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Liew YJ, Dimwamwa ED, Wright NC, Zhang Y, Stanley GB. Multiple Distinct Timescales of Rapid Sensory Adaption in the Thalamocortical Circuit. J Neurosci 2025; 45:e1057242025. [PMID: 39933928 PMCID: PMC11968529 DOI: 10.1523/jneurosci.1057-24.2025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 01/03/2025] [Accepted: 01/19/2025] [Indexed: 02/13/2025] Open
Abstract
Numerous studies have shown that neuronal representations in sensory pathways are far from static but are instead strongly shaped by the complex properties of the sensory inputs they receive. Adaptation dynamically shapes the neural signaling that underlies our perception of the world yet remains poorly understood. We investigated rapid adaptation across timescales from hundreds of milliseconds to seconds through simultaneous multielectrode recordings from the ventro-posteromedial nucleus of the thalamus (VPm) and layer 4 of the primary somatosensory cortex (S1) in male and female anesthetized mice in response to controlled, persistent whisker stimulation. Observations in VPm and S1 reveal a degree of adaptation that progresses through the pathway. Under these experimental conditions, signatures of two distinct timescales of rapid adaptation in the firing rates of both thalamic and cortical neuronal populations were revealed, also reflected in the synchrony of the thalamic population and in the thalamocortical synaptic efficacy that was measured in putatively monosynaptically connected thalamocortical pairs. Controlled optogenetic activation of VPm further demonstrated that the longer timescale adaptation observed in S1 is likely inherited from slow decreases in thalamic firing rate and synchrony. Despite the degraded sensory responses, adaptation induced by the controlled repetitive stimulation presented here resulted in a shift in coding strategy that favors theoretical discrimination over detection across the observed timescales of adaptation. Overall, although multiple mechanisms contribute to rapid adaptation at distinct timescales, they support a unifying framework on the role of adaptation in sensory processing.
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Affiliation(s)
- Yi Juin Liew
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332
- Joint PhD Program in Biomedical Engineering, Georgia Institute of Technology - Emory University - Peking University, Atlanta, Georgia 30332
| | - Elaida D Dimwamwa
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332
| | - Nathaniel C Wright
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332
| | - Yong Zhang
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Peking University, Key Laboratory for Neuroscience, Ministry of Education of China and National Health Commission of the People's Republic of China, Beijing 100083, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
| | - Garrett B Stanley
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332
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2
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Su C, Mendes-Platt RF, Alonso JM, Swadlow HA, Bereshpolova Y. Fast-Spike Interneurons in Visual Cortical Layer 5: Heterogeneous Response Properties Are Related to Thalamocortical Connectivity. J Neurosci 2025; 45:e1116242024. [PMID: 39667901 PMCID: PMC11756620 DOI: 10.1523/jneurosci.1116-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 11/01/2024] [Accepted: 11/26/2024] [Indexed: 12/14/2024] Open
Abstract
Layer 4 (L4) of rabbit V1 contains fast-spike GABAergic interneurons (suspected inhibitory interneurons, SINs) that receive potent synaptic input from the LGN and generate fast, local feedforward inhibition. These cells display receptive fields with overlapping ON/OFF subregions, nonlinear spatial summation, very broad orientation/directional tuning, and high spontaneous and visually driven firing rates. Fast-spike interneurons are also found in Layer 5 (L5), which receives a much sparser input from the LGN, but the response properties and thalamocortical connectivity of L5 SINs are relatively unstudied. Here, we study L5 SINs in awake rabbits (both sexes) and compare their response properties with previously studied SINs of L4. We also assess thalamocortical connectivity of L5 SINs, examining cross-correlation of retinotopically aligned LGN-SIN spike trains and L5 SIN responses to electrical stimulation of the LGN. These analyses confirmed that many L5 SINs, like L4 SINs, receive a strong, fast monosynaptic drive from the LGN. Moreover, these LGN-connected L5 SINs had response properties similar to those of L4 SINs and were predominantly found in the upper half of L5. In contrast, L5 SINs with longer synaptic latencies to LGN stimulation displayed (1) sharper orientation tuning, (2) longer visual response latencies, (3) lower spontaneous and (4) visually driven firing rates, and (5) were found in the deeper half of L5. We suggest that the long-latency synaptic responses in such L5 SINs reflect a multisynaptic intracortical pathway that generates a different constellation of response properties than seen in L5 SINs that are driven directly by LGN input.
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Affiliation(s)
- Chuyi Su
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
| | | | - Jose-Manuel Alonso
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
- Department of Biological Sciences, SUNY-Optometry, New York, New York
| | - Harvey A Swadlow
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
- Department of Biological Sciences, SUNY-Optometry, New York, New York
| | - Yulia Bereshpolova
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
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3
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Su C, Mendes-Platt RF, Alonso JM, Swadlow HA, Bereshpolova Y. Retinal direction of motion is reliably transmitted to visual cortex through highly selective thalamocortical connections. Curr Biol 2025; 35:217-223.e4. [PMID: 39644892 DOI: 10.1016/j.cub.2024.11.013] [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: 06/04/2024] [Revised: 09/27/2024] [Accepted: 11/07/2024] [Indexed: 12/09/2024]
Abstract
Motion perception is crucial to animal survival and effective environmental interactions. In mammals, detection of movement begins in the retina. Directionally selective (DS) retinal ganglion cells were first discovered in the rabbit eye,1 and they have since been found in mouse,2,3 cat,4 and monkey.5,6 These DS retinal neurons contact a small population of neurons in the visual thalamus (dorsal lateral geniculate nucleus [LGN]) that are highly DS.7,8,9,10 The primary visual cortex (V1) also contains DS neurons, but whether directional selectivity in V1 emerges de novo11,12,13 or is inherited from DS thalamic inputs14,15,16 remains unclear. We previously found that LGN-DS neurons generate strong and focal synaptic currents in rabbit V1, similar to those generated by LGN concentric cells.17 Thus, the synaptic drive generated by LGN-DS neurons in V1 is spatially well situated to influence the firing of layer 4 (L4) simple cells, most of which show strong directional selectivity.18 However, two important questions remain: do LGN-DS neurons synaptically target DS simple cells in L4, and, if so, do they contribute to the directional preferences of these V1 DS neurons? We used spike-train cross-correlation analysis of pairs of LGN-DS and L4 simple cells to address these questions. We found that LGN-DS neurons do target L4 DS simple cells and that the targeting is highly selective, largely following a simple set of "connectivity rules." We conclude that this highly selective thalamocortical connectivity of LGN-DS neurons contributes to the sharp directional selectivity of cortical simple cells.
