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Bian Y, Kawabata R, Enwright JF, Tsubomoto M, Okuda T, Kamikawa K, Kimoto S, Kikuchi M, Lewis DA, Hashimoto T. Expression of activity-regulated transcripts in pyramidal neurons across the cortical visuospatial working memory network in unaffected comparison individuals and individuals with schizophrenia. Psychiatry Res 2024; 339:116084. [PMID: 39033685 DOI: 10.1016/j.psychres.2024.116084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 07/03/2024] [Accepted: 07/10/2024] [Indexed: 07/23/2024]
Abstract
Visuospatial working memory (vsWM), which is impaired in schizophrenia (SZ), is mediated by multiple cortical regions including the primary (V1) and association (V2) visual, posterior parietal (PPC) and dorsolateral prefrontal (DLPFC) cortices. In these regions, parvalbumin (PV) or somatostatin (SST) GABA neurons are altered in SZ as reflected in lower levels of activity-regulated transcripts. As PV and SST neurons receive excitatory inputs from neighboring pyramidal neurons, we hypothesized that levels of activity-regulated transcripts are also lower in pyramidal neurons in these regions. Thus, we quantified levels of four activity-regulated, pyramidal neuron-selective transcripts, namely adenylate cyclase-activating polypeptide-1 (ADCYAP1), brain-derived neurotrophic factor (BDNF), neuronal pentraxin-2 (NPTX2) and neuritin-1 (NRN1) mRNAs, in V1, V2, PPC and DLPFC from unaffected comparison and SZ individuals. In SZ, BDNF and NPTX2 mRNA levels were lower across all four regions, whereas ADCYAP1 and NRN1 mRNA levels were lower in V1 and V2. The regional pattern of deficits in BDNF and NPTX2 mRNAs was similar to that in transcripts in PV and SST neurons in SZ. These findings suggest that lower activity of pyramidal neurons expressing BDNF and/or NPTX2 mRNAs might contribute to alterations in PV and SST neurons across the vsWM network in SZ.
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Affiliation(s)
- Yufan Bian
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Rika Kawabata
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - John F Enwright
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Makoto Tsubomoto
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Takeshi Okuda
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
| | - Kohei Kamikawa
- Department of Psychiatry, Nara Medical University School of Medicine, Kashihara, 634-8521, Japan
| | - Sohei Kimoto
- Department of Psychiatry, Nara Medical University School of Medicine, Kashihara, 634-8521, Japan; Department of Neuropsychiatry, Wakayama Medical University School of Medicine, Wakayama, 641-8509, Japan
| | - Mitsuru Kikuchi
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan; Research Center for Child Development, Kanazawa University, Kanazawa 920-8640, Japan
| | - David A Lewis
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15213, USA.
| | - Takanori Hashimoto
- Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; National Hospital Organization Hokuriku Hospital, Nanto, 939-1893, Japan.
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2
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Yip MC, Gonzalez MM, Lewallen CF, Landry CR, Kolb I, Yang B, Stoy WM, Fong MF, Rowan MJ, Boyden ES, Forest CR. Patch-walking: Coordinated multi-pipette patch clamp for efficiently finding synaptic connections. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.30.587445. [PMID: 39185225 PMCID: PMC11343158 DOI: 10.1101/2024.03.30.587445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Significant technical challenges exist when measuring synaptic connections between neurons in living brain tissue. The patch clamping technique, when used to probe for synaptic connections, is manually laborious and time-consuming. To improve its efficiency, we pursued another approach: instead of retracting all patch clamping electrodes after each recording attempt, we cleaned just one of them and reused it to obtain another recording while maintaining the others. With one new patch clamp recording attempt, many new connections can be probed. By placing one pipette in front of the others in this way, one can "walk" across the tissue, termed "patch-walking." We performed 136 patch clamp attempts for two pipettes, achieving 71 successful whole cell recordings (52.2%). Of these, we probed 29 pairs (i.e., 58 bidirectional probed connections) averaging 91 μm intersomatic distance, finding 3 connections. Patch-walking yields 80-92% more probed connections, for experiments with 10-100 cells than the traditional synaptic connection searching method.
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Affiliation(s)
- Mighten C. Yip
- George W Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 315 Ferst Dr, Atlanta, GA, 30363, USA
| | - Mercedes M. Gonzalez
- George W Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 315 Ferst Dr, Atlanta, GA, 30363, USA
| | - Colby F. Lewallen
- Ocular and Stem Cell Translational Research Section, Ophthalmic Genetics and Visual Function Branch, National Eye Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Corey R. Landry
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 315 Ferst Dr, Atlanta, GA, 30363, USA
| | - Ilya Kolb
- GENIE Project Team, Janelia Research Campus Howard Hughes Medical Institute, Ashburn, VA, 20147, USA
| | - Bo Yang
- George W Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 315 Ferst Dr, Atlanta, GA, 30363, USA
| | - William M. Stoy
- Department of Electrical Engineering, Columbia University, New York, NY, 10027, USA
| | - Ming-fai Fong
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 315 Ferst Dr, Atlanta, GA, 30363, USA
| | - Matthew J.M. Rowan
- Department of Cell Biology, Emory University, 615 Michael St, Atlanta, GA, 30322, USA
| | - Edward S. Boyden
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Howard Hughes Medical Institute, Cambridge, MA, USA
| | - Craig R. Forest
- George W Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 315 Ferst Dr, Atlanta, GA, 30363, USA
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3
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Lee SY, Kozalakis K, Baftizadeh F, Campagnola L, Jarsky T, Koch C, Anastassiou CA. Cell-class-specific electric field entrainment of neural activity. Neuron 2024; 112:2614-2630.e5. [PMID: 38838670 PMCID: PMC11309920 DOI: 10.1016/j.neuron.2024.05.009] [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: 02/06/2023] [Revised: 12/14/2023] [Accepted: 05/08/2024] [Indexed: 06/07/2024]
Abstract
Electric fields affect the activity of neurons and brain circuits, yet how this happens at the cellular level remains enigmatic. Lack of understanding of how to stimulate the brain to promote or suppress specific activity significantly limits basic research and clinical applications. Here, we study how electric fields impact subthreshold and spiking properties of major cortical neuronal classes. We find that neurons in the rodent and human cortex exhibit strong, cell-class-dependent entrainment that depends on stimulation frequency. Excitatory pyramidal neurons, with their slower spike rate, entrain to both slow and fast electric fields, while inhibitory classes like Pvalb and Sst (with their fast spiking) predominantly phase-lock to fast fields. We show that this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties are present across cortical areas and species. These findings allow for the design of selective and class-specific neuromodulation.
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Affiliation(s)
| | | | | | | | | | | | - Costas A Anastassiou
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Center for Biomedical Science, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
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4
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Cho E, Kwon J, Lee G, Shin J, Lee H, Lee SH, Chung CK, Yoon J, Ho WK. Net synaptic drive of fast-spiking interneurons is inverted towards inhibition in human FCD I epilepsy. Nat Commun 2024; 15:6683. [PMID: 39107293 PMCID: PMC11303528 DOI: 10.1038/s41467-024-51065-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 07/26/2024] [Indexed: 08/10/2024] Open
Abstract
Focal cortical dysplasia type I (FCD I) is the most common cause of pharmaco-resistant epilepsy with the poorest prognosis. To understand the epileptogenic mechanisms of FCD I, we obtained tissue resected from patients with FCD I epilepsy, and from tumor patients as control. Using whole-cell patch clamp in acute human brain slices, we investigated the cellular properties of fast-spiking interneurons (FSINs) and pyramidal neurons (PNs) within the ictal onset zone. In FCD I epilepsy, FSINs exhibited lower firing rates from slower repolarization and action potential broadening, while PNs had increased firing. Importantly, excitatory synaptic drive of FSINs increased progressively with the scale of cortical activation as a general property across species, but this relationship was inverted towards net inhibition in FCD I epilepsy. Further comparison with intracranial electroencephalography (iEEG) from the same patients revealed that the spatial extent of pathological high-frequency oscillations (pHFO) was associated with synaptic events at FSINs.
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Affiliation(s)
- Eunhye Cho
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Jii Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Gyuwon Lee
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Jiwoo Shin
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Hyunsu Lee
- Department of Physiology, Pusan National University School of Medicine, Busan, Korea
| | - Suk-Ho Lee
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Chun Kee Chung
- Department of Neurosurgery, Seoul National University Hospital, Seoul, Korea.
- Neuroscience Research Institute, Seoul National University Medical Research Center, Seoul, Korea.
| | - Jaeyoung Yoon
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea.
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Won-Kyung Ho
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea.
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea.
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5
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Iwase M, Diba K, Pastalkova E, Mizuseki K. Dynamics of spike transmission and suppression between principal cells and interneurons in the hippocampus and entorhinal cortex. Hippocampus 2024; 34:393-421. [PMID: 38874439 DOI: 10.1002/hipo.23612] [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: 12/01/2023] [Revised: 03/29/2024] [Accepted: 05/07/2024] [Indexed: 06/15/2024]
Abstract
Synaptic excitation and inhibition are essential for neuronal communication. However, the variables that regulate synaptic excitation and inhibition in the intact brain remain largely unknown. Here, we examined how spike transmission and suppression between principal cells (PCs) and interneurons (INTs) are modulated by activity history, brain state, cell type, and somatic distance between presynaptic and postsynaptic neurons by applying cross-correlogram analyses to datasets recorded from the dorsal hippocampus and medial entorhinal cortex (MEC) of 11 male behaving and sleeping Long Evans rats. The strength, temporal delay, and brain-state dependency of the spike transmission and suppression depended on the subregions/layers. The spike transmission probability of PC-INT excitatory pairs that showed short-term depression versus short-term facilitation was higher in CA1 and lower in CA3. Likewise, the intersomatic distance affected the proportion of PC-INT excitatory pairs that showed short-term depression and facilitation in the opposite manner in CA1 compared with CA3. The time constant of depression was longer, while that of facilitation was shorter in MEC than in CA1 and CA3. During sharp-wave ripples, spike transmission showed a larger gain in the MEC than in CA1 and CA3. The intersomatic distance affected the spike transmission gain during sharp-wave ripples differently in CA1 versus CA3. A subgroup of MEC layer 3 (EC3) INTs preferentially received excitatory inputs from and inhibited MEC layer 2 (EC2) PCs. The EC2 PC-EC3 INT excitatory pairs, most of which showed short-term depression, exhibited higher spike transmission probabilities than the EC2 PC-EC2 INT and EC3 PC-EC3 INT excitatory pairs. EC2 putative stellate cells exhibited stronger spike transmission to and received weaker spike suppression from EC3 INTs than EC2 putative pyramidal cells. This study provides detailed comparisons of monosynaptic interaction dynamics in the hippocampal-entorhinal loop, which may help to elucidate circuit operations.
