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Dorman R, Bos JJ, Vinck MA, Marchesi P, Fiorilli J, Lorteije JAM, Reiten I, Bjaalie JG, Okun M, Pennartz CMA. Spike-based coupling between single neurons and populations across rat sensory cortices, perirhinal cortex, and hippocampus. Cereb Cortex 2023; 33:8247-8264. [PMID: 37118890 PMCID: PMC10425201 DOI: 10.1093/cercor/bhad111] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 04/30/2023] Open
Abstract
Cortical computations require coordination of neuronal activity within and across multiple areas. We characterized spiking relationships within and between areas by quantifying coupling of single neurons to population firing patterns. Single-neuron population coupling (SNPC) was investigated using ensemble recordings from hippocampal CA1 region and somatosensory, visual, and perirhinal cortices. Within-area coupling was heterogeneous across structures, with area CA1 showing higher levels than neocortical regions. In contrast to known anatomical connectivity, between-area coupling showed strong firing coherence of sensory neocortices with CA1, but less with perirhinal cortex. Cells in sensory neocortices and CA1 showed positive correlations between within- and between-area coupling; these were weaker for perirhinal cortex. All four areas harbored broadcasting cells, connecting to multiple external areas, which was uncorrelated to within-area coupling strength. When examining correlations between SNPC and spatial coding, we found that, if such correlations were significant, they were negative. This result was consistent with an overall preservation of SNPC across different brain states, suggesting a strong dependence on intrinsic network connectivity. Overall, SNPC offers an important window on cell-to-population synchronization in multi-area networks. Instead of pointing to specific information-coding functions, our results indicate a primary function of SNPC in dynamically organizing communication in systems composed of multiple, interconnected areas.
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Affiliation(s)
- Reinder Dorman
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Jeroen J Bos
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HC Nijmegen, The Netherlands
| | - Martin A Vinck
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Plank Society, 60528 Frankfurt, Germany
| | - Pietro Marchesi
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Julien Fiorilli
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Jeanette A M Lorteije
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Ingrid Reiten
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Jan G Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Michael Okun
- Department of Psychology and Neuroscience Institute, University of Sheffield, Sheffield S10 2TN, UK
| | - Cyriel M A Pennartz
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
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52
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Pang JC, Aquino KM, Oldehinkel M, Robinson PA, Fulcher BD, Breakspear M, Fornito A. Geometric constraints on human brain function. Nature 2023; 618:566-574. [PMID: 37258669 PMCID: PMC10266981 DOI: 10.1038/s41586-023-06098-1] [Citation(s) in RCA: 71] [Impact Index Per Article: 71.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 04/18/2023] [Indexed: 06/02/2023]
Abstract
The anatomy of the brain necessarily constrains its function, but precisely how remains unclear. The classical and dominant paradigm in neuroscience is that neuronal dynamics are driven by interactions between discrete, functionally specialized cell populations connected by a complex array of axonal fibres1-3. However, predictions from neural field theory, an established mathematical framework for modelling large-scale brain activity4-6, suggest that the geometry of the brain may represent a more fundamental constraint on dynamics than complex interregional connectivity7,8. Here, we confirm these theoretical predictions by analysing human magnetic resonance imaging data acquired under spontaneous and diverse task-evoked conditions. Specifically, we show that cortical and subcortical activity can be parsimoniously understood as resulting from excitations of fundamental, resonant modes of the brain's geometry (that is, its shape) rather than from modes of complex interregional connectivity, as classically assumed. We then use these geometric modes to show that task-evoked activations across over 10,000 brain maps are not confined to focal areas, as widely believed, but instead excite brain-wide modes with wavelengths spanning over 60 mm. Finally, we confirm predictions that the close link between geometry and function is explained by a dominant role for wave-like activity, showing that wave dynamics can reproduce numerous canonical spatiotemporal properties of spontaneous and evoked recordings. Our findings challenge prevailing views and identify a previously underappreciated role of geometry in shaping function, as predicted by a unifying and physically principled model of brain-wide dynamics.
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Affiliation(s)
- James C Pang
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
| | - Kevin M Aquino
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
- BrainKey Inc., San Francisco, CA, USA
| | - Marianne Oldehinkel
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Peter A Robinson
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
| | - Ben D Fulcher
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
| | - Michael Breakspear
- School of Psychological Sciences, College of Engineering, Science and the Environment, University of Newcastle, Callaghan, New South Wales, Australia
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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53
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The geometry of the human brain shapes its function. Nature 2023:10.1038/d41586-023-01495-y. [PMID: 37258731 DOI: 10.1038/d41586-023-01495-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
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54
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Lee JM, Lin D, Pyo YW, Kim HR, Park HG, Lieber CM. Stitching Flexible Electronics into the Brain. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2300220. [PMID: 37127888 DOI: 10.1002/advs.202300220] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 03/13/2023] [Indexed: 05/03/2023]
Abstract
Understanding complex neuronal networks requires monitoring long-term neuronal activity in various regions of the brain. Significant progress has been made in multisite implantations of well-designed probes, such as multisite implantation of Si-based and polymer-based probes. However, these multiprobe strategies are limited by the sizes and weights of interfaces to the multiple probes and the inability to track the activity of the same neurons and changes in neuronal activity over longer time periods. Here, a long single flexible probe that can be implanted by stitching into multiple regions of the mouse brain and subsequently transmit chronically stable neuronal signals from the multiple sites via a single low-mass interface is reported. The probe at four different sites is implemented using a glass capillary needle or two sites using an ultrathin metal needle. In vitro tests in brain-mimicking hydrogel show that multisite probe implantations achieve a high connection yield of >86%. In vivo histological images at each site of probes, implanted by stitching using either glass capillary or ultrathin metal insertion needles exhibit seamless tissue-probe interfaces with negligible chronic immune response. In addition, electrophysiology studies demonstrate the ability to track single neuron activities at every injection site with chronic stability over at least one month. Notably, the measured spike amplitudes and signal-to-noise ratios at different implantation sites show no statistically significant differences. Multisite stitching implantation of flexible electronics in the brain opens up new opportunities for both fundamental neuroscience research and electrotherapeutic applications.