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Affiliation(s)
- Chuyi Su
- Deptartment of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA
| | | | - Jose-Manuel Alonso
- Deptartment of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA; Deptartment of Biological and Vision Sciences, SUNY-Optometry, New York, NY 10036, USA
| | - Harvey A Swadlow
- Deptartment of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA; Deptartment of Biological and Vision Sciences, SUNY-Optometry, New York, NY 10036, USA
| | - Yulia Bereshpolova
- Deptartment of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA.
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4
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Ho JC, Grigsby EM, Damiani A, Liang L, Balaguer JM, Kallakuri S, Tang LW, Barrios-Martinez J, Karapetyan V, Fields D, Gerszten PC, Hitchens TK, Constantine T, Adams GM, Crammond DJ, Capogrosso M, Gonzalez-Martinez JA, Pirondini E. Potentiation of cortico-spinal output via targeted electrical stimulation of the motor thalamus. Nat Commun 2024; 15:8461. [PMID: 39353911 PMCID: PMC11445460 DOI: 10.1038/s41467-024-52477-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Accepted: 09/05/2024] [Indexed: 10/03/2024] Open
Abstract
Cerebral white matter lesions prevent cortico-spinal descending inputs from effectively activating spinal motoneurons, leading to loss of motor control. However, in most cases, the damage to cortico-spinal axons is incomplete offering a potential target for therapies aimed at improving volitional muscle activation. Here we hypothesize that, by engaging direct excitatory connections to cortico-spinal motoneurons, stimulation of the motor thalamus could facilitate activation of surviving cortico-spinal fibers thereby immediately potentiating motor output. To test this hypothesis, we identify optimal thalamic targets and stimulation parameters that enhance upper-limb motor-evoked potentials and grip forces in anesthetized monkeys. This potentiation persists after white matter lesions. We replicate these results in humans during intra-operative testing. We then design a stimulation protocol that immediately improves strength and force control in a patient with a chronic white matter lesion. Our results show that electrical stimulation targeting surviving neural pathways can improve motor control after white matter lesions.
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Affiliation(s)
- Jonathan C Ho
- School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Erinn M Grigsby
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Arianna Damiani
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lucy Liang
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Josep-Maria Balaguer
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Sridula Kallakuri
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lilly W Tang
- School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Vahagn Karapetyan
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Daryl Fields
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Peter C Gerszten
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - T Kevin Hitchens
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Theodora Constantine
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Gregory M Adams
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Donald J Crammond
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Marco Capogrosso
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jorge A Gonzalez-Martinez
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Elvira Pirondini
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
- University of Pittsburgh Clinical and Translational Science Institute (CTSI), Pittsburgh, PA, USA.
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5
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Liew YJ, Dimwamwa ED, Wright NC, Zhang Y, Stanley GB. MULTIPLE DISTINCT TIMESCALES OF RAPID SENSORY ADAPATION IN THE THALAMOCORTICAL CIRCUIT. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597761. [PMID: 38895470 PMCID: PMC11185625 DOI: 10.1101/2024.06.06.597761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Numerous studies have shown that neuronal representations in sensory pathways are far from static but are instead strongly shaped by the complex properties of the sensory inputs they receive. Adaptation dynamically shapes the neural signaling that underlies our perception of the world yet remains poorly understood. We investigated rapid adaptation across timescales from hundreds of milliseconds to seconds through simultaneous multi-electrode recordings from the ventro-posteromedial nucleus of the thalamus (VPm) and layer 4 of the primary somatosensory cortex (S1) in male and female anesthetized mice in response to controlled, persistent whisker stimulation. Observations in VPm and S1 reveal a degree of adaptation that progresses through the pathway. Signatures of two distinct timescales of rapid adaptation in the firing rates of both thalamic and cortical neuronal populations were revealed, also reflected in the synchrony of the thalamic population and in the thalamocortical synaptic efficacy that was measured in putatively monosynaptically connected thalamocortical pairs. Controlled optogenetic activation of VPm further demonstrated that the longer timescale adaptation observed in S1 is likely inherited from slow decreases in thalamic firing rate and synchrony. Despite the degraded sensory responses, adaptation resulted in a shift in coding strategy that favors theoretical discrimination over detection across the observed timescales of adaptation. Overall, although multiple mechanisms contribute to rapid adaptation at distinct timescales, they support a unifying framework on the role of adaptation in sensory processing.
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Affiliation(s)
- Yi Juin Liew
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Joint PhD Program in Biomedical Engineering, Georgia Institute of Technology – Emory University – Peking University, Atlanta, GA 30332, USA
| | - Elaida D Dimwamwa
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Nathaniel C Wright
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Yong Zhang
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Peking University, Key Laboratory for Neuroscience, Ministry of Education of China and National Health Commission of the People’s Republic of China, Beijing 100083, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, 100871, China
| | - Garrett B Stanley
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
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6
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Kobayashi R, Shinomoto S. Inference of monosynaptic connections from parallel spike trains: A review. Neurosci Res 2024:S0168-0102(24)00097-X. [PMID: 39098768 DOI: 10.1016/j.neures.2024.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 07/12/2024] [Accepted: 07/19/2024] [Indexed: 08/06/2024]
Abstract
This article presents a mini-review about the progress in inferring monosynaptic connections from spike trains of multiple neurons over the past twenty years. First, we explain a variety of meanings of "neuronal connectivity" in different research areas of neuroscience, such as structural connectivity, monosynaptic connectivity, and functional connectivity. Among these, we focus on the methods used to infer the monosynaptic connectivity from spike data. We then summarize the inference methods based on two main approaches, i.e., correlation-based and model-based approaches. Finally, we describe available source codes for connectivity inference and future challenges. Although inference will never be perfect, the accuracy of identifying the monosynaptic connections has improved dramatically in recent years due to continuous efforts.