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Affiliation(s)
- Motosada Iwase
- Department of Physiology, Graduate School of Medicine, Osaka City University, Osaka, Japan
- Department of Physiology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
| | - Kamran Diba
- Department of Anesthesiology, Neuroscience Graduate Program, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Eva Pastalkova
- The William Alanson White Institute of Psychiatry, Psychoanalysis & Psychology, New York, New York, USA
| | - Kenji Mizuseki
- Department of Physiology, Graduate School of Medicine, Osaka City University, Osaka, Japan
- Department of Physiology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
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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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7
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Tobin M, Sheth J, Wood KC, Michel EK, Geffen MN. "Distinct inhibitory neurons differently shape neuronal codes for sound intensity in the auditory cortex". BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.02.01.526470. [PMID: 36778269 PMCID: PMC9915672 DOI: 10.1101/2023.02.01.526470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons have distinct effects on population neuronal responses to noise bursts of varying intensities. We optogenetically stimulated SST or VIP neurons while simultaneously measuring the calcium responses of populations of hundreds of neurons in the auditory cortex of male and female awake, head-fixed mice to sounds. Upon SST neuronal activation, noise bursts representations became more discrete for different intensity levels, relying on cell identity rather than strength. By contrast, upon VIP neuronal activation, noise bursts of different intensity level activated overlapping neuronal populations, albeit at different response strengths. At the single-cell level, SST and VIP neuronal activation differentially activated the response-level curves of monotonic and nonmonotonic neurons. SST neuronal activation effects were consistent with a shift of the neuronal population responses toward a more localist code with different cells responding to sounds of different intensity. By contrast, VIP neuronal activation shifted responses towards a more distributed code, in which sounds of different intensity level are encoded in the relative response of similar populations of cells. These results delineate how distinct inhibitory neurons in the auditory cortex dynamically control cortical population codes. Different inhibitory neuronal populations may be recruited under different behavioral demands, depending on whether categorical or invariant representations are advantageous for the task.
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Affiliation(s)
- Melanie Tobin
- Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Janaki Sheth
- Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Katherine C. Wood
- Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Erin K. Michel
- Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Maria N. Geffen
- Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, PA 19104, United States
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, United States
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, United States
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Yang X, La Camera G. Co-existence of synaptic plasticity and metastable dynamics in a spiking model of cortical circuits. PLoS Comput Biol 2024; 20:e1012220. [PMID: 38950068 PMCID: PMC11244818 DOI: 10.1371/journal.pcbi.1012220] [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: 01/05/2024] [Revised: 07/12/2024] [Accepted: 06/01/2024] [Indexed: 07/03/2024] Open
Abstract
Evidence for metastable dynamics and its role in brain function is emerging at a fast pace and is changing our understanding of neural coding by putting an emphasis on hidden states of transient activity. Clustered networks of spiking neurons have enhanced synaptic connections among groups of neurons forming structures called cell assemblies; such networks are capable of producing metastable dynamics that is in agreement with many experimental results. However, it is unclear how a clustered network structure producing metastable dynamics may emerge from a fully local plasticity rule, i.e., a plasticity rule where each synapse has only access to the activity of the neurons it connects (as opposed to the activity of other neurons or other synapses). Here, we propose a local plasticity rule producing ongoing metastable dynamics in a deterministic, recurrent network of spiking neurons. The metastable dynamics co-exists with ongoing plasticity and is the consequence of a self-tuning mechanism that keeps the synaptic weights close to the instability line where memories are spontaneously reactivated. In turn, the synaptic structure is stable to ongoing dynamics and random perturbations, yet it remains sufficiently plastic to remap sensory representations to encode new sets of stimuli. Both the plasticity rule and the metastable dynamics scale well with network size, with synaptic stability increasing with the number of neurons. Overall, our results show that it is possible to generate metastable dynamics over meaningful hidden states using a simple but biologically plausible plasticity rule which co-exists with ongoing neural dynamics.
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Affiliation(s)
- Xiaoyu Yang
- Graduate Program in Physics and Astronomy, Stony Brook University, Stony Brook, New York, United States of America
- Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, New York, United States of America
- Center for Neural Circuit Dynamics, Stony Brook University, Stony Brook, New York, United States of America
| | - Giancarlo La Camera
- Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, New York, United States of America
- Center for Neural Circuit Dynamics, Stony Brook University, Stony Brook, New York, United States of America
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Tan S, Dengler AS, Darawsheh RZ, Kory N. The iAAA-mitochondrial protease YME1L1 regulates the degradation of the short-lived mitochondrial transporter SLC25A38. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.12.593764. [PMID: 38979268 PMCID: PMC11230184 DOI: 10.1101/2024.05.12.593764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Mitochondrial transporters facilitate the exchange of diverse metabolic intermediates across the inner mitochondrial membrane, ensuring an adequate supply of substrates and cofactors to support redox and biosynthetic reactions within the mitochondrial matrix. However, the regulatory mechanisms governing the abundance of these transporters, crucial for maintaining metabolic compartmentalization and mitochondrial functions, remain poorly defined. Through analysis of protein half-life data and mRNA-protein correlations, we identified SLC25A38, a mitochondrial glycine transporter, as a short- lived protein with a half-life of 4 hours under steady-state conditions. Pharmacological inhibition and genetic depletion of various cellular proteolytic systems revealed that SLC25A38 is rapidly degraded by the iAAA-mitochondrial protease YME1L1. Depolarization of the mitochondrial membrane potential induced by the mitochondrial uncoupler carbonyl cyanide m-chlorophenylhydrozone prevented the degradation of SLC25A38. This dual regulation of SLC25A38 abundance by YME1L1 and mitochondrial membrane potential suggests a link between SLC25A38 turnover, the integrity of the inner mitochondrial membrane, and electron transport chain function. These findings open avenues for investigating whether mitochondrial glycine import coordinates with mitochondrial bioenergetics.
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Mahon S. Variation and convergence in the morpho-functional properties of the mammalian neocortex. Front Syst Neurosci 2024; 18:1413780. [PMID: 38966330 PMCID: PMC11222651 DOI: 10.3389/fnsys.2024.1413780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Accepted: 06/03/2024] [Indexed: 07/06/2024] Open
Abstract
Man's natural inclination to classify and hierarchize the living world has prompted neurophysiologists to explore possible differences in brain organisation between mammals, with the aim of understanding the diversity of their behavioural repertoires. But what really distinguishes the human brain from that of a platypus, an opossum or a rodent? In this review, we compare the structural and electrical properties of neocortical neurons in the main mammalian radiations and examine their impact on the functioning of the networks they form. We discuss variations in overall brain size, number of neurons, length of their dendritic trees and density of spines, acknowledging their increase in humans as in most large-brained species. Our comparative analysis also highlights a remarkable consistency, particularly pronounced in marsupial and placental mammals, in the cell typology, intrinsic and synaptic electrical properties of pyramidal neuron subtypes, and in their organisation into functional circuits. These shared cellular and network characteristics contribute to the emergence of strikingly similar large-scale physiological and pathological brain dynamics across a wide range of species. These findings support the existence of a core set of neural principles and processes conserved throughout mammalian evolution, from which a number of species-specific adaptations appear, likely allowing distinct functional needs to be met in a variety of environmental contexts.
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Affiliation(s)
- Séverine Mahon
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
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11
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Koren V, Emanuel AJ, Panzeri S. Spiking networks that efficiently process dynamic sensory features explain receptor information mixing in somatosensory cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.07.597979. [PMID: 38895477 PMCID: PMC11185787 DOI: 10.1101/2024.06.07.597979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
How do biological neural systems efficiently encode, transform and propagate information between the sensory periphery and the sensory cortex about sensory features evolving at different time scales? Are these computations efficient in normative information processing terms? While previous work has suggested that biologically plausible models of of such neural information processing may be implemented efficiently within a single processing layer, how such computations extend across several processing layers is less clear. Here, we model propagation of multiple time-varying sensory features across a sensory pathway, by extending the theory of efficient coding with spikes to efficient encoding, transformation and transmission of sensory signals. These computations are optimally realized by a multilayer spiking network with feedforward networks of spiking neurons (receptor layer) and recurrent excitatory-inhibitory networks of generalized leaky integrate-and-fire neurons (recurrent layers). Our model efficiently realizes a broad class of feature transformations, including positive and negative interaction across features, through specific and biologically plausible structures of feedforward connectivity. We find that mixing of sensory features in the activity of single neurons is beneficial because it lowers the metabolic cost at the network level. We apply the model to the somatosensory pathway by constraining it with parameters measured empirically and include in its last node, analogous to the primary somatosensory cortex (S1), two types of inhibitory neurons: parvalbumin-positive neurons realizing lateral inhibition, and somatostatin-positive neurons realizing winner-take-all inhibition. By implementing a negative interaction across stimulus features, this model captures several intriguing empirical observations from the somatosensory system of the mouse, including a decrease of sustained responses from subcortical networks to S1, a non-linear effect of the knock-out of receptor neuron types on the activity in S1, and amplification of weak signals from sensory neurons across the pathway.
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Affiliation(s)
- Veronika Koren
- Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), 20251 Hamburg, Germany
| | - Alan J Emanuel
- Department of Cell Biology, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Stefano Panzeri
- Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), 20251 Hamburg, Germany
- Istituto Italiano di Tecnologia, Genova, Italy
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Piet A, Ponvert N, Ollerenshaw D, Garrett M, Groblewski PA, Olsen S, Koch C, Arkhipov A. Behavioral strategy shapes activation of the Vip-Sst disinhibitory circuit in visual cortex. Neuron 2024; 112:1876-1890.e4. [PMID: 38447579 PMCID: PMC11156560 DOI: 10.1016/j.neuron.2024.02.008] [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: 05/31/2023] [Revised: 11/17/2023] [Accepted: 02/08/2024] [Indexed: 03/08/2024]
Abstract
In complex environments, animals can adopt diverse strategies to find rewards. How distinct strategies differentially engage brain circuits is not well understood. Here, we investigate this question, focusing on the cortical Vip-Sst disinhibitory circuit between vasoactive intestinal peptide-postive (Vip) interneurons and somatostatin-positive (Sst) interneurons. We characterize the behavioral strategies used by mice during a visual change detection task. Using a dynamic logistic regression model, we find that individual mice use mixtures of a visual comparison strategy and a statistical timing strategy. Separately, mice also have periods of task engagement and disengagement. Two-photon calcium imaging shows large strategy-dependent differences in neural activity in excitatory, Sst inhibitory, and Vip inhibitory cells in response to both image changes and image omissions. In contrast, task engagement has limited effects on neural population activity. We find that the diversity of neural correlates of strategy can be understood parsimoniously as the increased activation of the Vip-Sst disinhibitory circuit during the visual comparison strategy, which facilitates task-appropriate responses.
