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Del Rosario J, Coletta S, Kim SH, Mobille Z, Peelman K, Williams B, Otsuki AJ, Del Castillo Valerio A, Worden K, Blanpain LT, Lovell L, Choi H, Haider B. Lateral inhibition in V1 controls neural & perceptual contrast sensitivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.10.566605. [PMID: 38014014 PMCID: PMC10680635 DOI: 10.1101/2023.11.10.566605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with anatomy and direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.
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2
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Negrón A, Getz MP, Handy G, Doiron B. The mechanics of correlated variability in segregated cortical excitatory subnetworks. Proc Natl Acad Sci U S A 2024; 121:e2306800121. [PMID: 38959037 PMCID: PMC11252788 DOI: 10.1073/pnas.2306800121] [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: 04/25/2023] [Accepted: 04/03/2024] [Indexed: 07/04/2024] Open
Abstract
Understanding the genesis of shared trial-to-trial variability in neuronal population activity within the sensory cortex is critical to uncovering the biological basis of information processing in the brain. Shared variability is often a reflection of the structure of cortical connectivity since it likely arises, in part, from local circuit inputs. A series of experiments from segregated networks of (excitatory) pyramidal neurons in the mouse primary visual cortex challenge this view. Specifically, the across-network correlations were found to be larger than predicted given the known weak cross-network connectivity. We aim to uncover the circuit mechanisms responsible for these enhanced correlations through biologically motivated cortical circuit models. Our central finding is that coupling each excitatory subpopulation with a specific inhibitory subpopulation provides the most robust network-intrinsic solution in shaping these enhanced correlations. This result argues for the existence of excitatory-inhibitory functional assemblies in early sensory areas which mirror not just response properties but also connectivity between pyramidal cells. Furthermore, our findings provide theoretical support for recent experimental observations showing that cortical inhibition forms structural and functional subnetworks with excitatory cells, in contrast to the classical view that inhibition is a nonspecific blanket suppression of local excitation.
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Affiliation(s)
- Alex Negrón
- Department of Applied Mathematics, Illinois Institute of Technology, Chicago, IL60616
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL60637
| | - Matthew P. Getz
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL60637
- Department of Neurobiology, University of Chicago, Chicago, IL60637
- Department of Statistics, University of Chicago, Chicago, IL60637
| | - Gregory Handy
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL60637
- Department of Neurobiology, University of Chicago, Chicago, IL60637
- Department of Statistics, University of Chicago, Chicago, IL60637
| | - Brent Doiron
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL60637
- Department of Neurobiology, University of Chicago, Chicago, IL60637
- Department of Statistics, University of Chicago, Chicago, IL60637
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3
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Shields BC, Yan H, Lim SSX, Burwell SCV, Cammarata CM, Fleming EA, Yousefzadeh SA, Goldenshtein VZ, Kahuno EW, Vagadia PP, Loughran MH, Zhiquan L, McDonnell ME, Scalabrino ML, Thapa M, Hawley TM, Field GD, Hull C, Schiltz GE, Glickfeld LL, Reitz AB, Tadross MR. DART.2: bidirectional synaptic pharmacology with thousandfold cellular specificity. Nat Methods 2024; 21:1288-1297. [PMID: 38877316 DOI: 10.1038/s41592-024-02292-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 04/25/2024] [Indexed: 06/16/2024]
Abstract
Precision pharmacology aims to manipulate specific cellular interactions within complex tissues. In this pursuit, we introduce DART.2 (drug acutely restricted by tethering), a second-generation cell-specific pharmacology technology. The core advance is optimized cellular specificity-up to 3,000-fold in 15 min-enabling the targeted delivery of even epileptogenic drugs without off-target effects. Additionally, we introduce brain-wide dosing methods as an alternative to local cannulation and tracer reagents for brain-wide dose quantification. We describe four pharmaceuticals-two that antagonize excitatory and inhibitory postsynaptic receptors, and two that allosterically potentiate these receptors. Their versatility is showcased across multiple mouse-brain regions, including cerebellum, striatum, visual cortex and retina. Finally, in the ventral tegmental area, we find that blocking inhibitory inputs to dopamine neurons accelerates locomotion, contrasting with previous optogenetic and pharmacological findings. Beyond enabling the bidirectional perturbation of chemical synapses, these reagents offer intersectional precision-between genetically defined postsynaptic cells and neurotransmitter-defined presynaptic partners.
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Affiliation(s)
- Brenda C Shields
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Haidun Yan
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Shaun S X Lim
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | | | | | | | | | | | - Purav P Vagadia
- Department of Chemistry, Northwestern University, Evanston, IL, USA
| | | | - Lei Zhiquan
- Department of Chemistry, Northwestern University, Evanston, IL, USA
| | | | | | - Mishek Thapa
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Tammy M Hawley
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Greg D Field
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Court Hull
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Gary E Schiltz
- Department of Chemistry, Northwestern University, Evanston, IL, USA
| | | | - Allen B Reitz
- Fox Chase Therapeutics Discovery, Inc., Doylestown, PA, USA
| | - Michael R Tadross
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Department of Neurobiology, Duke University, Durham, NC, USA.
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4
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Capitano F, Kuchenbuch M, Lavigne J, Chaptoukaev H, Zuluaga MA, Lorenzi M, Nabbout R, Mantegazza M. Preictal dysfunctions of inhibitory interneurons paradoxically lead to their rebound hyperactivity and to low-voltage-fast onset seizures in Dravet syndrome. Proc Natl Acad Sci U S A 2024; 121:e2316364121. [PMID: 38809712 PMCID: PMC11161744 DOI: 10.1073/pnas.2316364121] [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: 09/26/2023] [Accepted: 05/01/2024] [Indexed: 05/31/2024] Open
Abstract
Epilepsies have numerous specific mechanisms. The understanding of neural dynamics leading to seizures is important for disclosing pathological mechanisms and developing therapeutic approaches. We investigated electrographic activities and neural dynamics leading to convulsive seizures in patients and mouse models of Dravet syndrome (DS), a developmental and epileptic encephalopathy in which hypoexcitability of GABAergic neurons is considered to be the main dysfunction. We analyzed EEGs from DS patients carrying a SCN1A pathogenic variant, as well as epidural electrocorticograms, hippocampal local field potentials, and hippocampal single-unit neuronal activities in Scn1a+/- and Scn1aRH/+ DS mice. Strikingly, most seizures had low-voltage-fast onset in both patients and mice, which is thought to be generated by hyperactivity of GABAergic interneurons, the opposite of the main pathological mechanism of DS. Analyzing single-unit recordings, we observed that temporal disorganization of the firing of putative interneurons in the period immediately before the seizure (preictal) precedes the increase of their activity at seizure onset, together with the entire neuronal network. Moreover, we found early signatures of the preictal period in the spectral features of hippocampal and cortical field potential of Scn1a mice and of patients' EEG, which are consistent with the dysfunctions that we observed in single neurons and that allowed seizure prediction. Therefore, the perturbed preictal activity of interneurons leads to their hyperactivity at the onset of generalized seizures, which have low-voltage-fast features that are similar to those observed in other epilepsies and are triggered by hyperactivity of GABAergic neurons. Preictal spectral features may be used as predictive seizure biomarkers.
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Affiliation(s)
- Fabrizio Capitano
- University Cote d’Azur, Institute of Molecular and Cellular Pharmacology, Valbonne-Sophia Antipolis06560, France
- CNRS UMR 7275, Valbonne-Sophia Antipolis06560, France
- Inserm U1323, Valbonne-Sophia Antipolis06650, France
| | - Mathieu Kuchenbuch
- Reference Centre for Rare Epilepsies, Member of European Reference Network EpiCARE, Department of Pediatric Neurology, Hôpital Necker-Enfants Malades, Assistance Publique Hôpitaux de Paris, Paris75015, France
- Laboratory of Translational Research for Neurological Disorders, Inserm UMR 1163, Imagine Institute, Université Paris Cité, Paris75015, France
| | - Jennifer Lavigne
- University Cote d’Azur, Institute of Molecular and Cellular Pharmacology, Valbonne-Sophia Antipolis06560, France
- CNRS UMR 7275, Valbonne-Sophia Antipolis06560, France
- Inserm U1323, Valbonne-Sophia Antipolis06650, France
| | | | | | - Marco Lorenzi
- University Cote d’Azur, Institute of Molecular and Cellular Pharmacology, Valbonne-Sophia Antipolis06560, France
- Epione Research team, Inria Center of Université Côte d’Azur, Biot-Sophia Antipolis06410, France
| | - Rima Nabbout
- Reference Centre for Rare Epilepsies, Member of European Reference Network EpiCARE, Department of Pediatric Neurology, Hôpital Necker-Enfants Malades, Assistance Publique Hôpitaux de Paris, Paris75015, France
- Laboratory of Translational Research for Neurological Disorders, Inserm UMR 1163, Imagine Institute, Université Paris Cité, Paris75015, France
| | - Massimo Mantegazza
- University Cote d’Azur, Institute of Molecular and Cellular Pharmacology, Valbonne-Sophia Antipolis06560, France
- CNRS UMR 7275, Valbonne-Sophia Antipolis06560, France
- Inserm U1323, Valbonne-Sophia Antipolis06650, France
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Holt CJ, Miller KD, Ahmadian Y. The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations. PLoS Comput Biol 2024; 20:e1012190. [PMID: 38935792 PMCID: PMC11236182 DOI: 10.1371/journal.pcbi.1012190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 07/10/2024] [Accepted: 05/23/2024] [Indexed: 06/29/2024] Open
Abstract
When stimulated, neural populations in the visual cortex exhibit fast rhythmic activity with frequencies in the gamma band (30-80 Hz). The gamma rhythm manifests as a broad resonance peak in the power-spectrum of recorded local field potentials, which exhibits various stimulus dependencies. In particular, in macaque primary visual cortex (V1), the gamma peak frequency increases with increasing stimulus contrast. Moreover, this contrast dependence is local: when contrast varies smoothly over visual space, the gamma peak frequency in each cortical column is controlled by the local contrast in that column's receptive field. No parsimonious mechanistic explanation for these contrast dependencies of V1 gamma oscillations has been proposed. The stabilized supralinear network (SSN) is a mechanistic model of cortical circuits that has accounted for a range of visual cortical response nonlinearities and contextual modulations, as well as their contrast dependence. Here, we begin by showing that a reduced SSN model without retinotopy robustly captures the contrast dependence of gamma peak frequency, and provides a mechanistic explanation for this effect based on the observed non-saturating and supralinear input-output function of V1 neurons. Given this result, the local dependence on contrast can trivially be captured in a retinotopic SSN which however lacks horizontal synaptic connections between its cortical columns. However, long-range horizontal connections in V1 are in fact strong, and underlie contextual modulation effects such as surround suppression. We thus explored whether a retinotopically organized SSN model of V1 with strong excitatory horizontal connections can exhibit both surround suppression and the local contrast dependence of gamma peak frequency. We found that retinotopic SSNs can account for both effects, but only when the horizontal excitatory projections are composed of two components with different patterns of spatial fall-off with distance: a short-range component that only targets the source column, combined with a long-range component that targets columns neighboring the source column. We thus make a specific qualitative prediction for the spatial structure of horizontal connections in macaque V1, consistent with the columnar structure of cortex.