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Affiliation(s)
- Ryota Kobayashi
- Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8561, Japan; Mathematics and Informatics Center, The University of Tokyo, Tokyo 113-8656, Japan.
| | - Shigeru Shinomoto
- Graduate School of Biostudies, Kyoto University, Kyoto 606-8501, Japan; Research Organization of Open Innovation and Collaboration, Ritsumeikan University, Osaka 567-8570, Japan
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7
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Su C, Mendes-Platt RF, Alonso JM, Swadlow HA, Bereshpolova Y. Visual Corticotectal Neurons in Awake Rabbits: Receptive Fields and Driving Monosynaptic Thalamocortical Inputs. J Neurosci 2024; 44:e1945232024. [PMID: 38485258 PMCID: PMC11079980 DOI: 10.1523/jneurosci.1945-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/25/2024] [Accepted: 02/27/2024] [Indexed: 03/26/2024] Open
Abstract
The superior colliculus receives powerful synaptic inputs from corticotectal neurons in the visual cortex. The function of these corticotectal neurons remains largely unknown due to a limited understanding of their response properties and connectivity. Here, we use antidromic methods to identify corticotectal neurons in awake male and female rabbits, and measure their axonal conduction times, thalamic inputs and receptive field properties. All corticotectal neurons responded to sinusoidal drifting gratings with a nonlinear (nonsinusoidal) increase in mean firing rate but showed pronounced differences in their ON-OFF receptive field structures that we classified into three groups, Cx, S2, and S1. Cx receptive fields had highly overlapping ON and OFF subfields as classical complex cells, S2 had largely separated ON and OFF subfields as classical simple cells, and S1 had a single ON or OFF subfield. Thus, all corticotectal neurons are homogeneous in their nonlinear spatial summation but very heterogeneous in their spatial integration of ON and OFF inputs. The Cx type had the fastest conducting axons, the highest spontaneous activity, and the strongest and fastest visual responses. The S2 type had the highest orientation selectivity, and the S1 type had the slowest conducting axons. Moreover, our cross-correlation analyses found that a subpopulation of corticotectal neurons with very fast conducting axons and high spontaneous firing rates (largely "Cx" type) receives monosynaptic input from retinotopically aligned thalamic neurons. This previously unrecognized fast-conducting thalamic-mediated corticotectal pathway may provide specialized information to superior colliculus and prime recipient neurons for subsequent corticotectal or retinal synaptic input.
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Affiliation(s)
- Chuyi Su
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
| | | | - Jose-Manuel Alonso
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
- Department of Biological Sciences, SUNY-Optometry, New York, New York
| | - Harvey A Swadlow
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
- Department of Biological Sciences, SUNY-Optometry, New York, New York
| | - Yulia Bereshpolova
- Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut
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8
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Dimwamwa ED, Pala A, Chundru V, Wright NC, Stanley GB. Dynamic corticothalamic modulation of the somatosensory thalamocortical circuit during wakefulness. Nat Commun 2024; 15:3529. [PMID: 38664415 PMCID: PMC11045850 DOI: 10.1038/s41467-024-47863-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
The feedback projections from cortical layer 6 (L6CT) to the sensory thalamus have long been implicated in playing a primary role in gating sensory signaling but remain poorly understood. To causally elucidate the full range of effects of these projections, we targeted silicon probe recordings to the whisker thalamocortical circuit of awake mice selectively expressing Channelrhodopsin-2 in L6CT neurons. Through optogenetic manipulation of L6CT neurons, multi-site electrophysiological recordings, and modeling of L6CT circuitry, we establish L6CT neurons as dynamic modulators of ongoing spiking in the ventral posteromedial nucleus of the thalamus (VPm), either suppressing or enhancing VPm spiking depending on L6CT neurons' firing rate and synchrony. Differential effects across the cortical excitatory and inhibitory sub-populations point to an overall influence of L6CT feedback on cortical excitability that could have profound implications for regulating sensory signaling across a range of ethologically relevant conditions.
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Affiliation(s)
- Elaida D Dimwamwa
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Aurélie Pala
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
- Department of Biology, Emory University, Atlanta, GA, USA
| | - Vivek Chundru
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Nathaniel C Wright
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Garrett B Stanley
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
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9
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Duncan JL, Wang JJ, Glusauskas G, Weagraff GR, Gao Y, Hoeferlin GF, Hunter AH, Hess-Dunning A, Ereifej ES, Capadona JR. In Vivo Characterization of Intracortical Probes with Focused Ion Beam-Etched Nanopatterned Topographies. MICROMACHINES 2024; 15:286. [PMID: 38399014 PMCID: PMC10893395 DOI: 10.3390/mi15020286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/09/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024]
Abstract
(1) Background: Intracortical microelectrodes (IMEs) are an important part of interfacing with the central nervous system (CNS) and recording neural signals. However, recording electrodes have shown a characteristic steady decline in recording performance owing to chronic neuroinflammation. The topography of implanted devices has been explored to mimic the nanoscale three-dimensional architecture of the extracellular matrix. Our previous work used histology to study the implant sites of non-recording probes and showed that a nanoscale topography at the probe surface mitigated the neuroinflammatory response compared to probes with smooth surfaces. Here, we hypothesized that the improvement in the neuroinflammatory response for probes with nanoscale surface topography would extend to improved recording performance. (2) Methods: A novel design modification was implemented on planar silicon-based neural probes by etching nanopatterned grooves (with a 500 nm pitch) into the probe shank. To assess the hypothesis, two groups of rats were implanted with either nanopatterned (n = 6) or smooth control (n = 6) probes, and their recording performance was evaluated over 4 weeks. Postmortem gene expression analysis was performed to compare the neuroinflammatory response from the two groups. (3) Results: Nanopatterned probes demonstrated an increased impedance and noise floor compared to controls. However, the recording performances of the nanopatterned and smooth probes were similar, with active electrode yields for control probes and nanopatterned probes being approximately 50% and 45%, respectively, by 4 weeks post-implantation. Gene expression analysis showed one gene, Sirt1, differentially expressed out of 152 in the panel. (4) Conclusions: this study provides a foundation for investigating novel nanoscale topographies on neural probes.