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Affiliation(s)
- Alex Piet
- Allen Institute, Mindscope Program, Seattle, WA, USA.
| | - Nick Ponvert
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | | | | | | | - Shawn Olsen
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | - Christof Koch
- Allen Institute, Mindscope Program, Seattle, WA, USA
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13
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Aitken K, Campagnola L, Garrett ME, Olsen SR, Mihalas S. Simple synaptic modulations implement diverse novelty computations. Cell Rep 2024; 43:114188. [PMID: 38713584 DOI: 10.1016/j.celrep.2024.114188] [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: 11/06/2023] [Revised: 02/09/2024] [Accepted: 04/17/2024] [Indexed: 05/09/2024] Open
Abstract
Detecting novelty is ethologically useful for an organism's survival. Recent experiments characterize how different types of novelty over timescales from seconds to weeks are reflected in the activity of excitatory and inhibitory neuron types. Here, we introduce a learning mechanism, familiarity-modulated synapses (FMSs), consisting of multiplicative modulations dependent on presynaptic or pre/postsynaptic neuron activity. With FMSs, network responses that encode novelty emerge under unsupervised continual learning and minimal connectivity constraints. Implementing FMSs within an experimentally constrained model of a visual cortical circuit, we demonstrate the generalizability of FMSs by simultaneously fitting absolute, contextual, and omission novelty effects. Our model also reproduces functional diversity within cell subpopulations, leading to experimentally testable predictions about connectivity and synaptic dynamics that can produce both population-level novelty responses and heterogeneous individual neuron signals. Altogether, our findings demonstrate how simple plasticity mechanisms within a cortical circuit structure can produce qualitatively distinct and complex novelty responses.
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Affiliation(s)
- Kyle Aitken
- Center for Data-Driven Discovery for Biology, Allen Institute, Seattle, WA 98109, USA.
| | | | | | - Shawn R Olsen
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Stefan Mihalas
- Center for Data-Driven Discovery for Biology, Allen Institute, Seattle, WA 98109, USA; Applied Mathematics, University of Washington, Seattle, WA 98195, USA
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14
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Shah PT, Valiante TA, Packer AM. Highly local activation of inhibition at the seizure wavefront in vivo. Cell Rep 2024; 43:114189. [PMID: 38703365 DOI: 10.1016/j.celrep.2024.114189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 12/22/2023] [Accepted: 04/17/2024] [Indexed: 05/06/2024] Open
Abstract
The propagation of a seizure wavefront in the cortex divides an intensely firing seizure core from a low-firing seizure penumbra. Seizure propagation is currently thought to generate strong activation of inhibition in the seizure penumbra that leads to its decreased neuronal firing. However, the direct measurement of neuronal excitability during seizures has been difficult to perform in vivo. We used simultaneous optogenetics and calcium imaging (all-optical interrogation) to characterize real-time neuronal excitability in an acute mouse model of seizure propagation. We find that single-neuron excitability is decreased in close proximity to the seizure wavefront but becomes increased distal to the seizure wavefront. This suggests that inhibitory neurons of the seizure wavefront create a proximal circumference of hypoexcitability but do not influence neuronal excitability in the penumbra.
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Affiliation(s)
- Prajay T Shah
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Taufik A Valiante
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada; Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Adam M Packer
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK.
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15
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Benavides-Piccione R, Blazquez-Llorca L, Kastanauskaite A, Fernaud-Espinosa I, Tapia-González S, DeFelipe J. Key morphological features of human pyramidal neurons. Cereb Cortex 2024; 34:bhae180. [PMID: 38745556 PMCID: PMC11094408 DOI: 10.1093/cercor/bhae180] [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: 01/03/2024] [Revised: 04/01/2024] [Accepted: 04/18/2024] [Indexed: 05/16/2024] Open
Abstract
The basic building block of the cerebral cortex, the pyramidal cell, has been shown to be characterized by a markedly different dendritic structure among layers, cortical areas, and species. Functionally, differences in the structure of their dendrites and axons are critical in determining how neurons integrate information. However, within the human cortex, these neurons have not been quantified in detail. In the present work, we performed intracellular injections of Lucifer Yellow and 3D reconstructed over 200 pyramidal neurons, including apical and basal dendritic and local axonal arbors and dendritic spines, from human occipital primary visual area and associative temporal cortex. We found that human pyramidal neurons from temporal cortex were larger, displayed more complex apical and basal structural organization, and had more spines compared to those in primary sensory cortex. Moreover, these human neocortical neurons displayed specific shared and distinct characteristics in comparison to previously published human hippocampal pyramidal neurons. Additionally, we identified distinct morphological features in human neurons that set them apart from mouse neurons. Lastly, we observed certain consistent organizational patterns shared across species. This study emphasizes the existing diversity within pyramidal cell structures across different cortical areas and species, suggesting substantial species-specific variations in their computational properties.
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Affiliation(s)
- Ruth Benavides-Piccione
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
| | - Lidia Blazquez-Llorca
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
- Departamento de Tecnología Fotónica y Bioingeniería, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040, Spain
| | - Asta Kastanauskaite
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
| | - Isabel Fernaud-Espinosa
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
| | - Silvia Tapia-González
- Laboratorio de Neurofisiología Celular, Facultad de Medicina, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
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16
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Huang Z, Wei X, Tian J, Fu Y, Dong J, Wang Y, Shi J, Lu L, Zhang W. A disinhibitory microcircuit of the orbitofrontal cortex mediates cocaine preference in mice. Mol Psychiatry 2024:10.1038/s41380-024-02579-5. [PMID: 38698268 DOI: 10.1038/s41380-024-02579-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 04/18/2024] [Accepted: 04/22/2024] [Indexed: 05/05/2024]
Abstract
Both clinical and animal studies showed that the impaired functions of the orbitofrontal cortex (OFC) underlie the compulsive drug-seeking behavior of drug addiction. However, the functional changes of the microcircuit in the OFC and the underlying molecular mechanisms in drug addiction remain elusive, and little is known for whether microcircuits in the OFC contributed to drug addiction-related behaviors. Utilizing the cocaine-induced conditioned-place preference model, we found that the malfunction of the microcircuit led to disinhibition in the OFC after cocaine withdrawal. We further showed that enhanced Somatostatin-Parvalbumin (SST-PV) inhibitory synapse strength changed microcircuit function, and SST and PV inhibitory neurons showed opposite contributions to the drug addiction-related behavior of mice. Brevican of the perineuronal nets of PV neurons regulated SST-PV synapse strength, and the knockdown of Brevican alleviated cocaine preference. These results reveal a novel molecular mechanism of the regulation of microcircuit function and a novel circuit mechanism of the OFC in gating cocaine preference.
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Affiliation(s)
- Ziran Huang
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, 100191, China
| | - Xiaoyan Wei
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, 100191, China
| | - Jing Tian
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, 100191, China
| | - Yangxue Fu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, 100191, China
| | - Jihui Dong
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, 100191, China
| | - Yihui Wang
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, 100191, China
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, 100191, China
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital); Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100191, China
| | - Wen Zhang
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, 100191, China.
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17
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Maass W. How can neuromorphic hardware attain brain-like functional capabilities? Natl Sci Rev 2024; 11:nwad301. [PMID: 38577672 PMCID: PMC10989294 DOI: 10.1093/nsr/nwad301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 10/22/2023] [Accepted: 11/30/2023] [Indexed: 04/06/2024] Open
Abstract
The author provides 4 design principles of how to make cortical microcircuits into neuromorphic hardwares, shedding light for the next generation neuromorphic hardware design.
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Affiliation(s)
- Wolfgang Maass
- Computer Science and Biomedical Engineering, Graz University of Technology, Austria
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18
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Koren V, Malerba SB, Schwalger T, Panzeri S. Structure, dynamics, coding and optimal biophysical parameters of efficient excitatory-inhibitory spiking networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.590955. [PMID: 38712237 PMCID: PMC11071478 DOI: 10.1101/2024.04.24.590955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuro-science, it has remained unclear whether fundamental empirical properties of neural network activity can be explained solely based on this normative principle. Here, we rigorously derive the structural, coding, biophysical and dynamical properties of excitatory-inhibitory recurrent networks of spiking neurons that emerge directly from imposing that the network minimizes an instantaneous loss function and a time-averaged performance measure enacting efficient coding. The optimal network has biologically-plausible biophysical features, including realistic integrate-and-fire spiking dynamics, spike-triggered adaptation, and a non-stimulus-specific excitatory external input regulating metabolic cost. The efficient network has excitatory-inhibitory recurrent connectivity between neurons with similar stimulus tuning implementing feature-specific competition, similar to that recently found in visual cortex. Networks with unstructured connectivity cannot reach comparable levels of coding efficiency. The optimal biophysical parameters include 4 to 1 ratio of excitatory vs inhibitory neurons and 3 to 1 ratio of mean inhibitory-to-inhibitory vs. excitatory-to-inhibitory connectivity that closely match those of cortical sensory networks. The efficient network has biologically-plausible spiking dynamics, with a tight instantaneous E-I balance that makes them capable to achieve efficient coding of external stimuli varying over multiple time scales. Together, these results explain how efficient coding may be implemented in cortical networks and suggests that key properties of biological neural networks may be accounted for by efficient coding.
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19
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Celii B, Papadopoulos S, Ding Z, Fahey PG, Wang E, Papadopoulos C, Kunin AB, Patel S, Bae JA, Bodor AL, Brittain D, Buchanan J, Bumbarger DJ, Castro MA, Cobos E, Dorkenwald S, Elabbady L, Halageri A, Jia Z, Jordan C, Kapner D, Kemnitz N, Kinn S, Lee K, Li K, Lu R, Macrina T, Mahalingam G, Mitchell E, Mondal SS, Mu S, Nehoran B, Popovych S, Schneider-Mizell CM, Silversmith W, Takeno M, Torres R, Turner NL, Wong W, Wu J, Yu SC, Yin W, Xenes D, Kitchell LM, Rivlin PK, Rose VA, Bishop CA, Wester B, Froudarakis E, Walker EY, Sinz F, Seung HS, Collman F, da Costa NM, Reid RC, Pitkow X, Tolias AS, Reimer J. NEURD: automated proofreading and feature extraction for connectomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.14.532674. [PMID: 36993282 PMCID: PMC10055177 DOI: 10.1101/2023.03.14.532674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods can now yield exceptionally accurate reconstructions of cells, but despite this accuracy, laborious post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons produced by these segmentations contain detailed morphological information, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting information about these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes each meshed neuron into a compact and extensively-annotated graph representation. With these feature-rich graphs, we implement workflows to automate a variety of tasks that would otherwise require extensive manual effort, such as state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and computation of other features. These features enable many downstream analyses of neural morphology and connectivity, making these new massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.
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20
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Chen X, Fischer S, Rue MCP, Zhang A, Mukherjee D, Kanold PO, Gillis J, Zador AM. Whole-cortex in situ sequencing reveals input-dependent area identity. Nature 2024:10.1038/s41586-024-07221-6. [PMID: 38658747 DOI: 10.1038/s41586-024-07221-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 02/22/2024] [Indexed: 04/26/2024]
Abstract
The cerebral cortex is composed of neuronal types with diverse gene expression that are organized into specialized cortical areas. These areas, each with characteristic cytoarchitecture1,2, connectivity3,4 and neuronal activity5,6, are wired into modular networks3,4,7. However, it remains unclear whether these spatial organizations are reflected in neuronal transcriptomic signatures and how such signatures are established in development. Here we used BARseq, a high-throughput in situ sequencing technique, to interrogate the expression of 104 cell-type marker genes in 10.3 million cells, including 4,194,658 cortical neurons over nine mouse forebrain hemispheres, at cellular resolution. De novo clustering of gene expression in single neurons revealed transcriptomic types consistent with previous single-cell RNA sequencing studies8,9. The composition of transcriptomic types is highly predictive of cortical area identity. Moreover, areas with similar compositions of transcriptomic types, which we defined as cortical modules, overlap with areas that are highly connected, suggesting that the same modular organization is reflected in both transcriptomic signatures and connectivity. To explore how the transcriptomic profiles of cortical neurons depend on development, we assessed cell-type distributions after neonatal binocular enucleation. Notably, binocular enucleation caused the shifting of the cell-type compositional profiles of visual areas towards neighbouring cortical areas within the same module, suggesting that peripheral inputs sharpen the distinct transcriptomic identities of areas within cortical modules. Enabled by the high throughput, low cost and reproducibility of BARseq, our study provides a proof of principle for the use of large-scale in situ sequencing to both reveal brain-wide molecular architecture and understand its development.