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Affiliation(s)
- Caleb J Holt
- Department of Physics, Institute of Neuroscience, University of Oregon, Eugene, Oregon, United States of America
| | - Kenneth D Miller
- Deptartment of Neuroscience, Center for Theoretical Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, College of Physicians and Surgeons, and Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, New York, United States of America
| | - Yashar Ahmadian
- Department of Engineering, Computational and Biological Learning Lab, University of Cambridge, Cambridge, United Kingdom
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Zarei Eskikand P, Soto-Breceda A, Cook MJ, Burkitt AN, Grayden DB. Inhibitory stabilized network behaviour in a balanced neural mass model of a cortical column. Neural Netw 2023; 166:296-312. [PMID: 37541162 DOI: 10.1016/j.neunet.2023.07.020] [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: 03/08/2023] [Revised: 06/16/2023] [Accepted: 07/12/2023] [Indexed: 08/06/2023]
Abstract
Strong inhibitory recurrent connections can reduce the tendency for a neural network to become unstable. This is known as inhibitory stabilization; networks that are unstable in the absence of strong inhibitory feedback because of their unstable excitatory recurrent connections are known as Inhibition Stabilized Networks (ISNs). One of the characteristics of ISNs is their "paradoxical response", where perturbing the inhibitory neurons with additional excitatory input results in a decrease in their activity after a temporal delay instead of increasing their activity. Here, we develop a model of populations of neurons across different layers of cortex. Within each layer, there is one population of inhibitory neurons and one population of excitatory neurons. The connectivity weights across different populations in the model are derived from a synaptic physiology database provided by the Allen Institute. The model shows a gradient of excitation-inhibition balance across different layers in the cortex, where superficial layers are more inhibitory dominated compared to deeper layers. To investigate the presence of ISNs across different layers, we measured the membrane potentials of neural populations in the model after perturbing inhibitory populations. The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime. These results accord with neurophysiological findings that explored the presence of ISNs across different layers in the cortex. The results show that there may be a systematic macroscopic gradient of inhibitory stabilization across different layers in the cortex that depends on the level of excitation-inhibition balance, and that the strength of the paradoxical response increases as the model moves closer to bifurcation points.
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Affiliation(s)
- Parvin Zarei Eskikand
- Department of Biomedical Engineering, The University of Melbourne, Victoria, Australia.
| | - Artemio Soto-Breceda
- Department of Biomedical Engineering, The University of Melbourne, Victoria, Australia
| | - Mark J Cook
- Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Victoria, Australia; Department of Medicine, St Vincent's Hospital, Melbourne, Victoria, Australia
| | - Anthony N Burkitt
- Department of Biomedical Engineering, The University of Melbourne, Victoria, Australia
| | - David B Grayden
- Department of Biomedical Engineering, The University of Melbourne, Victoria, Australia; Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Victoria, Australia; Department of Medicine, St Vincent's Hospital, Melbourne, Victoria, Australia
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7
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Kumar M, Handy G, Kouvaros S, Zhao Y, Brinson LL, Wei E, Bizup B, Doiron B, Tzounopoulos T. Cell-type-specific plasticity of inhibitory interneurons in the rehabilitation of auditory cortex after peripheral damage. Nat Commun 2023; 14:4170. [PMID: 37443148 PMCID: PMC10345144 DOI: 10.1038/s41467-023-39732-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
Peripheral sensory organ damage leads to compensatory cortical plasticity that is associated with a remarkable recovery of cortical responses to sound. The precise mechanisms that explain how this plasticity is implemented and distributed over a diverse collection of excitatory and inhibitory cortical neurons remain unknown. After noise trauma and persistent peripheral deficits, we found recovered sound-evoked activity in mouse A1 excitatory principal neurons (PNs), parvalbumin- and vasoactive intestinal peptide-expressing neurons (PVs and VIPs), but reduced activity in somatostatin-expressing neurons (SOMs). This cell-type-specific recovery was also associated with cell-type-specific intrinsic plasticity. These findings, along with our computational modelling results, are consistent with the notion that PV plasticity contributes to PN stability, SOM plasticity allows for increased PN and PV activity, and VIP plasticity enables PN and PV recovery by inhibiting SOMs.
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Affiliation(s)
- Manoj Kumar
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA.
| | - Gregory Handy
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, 60637, USA
| | - Stylianos Kouvaros
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Yanjun Zhao
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Lovisa Ljungqvist Brinson
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Eric Wei
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Brandon Bizup
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Brent Doiron
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, 60637, USA
| | - Thanos Tzounopoulos
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA.
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8
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Holt CJ, Miller KD, Ahmadian Y. The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.11.540442. [PMID: 37214812 PMCID: PMC10197697 DOI: 10.1101/2023.05.11.540442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
When stimulated, neural populations in the visual cortex exhibit fast rhythmic activity with frequencies in the gamma band (30-80 Hz). The gamma rhythm manifests as a broad resonance peak in the power-spectrum of recorded local field potentials, which exhibits various stimulus dependencies. In particular, in macaque primary visual cortex (V1), the gamma peak frequency increases with increasing stimulus contrast. Moreover, this contrast dependence is local: when contrast varies smoothly over visual space, the gamma peak frequency in each cortical column is controlled by the local contrast in that column's receptive field. No parsimonious mechanistic explanation for these contrast dependencies of V1 gamma oscillations has been proposed. The stabilized supralinear network (SSN) is a mechanistic model of cortical circuits that has accounted for a range of visual cortical response nonlinearities and contextual modulations, as well as their contrast dependence. Here, we begin by showing that a reduced SSN model without retinotopy robustly captures the contrast dependence of gamma peak frequency, and provides a mechanistic explanation for this effect based on the observed non-saturating and supralinear input-output function of V1 neurons. Given this result, the local dependence on contrast can trivially be captured in a retinotopic SSN which however lacks horizontal synaptic connections between its cortical columns. However, long-range horizontal connections in V1 are in fact strong, and underlie contextual modulation effects such as surround suppression. We thus explored whether a retinotopically organized SSN model of V1 with strong excitatory horizontal connections can exhibit both surround suppression and the local contrast dependence of gamma peak frequency. We found that retinotopic SSNs can account for both effects, but only when the horizontal excitatory projections are composed of two components with different patterns of spatial fall-off with distance: a short-range component that only targets the source column, combined with a long-range component that targets columns neighboring the source column. We thus make a specific qualitative prediction for the spatial structure of horizontal connections in macaque V1, consistent with the columnar structure of cortex.
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Affiliation(s)
- Caleb J Holt
- Institute of Neuroscience, Department of Physics, University of Oregon, OR, USA
| | - Kenneth D Miller
- Center for Theoretical Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, and Dept. of Neuroscience, College of Physicians and Surgeons and Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, NY, USA
| | - Yashar Ahmadian
- Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK
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Negrón A, Getz MP, Handy G, Doiron B. The mechanics of correlated variability in segregated cortical excitatory subnetworks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.25.538323. [PMID: 37162867 PMCID: PMC10168290 DOI: 10.1101/2023.04.25.538323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Understanding the genesis of shared trial-to-trial variability in neural activity within sensory cortex is critical to uncovering the biological basis of information processing in the brain. Shared variability is often a reflection of the structure of cortical connectivity since this variability likely arises, in part, from local circuit inputs. A series of experiments from segregated networks of (excitatory) pyramidal neurons in mouse primary visual cortex challenge this view. Specifically, the across-network correlations were found to be larger than predicted given the known weak cross-network connectivity. We aim to uncover the circuit mechanisms responsible for these enhanced correlations through biologically motivated cortical circuit models. Our central finding is that coupling each excitatory subpopulation with a specific inhibitory subpopulation provides the most robust network-intrinsic solution in shaping these enhanced correlations. This result argues for the existence of excitatory-inhibitory functional assemblies in early sensory areas which mirror not just response properties but also connectivity between pyramidal cells.
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Affiliation(s)
- Alex Negrón
- Department of Applied Mathematics, Illinois Institute of Technology
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago
| | - Matthew P. Getz
- Departments of Neurobiology and Statistics, University of Chicago
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago
| | - Gregory Handy
- Departments of Neurobiology and Statistics, University of Chicago
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago
| | - Brent Doiron
- Departments of Neurobiology and Statistics, University of Chicago
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago
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10
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Orekhova EV, Manyukhina VO, Galuta IA, Prokofyev AO, Goiaeva DE, Obukhova TS, Fadeev KA, Schneiderman JF, Stroganova TA. Gamma oscillations point to the role of primary visual cortex in atypical motion processing in autism. PLoS One 2023; 18:e0281531. [PMID: 36780507 PMCID: PMC9925089 DOI: 10.1371/journal.pone.0281531] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/25/2023] [Indexed: 02/15/2023] Open
Abstract
Neurophysiological studies suggest that abnormal neural inhibition may explain a range of sensory processing differences in autism spectrum disorders (ASD). In particular, the impaired ability of people with ASD to visually discriminate the motion direction of small-size objects and their reduced perceptual suppression of background-like visual motion may stem from deficient surround inhibition within the primary visual cortex (V1) and/or its atypical top-down modulation by higher-tier cortical areas. In this study, we estimate the contribution of abnormal surround inhibition to the motion-processing deficit in ASD. For this purpose, we used a putative correlate of surround inhibition-suppression of the magnetoencephalographic (MEG) gamma response (GR) caused by an increase in the drift rate of a large annular high-contrast grating. The motion direction discrimination thresholds for the gratings of different angular sizes (1° and 12°) were assessed in a separate psychophysical paradigm. The MEG data were collected in 42 boys with ASD and 37 typically developing (TD) boys aged 7-15 years. Psychophysical data were available in 33 and 34 of these participants, respectively. The results showed that the GR suppression in V1 was reduced in boys with ASD, while their ability to detect the direction of motion was compromised only in the case of small stimuli. In TD boys, the GR suppression directly correlated with perceptual suppression caused by increasing stimulus size, thus suggesting the role of the top-down modulations of V1 in surround inhibition. In ASD, weaker GR suppression was associated with the poor directional sensitivity to small stimuli, but not with perceptual suppression. These results strongly suggest that a local inhibitory deficit in V1 plays an important role in the reduction of directional sensitivity in ASD and that this perceptual deficit cannot be explained exclusively by atypical top-down modulation of V1 by higher-tier cortical areas.
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Affiliation(s)
- Elena V. Orekhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
- * E-mail:
| | - Viktoriya O. Manyukhina
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
- National Research University Higher School of Economics, Moscow, Russian Federation
| | - Ilia A. Galuta
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Andrey O. Prokofyev
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Dzerassa E. Goiaeva
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Tatiana S. Obukhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Kirill A. Fadeev
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Justin F. Schneiderman
- MedTech West and the Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden
| | - Tatiana A. Stroganova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
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11
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Altered visual cortex excitability in premenstrual dysphoric disorder: Evidence from magnetoencephalographic gamma oscillations and perceptual suppression. PLoS One 2022; 17:e0279868. [PMID: 36584199 PMCID: PMC9803314 DOI: 10.1371/journal.pone.0279868] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 12/15/2022] [Indexed: 12/31/2022] Open
Abstract
Premenstrual dysphoric disorder (PMDD) is a psychiatric condition characterized by extreme mood shifts during the luteal phase of the menstrual cycle (MC) due to abnormal sensitivity to neurosteroids and unbalanced neural excitation/inhibition (E/I) ratio. We hypothesized that in women with PMDD in the luteal phase, these factors would alter the frequency of magnetoencephalographic visual gamma oscillations, affect modulation of their power by excitatory drive, and decrease perceptual spatial suppression. Women with PMDD and control women were examined twice-during the follicular and luteal phases of their MC. We recorded visual gamma response (GR) while modulating the excitatory drive by increasing the drift rate of the high-contrast grating (static, 'slow', 'medium', and 'fast'). Contrary to our expectations, GR frequency was not affected in women with PMDD in either phase of the MC. GR power suppression, which is normally associated with a switch from the 'optimal' for GR slow drift rate to the medium drift rate, was reduced in women with PMDD and was the only GR parameter that distinguished them from control participants specifically in the luteal phase and predicted severity of their premenstrual symptoms. Over and above the atypical luteal GR suppression, in both phases of the MC women with PMDD had abnormally strong GR facilitation caused by a switch from the 'suboptimal' static to the 'optimal' slow drift rate. Perceptual spatial suppression did not differ between the groups but decreased from the follicular to the luteal phase only in PMDD women. The atypical modulation of GR power suggests that neuronal excitability in the visual cortex is constitutively elevated in PMDD and that this E/I imbalance is further exacerbated during the luteal phase. However, the unaltered GR frequency does not support the hypothesis of inhibitory neuron dysfunction in PMDD.