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Affiliation(s)
- Jonathan L. Duncan
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd, Cleveland, OH 44106, USA
| | - Jaime J. Wang
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd, Cleveland, OH 44106, USA
| | - Gabriele Glusauskas
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd, Cleveland, OH 44106, USA
| | - Gwendolyn R. Weagraff
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd, Cleveland, OH 44106, USA
| | - Yue Gao
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
| | - George F. Hoeferlin
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd, Cleveland, OH 44106, USA
| | - Allen H. Hunter
- Michigan Center for Materials Characterization, University of Michigan, 500 S. State St, Ann Arbor, MI 48109, USA
| | - Allison Hess-Dunning
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd, Cleveland, OH 44106, USA
| | - Evon S. Ereifej
- Department of Biomedical Engineering, University of Michigan, 500 S. State St, Ann Arbor, MI 48109, USA
- Veterans Affairs Hospital, 2215 Fuller Rd, Ann Arbor, MI 48105, USA
| | - Jeffrey R. Capadona
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd, Cleveland, OH 44106, USA
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10
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Dimwamwa E, Pala A, Chundru V, Wright NC, Stanley GB. Dynamic corticothalamic modulation of the somatosensory thalamocortical circuit during wakefulness. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.18.549491. [PMID: 37503253 PMCID: PMC10370106 DOI: 10.1101/2023.07.18.549491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
The feedback projections from cortical layer 6 (L6CT) to sensory thalamus have long been implicated in playing a primary role in gating sensory signaling but remain poorly understood. To causally elucidate the full range of effects of these projections, we targeted silicon probe recordings to the whisker thalamocortical circuit of awake mice selectively expressing Channelrhodopsin-2 in L6CT neurons. Through optogenetic manipulation of L6CT neurons, multi-site electrophysiological recordings, and modeling of L6CT circuitry, we establish L6CT neurons as dynamic modulators of ongoing spiking in the ventro-posterior-medial nucleus of thalamus (VPm), either suppressing or enhancing VPm spiking depending on L6CT neurons' firing rate and synchrony. Differential effects across the cortical excitatory and inhibitory sub-populations point to an overall influence of L6CT feedback on cortical excitability that could have profound implications for regulating sensory signaling across a range of ethologically relevant conditions.
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11
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Weiss DA, Borsa AMF, Pala A, Sederberg AJ, Stanley GB. A machine learning approach for real-time cortical state estimation. J Neural Eng 2024; 21:10.1088/1741-2552/ad1f7b. [PMID: 38232377 PMCID: PMC10868597 DOI: 10.1088/1741-2552/ad1f7b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/17/2024] [Indexed: 01/19/2024]
Abstract
Objective.Cortical function is under constant modulation by internally-driven, latent variables that regulate excitability, collectively known as 'cortical state'. Despite a vast literature in this area, the estimation of cortical state remains relatively ad hoc, and not amenable to real-time implementation. Here, we implement robust, data-driven, and fast algorithms that address several technical challenges for online cortical state estimation.Approach. We use unsupervised Gaussian mixture models to identify discrete, emergent clusters in spontaneous local field potential signals in cortex. We then extend our approach to a temporally-informed hidden semi-Markov model (HSMM) with Gaussian observations to better model and infer cortical state transitions. Finally, we implement our HSMM cortical state inference algorithms in a real-time system, evaluating their performance in emulation experiments.Main results. Unsupervised clustering approaches reveal emergent state-like structure in spontaneous electrophysiological data that recapitulate arousal-related cortical states as indexed by behavioral indicators. HSMMs enable cortical state inferences in a real-time context by modeling the temporal dynamics of cortical state switching. Using HSMMs provides robustness to state estimates arising from noisy, sequential electrophysiological data.Significance. To our knowledge, this work represents the first implementation of a real-time software tool for continuously decoding cortical states with high temporal resolution (40 ms). The software tools that we provide can facilitate our understanding of how cortical states dynamically modulate cortical function on a moment-by-moment basis and provide a basis for state-aware brain machine interfaces across health and disease.
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Affiliation(s)
- David A Weiss
- Program in Bioengineering, Georgia Institute of Technology, Atlanta, GA, USA
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Adriano MF Borsa
- Program in Bioengineering, Georgia Institute of Technology, Atlanta, GA, USA
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Aurélie Pala
- Department of Biology, Emory University, Atlanta, GA, USA
| | - Audrey J Sederberg
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN
- Medical Discovery Team in Optical Imaging and Brain Science, University of Minnesota, Minneapolis, MN
| | - Garrett B Stanley
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
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12
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Sibille J, Gehr C, Kremkow J. Efficient mapping of the thalamocortical monosynaptic connectivity in vivo by tangential insertions of high-density electrodes in the cortex. Proc Natl Acad Sci U S A 2024; 121:e2313048121. [PMID: 38241439 PMCID: PMC10823237 DOI: 10.1073/pnas.2313048121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 12/13/2023] [Indexed: 01/21/2024] Open
Abstract
The thalamus provides the principal input to the cortex and therefore understanding the mechanisms underlying cortical integration of sensory inputs requires to characterize the thalamocortical connectivity in behaving animals. Here, we propose tangential insertions of high-density electrodes into mouse cortical layer 4 as a method to capture the activity of thalamocortical axons simultaneously with their synaptically connected cortical neurons. This technique can reliably monitor multiple parallel thalamic synaptic inputs to cortical neurons, providing an efficient approach to map thalamocortical connectivity in both awake and anesthetized mice.