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Affiliation(s)
- Xiaoyin Chen
- Allen Institute for Brain Science, Seattle, WA, USA.
| | - Stephan Fischer
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris, France
| | - Mara C P Rue
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Aixin Zhang
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Didhiti Mukherjee
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Patrick O Kanold
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA
| | - Jesse Gillis
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada.
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21
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Peng Y, Bjelde A, Aceituno PV, Mittermaier FX, Planert H, Grosser S, Onken J, Faust K, Kalbhenn T, Simon M, Radbruch H, Fidzinski P, Schmitz D, Alle H, Holtkamp M, Vida I, Grewe BF, Geiger JRP. Directed and acyclic synaptic connectivity in the human layer 2-3 cortical microcircuit. Science 2024; 384:338-343. [PMID: 38635709 DOI: 10.1126/science.adg8828] [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: 01/27/2023] [Accepted: 03/12/2024] [Indexed: 04/20/2024]
Abstract
The computational capabilities of neuronal networks are fundamentally constrained by their specific connectivity. Previous studies of cortical connectivity have mostly been carried out in rodents; whether the principles established therein also apply to the evolutionarily expanded human cortex is unclear. We studied network properties within the human temporal cortex using samples obtained from brain surgery. We analyzed multineuron patch-clamp recordings in layer 2-3 pyramidal neurons and identified substantial differences compared with rodents. Reciprocity showed random distribution, synaptic strength was independent from connection probability, and connectivity of the supragranular temporal cortex followed a directed and mostly acyclic graph topology. Application of these principles in neuronal models increased dimensionality of network dynamics, suggesting a critical role for cortical computation.
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Affiliation(s)
- Yangfan Peng
- Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Antje Bjelde
- Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Pau Vilimelis Aceituno
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, 8057 Zürich, Switzerland
| | - Franz X Mittermaier
- Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Henrike Planert
- Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Sabine Grosser
- Institute for Integrative Neuroanatomy, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Julia Onken
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Katharina Faust
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Thilo Kalbhenn
- Department of Neurosurgery (Evangelisches Klinikum Bethel), Medical School, Bielefeld University, 33617 Bielefeld, Germany
| | - Matthias Simon
- Department of Neurosurgery (Evangelisches Klinikum Bethel), Medical School, Bielefeld University, 33617 Bielefeld, Germany
| | - Helena Radbruch
- Department of Neuropathology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Pawel Fidzinski
- Clinical Study Center, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE) Berlin, 10117 Berlin, Germany
| | - Dietmar Schmitz
- German Center for Neurodegenerative Diseases (DZNE) Berlin, 10117 Berlin, Germany
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Henrik Alle
- Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Martin Holtkamp
- Epilepsy-Center Berlin-Brandenburg, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Imre Vida
- Institute for Integrative Neuroanatomy, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Benjamin F Grewe
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, 8057 Zürich, Switzerland
| | - Jörg R P Geiger
- Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany
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22
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Khanjanianpak M, Azimi-Tafreshi N, Valizadeh A. Emergence of complex oscillatory dynamics in the neuronal networks with long activity time of inhibitory synapses. iScience 2024; 27:109401. [PMID: 38532887 PMCID: PMC10963234 DOI: 10.1016/j.isci.2024.109401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 12/30/2023] [Accepted: 02/28/2024] [Indexed: 03/28/2024] Open
Abstract
The brain displays complex dynamics, including collective oscillations, and extensive research has been conducted to understand their generation. However, our understanding of how biological constraints influence these oscillations is incomplete. This study investigates the essential properties of neuronal networks needed to generate oscillations resembling those in the brain. A simple discrete-time model of interconnected excitable elements is developed, capable of closely resembling the complex oscillations observed in biological neural networks. In the model, synaptic connections remain active for a duration exceeding individual neuron activity. We show that the inhibitory synapses must exhibit longer activity than excitatory synapses to produce a diverse range of the dynamical states, including biologically plausible oscillations. Upon meeting this condition, the transition between different dynamical states can be controlled by external stochastic input to the neurons. The study provides a comprehensive explanation for the emergence of distinct dynamical states in neural networks based on specific parameters.
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Affiliation(s)
- Mozhgan Khanjanianpak
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran 1991633357, Iran
| | - Nahid Azimi-Tafreshi
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
| | - Alireza Valizadeh
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran 1991633357, Iran
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23
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McFarlan AR, Guo C, Gomez I, Weinerman C, Liang TA, Sjöström PJ. The spike-timing-dependent plasticity of VIP interneurons in motor cortex. Front Cell Neurosci 2024; 18:1389094. [PMID: 38706517 PMCID: PMC11066220 DOI: 10.3389/fncel.2024.1389094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 04/09/2024] [Indexed: 05/07/2024] Open
Abstract
The plasticity of inhibitory interneurons (INs) plays an important role in the organization and maintenance of cortical microcircuits. Given the many different IN types, there is an even greater diversity in synapse-type-specific plasticity learning rules at excitatory to excitatory (E→I), I→E, and I→I synapses. I→I synapses play a key disinhibitory role in cortical circuits. Because they typically target other INs, vasoactive intestinal peptide (VIP) INs are often featured in I→I→E disinhibition, which upregulates activity in nearby excitatory neurons. VIP IN dysregulation may thus lead to neuropathologies such as epilepsy. In spite of the important activity regulatory role of VIP INs, their long-term plasticity has not been described. Therefore, we characterized the phenomenology of spike-timing-dependent plasticity (STDP) at inputs and outputs of genetically defined VIP INs. Using a combination of whole-cell recording, 2-photon microscopy, and optogenetics, we explored I→I STDP at layer 2/3 (L2/3) VIP IN outputs onto L5 Martinotti cells (MCs) and basket cells (BCs). We found that VIP IN→MC synapses underwent causal long-term depression (LTD) that was presynaptically expressed. VIP IN→BC connections, however, did not undergo any detectable plasticity. Conversely, using extracellular stimulation, we explored E→I STDP at inputs to VIP INs which revealed long-term potentiation (LTP) for both causal and acausal timings. Taken together, our results demonstrate that VIP INs possess synapse-type-specific learning rules at their inputs and outputs. This suggests the possibility of harnessing VIP IN long-term plasticity to control activity-related neuropathologies such as epilepsy.
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Affiliation(s)
- Amanda R. McFarlan
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Connie Guo
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Isabella Gomez
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
| | - Chaim Weinerman
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
| | - Tasha A. Liang
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
| | - P. Jesper Sjöström
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
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24
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Waitzmann F, Wu YK, Gjorgjieva J. Top-down modulation in canonical cortical circuits with short-term plasticity. Proc Natl Acad Sci U S A 2024; 121:e2311040121. [PMID: 38593083 PMCID: PMC11032497 DOI: 10.1073/pnas.2311040121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 02/14/2024] [Indexed: 04/11/2024] Open
Abstract
Cortical dynamics and computations are strongly influenced by diverse GABAergic interneurons, including those expressing parvalbumin (PV), somatostatin (SST), and vasoactive intestinal peptide (VIP). Together with excitatory (E) neurons, they form a canonical microcircuit and exhibit counterintuitive nonlinear phenomena. One instance of such phenomena is response reversal, whereby SST neurons show opposite responses to top-down modulation via VIP depending on the presence of bottom-up sensory input, indicating that the network may function in different regimes under different stimulation conditions. Combining analytical and computational approaches, we demonstrate that model networks with multiple interneuron subtypes and experimentally identified short-term plasticity mechanisms can implement response reversal. Surprisingly, despite not directly affecting SST and VIP activity, PV-to-E short-term depression has a decisive impact on SST response reversal. We show how response reversal relates to inhibition stabilization and the paradoxical effect in the presence of several short-term plasticity mechanisms demonstrating that response reversal coincides with a change in the indispensability of SST for network stabilization. In summary, our work suggests a role of short-term plasticity mechanisms in generating nonlinear phenomena in networks with multiple interneuron subtypes and makes several experimentally testable predictions.
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Affiliation(s)
- Felix Waitzmann
- School of Life Sciences, Technical University of Munich, 85354Freising, Germany
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, 60438Frankfurt, Germany
| | - Yue Kris Wu
- School of Life Sciences, Technical University of Munich, 85354Freising, Germany
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, 60438Frankfurt, Germany
| | - Julijana Gjorgjieva
- School of Life Sciences, Technical University of Munich, 85354Freising, Germany
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, 60438Frankfurt, Germany
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25
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Shen Y, Shao M, Hao ZZ, Huang M, Xu N, Liu S. Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity. Neurosci Bull 2024; 40:517-532. [PMID: 38194157 PMCID: PMC11003949 DOI: 10.1007/s12264-023-01160-4] [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: 03/22/2023] [Accepted: 09/23/2023] [Indexed: 01/10/2024] Open
Abstract
Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.
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Affiliation(s)
- Yuhui Shen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Mingting Shao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Zhao-Zhe Hao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Mengyao Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Nana Xu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Sheng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Guangzhou, 510080, China.
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26
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Lagzi F, Fairhall AL. Emergence of co-tuning in inhibitory neurons as a network phenomenon mediated by randomness, correlations, and homeostatic plasticity. SCIENCE ADVANCES 2024; 10:eadi4350. [PMID: 38507489 DOI: 10.1126/sciadv.adi4350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 02/15/2024] [Indexed: 03/22/2024]
Abstract
Cortical excitatory neurons show clear tuning to stimulus features, but the tuning properties of inhibitory interneurons are ambiguous. While inhibitory neurons have been considered to be largely untuned, some studies show that some parvalbumin-expressing (PV) neurons do show feature selectivity and participate in co-tuned subnetworks with pyramidal neurons. In this study, we first use mean-field theory to demonstrate that a combination of homeostatic plasticity governing the synaptic dynamics of the connections from PV to excitatory neurons, heterogeneity in the excitatory postsynaptic potentials that impinge on PV neurons, and shared correlated input from layer 4 results in the functional and structural self-organization of PV subnetworks. Second, we show that structural and functional feature tuning of PV neurons emerges more clearly at the network level, i.e., that population-level measures identify functional and structural co-tuning of PV neurons that are not evident in pairwise individual-level measures. Finally, we show that such co-tuning can enhance network stability at the cost of reduced feature selectivity.
