectively), which may engage different neural processing pathways or channels and fulfil quite different biological roles. In psychological and physiological literature, those two systems have been labelled as Pacinian and non-Pacinian channels. However, we present evidence that low-frequency spike trains in Pacinian afferents can readily induce a vibratory percept with the same low frequency attributes as sinusoidal stimuli of the same frequency, thus demonstrating a universal frequency decoding system. We achieved this using brief low-amplitude pulsatile mechanical stimuli to selectively activate Pacinian afferents. This indicates that spiking pattern, regardless of receptor type, determines vibrotactile frequency perception. This mechanism may underlie the constancy of vibrotactile frequency perception across different skin regions innervated by distinct afferent types.
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Affiliation(s)
- Ingvars Birznieks
- School of Medical Sciences, Faculty of Medicine, UNSW Sydney, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia.,Biomedical Engineering and Neuroscience, MARCS Institute, Western Sydney University, Sydney, Australia
| | - Sarah McIntyre
- Neuroscience Research Australia, Sydney, Australia.,Biomedical Engineering and Neuroscience, MARCS Institute, Western Sydney University, Sydney, Australia.,Linköping University, Linköping, Sweden
| | - Hanna Maria Nilsson
- Neuroscience Research Australia, Sydney, Australia.,Linköping University, Linköping, Sweden
| | - Saad S Nagi
- Linköping University, Linköping, Sweden.,School of Medicine, Western Sydney University, Sydney, Australia
| | - Vaughan G Macefield
- Neuroscience Research Australia, Sydney, Australia.,School of Medicine, Western Sydney University, Sydney, Australia.,The Baker Heart and Diabetes Institute, Melbourne, Australia
| | - David A Mahns
- School of Medicine, Western Sydney University, Sydney, Australia
| | - Richard M Vickery
- School of Medical Sciences, Faculty of Medicine, UNSW Sydney, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia
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29
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Abstract
The nervous system processes phenomenal amounts of information. This processing must be conducted efficiently. In telecommunications systems, efficiency is increased by transmitting multiple signals through a single communication channel, or multiplexing. Neurons also multiplex. Here, we demonstrate a strategy for multiplexing different features of aperiodic stimuli: Cortical neurons use the rate of asynchronous spiking to encode stimulus intensity while using the timing of synchronous spikes to encode abrupt changes in stimulus intensity. This is possible because high-contrast features (e.g., edges) evoke spikes that transiently synchronize across neurons, whereas low-contrast features evoke sustained asynchronous spiking whose rate is proportional to stimulus intensity. Differentially synchronized spiking evoked in the same neurons by different stimulus features enables the formation of multiplexed representations. Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high-contrast features. We refer to this strategy as synchrony-division multiplexing.
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30
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Abstract
The sense of touch affords a remarkable sensitivity to the microstructure of surfaces, affording us the ability to sense elements ranging in size from tens of nanometers to tens of millimeters. The hand sends signals about texture to the brain using three classes of nerve fibers through two neural codes: coarse features in spatial patterns of activation and fine features in precise temporal spiking patterns. In this study, we show that these nerve signals culminate in a complex, high-dimensional representation of texture in somatosensory cortex, whose structure can account for the structure of texture perception. This complexity arises from the neurons that act as idiosyncratic detectors of spatial and/or temporal motifs in the afferent input. In the somatosensory nerves, the tactile perception of texture is driven by spatial and temporal patterns of activation distributed across three populations of afferents. These disparate streams of information must then be integrated centrally to achieve a unified percept of texture. To investigate the representation of texture in somatosensory cortex, we scanned a wide range of natural textures across the fingertips of rhesus macaques and recorded the responses evoked in Brodmann’s areas 3b, 1, and 2. We found that texture identity is reliably encoded in the idiosyncratic responses of populations of cortical neurons, giving rise to a high-dimensional representation of texture. Cortical neurons fall along a continuum in their sensitivity to fine vs. coarse texture, and neurons at the extrema of this continuum seem to receive their major input from different afferent populations. Finally, we show that cortical responses can account for several aspects of texture perception in humans.