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12
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Miehl C, Gjorgjieva J. Stability and learning in excitatory synapses by nonlinear inhibitory plasticity. PLoS Comput Biol 2022; 18:e1010682. [PMID: 36459503 PMCID: PMC9718420 DOI: 10.1371/journal.pcbi.1010682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/25/2022] [Indexed: 12/03/2022] Open
Abstract
Synaptic changes are hypothesized to underlie learning and memory formation in the brain. But Hebbian synaptic plasticity of excitatory synapses on its own is unstable, leading to either unlimited growth of synaptic strengths or silencing of neuronal activity without additional homeostatic mechanisms. To control excitatory synaptic strengths, we propose a novel form of synaptic plasticity at inhibitory synapses. Using computational modeling, we suggest two key features of inhibitory plasticity, dominance of inhibition over excitation and a nonlinear dependence on the firing rate of postsynaptic excitatory neurons whereby inhibitory synaptic strengths change with the same sign (potentiate or depress) as excitatory synaptic strengths. We demonstrate that the stable synaptic strengths realized by this novel inhibitory plasticity model affects excitatory/inhibitory weight ratios in agreement with experimental results. Applying a disinhibitory signal can gate plasticity and lead to the generation of receptive fields and strong bidirectional connectivity in a recurrent network. Hence, a novel form of nonlinear inhibitory plasticity can simultaneously stabilize excitatory synaptic strengths and enable learning upon disinhibition.
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Affiliation(s)
- Christoph Miehl
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- School of Life Sciences, Technical University of Munich, Freising, Germany
- * E-mail: (CM); (JG)
| | - Julijana Gjorgjieva
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- School of Life Sciences, Technical University of Munich, Freising, Germany
- * E-mail: (CM); (JG)
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13
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Thivierge JP, Giraud E, Lynn M, Théberge Charbonneau A. Key role of neuronal diversity in structured reservoir computing. CHAOS (WOODBURY, N.Y.) 2022; 32:113130. [PMID: 36456321 DOI: 10.1063/5.0111131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/24/2022] [Indexed: 06/17/2023]
Abstract
Chaotic time series have been captured by reservoir computing models composed of a recurrent neural network whose output weights are trained in a supervised manner. These models, however, are typically limited to randomly connected networks of homogeneous units. Here, we propose a new class of structured reservoir models that incorporates a diversity of cell types and their known connections. In a first version of the model, the reservoir was composed of mean-rate units separated into pyramidal, parvalbumin, and somatostatin cells. Stability analysis of this model revealed two distinct dynamical regimes, namely, (i) an inhibition-stabilized network (ISN) where strong recurrent excitation is balanced by strong inhibition and (ii) a non-ISN network with weak excitation. These results were extended to a leaky integrate-and-fire model that captured different cell types along with their network architecture. ISN and non-ISN reservoir networks were trained to relay and generate a chaotic Lorenz attractor. Despite their increased performance, ISN networks operate in a regime of activity near the limits of stability where external perturbations yield a rapid divergence in output. The proposed framework of structured reservoir computing opens avenues for exploring how neural microcircuits can balance performance and stability when representing time series through distinct dynamical regimes.
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Affiliation(s)
- Jean-Philippe Thivierge
- University of Ottawa Brain and Mind Research Institute, 451 Smyth Rd., Ottawa, Ontario K1H 8M5, Canada
| | - Eloïse Giraud
- School of Psychology, University of Ottawa, 156 Jean-Jacques Lussier, Ottawa, Ontario K1N 6N5, Canada
| | - Michael Lynn
- University of Ottawa Brain and Mind Research Institute, 451 Smyth Rd., Ottawa, Ontario K1H 8M5, Canada
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14
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Meneghetti N, Cerri C, Vannini E, Tantillo E, Tottene A, Pietrobon D, Caleo M, Mazzoni A. Synaptic alterations in visual cortex reshape contrast-dependent gamma oscillations and inhibition-excitation ratio in a genetic mouse model of migraine. J Headache Pain 2022; 23:125. [PMID: 36175826 PMCID: PMC9523950 DOI: 10.1186/s10194-022-01495-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 08/09/2022] [Indexed: 11/21/2022] Open
Abstract
Background Migraine affects a significant fraction of the world population, yet its etiology is not completely understood. In vitro results highlighted thalamocortical and intra-cortical glutamatergic synaptic gain-of-function associated with a monogenic form of migraine (familial-hemiplegic-migraine-type-1: FHM1). However, how these alterations reverberate on cortical activity remains unclear. As altered responsivity to visual stimuli and abnormal processing of visual sensory information are common hallmarks of migraine, herein we investigated the effects of FHM1-driven synaptic alterations in the visual cortex of awake mice. Methods We recorded extracellular field potentials from the primary visual cortex (V1) of head-fixed awake FHM1 knock-in (n = 12) and wild type (n = 12) mice in response to square-wave gratings with different visual contrasts. Additionally, we reproduced in silico the obtained experimental results with a novel spiking neurons network model of mouse V1, by implementing in the model both the synaptic alterations characterizing the FHM1 genetic mouse model adopted. Results FHM1 mice displayed similar amplitude but slower temporal evolution of visual evoked potentials. Visual contrast stimuli induced a lower increase of multi-unit activity in FHM1 mice, while the amount of information content about contrast level remained, however, similar to WT. Spectral analysis of the local field potentials revealed an increase in the β/low γ range of WT mice following the abrupt reversal of contrast gratings. Such frequency range transitioned to the high γ range in FHM1 mice. Despite this change in the encoding channel, these oscillations preserved the amount of information conveyed about visual contrast. The computational model showed how these network effects may arise from a combination of changes in thalamocortical and intra-cortical synaptic transmission, with the former inducing a lower cortical activity and the latter inducing the higher frequencies ɣ oscillations. Conclusions Contrast-driven ɣ modulation in V1 activity occurs at a much higher frequency in FHM1. This is likely to play a role in the altered processing of visual information. Computational studies suggest that this shift is specifically due to enhanced cortical excitatory transmission. Our network model can help to shed light on the relationship between cellular and network levels of migraine neural alterations. Graphical Abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s10194-022-01495-9.
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Affiliation(s)
- Nicolò Meneghetti
- The Biorobotics Institute, Scuola Superiore Sant'Anna, 56025, Pisa, Italy.,Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, 56025, Pisa, Italy
| | - Chiara Cerri
- Neuroscience Institute, National Research Council (CNR), 56124, Pisa, Italy.,Fondazione Umberto Veronesi, 20122, Milan, Italy.,Department of Pharmacy, University of Pisa, 56126, Pisa, Italy
| | - Eleonora Vannini
- Neuroscience Institute, National Research Council (CNR), 56124, Pisa, Italy.,Fondazione Umberto Veronesi, 20122, Milan, Italy
| | - Elena Tantillo
- Neuroscience Institute, National Research Council (CNR), 56124, Pisa, Italy.,Fondazione Pisana per la Scienza Onlus (FPS), 56017, Pisa, Italy.,Scuola Normale Superiore, 56100, Pisa, Italy
| | - Angelita Tottene
- Department of Biomedical Sciences, University of Padova, 35131, Padova, Italy
| | - Daniela Pietrobon
- Department of Biomedical Sciences, University of Padova, 35131, Padova, Italy.,Padova Neuroscience Center, University of Padova, 35131, Padova, Italy.,CNR Institute of Neuroscience, 35131, Padova, Italy
| | - Matteo Caleo
- Neuroscience Institute, National Research Council (CNR), 56124, Pisa, Italy.,Department of Biomedical Sciences, University of Padova, 35131, Padova, Italy.,Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, 56025, Pisa, Italy. .,Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, 56025, Pisa, Italy.
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15
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Dynamics and Mechanisms of Contrast-Dependent Modulation of Spatial-Frequency Tuning in the Early Visual Cortex. J Neurosci 2022; 42:7047-7059. [PMID: 35927035 PMCID: PMC9480874 DOI: 10.1523/jneurosci.2086-21.2022] [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: 10/16/2021] [Revised: 07/25/2022] [Accepted: 08/01/2022] [Indexed: 11/21/2022] Open
Abstract
The spatial-frequency (SF) tuning of neurons in the early visual cortex is adjusted for stimulus contrast. As the contrast increases, SF tuning is modulated so that the transmission of fine features is facilitated. A variety of mechanisms are involved in shaping SF tunings, but those responsible for the contrast-dependent modulations are unclear. To address this, we measured the time course of SF tunings of area 17 neurons in male cats under different contrasts with a reverse correlation. After response onset, the optimal SF continuously shifted to a higher SF over time, with a larger shift for higher contrast. At high contrast, whereas neurons with a large shift of optimal SF exhibited a large bandwidth decrease, those with a negligible shift increased the bandwidth over time. Between these two extremes, the degree of SF shift and bandwidth change continuously varied. At low contrast, bandwidth generally decreased over time. These dynamic effects enhanced the processing of high-frequency range under a high-contrast condition and allowed time-average SF tuning curves to show contrast-dependent modulation, like that of steady-state SF tuning curves reported previously. Combinations of two mechanisms, one that decreases bandwidth and shifts optimal SF, and another that increases bandwidth without shifting optimal SF, would explain the full range of SF tuning dynamics. Our results indicate that one of the essential roles of tuning dynamics of area 17 neurons, which have been observed for various visual features, is to adjust tunings depending on contrast.SIGNIFICANCE STATEMENT The spatial scales of features transmitted by cortical neurons are adjusted depending on stimulus contrast. However, the underlying mechanism is not fully understood. We measured the time course of spatial frequency tunings of cat area 17 neurons under different contrast conditions and observed a variety of dynamic effects that contributed to spatial-scale adjustment, allowing neurons to adjust their spatial frequency tuning range depending on contrast. Our results suggest that one of the essential roles of tuning dynamics of area 17 neurons, which have been observed for various visual features, is to adjust tunings depending on contrast.
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16
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A circuit mechanism for independent modulation of excitatory and inhibitory firing rates after sensory deprivation. Proc Natl Acad Sci U S A 2022; 119:e2116895119. [PMID: 35925891 PMCID: PMC9371725 DOI: 10.1073/pnas.2116895119] [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: 11/18/2022] Open
Abstract
The cortex is particularly vulnerable to perturbations during sensitive periods, such as the critical period when manipulating sensory experience can induce long-lasting changes in brain structure. Depriving rodents of vision in one eye (known as monocular deprivation [MD]) reduces network activity over two days, whereby inhibitory neurons decrease their firing rates one day after MD, while excitatory neurons are delayed by an additional day. We use spiking networks to mechanistically dissect the requirements for this independent firing-rate regulation after sensory deprivation. We find that in networks stabilized by recurrent inhibition, at least two interneuron subtypes (parvalbumin-expressing and somatostatin-expressing interneurons) are necessary to dynamically alter the circuit response after deprivation and generalize the result across sensory cortices. Diverse interneuron subtypes shape sensory processing in mature cortical circuits. During development, sensory deprivation evokes powerful synaptic plasticity that alters circuitry, but how different inhibitory subtypes modulate circuit dynamics in response to this plasticity remains unclear. We investigate how deprivation-induced synaptic changes affect excitatory and inhibitory firing rates in a microcircuit model of the sensory cortex with multiple interneuron subtypes. We find that with a single interneuron subtype (parvalbumin-expressing [PV]), excitatory and inhibitory firing rates can only be comodulated—increased or decreased together. To explain the experimentally observed independent modulation, whereby one firing rate increases and the other decreases, requires strong feedback from a second interneuron subtype (somatostatin-expressing [SST]). Our model applies to the visual and somatosensory cortex, suggesting a general mechanism across sensory cortices. Therefore, we provide a mechanistic explanation for the differential role of interneuron subtypes in regulating firing rates, contributing to the already diverse roles they serve in the cortex.