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Affiliation(s)
- Jérémie Sibille
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Berlin10117, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin10115, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin10115, Germany
- Einstein Center for Neurosciences Berlin, Berlin10117, Germany
| | - Carolin Gehr
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Berlin10117, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin10115, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin10115, Germany
- Einstein Center for Neurosciences Berlin, Berlin10117, Germany
| | - Jens Kremkow
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Berlin10117, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin10115, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin10115, Germany
- Einstein Center for Neurosciences Berlin, Berlin10117, Germany
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13
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Ho JC, Grigsby EM, Damiani A, Liang L, Balaguer JM, Kallakuri S, Barrios-Martinez J, Karapetyan V, Fields D, Gerszten PC, Kevin Hitchens T, Constantine T, Adams GM, Crammond DJ, Capogrosso M, Gonzalez-Martinez JA, Pirondini E. POTENTIATION OF CORTICO-SPINAL OUTPUT VIA TARGETED ELECTRICAL STIMULATION OF THE MOTOR THALAMUS. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.08.23286720. [PMID: 36945514 PMCID: PMC10029067 DOI: 10.1101/2023.03.08.23286720] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
Cerebral white matter lesions prevent cortico-spinal descending inputs from effectively activating spinal motoneurons, leading to loss of motor control. However, in most cases, the damage to cortico-spinal axons is incomplete offering a potential target for new therapies aimed at improving volitional muscle activation. Here we hypothesized that, by engaging direct excitatory connections to cortico-spinal motoneurons, stimulation of the motor thalamus could facilitate activation of surviving cortico-spinal fibers thereby potentiating motor output. To test this hypothesis, we identified optimal thalamic targets and stimulation parameters that enhanced upper-limb motor evoked potentials and grip forces in anesthetized monkeys. This potentiation persisted after white matter lesions. We replicated these results in humans during intra-operative testing. We then designed a stimulation protocol that immediately improved voluntary grip force control in a patient with a chronic white matter lesion. Our results show that electrical stimulation targeting surviving neural pathways can improve motor control after white matter lesions.
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Affiliation(s)
- Jonathan C. Ho
- School of Medicine, University of Pittsburgh, 3550 Terrace St, Pittsburgh, PA, USA 15213
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
| | - Erinn M. Grigsby
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, 3471 Fifth Avenue, Suite 910, Pittsburgh, PA, USA, 15213
| | - Arianna Damiani
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, 151 Benedum Hall, Pittsburgh, PA, USA, 15261
- Center for the Neural Basis of Cognition, 4400 Fifth Avenue, Suite 115, Pittsburgh, PA, USA, 15213
| | - Lucy Liang
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, 151 Benedum Hall, Pittsburgh, PA, USA, 15261
- Center for the Neural Basis of Cognition, 4400 Fifth Avenue, Suite 115, Pittsburgh, PA, USA, 15213
| | - Josep-Maria Balaguer
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, 151 Benedum Hall, Pittsburgh, PA, USA, 15261
- Center for the Neural Basis of Cognition, 4400 Fifth Avenue, Suite 115, Pittsburgh, PA, USA, 15213
| | - Sridula Kallakuri
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Neuroscience, University of Pittsburgh, A210 Langley Hall, Pittsburgh, PA, USA, 15260
| | - Jessica Barrios-Martinez
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
| | - Vahagn Karapetyan
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, 151 Benedum Hall, Pittsburgh, PA, USA, 15261
- Center for the Neural Basis of Cognition, 4400 Fifth Avenue, Suite 115, Pittsburgh, PA, USA, 15213
| | - Daryl Fields
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
| | - Peter C. Gerszten
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
| | - T. Kevin Hitchens
- Department of Neurobiology, University of Pittsburgh, 200 Lothrop Street, Room E1440, Pittsburgh, PA, USA, 15213
| | - Theodora Constantine
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
| | - Gregory M. Adams
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
| | - Donald J. Crammond
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
| | - Marco Capogrosso
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, 151 Benedum Hall, Pittsburgh, PA, USA, 15261
- Center for the Neural Basis of Cognition, 4400 Fifth Avenue, Suite 115, Pittsburgh, PA, USA, 15213
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
| | - Jorge A. Gonzalez-Martinez
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
- Department of Neurobiology, University of Pittsburgh, 200 Lothrop Street, Room E1440, Pittsburgh, PA, USA, 15213
| | - Elvira Pirondini
- Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA, USA, 15213
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, 3471 Fifth Avenue, Suite 910, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, 151 Benedum Hall, Pittsburgh, PA, USA, 15261
- Center for the Neural Basis of Cognition, 4400 Fifth Avenue, Suite 115, Pittsburgh, PA, USA, 15213
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, suite b-400, Pittsburgh, PA, USA, 15213
- Department of Neurobiology, University of Pittsburgh, 200 Lothrop Street, Room E1440, Pittsburgh, PA, USA, 15213
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14
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Solis EM, Good LB, Vázquez RG, Patnaik S, Hernandez-Reynoso AG, Ma Q, Angulo G, Dobariya A, Cogan SF, Pancrazio JJ, Pascual JM, Jakkamsetti V. Isolation of the murine Glut1 deficient thalamocortical circuit: wavelet characterization and reverse glucose dependence of low and gamma frequency oscillations. Front Neurosci 2023; 17:1191492. [PMID: 37829723 PMCID: PMC10565352 DOI: 10.3389/fnins.2023.1191492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 08/25/2023] [Indexed: 10/14/2023] Open
Abstract
Glucose represents the principal brain energy source. Thus, not unexpectedly, genetic glucose transporter 1 (Glut1) deficiency (G1D) manifests with encephalopathy. G1D seizures, which constitute a prominent disease manifestation, often prove refractory to medications but may respond to therapeutic diets. These seizures are associated with aberrant thalamocortical oscillations as inferred from human electroencephalography and functional imaging. Mouse electrophysiological recordings indicate that inhibitory neuron failure in thalamus and cortex underlies these abnormalities. This provides the motivation to develop a neural circuit testbed to characterize the mechanisms of thalamocortical synchronization and the effects of known or novel interventions. To this end, we used mouse thalamocortical slices on multielectrode arrays and characterized spontaneous low frequency oscillations and less frequent 30-50 Hz or gamma oscillations under near-physiological bath glucose concentration. Using the cortical recordings from layer IV among other regions recorded, we quantified oscillation epochs via an automated wavelet-based algorithm. This method proved analytically superior to power spectral density, short-time Fourier transform or amplitude-threshold detection. As expected from human observations, increased bath glucose reduced the lower frequency oscillations while augmenting the gamma oscillations, likely reflecting strengthened inhibitory neuron activity, and thus decreasing the low:high frequency ratio (LHR). This approach provides an ex vivo method for the evaluation of mechanisms, fuels, and pharmacological agents in a crucial G1D epileptogenic circuit.