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31
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Crommett LE, Madala D, Yau JM. Multisensory perceptual interactions between higher-order temporal frequency signals. J Exp Psychol Gen 2018; 148:1124-1137. [PMID: 30335446 DOI: 10.1037/xge0000513] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Naturally occurring signals in audition and touch can be complex and marked by temporal variations in frequency and amplitude. Auditory frequency sweep processing has been studied extensively; however, much less is known about sweep processing in touch because studies have primarily focused on the perception of simple sinusoidal vibrations. Given the extensive interactions between audition and touch in the frequency processing of pure tone signals, we reasoned that these senses might also interact in the processing of higher-order frequency representations like sweeps. In a series of psychophysical experiments, we characterized the influence of auditory distractors on the ability of participants to discriminate tactile frequency sweeps. Auditory frequency sweeps systematically biased the tactile perception of sweep direction. Importantly, auditory cues exerted little influence on tactile sweep direction perception when the sounds and vibrations occupied different absolute frequency ranges or when the sounds consisted of intensity sweeps. Thus, audition and touch interact in frequency sweep perception in a frequency- and feature-specific manner. Our results demonstrate that audio-tactile interactions are not constrained to the processing of simple sinusoids. Because higher-order frequency representations may be synthesized from simpler representations, our findings imply that multisensory interactions in the temporal frequency domain span multiple hierarchical levels in sensory processing. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Affiliation(s)
| | - Deeksha Madala
- Department of Biochemistry and Cell Biology, Rice University
| | - Jeffrey M Yau
- Department of Neuroscience, Baylor College of Medicine
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32
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Delhaye BP, Long KH, Bensmaia SJ. Neural Basis of Touch and Proprioception in Primate Cortex. Compr Physiol 2018; 8:1575-1602. [PMID: 30215864 PMCID: PMC6330897 DOI: 10.1002/cphy.c170033] [Citation(s) in RCA: 102] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The sense of proprioception allows us to keep track of our limb posture and movements and the sense of touch provides us with information about objects with which we come into contact. In both senses, mechanoreceptors convert the deformation of tissues-skin, muscles, tendons, ligaments, or joints-into neural signals. Tactile and proprioceptive signals are then relayed by the peripheral nerves to the central nervous system, where they are processed to give rise to percepts of objects and of the state of our body. In this review, we first examine briefly the receptors that mediate touch and proprioception, their associated nerve fibers, and pathways they follow to the cerebral cortex. We then provide an overview of the different cortical areas that process tactile and proprioceptive information. Next, we discuss how various features of objects-their shape, motion, and texture, for example-are encoded in the various cortical fields, and the susceptibility of these neural codes to attention and other forms of higher-order modulation. Finally, we summarize recent efforts to restore the senses of touch and proprioception by electrically stimulating somatosensory cortex. © 2018 American Physiological Society. Compr Physiol 8:1575-1602, 2018.
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Affiliation(s)
- Benoit P Delhaye
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, USA
| | - Katie H Long
- Committee on Computational Neuroscience, University of Chicago, Chicago, USA
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, USA.,Committee on Computational Neuroscience, University of Chicago, Chicago, USA
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33
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Paradigms for restoration of somatosensory feedback via stimulation of the peripheral nervous system. Clin Neurophysiol 2018; 129:851-862. [DOI: 10.1016/j.clinph.2017.12.027] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 12/05/2017] [Accepted: 12/13/2017] [Indexed: 02/08/2023]
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34
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Abstract
When we touch an object, the skin copies its surface shape/texture, and this deformation pattern shifts according to the objects movement. This shift pattern directly encodes spatio-temporal “motion” information of the event, and has been detected in other modalities (e.g., inter-aural time differences for audition and first-order motion for vision). Since previous studies suggested that mechanoreceptor-afferent channels with small receptive field and slow temporal characteristics contribute to tactile motion perception, we tried to tap the spatio-temporal processor using low-frequency sine-waves as primitive probes in our previous study. However, we found that asynchrony of sine-wave pair presented on adjacent fingers was difficult to detect. Here, to take advantage of the small receptive field, we investigated within-finger motion and found above threshold performance when observers touched localized sine-wave stimuli with one finger. Though observers could not perceptually discriminate rightward from leftward motion, the adaptation occurred in a direction-sensitive way: the motion/asynchronous detection was impaired by adapting to asynchronous stimuli moving in the same direction. These findings are consistent with a possibility that human can directly encode short-range spatio-temporal patterns of skin deformation by using phase-shifted low-frequency components, in addition to detecting short- and long-range motion using energy shifts of high-frequency components.