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17
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Khalife MR, Scott RC, Hernan AE. Mechanisms for Cognitive Impairment in Epilepsy: Moving Beyond Seizures. Front Neurol 2022; 13:878991. [PMID: 35645970 PMCID: PMC9135108 DOI: 10.3389/fneur.2022.878991] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
There has been a major emphasis on defining the role of seizures in the causation of cognitive impairments like memory deficits in epilepsy. Here we focus on an alternative hypothesis behind these deficits, emphasizing the mechanisms of information processing underlying healthy cognition characterized as rate, temporal and population coding. We discuss the role of the underlying etiology of epilepsy in altering neural networks thereby leading to both the propensity for seizures and the associated cognitive impairments. In addition, we address potential treatments that can recover the network function in the context of a diseased brain, thereby improving both seizure and cognitive outcomes simultaneously. This review shows the importance of moving beyond seizures and approaching the deficits from a system-level perspective with the guidance of network neuroscience.
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Affiliation(s)
- Mohamed R. Khalife
- Division of Neuroscience, Nemours Children's Health, Wilmington, DE, United States
- Psychological and Brain Sciences, University of Delaware, Newark, DE, United States
| | - Rod C. Scott
- Division of Neuroscience, Nemours Children's Health, Wilmington, DE, United States
- Psychological and Brain Sciences, University of Delaware, Newark, DE, United States
- Institute of Child Health, Neurosciences Unit University College London, London, United Kingdom
| | - Amanda E. Hernan
- Division of Neuroscience, Nemours Children's Health, Wilmington, DE, United States
- Psychological and Brain Sciences, University of Delaware, Newark, DE, United States
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18
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Onodera K, Kato HK. Translaminar recurrence from layer 5 suppresses superficial cortical layers. Nat Commun 2022; 13:2585. [PMID: 35546553 PMCID: PMC9095870 DOI: 10.1038/s41467-022-30349-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 04/26/2022] [Indexed: 12/23/2022] Open
Abstract
Information flow in the sensory cortex has been described as a predominantly feedforward sequence with deep layers as the output structure. Although recurrent excitatory projections from layer 5 (L5) to superficial L2/3 have been identified by anatomical and physiological studies, their functional impact on sensory processing remains unclear. Here, we use layer-selective optogenetic manipulations in the primary auditory cortex to demonstrate that feedback inputs from L5 suppress the activity of superficial layers regardless of the arousal level, contrary to the prediction from their excitatory connectivity. This suppressive effect is predominantly mediated by translaminar circuitry through intratelencephalic neurons, with an additional contribution of subcortical projections by pyramidal tract neurons. Furthermore, L5 activation sharpened tone-evoked responses of superficial layers in both frequency and time domains, indicating its impact on cortical spectro-temporal integration. Together, our findings establish a translaminar inhibitory recurrence from deep layers that sharpens feature selectivity in superficial cortical layers.
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Affiliation(s)
- Koun Onodera
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- JSPS Overseas Research Fellow, Japan Society for the Promotion of Science, Tokyo, Japan
| | - Hiroyuki K Kato
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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19
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Padamsey Z, Katsanevaki D, Dupuy N, Rochefort NL. Neocortex saves energy by reducing coding precision during food scarcity. Neuron 2022; 110:280-296.e10. [PMID: 34741806 PMCID: PMC8788933 DOI: 10.1016/j.neuron.2021.10.024] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 09/07/2021] [Accepted: 10/15/2021] [Indexed: 11/21/2022]
Abstract
Information processing is energetically expensive. In the mammalian brain, it is unclear how information coding and energy use are regulated during food scarcity. Using whole-cell recordings and two-photon imaging in layer 2/3 mouse visual cortex, we found that food restriction reduced AMPA receptor conductance, reducing synaptic ATP use by 29%. Neuronal excitability was nonetheless preserved by a compensatory increase in input resistance and a depolarized resting potential. Consequently, neurons spiked at similar rates as controls but spent less ATP on underlying excitatory currents. This energy-saving strategy had a cost because it amplified the variability of visually-evoked subthreshold responses, leading to a 32% broadening of orientation tuning and impaired fine visual discrimination. This reduction in coding precision was associated with reduced levels of the fat mass-regulated hormone leptin and was restored by exogenous leptin supplementation. Our findings reveal that metabolic state dynamically regulates the energy spent on coding precision in neocortex.
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Affiliation(s)
- Zahid Padamsey
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK.
| | - Danai Katsanevaki
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK
| | - Nathalie Dupuy
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK
| | - Nathalie L Rochefort
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK; Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh EH8 9XD, UK.
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20
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Müller-Komorowska D, Parabucki A, Elyasaf G, Katz Y, Beck H, Lampl I. A novel theoretical framework for simultaneous measurement of excitatory and inhibitory conductances. PLoS Comput Biol 2021; 17:e1009725. [PMID: 34962935 PMCID: PMC8746761 DOI: 10.1371/journal.pcbi.1009725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 01/10/2022] [Accepted: 12/06/2021] [Indexed: 11/20/2022] Open
Abstract
The firing of neurons throughout the brain is determined by the precise relations between excitatory and inhibitory inputs, and disruption of their balance underlies many psychiatric diseases. Whether or not these inputs covary over time or between repeated stimuli remains unclear due to the lack of experimental methods for measuring both inputs simultaneously. We developed a new analytical framework for instantaneous and simultaneous measurements of both the excitatory and inhibitory neuronal inputs during a single trial under current clamp recording. This can be achieved by injecting a current composed of two high frequency sinusoidal components followed by analytical extraction of the conductances. We demonstrate the ability of this method to measure both inputs in a single trial under realistic recording constraints and from morphologically realistic CA1 pyramidal model cells. Future experimental implementation of our new method will facilitate the understanding of fundamental questions about the health and disease of the nervous system. Most neurons in the brain receive synaptic inputs from both excitatory and inhibitory neurons. Together, these inputs determine neuronal activity: excitatory synapses shift the electrical potential across the membrane towards the threshold for generation of action potentials, whereas inhibitory synapses lower this potential away from the threshold. Action potentials are the rapid electrochemical signals that transmit information to other neurons and they are critical for the information processing abilities of the brain. Although there are many ways to measure either excitatory or inhibitory inputs, these methods have been unable to measure both at the same time. Measuring both inputs together is essential towards understanding how neurons integrate information. We developed a new analytical method to measure excitatory and inhibitory inputs at the same time from the voltage response to injection of an alternating current into a neuron. We describe the foundation of this new method and find that it works in biologically realistic simulations of neurons. By using this technique in real neurons, scientists could investigate basic principles of information processing in the healthy and diseased brain.
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Affiliation(s)
- Daniel Müller-Komorowska
- Institute of Experimental Epileptology and Cognition Research, Life and Brain Center, University of Bonn Medical Center, Bonn, Germany.,International Max Planck Research School for Brain and Behavior, University of Bonn, Bonn, Germany
| | - Ana Parabucki
- Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel
| | - Gal Elyasaf
- Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel
| | - Yonatan Katz
- Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel
| | - Heinz Beck
- Institute of Experimental Epileptology and Cognition Research, Life and Brain Center, University of Bonn Medical Center, Bonn, Germany
| | - Ilan Lampl
- Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel
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21
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Larisch R, Gönner L, Teichmann M, Hamker FH. Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity. PLoS Comput Biol 2021; 17:e1009566. [PMID: 34843455 PMCID: PMC8629393 DOI: 10.1371/journal.pcbi.1009566] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 10/15/2021] [Indexed: 11/18/2022] Open
Abstract
Visual stimuli are represented by a highly efficient code in the primary visual cortex, but the development of this code is still unclear. Two distinct factors control coding efficiency: Representational efficiency, which is determined by neuronal tuning diversity, and metabolic efficiency, which is influenced by neuronal gain. How these determinants of coding efficiency are shaped during development, supported by excitatory and inhibitory plasticity, is only partially understood. We investigate a fully plastic spiking network of the primary visual cortex, building on phenomenological plasticity rules. Our results suggest that inhibitory plasticity is key to the emergence of tuning diversity and accurate input encoding. We show that inhibitory feedback (random and specific) increases the metabolic efficiency by implementing a gain control mechanism. Interestingly, this led to the spontaneous emergence of contrast-invariant tuning curves. Our findings highlight that (1) interneuron plasticity is key to the development of tuning diversity and (2) that efficient sensory representations are an emergent property of the resulting network. Synaptic plasticity is crucial for the development of efficient input representation in the different sensory cortices, such as the primary visual cortex. Efficient visual representation is determined by two factors: representational efficiency, i.e. how many different input features can be represented, and metabolic efficiency, i.e. how many spikes are required to represent a specific feature. Previous research has pointed out the importance of plasticity at excitatory synapses to achieve high representational efficiency and feedback inhibition as a gain control mechanism for controlling metabolic efficiency. However, it is only partially understood how the influence of inhibitory plasticity on excitatory plasticity can lead to an efficient representation. Using a spiking neural network, we show that plasticity at feed-forward and feedback inhibitory synapses is necessary for the emergence of well-distributed neuronal selectivity to improve representational efficiency. Further, the emergent balance between excitatory and inhibitory currents improves the metabolic efficiency, and leads to contrast-invariant tuning as an inherent network property. Extending previous work, our simulation results highlight the importance of plasticity at inhibitory synapses.
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Affiliation(s)
- René Larisch
- Department of Computer Science, Artificial Intelligence, TU Chemnitz, Chemnitz, Germany
- * E-mail: (RL); (FHH)
| | - Lorenz Gönner
- Department of Computer Science, Artificial Intelligence, TU Chemnitz, Chemnitz, Germany
- Faculty of Psychology, Lifespan Developmental Neuroscience, TU Dresden, Dresden, Germany
| | - Michael Teichmann
- Department of Computer Science, Artificial Intelligence, TU Chemnitz, Chemnitz, Germany
| | - Fred H. Hamker
- Department of Computer Science, Artificial Intelligence, TU Chemnitz, Chemnitz, Germany
- Bernstein Center Computational Neuroscience, Berlin, Germany
- * E-mail: (RL); (FHH)
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22
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Kimura R, Yoshimura Y. The contribution of low contrast-preferring neurons to information representation in the primary visual cortex after learning. SCIENCE ADVANCES 2021; 7:eabj9976. [PMID: 34826242 PMCID: PMC8626071 DOI: 10.1126/sciadv.abj9976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 10/07/2021] [Indexed: 06/13/2023]
Abstract
Animals exhibit improved perception of lower-contrast visual objects after training. We explored this neuronal mechanism using multiple single-unit recordings from deep layers of the primary visual cortex (V1) of trained rats during orientation discrimination. We found that the firing rates of a subset of neurons increased by reducing luminance contrast, being at least above basal activities at low contrast. These low contrast–preferring neurons were rare during passive viewing without training or anesthesia after training. They fired more frequently in correct-choice than incorrect-choice trials. At single-neuron and population levels, they efficiently represented low-contrast orientations. Following training, in addition to generally enhanced excitation, the phase synchronization of spikes to beta oscillations at high contrast was stronger in putative inhibitory than excitatory neurons. The change in excitation-inhibition balance might contribute to low-contrast preference. Thus, low-contrast preference in V1 activity is strengthened in an experience-dependent manner, which may contribute to low-contrast visual discrimination.