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Affiliation(s)
- Elysandra M. Solis
- Department of Bioengineering, The University of Texas at Dallas, Richardson, TX, United States
| | - Levi B. Good
- Department of Bioengineering, The University of Texas at Dallas, Richardson, TX, United States
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Rafael Granja Vázquez
- Department of Neuroscience and the Center for Advanced Pain Studies, The University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Sourav Patnaik
- Department of Bioengineering, The University of Texas at Dallas, Richardson, TX, United States
| | | | - Qian Ma
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Gustavo Angulo
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Aksharkumar Dobariya
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Stuart F. Cogan
- Department of Bioengineering, The University of Texas at Dallas, Richardson, TX, United States
| | - Joseph J. Pancrazio
- Department of Bioengineering, The University of Texas at Dallas, Richardson, TX, United States
| | - Juan M. Pascual
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Department of Physiology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Department of Pediatrics, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Eugene McDermott Center for Human Growth & Development/Center for Human Genetics, The University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Vikram Jakkamsetti
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, TX, United States
- Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
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15
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Solis EM, Good LB, Granja Vázquez R, Patnaik S, Hernandez-Reynoso AG, Ma Q, Angulo G, Dobariya A, Cogan SF, Pancrazio JJ, Pascual JM, Jakkamsetti V. Isolation of the murine Glut1 deficient thalamocortical circuit: wavelet characterization and reverse glucose dependence of low and gamma frequency oscillations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.05.543611. [PMID: 37645928 PMCID: PMC10461930 DOI: 10.1101/2023.06.05.543611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Glucose represents the principal brain energy source. Thus, not unexpectedly, genetic glucose transporter 1 (Glut1) deficiency (G1D) manifests with encephalopathy. G1D seizures, which constitute a prominent disease manifestation, often prove refractory to medications but may respond to therapeutic diets. These seizures are associated with aberrant thalamocortical oscillations as inferred from human electroencephalography and functional imaging. Mouse electrophysiological recordings indicate that inhibitory neuron failure in thalamus and cortex underlies these abnormalities. This provides the motivation to develop a neural circuit testbed to characterize the mechanisms of thalamocortical synchronization and the effects of known or novel interventions. To this end, we used mouse thalamocortical slices on multielectrode arrays and characterized spontaneous low frequency oscillations and less frequent 30-50 Hz or gamma oscillations under near-physiological bath glucose concentration. Using the cortical recordings from layer IV, we quantified oscillation epochs via an automated wavelet-based algorithm. This method proved analytically superior to power spectral density, short-time Fourier transform or amplitude-threshold detection. As expected from human observations, increased bath glucose reduced the lower frequency oscillations while augmenting the gamma oscillations, likely reflecting strengthened inhibitory neuron activity. This approach provides an ex vivo method for the evaluation of mechanisms, fuels, and pharmacological agents in a crucial G1D epileptogenic circuit.
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Affiliation(s)
- Elysandra M. Solis
- Department of Bioengineering; The University of Texas at Dallas, Richardson, Texas, USA
| | - Levi B. Good
- Department of Bioengineering; The University of Texas at Dallas, Richardson, Texas, USA
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neurology; The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Rafael Granja Vázquez
- Department of Bioengineering; The University of Texas at Dallas, Richardson, Texas, USA
| | - Sourav Patnaik
- Department of Bioengineering; The University of Texas at Dallas, Richardson, Texas, USA
| | | | - Qian Ma
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neurology; The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Gustavo Angulo
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neurology; The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Aksharkumar Dobariya
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neurology; The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Stuart F. Cogan
- Department of Bioengineering; The University of Texas at Dallas, Richardson, Texas, USA
| | - Joseph J. Pancrazio
- Department of Bioengineering; The University of Texas at Dallas, Richardson, Texas, USA
| | - Juan M. Pascual
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neurology; The University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Physiology; The University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Pediatrics; The University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Eugene McDermott Center for Human Growth & Development / Center for Human Genetics; The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Vikram Jakkamsetti
- Department of Bioengineering; The University of Texas at Dallas, Richardson, Texas, USA
- Rare Brain Disorders Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
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16
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Trepka EB, Zhu S, Xia R, Chen X, Moore T. Functional interactions among neurons within single columns of macaque V1. eLife 2022; 11:e79322. [PMID: 36321687 PMCID: PMC9662816 DOI: 10.7554/elife.79322] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 10/30/2022] [Indexed: 11/16/2022] Open
Abstract
Recent developments in high-density neurophysiological tools now make it possible to record from hundreds of single neurons within local, highly interconnected neural networks. Among the many advantages of such recordings is that they dramatically increase the quantity of identifiable, functional interactions between neurons thereby providing an unprecedented view of local circuits. Using high-density, Neuropixels recordings from single neocortical columns of primary visual cortex in nonhuman primates, we identified 1000s of functionally interacting neuronal pairs using established crosscorrelation approaches. Our results reveal clear and systematic variations in the synchrony and strength of functional interactions within single cortical columns. Despite neurons residing within the same column, both measures of interactions depended heavily on the vertical distance separating neuronal pairs, as well as on the similarity of stimulus tuning. In addition, we leveraged the statistical power afforded by the large numbers of functionally interacting pairs to categorize interactions between neurons based on their crosscorrelation functions. These analyses identified distinct, putative classes of functional interactions within the full population. These classes of functional interactions were corroborated by their unique distributions across defined laminar compartments and were consistent with known properties of V1 cortical circuitry, such as the lead-lag relationship between simple and complex cells. Our results provide a clear proof-of-principle for the use of high-density neurophysiological recordings to assess circuit-level interactions within local neuronal networks.