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35
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Lieber JD, Xia X, Weber AI, Bensmaia SJ. The neural code for tactile roughness in the somatosensory nerves. J Neurophysiol 2017; 118:3107-3117. [PMID: 28855289 DOI: 10.1152/jn.00374.2017] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 08/01/2017] [Accepted: 08/24/2017] [Indexed: 11/22/2022] Open
Abstract
Roughness is the most salient perceptual dimension of surface texture but has no well-defined physical basis. We seek to determine the neural determinants of tactile roughness in the somatosensory nerves. Specifically, we record the patterns of activation evoked in tactile nerve fibers of anesthetized Rhesus macaques to a large and diverse set of natural textures and assess what aspect of these patterns of activation can account for psychophysical judgments of roughness, obtained from human observers. We show that perceived roughness is determined by the variation in the population response, weighted by fiber type. That is, a surface will feel rough to the extent that the activity varies across nerve fibers and varies across time within nerve fibers. We show that this variation-based neural code can account not only for magnitude estimates of roughness but also for roughness discrimination performance.NEW & NOTEWORTHY Our sense of touch endows us with an exquisite sensitivity to the microstructure of surfaces, the most salient aspect of which is roughness. We analyze the responses evoked in tactile fibers of monkeys by natural textures and compare them to judgments of roughness obtained for the same textures from human observers. We then describe how texture signals from three populations of nerve fibers are integrated to culminate in a percept of roughness.
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Affiliation(s)
- Justin D Lieber
- Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois
| | - Xinyue Xia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois; and
| | - Alison I Weber
- Graduate Program in Neuroscience, University of Washington, Seattle, Washington
| | - Sliman J Bensmaia
- Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois; .,Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois; and
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36
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Hollins M, Corsi C, Sloan P. Pacinian Signals Determine the Direction and Magnitude of the Effect of Vibration on Pain. Perception 2017; 46:987-999. [PMID: 28715995 DOI: 10.1177/0301006617694630] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Although the ability of vibration to reduce pain has been extensively documented, an occasional participant reports that vibration increases pain. For pain patients, such reports may reflect pathophysiology, but this is unlikely in studies of experimental pain in healthy participants. In the present series of experiments on 27 pain-free individuals, we manipulated both the frequency (12, 50, and 80 Hz) and amplitude of vibration to more fully characterize vibratory pain modulation. The noxious stimulus was pressure applied to a finger, and vibration was delivered to the fleshy palmar pad at the base of the same finger. Subjects continuously reported pain on a Visual Analog Scale. Intermittent vibration was used to minimize peripheral vibratory adaptation. Pain records at 12 and 50 Hz were similar; pooling them revealed significant hypoalgesia at the highest amplitude. At 80 Hz, in contrast, the middle amplitude produced hypoalgesia, but a significant shift toward hyperalgesia occurred at the highest amplitude. The strong correlation ( r = .81) between the Pacinian-weighted power of a vibration and the absolute value of the pain modulation it produces indicates that the Pacinian system plays a key role in vibratory hypoalgesia or hyperalgesia.