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Affiliation(s)
- Fereshteh Lagzi
- Department of Physiology and Biophysics, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7290, USA
- Computational Neuroscience Center, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7290, USA
| | - Adrienne L Fairhall
- Department of Physiology and Biophysics, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7290, USA
- Computational Neuroscience Center, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195-7290, USA
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27
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Günther DM, Batiuk MY, Petukhov V, De Oliveira R, Wunderle T, Buchholz CJ, Fries P, Khodosevich K. Heterogeneity of layer 4 in visual areas of rhesus macaque cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.11.584345. [PMID: 38559123 PMCID: PMC10979896 DOI: 10.1101/2024.03.11.584345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Recently, single-cell RNA-sequencing (scRNA-seq) has enabled unprecedented insights to the cellular landscape of the brains of many different species, among them the rhesus macaque as a key animal model. Building on previous, broader surveys of the macaque brain, we closely examined five immediately neighboring areas within the visual cortex of the rhesus macaque: V1, V2, V4, MT and TEO. To facilitate this, we first devised a novel pipeline for brain spatial archive - the BrainSPACE - which enabled robust archiving and sampling from the whole unfixed brain. SnRNA-sequencing of ~100,000 nuclei from visual areas V1 and V4 revealed conservation within the GABAergic neuron subtypes, while seven and one distinct principle neuron subtypes were detected in V1 and V4, respectively, all most likely located in layer 4. Moreover, using small molecule fluorescence in situ hybridization, we identified cell type density gradients across V1, V2, V4, MT, and TEO appearing to reflect the visual hierarchy. These findings demonstrate an association between the clear areal specializations among neighboring areas with the hierarchical levels within the visual cortex of the rhesus macaque.
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Affiliation(s)
- Dorothee M. Günther
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, the Netherlands
- Molecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, 63225 Langen, Germany
| | - Mykhailo Y. Batiuk
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Viktor Petukhov
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Romain De Oliveira
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Thomas Wunderle
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Christian J. Buchholz
- Molecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, 63225 Langen, Germany
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, the Netherlands
| | - Konstantin Khodosevich
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
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28
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Lee SY, Kozalakis K, Baftizadeh F, Campagnola L, Jarsky T, Koch C, Anastassiou CA. Cell class-specific electric field entrainment of neural activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.02.14.528526. [PMID: 36824721 PMCID: PMC9948976 DOI: 10.1101/2023.02.14.528526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Electric fields affect the activity of neurons and brain circuits, yet how this interaction happens at the cellular level remains enigmatic. Lack of understanding on how to stimulate the human brain to promote or suppress specific activity patterns significantly limits basic research and clinical applications. Here we study how electric fields impact the subthreshold and spiking properties of major cortical neuronal classes. We find that cortical neurons in rodent neocortex and hippocampus as well as human cortex exhibit strong and cell class-dependent entrainment that depends on the stimulation frequency. Excitatory pyramidal neurons with their typically slower spike rate entrain to slow and fast electric fields, while inhibitory classes like Pvalb and SST with their fast spiking predominantly phase lock to fast fields. We show this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties of spike-field and class-specific entrainment are present in cells across cortical areas and species (mouse and human). These findings open the door to the design of selective and class-specific neuromodulation technologies.
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Affiliation(s)
- Soo Yeun Lee
- Allen Institute for Brain Science, Seattle, Washington 98101, USA
| | - Konstantinos Kozalakis
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
| | | | - Luke Campagnola
- Allen Institute for Brain Science, Seattle, Washington 98101, USA
| | - Tim Jarsky
- Allen Institute for Brain Science, Seattle, Washington 98101, USA
| | - Christof Koch
- Allen Institute for Brain Science, Seattle, Washington 98101, USA
| | - Costas A Anastassiou
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
- Center for Biomedical Science, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
- Lead contact:
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29
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Meneghetti N, Vannini E, Mazzoni A. Rodents' visual gamma as a biomarker of pathological neural conditions. J Physiol 2024; 602:1017-1048. [PMID: 38372352 DOI: 10.1113/jp283858] [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: 12/13/2022] [Accepted: 01/23/2024] [Indexed: 02/20/2024] Open
Abstract
Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.
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Affiliation(s)
- Nicolò Meneghetti
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eleonora Vannini
- Neuroscience Institute, National Research Council (CNR), Pisa, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
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30
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Mendoza-Halliday D, Major AJ, Lee N, Lichtenfeld MJ, Carlson B, Mitchell B, Meng PD, Xiong YS, Westerberg JA, Jia X, Johnston KD, Selvanayagam J, Everling S, Maier A, Desimone R, Miller EK, Bastos AM. A ubiquitous spectrolaminar motif of local field potential power across the primate cortex. Nat Neurosci 2024; 27:547-560. [PMID: 38238431 PMCID: PMC10917659 DOI: 10.1038/s41593-023-01554-7] [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: 11/22/2022] [Accepted: 12/13/2023] [Indexed: 03/08/2024]
Abstract
The mammalian cerebral cortex is anatomically organized into a six-layer motif. It is currently unknown whether a corresponding laminar motif of neuronal activity patterns exists across the cortex. Here we report such a motif in the power of local field potentials (LFPs). Using laminar probes, we recorded LFPs from 14 cortical areas across the cortical hierarchy in five macaque monkeys. The laminar locations of recordings were histologically identified by electrolytic lesions. Across all areas, we found a ubiquitous spectrolaminar pattern characterized by an increasing deep-to-superficial layer gradient of high-frequency power peaking in layers 2/3 and an increasing superficial-to-deep gradient of alpha-beta power peaking in layers 5/6. Laminar recordings from additional species showed that the spectrolaminar pattern is highly preserved among primates-macaque, marmoset and human-but more dissimilar in mouse. Our results suggest the existence of a canonical layer-based and frequency-based mechanism for cortical computation.
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Affiliation(s)
- Diego Mendoza-Halliday
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Alex James Major
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Noah Lee
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Brock Carlson
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Blake Mitchell
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Patrick D Meng
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Yihan Sophy Xiong
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Jacob A Westerberg
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Xiaoxuan Jia
- School of Life Sciences, Tsinghua University, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
| | - Kevin D Johnston
- Graduate Program in Neuroscience, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - Janahan Selvanayagam
- Graduate Program in Neuroscience, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Stefan Everling
- Graduate Program in Neuroscience, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - Alexander Maier
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Robert Desimone
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Earl K Miller
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - André M Bastos
- Department of Psychology, Vanderbilt University, Nashville, TN, USA.
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA.
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA.
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31
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Khodosevich K, Dragicevic K, Howes O. Drug targeting in psychiatric disorders - how to overcome the loss in translation? Nat Rev Drug Discov 2024; 23:218-231. [PMID: 38114612 DOI: 10.1038/s41573-023-00847-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2023] [Indexed: 12/21/2023]
Abstract
In spite of major efforts and investment in development of psychiatric drugs, many clinical trials have failed in recent decades, and clinicians still prescribe drugs that were discovered many years ago. Although multiple reasons have been discussed for the drug development deadlock, we focus here on one of the major possible biological reasons: differences between the characteristics of drug targets in preclinical models and the corresponding targets in patients. Importantly, based on technological advances in single-cell analysis, we propose here a framework for the use of available and newly emerging knowledge from single-cell and spatial omics studies to evaluate and potentially improve the translational predictivity of preclinical models before commencing preclinical and, in particular, clinical studies. We believe that these recommendations will improve preclinical models and the ability to assess drugs in clinical trials, reducing failure rates in expensive late-stage trials and ultimately benefitting psychiatric drug discovery and development.
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Affiliation(s)
- Konstantin Khodosevich
- Biotech Research and Innovation Centre, Faculty of Health, University of Copenhagen, Copenhagen, Denmark.
| | - Katarina Dragicevic
- Biotech Research and Innovation Centre, Faculty of Health, University of Copenhagen, Copenhagen, Denmark
| | - Oliver Howes
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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32
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Takács V, Bardóczi Z, Orosz Á, Major A, Tar L, Berki P, Papp P, Mayer MI, Sebők H, Zsolt L, Sos KE, Káli S, Freund TF, Nyiri G. Synaptic and dendritic architecture of different types of hippocampal somatostatin interneurons. PLoS Biol 2024; 22:e3002539. [PMID: 38470935 PMCID: PMC10959371 DOI: 10.1371/journal.pbio.3002539] [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: 07/08/2023] [Revised: 03/22/2024] [Accepted: 02/06/2024] [Indexed: 03/14/2024] Open
Abstract
GABAergic inhibitory neurons fundamentally shape the activity and plasticity of cortical circuits. A major subset of these neurons contains somatostatin (SOM); these cells play crucial roles in neuroplasticity, learning, and memory in many brain areas including the hippocampus, and are implicated in several neuropsychiatric diseases and neurodegenerative disorders. Two main types of SOM-containing cells in area CA1 of the hippocampus are oriens-lacunosum-moleculare (OLM) cells and hippocampo-septal (HS) cells. These cell types show many similarities in their soma-dendritic architecture, but they have different axonal targets, display different activity patterns in vivo, and are thought to have distinct network functions. However, a complete understanding of the functional roles of these interneurons requires a precise description of their intrinsic computational properties and their synaptic interactions. In the current study we generated, analyzed, and make available several key data sets that enable a quantitative comparison of various anatomical and physiological properties of OLM and HS cells in mouse. The data set includes detailed scanning electron microscopy (SEM)-based 3D reconstructions of OLM and HS cells along with their excitatory and inhibitory synaptic inputs. Combining this core data set with other anatomical data, patch-clamp electrophysiology, and compartmental modeling, we examined the precise morphological structure, inputs, outputs, and basic physiological properties of these cells. Our results highlight key differences between OLM and HS cells, particularly regarding the density and distribution of their synaptic inputs and mitochondria. For example, we estimated that an OLM cell receives about 8,400, whereas an HS cell about 15,600 synaptic inputs, about 16% of which are GABAergic. Our data and models provide insight into the possible basis of the different functionality of OLM and HS cell types and supply essential information for more detailed functional models of these neurons and the hippocampal network.
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Affiliation(s)
- Virág Takács
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
| | - Zsuzsanna Bardóczi
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
| | - Áron Orosz
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
- János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary
| | - Abel Major
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
| | - Luca Tar
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
- Roska Tamás Doctoral School of Sciences and Technology, Pázmány Péter Catholic University, Budapest, Hungary
| | - Péter Berki
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
- János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary
| | - Péter Papp
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
| | - Márton I. Mayer
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
- János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary
| | - Hunor Sebők
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
| | - Luca Zsolt
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
| | - Katalin E. Sos
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
- János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary
| | - Szabolcs Káli
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
| | - Tamás F. Freund
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
| | - Gábor Nyiri
- Laboratory of Cerebral Cortex Research, HUN-REN Institute of Experimental Medicine, Budapest, Hungary
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33
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Beninger J, Rossbroich J, Tóth K, Naud R. Functional subtypes of synaptic dynamics in mouse and human. Cell Rep 2024; 43:113785. [PMID: 38363673 DOI: 10.1016/j.celrep.2024.113785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 12/08/2023] [Accepted: 01/27/2024] [Indexed: 02/18/2024] Open
Abstract
Synapses preferentially respond to particular temporal patterns of activity with a large degree of heterogeneity that is informally or tacitly separated into classes. Yet, the precise number and properties of such classes are unclear. Do they exist on a continuum and, if so, when is it appropriate to divide that continuum into functional regions? In a large dataset of glutamatergic cortical connections, we perform model-based characterization to infer the number and characteristics of functionally distinct subtypes of synaptic dynamics. In rodent data, we find five clusters that partially converge with transgenic-associated subtypes. Strikingly, the application of the same clustering method in human data infers a highly similar number of clusters, supportive of stable clustering. This nuanced dictionary of functional subtypes shapes the heterogeneity of cortical synaptic dynamics and provides a lens into the basic motifs of information transmission in the brain.