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Affiliation(s)
- Rie Kimura
- Division of Visual Information Processing, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Japan
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), Okazaki, Japan
| | - Yumiko Yoshimura
- Division of Visual Information Processing, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Japan
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), Okazaki, Japan
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23
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Li JY, Hass CA, Matthews I, Kristl AC, Glickfeld LL. Distinct recruitment of feedforward and recurrent pathways across higher-order areas of mouse visual cortex. Curr Biol 2021; 31:5024-5036.e5. [PMID: 34637748 DOI: 10.1016/j.cub.2021.09.042] [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: 04/23/2021] [Revised: 08/18/2021] [Accepted: 09/16/2021] [Indexed: 10/20/2022]
Abstract
Cortical visual processing transforms features of the external world into increasingly complex and specialized neuronal representations. These transformations arise in part through target-specific routing of information; however, within-area computations may also contribute to area-specific function. Here, we sought to determine whether higher order visual cortical areas lateromedial (LM), anterolateral (AL), posteromedial (PM), and anteromedial (AM) have specialized anatomical and physiological properties by using a combination of whole-cell recordings and optogenetic stimulation of primary visual cortex (V1) axons in vitro. We discovered area-specific differences in the strength of recruitment of interneurons through feedforward and recurrent pathways, as well as differences in cell-intrinsic properties and interneuron densities. These differences were most striking when comparing across medial and lateral areas, suggesting that these areas have distinct profiles for net excitability and integration of V1 inputs. Thus, cortical areas are not defined simply by the information they receive but also by area-specific circuit properties that enable specialized filtering of these inputs.
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Affiliation(s)
- Jennifer Y Li
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Charles A Hass
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Ian Matthews
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Amy C Kristl
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Lindsey L Glickfeld
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA.
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24
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Ahmadian Y, Miller KD. What is the dynamical regime of cerebral cortex? Neuron 2021; 109:3373-3391. [PMID: 34464597 PMCID: PMC9129095 DOI: 10.1016/j.neuron.2021.07.031] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 07/05/2021] [Accepted: 07/30/2021] [Indexed: 01/13/2023]
Abstract
Many studies have shown that the excitation and inhibition received by cortical neurons remain roughly balanced across many conditions. A key question for understanding the dynamical regime of cortex is the nature of this balancing. Theorists have shown that network dynamics can yield systematic cancellation of most of a neuron's excitatory input by inhibition. We review a wide range of evidence pointing to this cancellation occurring in a regime in which the balance is loose, meaning that the net input remaining after cancellation of excitation and inhibition is comparable in size with the factors that cancel, rather than tight, meaning that the net input is very small relative to the canceling factors. This choice of regime has important implications for cortical functional responses, as we describe: loose balance, but not tight balance, can yield many nonlinear population behaviors seen in sensory cortical neurons, allow the presence of correlated variability, and yield decrease of that variability with increasing external stimulus drive as observed across multiple cortical areas.
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Affiliation(s)
- Yashar Ahmadian
- Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK.
| | - Kenneth D Miller
- Center for Theoretical Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, and Department of Neuroscience, College of Physicians and Surgeons and Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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Speed A, Haider B. Probing mechanisms of visual spatial attention in mice. Trends Neurosci 2021; 44:822-836. [PMID: 34446296 PMCID: PMC8484049 DOI: 10.1016/j.tins.2021.07.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/05/2021] [Accepted: 07/30/2021] [Indexed: 11/25/2022]
Abstract
The role of spatial attention for visual perception has been thoroughly studied in primates, but less so in mice. Several behavioral tasks in mice reveal spatial attentional effects, with similarities to observations in primates. Pairing these tasks with large-scale, cell-type-specific techniques could enable deeper access to underlying mechanisms, and help define the utility and limitations of resolving attentional effects on visual perception and neural activity in mice. In this Review, we evaluate behavioral and neural evidence for visual spatial attention in mice; assess how specializations of the mouse visual system and behavioral repertoire impact interpretation of spatial attentional effects; and outline how several measurement and manipulation techniques in mice could precisely test and refine models of attentional modulation across scales.
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Affiliation(s)
- Anderson Speed
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Bilal Haider
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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26
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Goetz L, Roth A, Häusser M. Active dendrites enable strong but sparse inputs to determine orientation selectivity. Proc Natl Acad Sci U S A 2021; 118:e2017339118. [PMID: 34301882 PMCID: PMC8325157 DOI: 10.1073/pnas.2017339118] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The dendrites of neocortical pyramidal neurons are excitable. However, it is unknown how synaptic inputs engage nonlinear dendritic mechanisms during sensory processing in vivo, and how they in turn influence action potential output. Here, we provide a quantitative account of the relationship between synaptic inputs, nonlinear dendritic events, and action potential output. We developed a detailed pyramidal neuron model constrained by in vivo dendritic recordings. We drive this model with realistic input patterns constrained by sensory responses measured in vivo and connectivity measured in vitro. We show mechanistically that under realistic conditions, dendritic Na+ and NMDA spikes are the major determinants of neuronal output in vivo. We demonstrate that these dendritic spikes can be triggered by a surprisingly small number of strong synaptic inputs, in some cases even by single synapses. We predict that dendritic excitability allows the 1% strongest synaptic inputs of a neuron to control the tuning of its output. Active dendrites therefore allow smaller subcircuits consisting of only a few strongly connected neurons to achieve selectivity for specific sensory features.
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Affiliation(s)
- Lea Goetz
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
| | - Arnd Roth
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, United Kingdom
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27
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Niell CM, Scanziani M. How Cortical Circuits Implement Cortical Computations: Mouse Visual Cortex as a Model. Annu Rev Neurosci 2021; 44:517-546. [PMID: 33914591 PMCID: PMC9925090 DOI: 10.1146/annurev-neuro-102320-085825] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The mouse, as a model organism to study the brain, gives us unprecedented experimental access to the mammalian cerebral cortex. By determining the cortex's cellular composition, revealing the interaction between its different components, and systematically perturbing these components, we are obtaining mechanistic insight into some of the most basic properties of cortical function. In this review, we describe recent advances in our understanding of how circuits of cortical neurons implement computations, as revealed by the study of mouse primary visual cortex. Further, we discuss how studying the mouse has broadened our understanding of the range of computations performed by visual cortex. Finally, we address how future approaches will fulfill the promise of the mouse in elucidating fundamental operations of cortex.
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Affiliation(s)
- Cristopher M. Niell
- Department of Biology and Institute of Neuroscience, University of Oregon, Eugene, Oregon 97403, USA
| | - Massimo Scanziani
- Department of Physiology and Howard Hughes Medical Institute, University of California San Francisco, San Francisco, California 94158, USA;
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28
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Pfeffer T, Ponce-Alvarez A, Tsetsos K, Meindertsma T, Gahnström CJ, van den Brink RL, Nolte G, Engel AK, Deco G, Donner TH. Circuit mechanisms for the chemical modulation of cortex-wide network interactions and behavioral variability. SCIENCE ADVANCES 2021; 7:eabf5620. [PMID: 34272245 PMCID: PMC8284895 DOI: 10.1126/sciadv.abf5620] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 06/03/2021] [Indexed: 05/07/2023]
Abstract
Influential theories postulate distinct roles of catecholamines and acetylcholine in cognition and behavior. However, previous physiological work reported similar effects of these neuromodulators on the response properties (specifically, the gain) of individual cortical neurons. Here, we show a double dissociation between the effects of catecholamines and acetylcholine at the level of large-scale interactions between cortical areas in humans. A pharmacological boost of catecholamine levels increased cortex-wide interactions during a visual task, but not rest. An acetylcholine boost decreased interactions during rest, but not task. Cortical circuit modeling explained this dissociation by differential changes in two circuit properties: the local excitation-inhibition balance (more strongly increased by catecholamines) and intracortical transmission (more strongly reduced by acetylcholine). The inferred catecholaminergic mechanism also predicted noisier decision-making, which we confirmed for both perceptual and value-based choice behavior. Our work highlights specific circuit mechanisms for shaping cortical network interactions and behavioral variability by key neuromodulatory systems.
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Affiliation(s)
- Thomas Pfeffer
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Adrian Ponce-Alvarez
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Konstantinos Tsetsos
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thomas Meindertsma
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - Christoffer Julius Gahnström
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ruud Lucas van den Brink
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Guido Nolte
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Andreas Karl Engel
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Tobias Hinrich Donner
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
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29
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Francioni V, Harnett MT. Rethinking Single Neuron Electrical Compartmentalization: Dendritic Contributions to Network Computation In Vivo. Neuroscience 2021; 489:185-199. [PMID: 34116137 DOI: 10.1016/j.neuroscience.2021.05.038] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/11/2021] [Accepted: 05/29/2021] [Indexed: 12/15/2022]
Abstract
Decades of experimental and theoretical work support a now well-established theory that active dendritic processing contributes to the computational power of individual neurons. This theory is based on the high degree of electrical compartmentalization observed in the dendrites of single neurons in ex vivo preparations. Compartmentalization allows dendrites to conduct semi-independent operations on their inputs before final integration and output at the axon, producing a "network-in-a-neuron." However, recent in vivo functional imaging experiments in mouse cortex have reported surprisingly little evidence for strong dendritic compartmentalization. In this review, we contextualize these new findings and discuss their impact on the future of the field. Specifically, we consider how highly coordinated, and thus less compartmentalized, activity in soma and dendrites can contribute to cortical computations including nonlinear mixed selectivity, prediction/expectation, multiplexing, and credit assignment.
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Affiliation(s)
- Valerio Francioni
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Mark T Harnett
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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30
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Manyukhina VO, Rostovtseva EN, Prokofyev AO, Obukhova TS, Schneiderman JF, Stroganova TA, Orekhova EV. Visual gamma oscillations predict sensory sensitivity in females as they do in males. Sci Rep 2021; 11:12013. [PMID: 34103578 PMCID: PMC8187436 DOI: 10.1038/s41598-021-91381-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Accepted: 05/21/2021] [Indexed: 02/05/2023] Open
Abstract
Gamma oscillations are driven by local cortical excitatory (E)-inhibitory (I) loops and may help to characterize neural processing involving excitatory-inhibitory interactions. In the visual cortex reliable gamma oscillations can be recorded with magnetoencephalography (MEG) in the majority of individuals, which makes visual gamma an attractive candidate for biomarkers of brain disorders associated with E/I imbalance. Little is known, however, about if/how these oscillations reflect individual differences in neural excitability and associated sensory/perceptual phenomena. The power of visual gamma response (GR) changes nonlinearly with increasing stimulation intensity: it increases with transition from static to slowly drifting high-contrast grating and then attenuates with further increase in the drift rate. In a recent MEG study we found that the GR attenuation predicted sensitivity to sensory stimuli in everyday life in neurotypical adult men and in men with autism spectrum disorders. Here, we replicated these results in neurotypical female participants. The GR enhancement with transition from static to slowly drifting grating did not correlate significantly with the sensory sensitivity measures. These findings suggest that weak velocity-related attenuation of the GR is a reliable neural concomitant of visual hypersensitivity and that the degree of GR attenuation may provide useful information about E/I balance in the visual cortex.