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Affiliation(s)
- Mark Hollins
- University of North Carolina at Chapel Hill, NC, USA
| | | | - Page Sloan
- University of North Carolina at Chapel Hill, NC, USA
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37
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Simulating tactile signals from the whole hand with millisecond precision. Proc Natl Acad Sci U S A 2017; 114:E5693-E5702. [PMID: 28652360 DOI: 10.1073/pnas.1704856114] [Citation(s) in RCA: 107] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
When we grasp and manipulate an object, populations of tactile nerve fibers become activated and convey information about the shape, size, and texture of the object and its motion across the skin. The response properties of tactile fibers have been extensively characterized in single-unit recordings, yielding important insights into how individual fibers encode tactile information. A recurring finding in this extensive body of work is that stimulus information is distributed over many fibers. However, our understanding of population-level representations remains primitive. To fill this gap, we have developed a model to simulate the responses of all tactile fibers innervating the glabrous skin of the hand to any spatiotemporal stimulus applied to the skin. The model first reconstructs the stresses experienced by mechanoreceptors when the skin is deformed and then simulates the spiking response that would be produced in the nerve fiber innervating that receptor. By simulating skin deformations across the palmar surface of the hand and tiling it with receptors at their known densities, we reconstruct the responses of entire populations of nerve fibers. We show that the simulated responses closely match their measured counterparts, down to the precise timing of the evoked spikes, across a wide variety of experimental conditions sampled from the literature. We then conduct three virtual experiments to illustrate how the simulation can provide powerful insights into population coding in touch. Finally, we discuss how the model provides a means to establish naturalistic artificial touch in bionic hands.
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38
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Integration of vibrotactile frequency information beyond the mechanoreceptor channel and somatotopy. Sci Rep 2017; 7:2758. [PMID: 28584282 PMCID: PMC5459808 DOI: 10.1038/s41598-017-02922-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Accepted: 04/19/2017] [Indexed: 11/08/2022] Open
Abstract
A wide variety of tactile sensations arise from the activation of several types of mechanoreceptor-afferent channels scattered all over the body, and their projections create a somatotopic map in the somatosensory cortex. Recent findings challenge the traditional view that tactile signals from different mechanoreceptor-channels/locations are independently processed in the brain, though the contribution of signal integration to perception remains obscure. Here we show that vibrotactile frequency perception is functionally enriched by signal integration across different mechanoreceptor channels and separate skin locations. When participants touched two sinusoidal vibrations of far-different frequency, which dominantly activated separate channels with the neighboring fingers or the different hand and judged the frequency of one vibration, the perceived frequency shifted toward the other (assimilation effect). Furthermore, when the participants judged the frequency of the pair as a whole, they consistently reported an intensity-based interpolation of the two vibrations (averaging effect). Both effects were similar in magnitude between the same and different hand conditions and significantly diminished by asynchronous presentation of the vibration pair. These findings indicate that human tactile processing is global and flexible in that it can estimate the ensemble property of a large-scale tactile event sensed by various receptors distributed over the body.
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39
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Intracortical Microstimulation as a Feedback Source for Brain-Computer Interface Users. SPRINGERBRIEFS IN ELECTRICAL AND COMPUTER ENGINEERING 2017. [DOI: 10.1007/978-3-319-64373-1_5] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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40
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Héricé C, Khalil R, Moftah M, Boraud T, Guthrie M, Garenne A. Decision making under uncertainty in a spiking neural network model of the basal ganglia. J Integr Neurosci 2016; 15:515-538. [PMID: 28002987 DOI: 10.1142/s021963521650028x] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbic modalities of decision-making. We have used these properties to develop and extend a connectionist model at a spiking neuron level based on a previous rate model approach. This model is demonstrated on decision-making tasks that have been studied in primates and the electrophysiology interpreted to show that the decision is made in two steps. To model this, we have used two parallel loops, each of which performs decision-making based on interactions between positive and negative feedback pathways. This model is able to perform two-level decision-making as in primates. We show here that, before learning, synaptic noise is sufficient to drive the decision-making process and that, after learning, the decision is based on the choice that has proven most likely to be rewarded. The model is then submitted to lesion tests, reversal learning and extinction protocols. We show that, under these conditions, it behaves in a consistent manner and provides predictions in accordance with observed experimental data.