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Affiliation(s)
- John Beninger
- Center for Neural Dynamics and Artificial Intelligence, University of Ottawa, Ottawa, ON K1H 8M5, Canada; uOttawa Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Julian Rossbroich
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland; Faculty of Science, University of Basel, Basel, Switzerland
| | - Katalin Tóth
- Center for Neural Dynamics and Artificial Intelligence, University of Ottawa, Ottawa, ON K1H 8M5, Canada; uOttawa Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Richard Naud
- Center for Neural Dynamics and Artificial Intelligence, University of Ottawa, Ottawa, ON K1H 8M5, Canada; uOttawa Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Physics, University of Ottawa, Ottawa, ON K1H 8M5, Canada.
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34
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Guet-McCreight A, Chameh HM, Mazza F, Prevot TD, Valiante TA, Sibille E, Hay E. In-silico testing of new pharmacology for restoring inhibition and human cortical function in depression. Commun Biol 2024; 7:225. [PMID: 38396202 PMCID: PMC10891083 DOI: 10.1038/s42003-024-05907-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 02/09/2024] [Indexed: 02/25/2024] Open
Abstract
Reduced inhibition by somatostatin-expressing interneurons is associated with depression. Administration of positive allosteric modulators of α5 subunit-containing GABAA receptor (α5-PAM) that selectively target this lost inhibition exhibit antidepressant and pro-cognitive effects in rodent models of chronic stress. However, the functional effects of α5-PAM on the human brain in vivo are unknown, and currently cannot be assessed experimentally. We modeled the effects of α5-PAM on tonic inhibition as measured in human neurons, and tested in silico α5-PAM effects on detailed models of human cortical microcircuits in health and depression. We found that α5-PAM effectively recovered impaired cortical processing as quantified by stimulus detection metrics, and also recovered the power spectral density profile of the microcircuit EEG signals. We performed an α5-PAM dose-response and identified simulated EEG biomarker candidates. Our results serve to de-risk and facilitate α5-PAM translation and provide biomarkers in non-invasive brain signals for monitoring target engagement and drug efficacy.
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Affiliation(s)
- Alexandre Guet-McCreight
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
| | | | - Frank Mazza
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Thomas D Prevot
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Taufik A Valiante
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- Department of Surgery, University of Toronto, Toronto, ON, Canada
- Center for Advancing Neurotechnological Innovation to Application, Toronto, ON, Canada
- Max Planck-University of Toronto Center for Neural Science and Technology, Toronto, ON, Canada
| | - Etienne Sibille
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Etay Hay
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Department of Physiology, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
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35
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Myers-Joseph D, Wilmes KA, Fernandez-Otero M, Clopath C, Khan AG. Disinhibition by VIP interneurons is orthogonal to cross-modal attentional modulation in primary visual cortex. Neuron 2024; 112:628-645.e7. [PMID: 38070500 DOI: 10.1016/j.neuron.2023.11.006] [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: 04/20/2023] [Revised: 08/24/2023] [Accepted: 11/08/2023] [Indexed: 02/24/2024]
Abstract
Attentional modulation of sensory processing is a key feature of cognition; however, its neural circuit basis is poorly understood. A candidate mechanism is the disinhibition of pyramidal cells through vasoactive intestinal peptide (VIP) and somatostatin (SOM)-positive interneurons. However, the interaction of attentional modulation and VIP-SOM disinhibition has never been directly tested. We used all-optical methods to bi-directionally manipulate VIP interneuron activity as mice performed a cross-modal attention-switching task. We measured the activities of VIP, SOM, and parvalbumin (PV)-positive interneurons and pyramidal neurons identified in the same tissue and found that although activity in all cell classes was modulated by both attention and VIP manipulation, their effects were orthogonal. Attention and VIP-SOM disinhibition relied on distinct patterns of changes in activity and reorganization of interactions between inhibitory and excitatory cells. Circuit modeling revealed a precise network architecture consistent with multiplexing strong yet non-interacting modulations in the same neural population.
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Affiliation(s)
- Dylan Myers-Joseph
- Centre for Developmental Neurobiology, King's College London, London SE1 1UL, UK
| | | | | | - Claudia Clopath
- Department of Bioengineering, Imperial College, London SW7 2AZ, UK
| | - Adil G Khan
- Centre for Developmental Neurobiology, King's College London, London SE1 1UL, UK.
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36
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Liu YH, Baratin A, Cornford J, Mihalas S, Shea-Brown E, Lajoie G. How connectivity structure shapes rich and lazy learning in neural circuits. ARXIV 2024:arXiv:2310.08513v2. [PMID: 37873007 PMCID: PMC10593070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
In theoretical neuroscience, recent work leverages deep learning tools to explore how some network attributes critically influence its learning dynamics. Notably, initial weight distributions with small (resp. large) variance may yield a rich (resp. lazy) regime, where significant (resp. minor) changes to network states and representation are observed over the course of learning. However, in biology, neural circuit connectivity could exhibit a low-rank structure and therefore differs markedly from the random initializations generally used for these studies. As such, here we investigate how the structure of the initial weights -- in particular their effective rank -- influences the network learning regime. Through both empirical and theoretical analyses, we discover that high-rank initializations typically yield smaller network changes indicative of lazier learning, a finding we also confirm with experimentally-driven initial connectivity in recurrent neural networks. Conversely, low-rank initialization biases learning towards richer learning. Importantly, however, as an exception to this rule, we find lazier learning can still occur with a low-rank initialization that aligns with task and data statistics. Our research highlights the pivotal role of initial weight structures in shaping learning regimes, with implications for metabolic costs of plasticity and risks of catastrophic forgetting.
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37
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Zhang A, Jin L, Yao S, Matsuyama M, van Velthoven CTJ, Sullivan HA, Sun N, Kellis M, Tasic B, Wickersham I, Chen X. Rabies virus-based barcoded neuroanatomy resolved by single-cell RNA and in situ sequencing. eLife 2024; 12:RP87866. [PMID: 38319699 PMCID: PMC10942611 DOI: 10.7554/elife.87866] [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] [Indexed: 02/07/2024] Open
Abstract
Mapping the connectivity of diverse neuronal types provides the foundation for understanding the structure and function of neural circuits. High-throughput and low-cost neuroanatomical techniques based on RNA barcode sequencing have the potential to map circuits at cellular resolution and a brain-wide scale, but existing Sindbis virus-based techniques can only map long-range projections using anterograde tracing approaches. Rabies virus can complement anterograde tracing approaches by enabling either retrograde labeling of projection neurons or monosynaptic tracing of direct inputs to genetically targeted postsynaptic neurons. However, barcoded rabies virus has so far been only used to map non-neuronal cellular interactions in vivo and synaptic connectivity of cultured neurons. Here we combine barcoded rabies virus with single-cell and in situ sequencing to perform retrograde labeling and transsynaptic labeling in the mouse brain. We sequenced 96 retrogradely labeled cells and 295 transsynaptically labeled cells using single-cell RNA-seq, and 4130 retrogradely labeled cells and 2914 transsynaptically labeled cells in situ. We found that the transcriptomic identities of rabies virus-infected cells can be robustly identified using both single-cell RNA-seq and in situ sequencing. By associating gene expression with connectivity inferred from barcode sequencing, we distinguished long-range projecting cortical cell types from multiple cortical areas and identified cell types with converging or diverging synaptic connectivity. Combining in situ sequencing with barcoded rabies virus complements existing sequencing-based neuroanatomical techniques and provides a potential path for mapping synaptic connectivity of neuronal types at scale.
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Affiliation(s)
- Aixin Zhang
- Allen Institute for Brain ScienceSeattleUnited States
| | - Lei Jin
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Shenqin Yao
- Allen Institute for Brain ScienceSeattleUnited States
| | - Makoto Matsuyama
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | | | - Heather Anne Sullivan
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Na Sun
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Broad Institute of MIT and HarvardCambridgeUnited States
- Broad Institute of MIT and HarvardCambridgeUnited States
| | - Manolis Kellis
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Broad Institute of MIT and HarvardCambridgeUnited States
- Broad Institute of MIT and HarvardCambridgeUnited States
| | | | - Ian Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Xiaoyin Chen
- Allen Institute for Brain ScienceSeattleUnited States
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38
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Shirani F, Choi H. On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks. J Comput Neurosci 2024; 52:73-107. [PMID: 37837534 DOI: 10.1007/s10827-023-00863-x] [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: 04/13/2023] [Revised: 06/25/2023] [Accepted: 09/08/2023] [Indexed: 10/16/2023]
Abstract
Overall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between neurons, which are organized by specific network connectivity structures and are dynamically controlled by modulating synaptic activities. Therefore, identifying how such structural and physiological factors contribute to establishment of overall balance of excitation and inhibition is crucial in understanding the homeostatic plasticity mechanisms that regulate the balance. We use biologically plausible mathematical models to extensively study the effects of multiple key factors on overall balance of a network. We characterize a network's baseline balanced state by certain functional properties, and demonstrate how variations in physiological and structural parameters of the network deviate this balance and, in particular, result in transitions in spontaneous activity of the network to high-amplitude slow oscillatory regimes. We show that deviations from the reference balanced state can be continuously quantified by measuring the ratio of mean excitatory to mean inhibitory synaptic conductances in the network. Our results suggest that the commonly observed ratio of the number of inhibitory to the number of excitatory neurons in local cortical networks is almost optimal for their stability and excitability. Moreover, the values of inhibitory synaptic decay time constants and density of inhibitory-to-inhibitory network connectivity are critical to overall balance and stability of cortical networks. However, network stability in our results is sufficiently robust against modulations of synaptic quantal conductances, as required by their role in learning and memory. Our study based on extensive bifurcation analyses thus reveal the functional optimality and criticality of structural and physiological parameters in establishing the baseline operating state of local cortical networks.