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Affiliation(s)
- Viktoriya O Manyukhina
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
- National Research University Higher School of Economics, Moscow, Russian Federation
| | - Ekaterina N Rostovtseva
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Andrey O Prokofyev
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Tatiana S Obukhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Justin F Schneiderman
- MedTech West and the Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden
| | - Tatiana A Stroganova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Elena V Orekhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation.
- MedTech West and the Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden.
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31
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Yalcinbas EA, Cazares C, Gremel CM. Call for a more balanced approach to understanding orbital frontal cortex function. Behav Neurosci 2021; 135:255-266. [PMID: 34060878 DOI: 10.1037/bne0000450] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Orbital frontal cortex (OFC) research has historically emphasized the function of this associative cortical area within top-down theoretical frameworks. This approach has largely focused on mapping OFC activity onto human-defined psychological or cognitive constructs and has often led to OFC circuitry bearing the weight of entire theoretical frameworks. New techniques and tools developed in the last decade have made it possible to revisit long-standing basic science questions in neuroscience and answer them with increasing sophistication. We can now study and specify the genetic, molecular, cellular, and circuit architecture of a brain region in much greater detail, which allows us to piece together how they contribute to emergent circuit functions. For instance, adopting such systematic and unbiased bottom-up approaches to elucidating the function of the visual system has paved the way to building a greater understanding of the spectrum of its computational capabilities. In the same vein, we argue that OFC research would benefit from a more balanced approach that also places focus on novel bottom-up investigations into OFC's computational capabilities. Furthermore, we believe that the knowledge gained by employing a more bottom-up approach to investigating OFC function will ultimately allow us to look at OFC's dysfunction in disease through a more nuanced biological lens. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Affiliation(s)
- Ege A Yalcinbas
- The Neurosciences Graduate Program, University of California, San Diego
| | - Christian Cazares
- The Neurosciences Graduate Program, University of California, San Diego
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32
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Aponte DA, Handy G, Kline AM, Tsukano H, Doiron B, Kato HK. Recurrent network dynamics shape direction selectivity in primary auditory cortex. Nat Commun 2021; 12:314. [PMID: 33436635 PMCID: PMC7804939 DOI: 10.1038/s41467-020-20590-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 12/11/2020] [Indexed: 02/03/2023] Open
Abstract
Detecting the direction of frequency modulation (FM) is essential for vocal communication in both animals and humans. Direction-selective firing of neurons in the primary auditory cortex (A1) has been classically attributed to temporal offsets between feedforward excitatory and inhibitory inputs. However, it remains unclear how cortical recurrent circuitry contributes to this computation. Here, we used two-photon calcium imaging and whole-cell recordings in awake mice to demonstrate that direction selectivity is not caused by temporal offsets between synaptic currents, but by an asymmetry in total synaptic charge between preferred and non-preferred directions. Inactivation of cortical somatostatin-expressing interneurons (SOM cells) reduced direction selectivity, revealing its cortical contribution. Our theoretical models showed that charge asymmetry arises due to broad spatial topography of SOM cell-mediated inhibition which regulates signal amplification in strongly recurrent circuitry. Together, our findings reveal a major contribution of recurrent network dynamics in shaping cortical tuning to behaviorally relevant complex sounds.
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Affiliation(s)
- Destinee A Aponte
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Gregory Handy
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, USA
- Department of Mathematics, University of Pittsburgh, Pittsburgh, USA
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, USA
| | - Amber M Kline
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Hiroaki Tsukano
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Brent Doiron
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, USA
- Department of Mathematics, University of Pittsburgh, Pittsburgh, USA
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, USA
| | - Hiroyuki K Kato
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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33
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Keller AJ, Dipoppa M, Roth MM, Caudill MS, Ingrosso A, Miller KD, Scanziani M. A Disinhibitory Circuit for Contextual Modulation in Primary Visual Cortex. Neuron 2020; 108:1181-1193.e8. [PMID: 33301712 PMCID: PMC7850578 DOI: 10.1016/j.neuron.2020.11.013] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 10/17/2020] [Accepted: 11/13/2020] [Indexed: 12/24/2022]
Abstract
Context guides perception by influencing stimulus saliency. Accordingly, in visual cortex, responses to a stimulus are modulated by context, the visual scene surrounding the stimulus. Responses are suppressed when stimulus and surround are similar but not when they differ. The underlying mechanisms remain unclear. Here, we use optical recordings, manipulations, and computational modeling to show that disinhibitory circuits consisting of vasoactive intestinal peptide (VIP)-expressing and somatostatin (SOM)-expressing inhibitory neurons modulate responses in mouse visual cortex depending on similarity between stimulus and surround, primarily by modulating recurrent excitation. When stimulus and surround are similar, VIP neurons are inactive, and activity of SOM neurons leads to suppression of excitatory neurons. However, when stimulus and surround differ, VIP neurons are active, inhibiting SOM neurons, which leads to relief of excitatory neurons from suppression. We have identified a canonical cortical disinhibitory circuit that contributes to contextual modulation and may regulate perceptual saliency.
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Affiliation(s)
- Andreas J Keller
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158-0444, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA.
| | - Mario Dipoppa
- Center for Theoretical Neuroscience, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY 10027, USA.
| | - Morgane M Roth
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158-0444, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA.
| | - Matthew S Caudill
- Center for Neural Circuits and Behavior, Neurobiology Section and Department of Neuroscience, University of California, San Diego, La Jolla, CA 92093-0634, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Alessandro Ingrosso
- Center for Theoretical Neuroscience, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY 10027, USA
| | - Kenneth D Miller
- Center for Theoretical Neuroscience, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY 10027, USA; Department of Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY, USA.
| | - Massimo Scanziani
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158-0444, USA; Center for Neural Circuits and Behavior, Neurobiology Section and Department of Neuroscience, University of California, San Diego, La Jolla, CA 92093-0634, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA.
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34
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Sadeh S, Clopath C. Inhibitory stabilization and cortical computation. Nat Rev Neurosci 2020; 22:21-37. [PMID: 33177630 DOI: 10.1038/s41583-020-00390-z] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/22/2020] [Indexed: 12/22/2022]
Abstract
Neuronal networks with strong recurrent connectivity provide the brain with a powerful means to perform complex computational tasks. However, high-gain excitatory networks are susceptible to instability, which can lead to runaway activity, as manifested in pathological regimes such as epilepsy. Inhibitory stabilization offers a dynamic, fast and flexible compensatory mechanism to balance otherwise unstable networks, thus enabling the brain to operate in its most efficient regimes. Here we review recent experimental evidence for the presence of such inhibition-stabilized dynamics in the brain and discuss their consequences for cortical computation. We show how the study of inhibition-stabilized networks in the brain has been facilitated by recent advances in the technological toolbox and perturbative techniques, as well as a concomitant development of biologically realistic computational models. By outlining future avenues, we suggest that inhibitory stabilization can offer an exemplary case of how experimental neuroscience can progress in tandem with technology and theory to advance our understanding of the brain.
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Affiliation(s)
- Sadra Sadeh
- Bioengineering Department, Imperial College London, London, UK
| | - Claudia Clopath
- Bioengineering Department, Imperial College London, London, UK.
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35
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Millman DJ, Ocker GK, Caldejon S, Kato I, Larkin JD, Lee EK, Luviano J, Nayan C, Nguyen TV, North K, Seid S, White C, Lecoq J, Reid C, Buice MA, de Vries SEJ. VIP interneurons in mouse primary visual cortex selectively enhance responses to weak but specific stimuli. eLife 2020; 9:e55130. [PMID: 33108272 PMCID: PMC7591255 DOI: 10.7554/elife.55130] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 10/11/2020] [Indexed: 01/20/2023] Open
Abstract
Vasoactive intestinal peptide-expressing (VIP) interneurons in the cortex regulate feedback inhibition of pyramidal neurons through suppression of somatostatin-expressing (SST) interneurons and, reciprocally, SST neurons inhibit VIP neurons. Although VIP neuron activity in the primary visual cortex (V1) of mouse is highly correlated with locomotion, the relevance of locomotion-related VIP neuron activity to visual coding is not known. Here we show that VIP neurons in mouse V1 respond strongly to low contrast front-to-back motion that is congruent with self-motion during locomotion but are suppressed by other directions and contrasts. VIP and SST neurons have complementary contrast tuning. Layer 2/3 contains a substantially larger population of low contrast preferring pyramidal neurons than deeper layers, and layer 2/3 (but not deeper layer) pyramidal neurons show bias for front-to-back motion specifically at low contrast. Network modeling indicates that VIP-SST mutual antagonism regulates the gain of the cortex to achieve sensitivity to specific weak stimuli without compromising network stability.
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Affiliation(s)
| | | | | | - India Kato
- Allen Institute for Brain ScienceSeattleUnited States
| | - Josh D Larkin
- Allen Institute for Brain ScienceSeattleUnited States
| | | | | | - Chelsea Nayan
- Allen Institute for Brain ScienceSeattleUnited States
| | | | - Kat North
- Allen Institute for Brain ScienceSeattleUnited States
| | - Sam Seid
- Allen Institute for Brain ScienceSeattleUnited States
| | | | - Jerome Lecoq
- Allen Institute for Brain ScienceSeattleUnited States
| | - Clay Reid
- Allen Institute for Brain ScienceSeattleUnited States
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36
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Scholl B, Fitzpatrick D. Cortical synaptic architecture supports flexible sensory computations. Curr Opin Neurobiol 2020; 64:41-45. [PMID: 32088662 PMCID: PMC8080306 DOI: 10.1016/j.conb.2020.01.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 01/17/2020] [Accepted: 01/23/2020] [Indexed: 12/11/2022]
Abstract
Establishing the fundamental principles that underlie the integration of excitatory and inhibitory presynaptic input populations is crucial to understanding how individual cortical neurons transform signals from peripheral receptors. Here we review recent studies using novel tools to examine the functional properties of excitatory synaptic inputs and the tuning of excitation and inhibition onto individual neurons. New evidence challenges existing synaptic connectivity rules and suggests a more complex functional synaptic architecture that supports a broad range of operations, enabling single neurons to encode multiple sensory features and flexibly shape their computations in the face of diverse sensory input.
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Affiliation(s)
- Benjamin Scholl
- Max Planck Florida Institute, 1 Max Planck Way, Jupiter, FL USA.
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37
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Johnson JK, Geng S, Hoffman MW, Adesnik H, Wessel R. Precision multidimensional neural population code recovered from single intracellular recordings. Sci Rep 2020; 10:15997. [PMID: 32994474 PMCID: PMC7524839 DOI: 10.1038/s41598-020-72936-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 08/20/2020] [Indexed: 11/08/2022] Open
Abstract
Neurons in sensory cortices are more naturally and deeply integrated than any current neural population recording tools (e.g. electrode arrays, fluorescence imaging). Two concepts facilitate efforts to observe population neural code with single-cell recordings. First, even the highest quality single-cell recording studies find a fraction of the stimulus information in high-dimensional population recordings. Finding any of this missing information provides proof of principle. Second, neurons and neural populations are understood as coupled nonlinear differential equations. Therefore, fitted ordinary differential equations provide a basis for single-trial single-cell stimulus decoding. We obtained intracellular recordings of fluctuating transmembrane current and potential in mouse visual cortex during stimulation with drifting gratings. We use mean deflection from baseline when comparing to prior single-cell studies because action potentials are too sparse and the deflection response to drifting grating stimuli (e.g. tuning curves) are well studied. Equation-based decoders allowed more precise single-trial stimulus discrimination than tuning-curve-base decoders. Performance varied across recorded signal types in a manner consistent with population recording studies and both classification bases evinced distinct stimulus-evoked phases of population dynamics, providing further corroboration. Naturally and deeply integrated observations of population dynamics would be invaluable. We offer proof of principle and a versatile framework.