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Affiliation(s)
- Ethan B Trepka
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
- Neurosciences Program, Stanford UniversityStanfordUnited States
| | - Shude Zhu
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Ruobing Xia
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Xiaomo Chen
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
- Center for Neuroscience, Department of Neurobiology, Physiology, and Behavior, University of California, DavisDavisUnited States
| | - Tirin Moore
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
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17
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Sibille J, Gehr C, Benichov JI, Balasubramanian H, Teh KL, Lupashina T, Vallentin D, Kremkow J. High-density electrode recordings reveal strong and specific connections between retinal ganglion cells and midbrain neurons. Nat Commun 2022; 13:5218. [PMID: 36064789 PMCID: PMC9445019 DOI: 10.1038/s41467-022-32775-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 08/16/2022] [Indexed: 11/29/2022] Open
Abstract
The superior colliculus is a midbrain structure that plays important roles in visually guided behaviors in mammals. Neurons in the superior colliculus receive inputs from retinal ganglion cells but how these inputs are integrated in vivo is unknown. Here, we discovered that high-density electrodes simultaneously capture the activity of retinal axons and their postsynaptic target neurons in the superior colliculus, in vivo. We show that retinal ganglion cell axons in the mouse provide a single cell precise representation of the retina as input to superior colliculus. This isomorphic mapping builds the scaffold for precise retinotopic wiring and functionally specific connection strength. Our methods are broadly applicable, which we demonstrate by recording retinal inputs in the optic tectum in zebra finches. We find common wiring rules in mice and zebra finches that provide a precise representation of the visual world encoded in retinal ganglion cells connections to neurons in retinorecipient areas.
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Affiliation(s)
- Jérémie Sibille
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Carolin Gehr
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Jonathan I Benichov
- Max Planck Institute for Ornithology, Eberhard-Gwinner Straße, 82319, Seewiesen, Germany
- Max Planck Institute for Biological Intelligence (in foundation), Eberhard-Gwinner Straße, 82319, Seewiesen, Germany
| | - Hymavathy Balasubramanian
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Kai Lun Teh
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Tatiana Lupashina
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Daniela Vallentin
- Max Planck Institute for Ornithology, Eberhard-Gwinner Straße, 82319, Seewiesen, Germany
- Max Planck Institute for Biological Intelligence (in foundation), Eberhard-Gwinner Straße, 82319, Seewiesen, Germany
| | - Jens Kremkow
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, 10115, Berlin, Germany.
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany.
- Einstein Center for Neurosciences Berlin, Charitéplatz 1, 10117, Berlin, Germany.
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18
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Xue X, Buccino AP, Kumar SS, Hierlemann A, Bartram J. Inferring monosynaptic connections from paired dendritic spine Ca 2+imaging and large-scale recording of extracellular spiking. J Neural Eng 2022; 19:046044. [PMID: 35931040 PMCID: PMC7613561 DOI: 10.1088/1741-2552/ac8765] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/05/2022] [Indexed: 11/12/2022]
Abstract
Objective: Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others.Approach: Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays.Main results: We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it onin vitrorecordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+transients based on measured spike trains in order to obtain simulated ground-truth connections.Significance: The proposed approach offers unique advantages as (a) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, (b) it provides precise information of presynaptic spiking, and (c) postsynaptic spine Ca2+signals and, finally, (d) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.
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19
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KC E, Islam J, Kim S, Kim HK, Park YS. Pain Relief in a Trigeminal Neuralgia Model via Optogenetic Inhibition on Trigeminal Ganglion Itself With Flexible Optic Fiber Cannula. Front Cell Neurosci 2022; 16:880369. [PMID: 35573830 PMCID: PMC9096083 DOI: 10.3389/fncel.2022.880369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 03/22/2022] [Indexed: 11/29/2022] Open
Abstract
The trigeminal ganglion (TG) is the primary site of aberration in trigeminal neuralgia (TN), and hence a crucial site where afferent input can be modulated. Here, we postulated that inhibiting TG via optogenetics using flexible optic cannula would diminish brainstem trigeminal nucleus caudalis (TNC) neuronal activity and pain behavior in TN rat model. Infraorbital nerve constriction was employed to induce TN in female Sprague-Dawley rats, while naive and sham rats served as controls. TG-directed microinjections of AAV virus containing either the optogenetic or null vector were delivered to rats in each group. In vivo electrophysiological responses were obtained from the ventral posteromedial nucleus (VPm) of the thalamus with simultaneous TG optogenetic stimulation using flexible optic cannula as well the effects on behavioral responses were investigated. Recordings in TN rats revealed a decrease in burst firing activity during yellow laser driven inhibition on TG, as well as considerably improved behavioral responses. In contrast, we noticed persistent hypersensitivity and increased tonic firing with blue laser stimulation which indicates that TG inhibition can synchronize trigeminal pain signal transmission in a TN animal model. The potential of an optogenetic approach in TG itself with flexible optic fiber to directly disrupt the trigeminal pain circuitry delivers fundamental underpinnings toward its prospective as a trigeminal neuralgia management.