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Affiliation(s)
- Farshad Shirani
- School of Mathematics, Georgia Institute of Technology, Atlanta, 30332, Georgia, USA.
| | - Hannah Choi
- School of Mathematics, Georgia Institute of Technology, Atlanta, 30332, Georgia, USA
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39
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Rimehaug AE, Dale AM, Arkhipov A, Einevoll GT. Uncovering population contributions to the extracellular potential in the mouse visual system using Laminar Population Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.15.575805. [PMID: 38293236 PMCID: PMC10827114 DOI: 10.1101/2024.01.15.575805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
The local field potential (LFP), the low-frequency part of the extracellular potential, reflects transmembrane currents in the vicinity of the recording electrode. Thought mainly to stem from currents caused by synaptic input, it provides information about neural activity complementary to that of spikes, the output of neurons. However, the many neural sources contributing to the LFP, and likewise the derived current source density (CSD), can often make it challenging to interpret. Efforts to improve its interpretability have included the application of statistical decomposition tools like principal component analysis (PCA) and independent component analysis (ICA) to disentangle the contributions from different neural sources. However, their underlying assumptions of, respectively, orthogonality and statistical independence are not always valid for the various processes or pathways generating LFP. Here, we expand upon and validate a decomposition algorithm named Laminar Population Analysis (LPA), which is based on physiological rather than statistical assumptions. LPA utilizes the multiunit activity (MUA) and LFP jointly to uncover the contributions of different populations to the LFP. To perform the validation of LPA, we used data simulated with the large-scale, biophysically detailed model of mouse V1 developed by the Allen Institute. We find that LPA can identify laminar positions within V1 and the temporal profiles of laminar population firing rates from the MUA. We also find that LPA can estimate the salient current sinks and sources generated by feedforward input from the lateral geniculate nucleus (LGN), recurrent activity in V1, and feedback input from the lateromedial (LM) area of visual cortex. LPA identifies and distinguishes these contributions with a greater accuracy than the alternative statistical decomposition methods, PCA and ICA. Lastly, we also demonstrate the application of LPA on experimentally recorded MUA and LFP from 24 animals in the publicly available Visual Coding dataset. Our results suggest that LPA can be used both as a method to estimate positions of laminar populations and to uncover salient features in LFP/CSD contributions from different populations.
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Affiliation(s)
| | - Anders M. Dale
- Department of Neuroscience, University of California San Diego, San Diego, California, USA
| | | | - Gaute T. Einevoll
- Department of Physics, Norwegian University of Life Sciences, Ås, Norway
- Department of Physics, University of Oslo, Oslo, Norway
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40
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Schneider-Mizell CM, Bodor AL, Brittain D, Buchanan J, Bumbarger DJ, Elabbady L, Gamlin C, Kapner D, Kinn S, Mahalingam G, Seshamani S, Suckow S, Takeno M, Torres R, Yin W, Dorkenwald S, Bae JA, Castro MA, Halageri A, Jia Z, Jordan C, Kemnitz N, Lee K, Li K, Lu R, Macrina T, Mitchell E, Mondal SS, Mu S, Nehoran B, Popovych S, Silversmith W, Turner NL, Wong W, Wu J, Reimer J, Tolias AS, Seung HS, Reid RC, Collman F, Maçarico da Costa N. Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.23.525290. [PMID: 36747710 PMCID: PMC9900837 DOI: 10.1101/2023.01.23.525290] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy1 to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses. Taking a data-driven approach inspired by classical neuroanatomy, we classified inhibitory neurons based on the relative targeting of dendritic compartments and other inhibitory cells and developed a novel classification of excitatory neurons based on the morphological and synaptic input properties. The synaptic connectivity between inhibitory cells revealed a novel class of disinhibitory specialist targeting basket cells, in addition to familiar subclasses. Analysis of the inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of certain subpopulations spatially intermingled with other potential targets. Inhibitory targeting was organized into "motif groups," diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking modern multimodal neuronal atlases with the cortical wiring diagram.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Sam Kinn
- Allen Institute for Brain Science, Seattle, WA
| | | | | | | | - Marc Takeno
- Allen Institute for Brain Science, Seattle, WA
| | | | - Wenjing Yin
- Allen Institute for Brain Science, Seattle, WA
| | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - J Alexander Bae
- Princeton Neuroscience Institute, Princeton University, NJ
- Electrical and Computer Engineering Department, Princeton University
| | | | | | - Zhen Jia
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - Chris Jordan
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Nico Kemnitz
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Kisuk Lee
- Brain & Cognitive Sciences Department, Massachusetts Institute of Technology
| | - Kai Li
- Computer Science Department, Princeton University
| | - Ran Lu
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Thomas Macrina
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - Eric Mitchell
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Shanka Subhra Mondal
- Princeton Neuroscience Institute, Princeton University, NJ
- Electrical and Computer Engineering Department, Princeton University
| | - Shang Mu
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Barak Nehoran
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - Sergiy Popovych
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | | | - Nicholas L Turner
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - William Wong
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Jingpeng Wu
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Jacob Reimer
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine
| | - Andreas S Tolias
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine
- Department of Electrical and Computer Engineering, Rice University
| | - H Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - R Clay Reid
- Allen Institute for Brain Science, Seattle, WA
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41
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Ding X, Froudist-Walsh S, Jaramillo J, Jiang J, Wang XJ. Cell type-specific connectome predicts distributed working memory activity in the mouse brain. eLife 2024; 13:e85442. [PMID: 38174734 PMCID: PMC10807864 DOI: 10.7554/elife.85442] [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: 12/08/2022] [Accepted: 12/14/2023] [Indexed: 01/05/2024] Open
Abstract
Recent advances in connectomics and neurophysiology make it possible to probe whole-brain mechanisms of cognition and behavior. We developed a large-scale model of the multiregional mouse brain for a cardinal cognitive function called working memory, the brain's ability to internally hold and process information without sensory input. The model is built on mesoscopic connectome data for interareal cortical connections and endowed with a macroscopic gradient of measured parvalbumin-expressing interneuron density. We found that working memory coding is distributed yet exhibits modularity; the spatial pattern of mnemonic representation is determined by long-range cell type-specific targeting and density of cell classes. Cell type-specific graph measures predict the activity patterns and a core subnetwork for memory maintenance. The model shows numerous attractor states, which are self-sustained internal states (each engaging a distinct subset of areas). This work provides a framework to interpret large-scale recordings of brain activity during cognition, while highlighting the need for cell type-specific connectomics.
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Affiliation(s)
- Xingyu Ding
- Center for Neural Science, New York UniversityNew YorkUnited States
| | - Sean Froudist-Walsh
- Center for Neural Science, New York UniversityNew YorkUnited States
- Bristol Computational Neuroscience Unit, School of Engineering Mathematics and Technology, University of BristolBristolUnited Kingdom
| | - Jorge Jaramillo
- Center for Neural Science, New York UniversityNew YorkUnited States
- Campus Institute for Dynamics of Biological Networks, University of GöttingenGöttingenGermany
| | - Junjie Jiang
- Center for Neural Science, New York UniversityNew YorkUnited States
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education,Institute of Health and Rehabilitation Science,School of Life Science and Technology, Research Center for Brain-inspired Intelligence, Xi’an Jiaotong UniversityXi'anChina
| | - Xiao-Jing Wang
- Center for Neural Science, New York UniversityNew YorkUnited States
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42
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Verzhbinsky IA, Rubin DB, Kajfez S, Bu Y, Kelemen JN, Kapitonava A, Williams ZM, Hochberg LR, Cash SS, Halgren E. Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans. Proc Natl Acad Sci U S A 2024; 121:e2312204121. [PMID: 38157452 PMCID: PMC10769862 DOI: 10.1073/pnas.2312204121] [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: 07/20/2023] [Accepted: 11/05/2023] [Indexed: 01/03/2024] Open
Abstract
How the human cortex integrates ("binds") information encoded by spatially distributed neurons remains largely unknown. One hypothesis suggests that synchronous bursts of high-frequency oscillations ("ripples") contribute to binding by facilitating integration of neuronal firing across different cortical locations. While studies have demonstrated that ripples modulate local activity in the cortex, it is not known whether their co-occurrence coordinates neural firing across larger distances. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in the supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during non-rapid eye movement sleep and waking, in temporal and Rolandic cortices, and at distances up to 16 mm (the longest tested). Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, indicating that it was not secondary to non-oscillatory activation. Co-rippling enhanced prediction was strongly modulated by ripple phase, supporting the most common posited mechanism for binding-by-synchrony. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple, supporting re-entrant facilitation. Together, these results support the hypothesis that trans-cortical co-occurring ripples increase the integration of neuronal firing of neurons in different cortical locations and do so in part through phase-modulation rather than unstructured activation.
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Affiliation(s)
- Ilya A. Verzhbinsky
- Neurosciences Graduate Program, University of California San Diego, La Jolla, CA92093
- Medical Scientist Training Program, University of California San Diego, La Jolla, CA92093
| | - Daniel B. Rubin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
| | - Sophie Kajfez
- Department of Radiology, University of California San Diego, La Jolla, CA92093
| | - Yiting Bu
- Department of Neurosciences, University of California San Diego, La Jolla, CA92093
| | - Jessica N. Kelemen
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
| | - Anastasia Kapitonava
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
| | - Ziv M. Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA02114
| | - Leigh R. Hochberg
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs, Providence, RI02908
- Carney Institute for Brain Science and School of Engineering, Brown University, Providence, RI02912
| | - Sydney S. Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
| | - Eric Halgren
- Department of Radiology, University of California San Diego, La Jolla, CA92093
- Department of Neurosciences, University of California San Diego, La Jolla, CA92093
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43
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Oldenburg IA, Hendricks WD, Handy G, Shamardani K, Bounds HA, Doiron B, Adesnik H. The logic of recurrent circuits in the primary visual cortex. Nat Neurosci 2024; 27:137-147. [PMID: 38172437 PMCID: PMC10774145 DOI: 10.1038/s41593-023-01510-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 10/27/2023] [Indexed: 01/05/2024]
Abstract
Recurrent cortical activity sculpts visual perception by refining, amplifying or suppressing visual input. However, the rules that govern the influence of recurrent activity remain enigmatic. We used ensemble-specific two-photon optogenetics in the mouse visual cortex to isolate the impact of recurrent activity from external visual input. We found that the spatial arrangement and the visual feature preference of the stimulated ensemble and the neighboring neurons jointly determine the net effect of recurrent activity. Photoactivation of these ensembles drives suppression in all cells beyond 30 µm but uniformly drives activation in closer similarly tuned cells. In nonsimilarly tuned cells, compact, cotuned ensembles drive net suppression, while diffuse, cotuned ensembles drive activation. Computational modeling suggests that highly local recurrent excitatory connectivity and selective convergence onto inhibitory neurons explain these effects. Our findings reveal a straightforward logic in which space and feature preference of cortical ensembles determine their impact on local recurrent activity.
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Affiliation(s)
- Ian Antón Oldenburg
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA.
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School, and Center for Advanced Biotechnology and Medicine, Rutgers University, Piscataway, NJ, USA.
| | - William D Hendricks
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Gregory Handy
- Department of Neurobiology and Statistics, University of Chicago, Chicago, IL, USA.
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, USA.
- Department of Mathematics, University of Minnesota, Minneapolis, MN, USA.
| | - Kiarash Shamardani
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Hayley A Bounds
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Brent Doiron
- Department of Neurobiology and Statistics, University of Chicago, Chicago, IL, USA
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, USA
| | - Hillel Adesnik
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA.