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Affiliation(s)
| | | | | | | | - Ralf Wessel
- Washington University in St. Louis, St. Louis, USA
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38
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Li H, Liang F, Zhong W, Yan L, Mesik L, Xiao Z, Tao HW, Zhang LI. Synaptic Mechanisms for Bandwidth Tuning in Awake Mouse Primary Auditory Cortex. Cereb Cortex 2020; 29:2998-3009. [PMID: 30010857 DOI: 10.1093/cercor/bhy165] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 06/08/2018] [Indexed: 11/12/2022] Open
Abstract
Spatial size tuning in the visual cortex has been considered as an important neuronal functional property for sensory perception. However, an analogous mechanism in the auditory system has remained controversial. In the present study, cell-attached recordings in the primary auditory cortex (A1) of awake mice revealed that excitatory neurons can be categorized into three types according to their bandwidth tuning profiles in response to band-passed noise (BPN) stimuli: nonmonotonic (NM), flat, and monotonic, with the latter two considered as non-tuned for bandwidth. The prevalence of bandwidth-tuned (i.e., NM) neurons increases significantly from layer 4 to layer 2/3. With sequential cell-attached and whole-cell voltage-clamp recordings from the same neurons, we found that the bandwidth preference of excitatory neurons is largely determined by the excitatory synaptic input they receive, and that the bandwidth selectivity is further enhanced by flatly tuned inhibition observed in all cells. The latter can be attributed at least partially to the flat tuning of parvalbumin inhibitory neurons. The tuning of auditory cortical neurons for bandwidth of BPN may contribute to the processing of complex sounds.
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Affiliation(s)
- Haifu Li
- Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.,Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Feixue Liang
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Medical Engineering, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Wen Zhong
- Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.,Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Linqing Yan
- Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.,Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Lucas Mesik
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
| | - Zhongju Xiao
- Department of Physiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Huizhong W Tao
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Li I Zhang
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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39
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Heeger DJ, Zemlianova KO. A recurrent circuit implements normalization, simulating the dynamics of V1 activity. Proc Natl Acad Sci U S A 2020; 117:22494-22505. [PMID: 32843341 PMCID: PMC7486719 DOI: 10.1073/pnas.2005417117] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model's defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. Despite the success of the normalization model, there are three unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how normalization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another's normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can recapitulate key experimental observations of the dynamics of neural activity in V1.
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Affiliation(s)
- David J Heeger
- Department of Psychology, New York University, New York, NY 10003;
- Center for Neural Science, New York University, New York, NY 10003
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40
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Herstel LJ, Wierenga CJ. Network control through coordinated inhibition. Curr Opin Neurobiol 2020; 67:34-41. [PMID: 32853970 DOI: 10.1016/j.conb.2020.08.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 07/29/2020] [Accepted: 08/01/2020] [Indexed: 12/29/2022]
Abstract
Coordinated excitatory and inhibitory activity is required for proper brain functioning. Recent computational and experimental studies have demonstrated that activity patterns in recurrent cortical networks are dominated by inhibition. Whereas previous studies have suggested that inhibitory plasticity is important for homeostatic control, this new framework puts inhibition in the driver's seat. Complex neuronal networks in the brain comprise many configurations in parallel, controlled by external and internal 'switches'. Context-dependent modulation and plasticity of inhibitory connections play a key role in memory and learning. It is therefore important to realize that synaptic plasticity is often multisynaptic and that a proper balance between excitation and inhibition is not fixed, but depends on context and activity level.
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Affiliation(s)
- Lotte J Herstel
- Cell Biology, Neurobiology and Biophysics, Biology Department, Faculty of Science, Utrecht University, The Netherlands
| | - Corette J Wierenga
- Cell Biology, Neurobiology and Biophysics, Biology Department, Faculty of Science, Utrecht University, The Netherlands.
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41
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Zhang Y, Zhang X. Portrait of visual cortical circuits for generating neural oscillation dynamics. Cogn Neurodyn 2020; 15:3-16. [PMID: 34109010 DOI: 10.1007/s11571-020-09623-4] [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: 12/30/2019] [Revised: 07/17/2020] [Accepted: 07/24/2020] [Indexed: 11/30/2022] Open
Abstract
The mouse primary visual cortex (V1) has emerged as a classical system to study neural circuit mechanisms underlying visual function and plasticity. A variety of efferent-afferent neuronal connections exists within the V1 and between the V1 and higher visual cortical areas or thalamic nuclei, indicating that the V1 system is more than a mere receiver in information processing. Sensory representations in the V1 are dynamically correlated with neural activity oscillations that are distributed across different cortical layers in an input-dependent manner. Circuits consisting of excitatory pyramidal cells (PCs) and inhibitory interneurons (INs) are the basis for generating neural oscillations. In general, INs are clustered with their adjacent PCs to form specific microcircuits that gate or filter the neural information. The interaction between these two cell populations has to be coordinated within a local circuit in order to preserve neural coding schemes and maintain excitation-inhibition (E-I) balance. Phasic alternations of the E-I balance can dynamically regulate temporal rhythms of neural oscillation. Accumulating experimental evidence suggests that the two major sub-types of INs, parvalbumin-expressing (PV+) cells and somatostatin-expressing (SOM+) INs, are active in controlling slow and fast oscillations, respectively, in the mouse V1. The review summarizes recent experimental findings on elucidating cellular or circuitry mechanisms for the generation of neural oscillations with distinct rhythms in either developing or matured mouse V1, mainly focusing on visual relaying circuits and distinct local inhibitory circuits.
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Affiliation(s)
- Yuan Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
| | - Xiaohui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
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42
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Li B, Routh BN, Johnston D, Seidemann E, Priebe NJ. Voltage-Gated Intrinsic Conductances Shape the Input-Output Relationship of Cortical Neurons in Behaving Primate V1. Neuron 2020; 107:185-196.e4. [PMID: 32348717 DOI: 10.1016/j.neuron.2020.04.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 01/02/2020] [Accepted: 03/31/2020] [Indexed: 12/01/2022]
Abstract
Neurons are input-output (I/O) devices-they receive synaptic inputs from other neurons, integrate those inputs with their intrinsic properties, and generate action potentials as outputs. To understand this fundamental process, we studied the interaction between synaptic inputs and intrinsic properties using whole-cell recordings from V1 neurons of awake, fixating macaque monkeys. Our measurements during spontaneous activity and visual stimulation reveal an intrinsic voltage-gated conductance that profoundly alters the integrative properties and visual responses of cortical neurons. This voltage-gated conductance increases neuronal gain and selectivity with subthreshold depolarization and linearizes the relationship between synaptic input and neural output. This intrinsic conductance is found in layer 2/3 V1 neurons of awake macaques, anesthetized mice, and acute brain slices. These results demonstrate that intrinsic conductances play an essential role in shaping the I/O relationship of cortical neurons and must be taken into account in future models of cortical computations.
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Affiliation(s)
- Baowang Li
- Center for Perceptual Systems, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA; Center for Learning and Memory, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA; Department of Neuroscience, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA; Department of Psychology, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA
| | - Brandy N Routh
- Center for Learning and Memory, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA; Department of Neuroscience, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA
| | - Daniel Johnston
- Center for Learning and Memory, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA; Department of Neuroscience, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA
| | - Eyal Seidemann
- Center for Perceptual Systems, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA; Department of Neuroscience, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA; Department of Psychology, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA.
| | - Nicholas J Priebe
- Center for Learning and Memory, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA; Department of Neuroscience, The University of Texas at Austin, 2415 Speedway, Austin, TX 78712, USA.
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43
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Sanzeni A, Akitake B, Goldbach HC, Leedy CE, Brunel N, Histed MH. Inhibition stabilization is a widespread property of cortical networks. eLife 2020; 9:e54875. [PMID: 32598278 PMCID: PMC7324160 DOI: 10.7554/elife.54875] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Accepted: 05/21/2020] [Indexed: 12/19/2022] Open
Abstract
Many cortical network models use recurrent coupling strong enough to require inhibition for stabilization. Yet it has been experimentally unclear whether inhibition-stabilized network (ISN) models describe cortical function well across areas and states. Here, we test several ISN predictions, including the counterintuitive (paradoxical) suppression of inhibitory firing in response to optogenetic inhibitory stimulation. We find clear evidence for ISN operation in mouse visual, somatosensory, and motor cortex. Simple two-population ISN models describe the data well and let us quantify coupling strength. Although some models predict a non-ISN to ISN transition with increasingly strong sensory stimuli, we find ISN effects without sensory stimulation and even during light anesthesia. Additionally, average paradoxical effects result only with transgenic, not viral, opsin expression in parvalbumin (PV)-positive neurons; theory and expression data show this is consistent with ISN operation. Taken together, these results show strong coupling and inhibition stabilization are common features of the cortex.
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Affiliation(s)
- Alessandro Sanzeni
- NIMH Intramural Program, National Institutes of HealthBethesdaUnited States
- Department of Neurobiology, Duke UniversityDurhamUnited States
| | - Bradley Akitake
- NIMH Intramural Program, National Institutes of HealthBethesdaUnited States
| | - Hannah C Goldbach
- NIMH Intramural Program, National Institutes of HealthBethesdaUnited States
| | - Caitlin E Leedy
- NIMH Intramural Program, National Institutes of HealthBethesdaUnited States
| | - Nicolas Brunel
- Department of Neurobiology, Duke UniversityDurhamUnited States
| | - Mark H Histed
- NIMH Intramural Program, National Institutes of HealthBethesdaUnited States
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44
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Orekhova EV, Rostovtseva EN, Manyukhina VO, Prokofiev AO, Obukhova TS, Nikolaeva AY, Schneiderman JF, Stroganova TA. Spatial suppression in visual motion perception is driven by inhibition: Evidence from MEG gamma oscillations. Neuroimage 2020; 213:116753. [PMID: 32194278 DOI: 10.1016/j.neuroimage.2020.116753] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 02/14/2020] [Accepted: 03/14/2020] [Indexed: 12/21/2022] Open
Abstract
Spatial suppression (SS) is a visual perceptual phenomenon that is manifest in a reduction of directional sensitivity for drifting high-contrast gratings whose size exceeds the center of the visual field. Gratings moving at faster velocities induce stronger SS. The neural processes that give rise to such size- and velocity-dependent reductions in directional sensitivity are currently unknown, and the role of surround inhibition is unclear. In magnetoencephalogram (MEG), large high-contrast drifting gratings induce a strong gamma response (GR), which also attenuates with an increase in the gratings' velocity. It has been suggested that the slope of this GR attenuation is mediated by inhibitory interactions in the primary visual cortex. Herein, we investigate whether SS is related to this inhibitory-based MEG measure. We evaluated SS and GR in two independent samples of participants: school-age boys and adult women. The slope of GR attenuation predicted inter-individual differences in SS in both samples. Test-retest reliability of the neuro-behavioral correlation was assessed in the adults, and was high between two sessions separated by several days or weeks. Neither frequencies nor absolute amplitudes of the GRs correlated with SS, which highlights the functional relevance of velocity-related changes in GR magnitude caused by augmentation of incoming input. Our findings provide evidence that links the psychophysical phenomenon of SS to inhibitory-based neural responses in the human primary visual cortex. This supports the role of inhibitory interactions as an important underlying mechanism for spatial suppression.