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Affiliation(s)
- Elina KC
- Department of Medical Neuroscience, College of Medicine, Chungbuk National University, Cheongju, South Korea
| | - Jaisan Islam
- Department of Medical Neuroscience, College of Medicine, Chungbuk National University, Cheongju, South Korea
| | - Soochong Kim
- Department of Veterinary Medicine, College of Veterinary Medicine, Chungbuk National University, Cheongju, South Korea
| | - Hyong Kyu Kim
- Department of Medicine and Microbiology, College of Medicine, Chungbuk National University, Cheongju, South Korea
| | - Young Seok Park
- Department of Medical Neuroscience, College of Medicine, Chungbuk National University, Cheongju, South Korea
- Department of Neurosurgery, Chungbuk National University Hospital, Cheongju, South Korea
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Wang C, Pesaran B, Shanechi MM. Modeling multiscale causal interactions between spiking and field potential signals during behavior. J Neural Eng 2022; 19:10.1088/1741-2552/ac4e1c. [PMID: 35073530 PMCID: PMC11524050 DOI: 10.1088/1741-2552/ac4e1c] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 01/24/2022] [Indexed: 11/12/2022]
Abstract
Objective.Brain recordings exhibit dynamics at multiple spatiotemporal scales, which are measured with spike trains and larger-scale field potential signals. To study neural processes, it is important to identify and model causal interactions not only at a single scale of activity, but also across multiple scales, i.e. between spike trains and field potential signals. Standard causality measures are not directly applicable here because spike trains are binary-valued but field potentials are continuous-valued. It is thus important to develop computational tools to recover multiscale neural causality during behavior, assess their performance on neural datasets, and study whether modeling multiscale causalities can improve the prediction of neural signals beyond what is possible with single-scale causality.Approach.We design a multiscale model-based Granger-like causality method based on directed information and evaluate its success both in realistic biophysical spike-field simulations and in motor cortical datasets from two non-human primates (NHP) performing a motor behavior. To compute multiscale causality, we learn point-process generalized linear models that predict the spike events at a given time based on the history of both spike trains and field potential signals. We also learn linear Gaussian models that predict the field potential signals at a given time based on their own history as well as either the history of binary spike events or that of latent firing rates.Main results.We find that our method reveals the true multiscale causality network structure in biophysical simulations despite the presence of model mismatch. Further, models with the identified multiscale causalities in the NHP neural datasets lead to better prediction of both spike trains and field potential signals compared to just modeling single-scale causalities. Finally, we find that latent firing rates are better predictors of field potential signals compared with the binary spike events in the NHP datasets.Significance.This multiscale causality method can reveal the directed functional interactions across spatiotemporal scales of brain activity to inform basic science investigations and neurotechnologies.
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Affiliation(s)
- Chuanmeizhi Wang
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States of America
| | - Bijan Pesaran
- Center for Neural Sciences, New York University, New York, NY, United States of America
| | - Maryam M Shanechi
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States of America
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, United States of America
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States of America
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Wright NC, Borden PY, Liew YJ, Bolus MF, Stoy WM, Forest CR, Stanley GB. Rapid Cortical Adaptation and the Role of Thalamic Synchrony during Wakefulness. J Neurosci 2021; 41:5421-5439. [PMID: 33986072 PMCID: PMC8221593 DOI: 10.1523/jneurosci.3018-20.2021] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/18/2021] [Accepted: 04/29/2021] [Indexed: 12/14/2022] Open
Abstract
Rapid sensory adaptation is observed across all sensory systems, and strongly shapes sensory percepts in complex sensory environments. Yet despite its ubiquity and likely necessity for survival, the mechanistic basis is poorly understood. A wide range of primarily in vitro and anesthetized studies have demonstrated the emergence of adaptation at the level of primary sensory cortex, with only modest signatures in earlier stages of processing. The nature of rapid adaptation and how it shapes sensory representations during wakefulness, and thus the potential role in perceptual adaptation, is underexplored, as are the mechanisms that underlie this phenomenon. To address these knowledge gaps, we recorded spiking activity in primary somatosensory cortex (S1) and the upstream ventral posteromedial (VPm) thalamic nucleus in the vibrissa pathway of awake male and female mice, and quantified responses to whisker stimuli delivered in isolation and embedded in an adapting sensory background. We found that cortical sensory responses were indeed adapted by persistent sensory stimulation; putative excitatory neurons were profoundly adapted, and inhibitory neurons only modestly so. Further optogenetic manipulation experiments and network modeling suggest this largely reflects adaptive changes in synchronous thalamic firing combined with robust engagement of feedforward inhibition, with little contribution from synaptic depression. Taken together, these results suggest that cortical adaptation in the regime explored here results from changes in the timing of thalamic input, and the way in which this differentially impacts cortical excitation and feedforward inhibition, pointing to a prominent role of thalamic gating in rapid adaptation of primary sensory cortex.SIGNIFICANCE STATEMENT Rapid adaptation of sensory activity strongly shapes representations of sensory inputs across all sensory pathways over the timescale of seconds, and has profound effects on sensory perception. Despite its ubiquity and theoretical role in the efficient encoding of complex sensory environments, the mechanistic basis is poorly understood, particularly during wakefulness. In this study in the vibrissa pathway of awake mice, we show that cortical representations of sensory inputs are strongly shaped by rapid adaptation, and that this is mediated primarily by adaptive gating of the thalamic inputs to primary sensory cortex and the differential way in which these inputs engage cortical subpopulations of neurons.
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Affiliation(s)
- Nathaniel C Wright
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332
| | - Peter Y Borden
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332
| | - Yi Juin Liew
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, Georgia 30332 and Beijing University, Beijing China 100871
| | - Michael F Bolus
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332
| | - William M Stoy
- Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332
| | - Craig R Forest
- Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332
| | - Garrett B Stanley
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332
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