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Affiliation(s)
- Charlotte Héricé
- * University de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France.,† CNRS, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France
| | - Radwa Khalil
- † CNRS, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France
| | | | - Thomas Boraud
- * University de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France.,† CNRS, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France
| | - Martin Guthrie
- * University de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France.,† CNRS, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France
| | - André Garenne
- * University de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France.,† CNRS, Institut des Maladies Neurodégénératives, UMR 5293, 33000 Bordeaux, France
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41
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Saal HP, Wang X, Bensmaia SJ. Importance of spike timing in touch: an analogy with hearing? Curr Opin Neurobiol 2016; 40:142-149. [PMID: 27504741 PMCID: PMC5315566 DOI: 10.1016/j.conb.2016.07.013] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Revised: 07/18/2016] [Accepted: 07/19/2016] [Indexed: 11/23/2022]
Abstract
Touch is often conceived as a spatial sense akin to vision. However, touch also involves the transduction and processing of signals that vary rapidly over time, inviting comparisons with hearing. In both sensory systems, first order afferents produce spiking responses that are temporally precise and the timing of their responses carries stimulus information. The precision and informativeness of spike timing in the two systems invites the possibility that both implement similar mechanisms to extract behaviorally relevant information from these precisely timed responses. Here, we explore the putative roles of spike timing in touch and hearing and discuss common mechanisms that may be involved in processing temporal spiking patterns.
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Affiliation(s)
- Hannes P Saal
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL 60637, USA
| | - Xiaoqin Wang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL 60637, USA.
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Metzen MG, Krahe R, Chacron MJ. Burst Firing in the Electrosensory System of Gymnotiform Weakly Electric Fish: Mechanisms and Functional Roles. Front Comput Neurosci 2016; 10:81. [PMID: 27531978 PMCID: PMC4969294 DOI: 10.3389/fncom.2016.00081] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2016] [Accepted: 07/20/2016] [Indexed: 11/13/2022] Open
Abstract
Neurons across sensory systems and organisms often display complex patterns of action potentials in response to sensory input. One example of such a pattern is the tendency of neurons to fire packets of action potentials (i.e., a burst) followed by quiescence. While it is well known that multiple mechanisms can generate bursts of action potentials at both the single-neuron and the network level, the functional role of burst firing in sensory processing is not so well understood to date. Here we provide a comprehensive review of the known mechanisms and functions of burst firing in processing of electrosensory stimuli in gymnotiform weakly electric fish. We also present new evidence from existing data showing that bursts and isolated spikes provide distinct information about stimulus variance. It is likely that these functional roles will be generally applicable to other systems and species.
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Affiliation(s)
- Michael G Metzen
- Department of Physiology, McGill University Montreal, QC, Canada
| | - Rüdiger Krahe
- Department of Biology, McGill University Montreal, QC, Canada
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Schroeder KE, Chestek CA. Intracortical Brain-Machine Interfaces Advance Sensorimotor Neuroscience. Front Neurosci 2016; 10:291. [PMID: 27445663 PMCID: PMC4923184 DOI: 10.3389/fnins.2016.00291] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 06/10/2016] [Indexed: 01/06/2023] Open
Abstract
Brain-machine interfaces (BMIs) decode brain activity to control external devices. Over the past two decades, the BMI community has grown tremendously and reached some impressive milestones, including the first human clinical trials using chronically implanted intracortical electrodes. It has also contributed experimental paradigms and important findings to basic neuroscience. In this review, we discuss neuroscience achievements stemming from BMI research, specifically that based upon upper limb prosthetic control with intracortical microelectrodes. We will focus on three main areas: first, we discuss progress in neural coding of reaches in motor cortex, describing recent results linking high dimensional representations of cortical activity to muscle activation. Next, we describe recent findings on learning and plasticity in motor cortex on various time scales. Finally, we discuss how bidirectional BMIs have led to better understanding of somatosensation in and related to motor cortex.
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Affiliation(s)
- Karen E Schroeder
- Department of Biomedical Engineering, University of Michigan Ann Arbor, MI, USA
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of MichiganAnn Arbor, MI, USA; Neuroscience Graduate Program, University of Michigan Medical SchoolAnn Arbor, MI, USA; Center for Consciousness Science, University of Michigan Medical SchoolAnn Arbor, MI, USA; Department of Electrical Engineering and Computer Science, University of MichiganAnn Arbor, MI, USA; Robotics Graduate Program, University of MichiganAnn Arbor, MI, USA
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