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Affiliation(s)
- Elena V Orekhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation; MedTech West and the Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden.
| | - Ekaterina N Rostovtseva
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Viktoriya O Manyukhina
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation; National Research University Higher School of Economics, Moscow, Russian Federation, Moscow, Russian Federation
| | - Andrey O Prokofiev
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Tatiana S Obukhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Anastasia Yu Nikolaeva
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Justin F Schneiderman
- MedTech West and the Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden
| | - Tatiana A Stroganova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
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45
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Sadeh S, Clopath C. Patterned perturbation of inhibition can reveal the dynamical structure of neural processing. eLife 2020; 9:e52757. [PMID: 32073400 PMCID: PMC7180056 DOI: 10.7554/elife.52757] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 02/19/2020] [Indexed: 12/18/2022] Open
Abstract
Perturbation of neuronal activity is key to understanding the brain's functional properties, however, intervention studies typically perturb neurons in a nonspecific manner. Recent optogenetics techniques have enabled patterned perturbations, in which specific patterns of activity can be invoked in identified target neurons to reveal more specific cortical function. Here, we argue that patterned perturbation of neurons is in fact necessary to reveal the specific dynamics of inhibitory stabilization, emerging in cortical networks with strong excitatory and inhibitory functional subnetworks, as recently reported in mouse visual cortex. We propose a specific perturbative signature of these networks and investigate how this can be measured under different experimental conditions. Functionally, rapid spontaneous transitions between selective ensembles of neurons emerge in such networks, consistent with experimental results. Our study outlines the dynamical and functional properties of feature-specific inhibitory-stabilized networks, and suggests experimental protocols that can be used to detect them in the intact cortex.
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Affiliation(s)
- Sadra Sadeh
- Bioengineering Department, Imperial College LondonLondonUnited Kingdom
| | - Claudia Clopath
- Bioengineering Department, Imperial College LondonLondonUnited Kingdom
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46
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Orekhova EV, Prokofyev AO, Nikolaeva AY, Schneiderman JF, Stroganova TA. Additive effect of contrast and velocity suggests the role of strong excitatory drive in suppression of visual gamma response. PLoS One 2020; 15:e0228937. [PMID: 32053681 PMCID: PMC7018047 DOI: 10.1371/journal.pone.0228937] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 01/27/2020] [Indexed: 11/19/2022] Open
Abstract
It is commonly acknowledged that gamma-band oscillations arise from interplay between neural excitation and inhibition; however, the neural mechanisms controlling the power of stimulus-induced gamma responses (GR) in the human brain remain poorly understood. A moderate increase in velocity of drifting gratings results in GR power enhancement, while increasing the velocity beyond some 'transition point' leads to GR power attenuation. We tested two alternative explanations for this nonlinear input-output dependency in the GR power. First, the GR power can be maximal at the preferable velocity/temporal frequency of motion-sensitive V1 neurons. This 'velocity tuning' hypothesis predicts that lowering contrast either will not affect the transition point or shift it to a lower velocity. Second, the GR power attenuation at high velocities of visual motion can be caused by changes in excitation/inhibition balance with increasing excitatory drive. Since contrast and velocity both add to excitatory drive, this 'excitatory drive' hypothesis predicts that the 'transition point' for low-contrast gratings would be reached at a higher velocity, as compared to high-contrast gratings. To test these alternatives, we recorded magnetoencephalography during presentation of low (50%) and high (100%) contrast gratings drifting at four velocities. We found that lowering contrast led to a highly reliable shift of the GR suppression transition point to higher velocities, thus supporting the excitatory drive hypothesis. No effects of contrast or velocity were found in the alpha-beta range. The results have implications for understanding the mechanisms of gamma oscillations and developing gamma-based biomarkers of disturbed excitation/inhibition balance in brain disorders.
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Affiliation(s)
- Elena V. Orekhova
- Moscow State University of Psychology and Education, Center for Neurocognitive Research (MEG Center), Moscow, Russia
- University of Gothenburg, Sahlgrenska Academy, Institute of Neuroscience &Physiology, Department of Clinical Neuroscience, Gothenburg, Sweden
- MedTech West, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Andrey O. Prokofyev
- Moscow State University of Psychology and Education, Center for Neurocognitive Research (MEG Center), Moscow, Russia
| | - Anastasia Yu. Nikolaeva
- Moscow State University of Psychology and Education, Center for Neurocognitive Research (MEG Center), Moscow, Russia
| | - Justin F. Schneiderman
- University of Gothenburg, Sahlgrenska Academy, Institute of Neuroscience &Physiology, Department of Clinical Neuroscience, Gothenburg, Sweden
- MedTech West, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Tatiana A. Stroganova
- Moscow State University of Psychology and Education, Center for Neurocognitive Research (MEG Center), Moscow, Russia
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47
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Abstract
Changes in brain state modulate how information is processed in sensory cortical areas. Here we use population imaging and intracellular recording to show that arousal regulates frequency tuning in layer 2/3 of primary auditory cortex. Increased arousal reduces lateral inhibition, broadens frequency tuning and enhances cortical representations of pure tones. Despite the arousal-dependent reduction in stimulus selectivity, frequency discrimination by cell ensembles improves due to a reduction in correlated variability (noise correlations). Changes in arousal influence cortical sensory representations, but the synaptic mechanisms underlying arousal-dependent modulation of cortical processing are unclear. Here, we use 2-photon Ca2+ imaging in the auditory cortex of awake mice to show that heightened arousal, as indexed by pupil diameter, broadens frequency-tuned activity of layer 2/3 (L2/3) pyramidal cells. Sensory representations are less sparse, and the tuning of nearby cells more similar when arousal increases. Despite the reduction in selectivity, frequency discrimination by cell ensembles improves due to a decrease in shared trial-to-trial variability. In vivo whole-cell recordings reveal that mechanisms contributing to the effects of arousal on sensory representations include state-dependent modulation of membrane potential dynamics, spontaneous firing, and tone-evoked synaptic potentials. Surprisingly, changes in short-latency tone-evoked excitatory input cannot explain the effects of arousal on the broadness of frequency-tuned output. However, we show that arousal strongly modulates a slow tone-evoked suppression of recurrent excitation underlying lateral inhibition [H. K. Kato, S. K. Asinof, J. S. Isaacson, Neuron, 95, 412–423, (2017)]. This arousal-dependent “network suppression” gates the duration of tone-evoked responses and regulates the broadness of frequency tuning. Thus, arousal can shape tuning via modulation of indirect changes in recurrent network activity.
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48
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Scholl B, Wilson DE, Jaepel J, Fitzpatrick D. Functional Logic of Layer 2/3 Inhibitory Connectivity in the Ferret Visual Cortex. Neuron 2019; 104:451-457.e3. [PMID: 31495646 DOI: 10.1016/j.neuron.2019.08.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 05/29/2019] [Accepted: 08/01/2019] [Indexed: 10/26/2022]
Abstract
Understanding how cortical inhibition shapes circuit function requires identifying the connectivity rules relating the response properties of inhibitory interneurons and their postsynaptic targets. Here we explore the orientation tuning of layer 2/3 inhibitory inputs in the ferret visual cortex using a combination of in vivo axon imaging, functional input mapping, and physiology. Inhibitory boutons exhibit robust orientation-tuned responses with preferences that can differ significantly from the cortical column in which they reside. Inhibitory input fields measured with patterned optogenetic stimulation and intracellular recordings revealed that these inputs originate from a wide range of orientation domains, inconsistent with a model of co-tuned inhibition and excitation. Intracellular synaptic conductance measurements confirm that individual neurons can depart from a co-tuned regime. Our results argue against a simple rule for the arrangement of inhibitory inputs supplied by layer 2/3 circuits and suggest that heterogeneity in presynaptic inhibitory networks contributes to neural response properties.
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Affiliation(s)
- Benjamin Scholl
- Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA.
| | | | - Juliane Jaepel
- Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA
| | - David Fitzpatrick
- Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA
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49
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Heeger DJ, Mackey WE. Oscillatory recurrent gated neural integrator circuits (ORGaNICs), a unifying theoretical framework for neural dynamics. Proc Natl Acad Sci U S A 2019; 116:22783-22794. [PMID: 31636212 PMCID: PMC6842604 DOI: 10.1073/pnas.1911633116] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Working memory is an example of a cognitive and neural process that is not static but evolves dynamically with changing sensory inputs; another example is motor preparation and execution. We introduce a theoretical framework for neural dynamics, based on oscillatory recurrent gated neural integrator circuits (ORGaNICs), and apply it to simulate key phenomena of working memory and motor control. The model circuits simulate neural activity with complex dynamics, including sequential activity and traveling waves of activity, that manipulate (as well as maintain) information during working memory. The same circuits convert spatial patterns of premotor activity to temporal profiles of motor control activity and manipulate (e.g., time warp) the dynamics. Derivative-like recurrent connectivity, in particular, serves to manipulate and update internal models, an essential feature of working memory and motor execution. In addition, these circuits incorporate recurrent normalization, to ensure stability over time and robustness with respect to perturbations of synaptic weights.
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Affiliation(s)
- David J Heeger
- Department of Psychology, New York University, New York, NY 10003;
- Center for Neural Science, New York University, New York, NY 10003
| | - Wayne E Mackey
- Department of Psychology, New York University, New York, NY 10003
- Center for Neural Science, New York University, New York, NY 10003
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50
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Coen-Cagli R, Solomon SS. Relating Divisive Normalization to Neuronal Response Variability. J Neurosci 2019; 39:7344-7356. [PMID: 31387914 PMCID: PMC6759019 DOI: 10.1523/jneurosci.0126-19.2019] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 06/13/2019] [Accepted: 06/18/2019] [Indexed: 01/13/2023] Open
Abstract
Cortical responses to repeated presentations of a sensory stimulus are variable. This variability is sensitive to several stimulus dimensions, suggesting that it may carry useful information beyond the average firing rate. Many experimental manipulations that affect response variability are also known to engage divisive normalization, a widespread operation that describes neuronal activity as the ratio of a numerator (representing the excitatory stimulus drive) and denominator (the normalization signal). Although it has been suggested that normalization affects response variability, we lack a quantitative framework to determine the relation between the two. Here we extend the standard normalization model, by treating the numerator and the normalization signal as variable quantities. The resulting model predicts a general stabilizing effect of normalization on neuronal responses, and allows us to infer the single-trial normalization strength, a quantity that cannot be measured directly. We test the model on neuronal responses to stimuli of varying contrast, recorded in primary visual cortex of male macaques. We find that neurons that are more strongly normalized fire more reliably, and response variability and pairwise noise correlations are reduced during trials in which normalization is inferred to be strong. Our results thus suggest a novel functional role for normalization, namely, modulating response variability. Our framework could enable a direct quantification of the impact of single-trial normalization strength on the accuracy of perceptual judgments, and can be readily applied to other sensory and nonsensory factors.SIGNIFICANCE STATEMENT Divisive normalization is a widespread neural operation across sensory and nonsensory brain areas, which describes neuronal responses as the ratio between the excitatory drive to the neuron and a normalization signal. Normalization plays a key role in several important computations, including adjusting the neuron's dynamic range, reducing redundancy, and facilitating probabilistic inference. However, the relation between normalization and neuronal response variability (a fundamental aspect of neural coding) remains unclear. Here we develop a new model and test it on primary visual cortex responses. We show that normalization has a stabilizing effect on neuronal activity, beyond the known suppression of firing rate. This modulation of variability suggests a new functional role for normalization in neural coding and perception.
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Affiliation(s)
- Ruben Coen-Cagli
- Department of Systems and Computational Biology, and
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York 10461
| | - Selina S Solomon
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York 10461
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