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
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44
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Becker LA, Li B, Priebe NJ, Seidemann E, Taillefumier T. Exact Analysis of the Subthreshold Variability for Conductance-Based Neuronal Models with Synchronous Synaptic Inputs. PHYSICAL REVIEW. X 2024; 14:011021. [PMID: 38911939 PMCID: PMC11194039 DOI: 10.1103/physrevx.14.011021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/25/2024]
Abstract
The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state, neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically, we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects postspiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime yields realistic subthreshold variability (voltage variance ≃4-9 mV2) only when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that, without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.
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Affiliation(s)
- Logan A. Becker
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Department of Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Baowang Li
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Department of Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Center for Perceptual Systems, The University of Texas at Austin, Austin, Texas 78712, USA
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas 78712, USA
- Department of Psychology, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Nicholas J. Priebe
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Department of Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Eyal Seidemann
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Department of Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Center for Perceptual Systems, The University of Texas at Austin, Austin, Texas 78712, USA
- Department of Psychology, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Thibaud Taillefumier
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Department of Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA
- Department of Mathematics, The University of Texas at Austin, Austin, Texas 78712, USA
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45
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Wallace JL, Pollen AA. Human neuronal maturation comes of age: cellular mechanisms and species differences. Nat Rev Neurosci 2024; 25:7-29. [PMID: 37996703 DOI: 10.1038/s41583-023-00760-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/12/2023] [Indexed: 11/25/2023]
Abstract
The delayed and prolonged postmitotic maturation of human neurons, compared with neurons from other species, may contribute to human-specific cognitive abilities and neurological disorders. Here we review the mechanisms of neuronal maturation, applying lessons from model systems to understand the specific features of protracted human cortical maturation and species differences. We cover cell-intrinsic features of neuronal maturation, including transcriptional, epigenetic and metabolic mechanisms, as well as cell-extrinsic features, including the roles of activity and synapses, the actions of glial cells and the contribution of the extracellular matrix. We discuss evidence for species differences in biochemical reaction rates, the proposed existence of an epigenetic maturation clock and the contributions of both general and modular mechanisms to species-specific maturation timing. Finally, we suggest approaches to measure, improve and accelerate the maturation of human neurons in culture, examine crosstalk and interactions among these different aspects of maturation and propose conceptual models to guide future studies.
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Affiliation(s)
- Jenelle L Wallace
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
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46
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Becker LA, Li B, Priebe NJ, Seidemann E, Taillefumier T. Exact analysis of the subthreshold variability for conductance-based neuronal models with synchronous synaptic inputs. ARXIV 2023:arXiv:2304.09280v3. [PMID: 37131877 PMCID: PMC10153295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects post-spiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime only yields realistic subthreshold variability (voltage variance ≃ 4 - 9 m V 2 ) when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.
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Affiliation(s)
- Logan A. Becker
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin
- Department of Neuroscience, The University of Texas at Austin
| | - Baowang Li
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin
- Department of Neuroscience, The University of Texas at Austin
- Center for Perceptual Systems, The University of Texas at Austin
- Center for Learning and Memory, The University of Texas at Austin
- Department of Psychology, The University of Texas at Austin
| | - Nicholas J. Priebe
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin
- Department of Neuroscience, The University of Texas at Austin
- Center for Learning and Memory, The University of Texas at Austin
| | - Eyal Seidemann
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin
- Department of Neuroscience, The University of Texas at Austin
- Center for Perceptual Systems, The University of Texas at Austin
- Department of Psychology, The University of Texas at Austin
| | - Thibaud Taillefumier
- Center for Theoretical and Computational Neuroscience, The University of Texas at Austin
- Department of Neuroscience, The University of Texas at Austin
- Department of Mathematics, The University of Texas at Austin
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47
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Patiño M, Lagos WN, Patne NS, Miyazaki PA, Bhamidipati SK, Collman F, Callaway EM. Postsynaptic cell type and synaptic distance do not determine efficiency of monosynaptic rabies virus spread measured at synaptic resolution. eLife 2023; 12:e89297. [PMID: 38096019 PMCID: PMC10721217 DOI: 10.7554/elife.89297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 11/19/2023] [Indexed: 12/17/2023] Open
Abstract
Retrograde monosynaptic tracing using glycoprotein-deleted rabies virus is an important component of the toolkit for investigation of neural circuit structure and connectivity. It allows for the identification of first-order presynaptic connections to cell populations of interest across both the central and peripheral nervous system, helping to decipher the complex connectivity patterns of neural networks that give rise to brain function. Despite its utility, the factors that influence the probability of transsynaptic rabies spread are not well understood. While it is well established that expression levels of rabies glycoprotein used to trans-complement G-deleted rabies can result in large changes in numbers of inputs labeled per starter cell (convergence index [CI]), it is not known how typical values of CI relate to the proportions of synaptic contacts or input neurons labeled. And it is not known whether inputs to different cell types, or synaptic contacts that are more proximal or distal to the cell body, are labeled with different probabilities. Here, we use a new rabies virus construct that allows for the simultaneous labeling of pre- and postsynaptic specializations to quantify the proportion of synaptic contacts labeled in mouse primary visual cortex. We demonstrate that with typical conditions about 40% of first-order presynaptic excitatory synapses to cortical excitatory and inhibitory neurons are labeled. We show that using matched tracing conditions there are similar proportions of labeled contacts onto L4 excitatory pyramidal, somatostatin (Sst) inhibitory, and vasoactive intestinal peptide (Vip) starter cell types. Furthermore, we find no difference in the proportions of labeled excitatory contacts onto postsynaptic sites at different subcellular locations.
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Affiliation(s)
- Maribel Patiño
- Systems Neurobiology Laboratories, The Salk Institute for Biological StudiesLa JollaUnited States
- Neuroscience Graduate Program, University of California, San DiegoLa JollaUnited States
- Medical Scientist Training Program, University of California, San DiegoLa JollaUnited States
| | - Willian N Lagos
- Systems Neurobiology Laboratories, The Salk Institute for Biological StudiesLa JollaUnited States
| | - Neelakshi S Patne
- Systems Neurobiology Laboratories, The Salk Institute for Biological StudiesLa JollaUnited States
| | - Paula A Miyazaki
- Systems Neurobiology Laboratories, The Salk Institute for Biological StudiesLa JollaUnited States
| | - Sai Krishna Bhamidipati
- Systems Neurobiology Laboratories, The Salk Institute for Biological StudiesLa JollaUnited States
| | | | - Edward M Callaway
- Systems Neurobiology Laboratories, The Salk Institute for Biological StudiesLa JollaUnited States
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48
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Pelkey KA, Vargish GA, Pellegrini LV, Calvigioni D, Chapeton J, Yuan X, Hunt S, Cummins AC, Eldridge MAG, Pickel J, Chittajallu R, Averbeck BB, Tóth K, Zaghloul K, McBain CJ. Evolutionary conservation of hippocampal mossy fiber synapse properties. Neuron 2023; 111:3802-3818.e5. [PMID: 37776852 PMCID: PMC10841147 DOI: 10.1016/j.neuron.2023.09.005] [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: 02/07/2023] [Revised: 07/03/2023] [Accepted: 09/06/2023] [Indexed: 10/02/2023]
Abstract
Various specialized structural/functional properties are considered essential for contextual memory encoding by hippocampal mossy fiber (MF) synapses. Although investigated to exquisite detail in model organisms, synapses, including MFs, have undergone minimal functional interrogation in humans. To determine the translational relevance of rodent findings, we evaluated MF properties within human tissue resected to treat epilepsy. Human MFs exhibit remarkably similar hallmark features to rodents, including AMPA receptor-dominated synapses with small contributions from NMDA and kainate receptors, large dynamic range with strong frequency facilitation, NMDA receptor-independent presynaptic long-term potentiation, and strong cyclic AMP (cAMP) sensitivity of release. Array tomography confirmed the evolutionary conservation of MF ultrastructure. The astonishing congruence of rodent and human MF core features argues that the basic MF properties delineated in animal models remain critical to human MF function. Finally, a selective deficit in GABAergic inhibitory tone onto human MF postsynaptic targets suggests that unrestrained detonator excitatory drive contributes to epileptic circuit hyperexcitability.
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Affiliation(s)
- Kenneth A Pelkey
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Geoffrey A Vargish
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Leonardo V Pellegrini
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Brain and Mind Research Institute, Ottawa, ON K1H 8M5, Canada
| | - Daniela Calvigioni
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Julio Chapeton
- National Institute of Neurological Disorders and Stroke Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaoqing Yuan
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Steven Hunt
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Alex C Cummins
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mark A G Eldridge
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - James Pickel
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ramesh Chittajallu
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Bruno B Averbeck
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Katalin Tóth
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Brain and Mind Research Institute, Ottawa, ON K1H 8M5, Canada
| | - Kareem Zaghloul
- National Institute of Neurological Disorders and Stroke Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Chris J McBain
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA.
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49
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Friedenberger Z, Harkin E, Tóth K, Naud R. Silences, spikes and bursts: Three-part knot of the neural code. J Physiol 2023; 601:5165-5193. [PMID: 37889516 DOI: 10.1113/jp281510] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 09/28/2023] [Indexed: 10/28/2023] Open
Abstract
When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.
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Affiliation(s)
- Zachary Friedenberger
- Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Neural Dynamics and Artifical Intelligence, Department of Physics, University of Ottawa, Ottawa, Ontario, Ottawa
| | - Emerson Harkin
- Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Katalin Tóth
- Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Richard Naud
- Brain and Mind Institute, Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Neural Dynamics and Artifical Intelligence, Department of Physics, University of Ottawa, Ottawa, Ontario, Ottawa
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50
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van Oostrum M, Blok TM, Giandomenico SL, Tom Dieck S, Tushev G, Fürst N, Langer JD, Schuman EM. The proteomic landscape of synaptic diversity across brain regions and cell types. Cell 2023; 186:5411-5427.e23. [PMID: 37918396 PMCID: PMC10686415 DOI: 10.1016/j.cell.2023.09.028] [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: 02/09/2023] [Revised: 08/18/2023] [Accepted: 09/28/2023] [Indexed: 11/04/2023]
Abstract
Neurons build synaptic contacts using different protein combinations that define the specificity, function, and plasticity potential of synapses; however, the diversity of synaptic proteomes remains largely unexplored. We prepared synaptosomes from 7 different transgenic mouse lines with fluorescently labeled presynaptic terminals. Combining microdissection of 5 different brain regions with fluorescent-activated synaptosome sorting (FASS), we isolated and analyzed the proteomes of 18 different synapse types. We discovered ∼1,800 unique synapse-type-enriched proteins and allocated thousands of proteins to different types of synapses (https://syndive.org/). We identify shared synaptic protein modules and highlight the proteomic hotspots for synapse specialization. We reveal unique and common features of the striatal dopaminergic proteome and discover the proteome signatures that relate to the functional properties of different interneuron classes. This study provides a molecular systems-biology analysis of synapses and a framework to integrate proteomic information for synapse subtypes of interest with cellular or circuit-level experiments.
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Affiliation(s)
- Marc van Oostrum
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
| | - Thomas M Blok
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
| | | | | | - Georgi Tushev
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
| | - Nicole Fürst
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
| | - Julian D Langer
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany; Max Planck Institute of Biophysics, Frankfurt am Main, Germany
| | - Erin M Schuman
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany.
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