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Affiliation(s)
- Jung Min Lee
- Department of Physics, Korea University, Seoul, 02841, Republic of Korea
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Dingchang Lin
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, 02138, USA
- Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Young-Woo Pyo
- Department of Physics, Korea University, Seoul, 02841, Republic of Korea
| | - Ha-Reem Kim
- Department of Physics, Korea University, Seoul, 02841, Republic of Korea
| | - Hong-Gyu Park
- Department of Physics, Korea University, Seoul, 02841, Republic of Korea
| | - Charles M Lieber
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, 02138, USA
- Center for Brain Science, Harvard University, Cambridge, MA, 02138, USA
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55
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Lines J, Yuste R. Visually evoked neuronal ensembles reactivate during sleep. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.26.538480. [PMID: 37162988 PMCID: PMC10168341 DOI: 10.1101/2023.04.26.538480] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Neuronal ensembles, defined as groups of coactive neurons, dominate cortical activity and are causally related to perceptual states and behavior. Interestingly, ensembles occur spontaneously in the absence of sensory stimulation. To better understand the function of ensembles in spontaneous activity, we explored if ensembles also occur during different brain states, including sleep, using two-photon calcium imaging from mouse primary visual cortex. We find that ensembles are present during all wake and sleep states, with different characteristics depending on the exact sleep stage. Moreover, visually evoked ensembles are reactivated during subsequent slow wave sleep cycles. Our results are consistent with the hypothesis that repeated sensory stimulation can reconfigure cortical circuits and imprint neuronal ensembles that are reactivated during sleep for potential processing or memory consolidation. One-Sentence Summary Cortical neuronal ensembles are present across wake and sleep states, and visually evoked ensembles are reactivated in subsequent slow-wave sleep.
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56
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Suzuki I, Matsuda N, Han X, Noji S, Shibata M, Nagafuku N, Ishibashi Y. Large-Area Field Potential Imaging Having Single Neuron Resolution Using 236 880 Electrodes CMOS-MEA Technology. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2207732. [PMID: 37088859 PMCID: PMC10369302 DOI: 10.1002/advs.202207732] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/21/2023] [Indexed: 05/03/2023]
Abstract
The electrophysiological technology having a high spatiotemporal resolution at the single-cell level and noninvasive measurements of large areas provide insights on underlying neuronal function. Here, a complementary metal-oxide semiconductor (CMOS)-microelectrode array (MEA) is used that uses 236 880 electrodes each with an electrode size of 11.22 × 11.22 µm and 236 880 covering a wide area of 5.5 × 5.9 mm in presenting a detailed and single-cell-level neural activity analysis platform for brain slices, human iPS cell-derived cortical networks, peripheral neurons, and human brain organoids. Propagation pattern characteristics between brain regions changes the synaptic propagation into compounds based on single-cell time-series patterns, classification based on single DRG neuron firing patterns and compound responses, axonal conduction characteristics and changes to anticancer drugs, and network activities and transition to compounds in brain organoids are extracted. This detailed analysis of neural activity at the single-cell level using the CMOS-MEA provides a new understanding of the basic mechanisms of brain circuits in vitro and ex vivo, on human neurological diseases for drug discovery, and compound toxicity assessment.
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Affiliation(s)
- Ikuro Suzuki
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Naoki Matsuda
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Xiaobo Han
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Shuhei Noji
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Mikako Shibata
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Nami Nagafuku
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Yuto Ishibashi
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
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57
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Jacob M, Ford J, Deacon T. Cognition is entangled with metabolism: relevance for resting-state EEG-fMRI. Front Hum Neurosci 2023; 17:976036. [PMID: 37113322 PMCID: PMC10126302 DOI: 10.3389/fnhum.2023.976036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 03/02/2023] [Indexed: 04/29/2023] Open
Abstract
The brain is a living organ with distinct metabolic constraints. However, these constraints are typically considered as secondary or supportive of information processing which is primarily performed by neurons. The default operational definition of neural information processing is that (1) it is ultimately encoded as a change in individual neuronal firing rate as this correlates with the presentation of a peripheral stimulus, motor action or cognitive task. Two additional assumptions are associated with this default interpretation: (2) that the incessant background firing activity against which changes in activity are measured plays no role in assigning significance to the extrinsically evoked change in neural firing, and (3) that the metabolic energy that sustains this background activity and which correlates with differences in neuronal firing rate is merely a response to an evoked change in neuronal activity. These assumptions underlie the design, implementation, and interpretation of neuroimaging studies, particularly fMRI, which relies on changes in blood oxygen as an indirect measure of neural activity. In this article we reconsider all three of these assumptions in light of recent evidence. We suggest that by combining EEG with fMRI, new experimental work can reconcile emerging controversies in neurovascular coupling and the significance of ongoing, background activity during resting-state paradigms. A new conceptual framework for neuroimaging paradigms is developed to investigate how ongoing neural activity is "entangled" with metabolism. That is, in addition to being recruited to support locally evoked neuronal activity (the traditional hemodynamic response), changes in metabolic support may be independently "invoked" by non-local brain regions, yielding flexible neurovascular coupling dynamics that inform the cognitive context. This framework demonstrates how multimodal neuroimaging is necessary to probe the neurometabolic foundations of cognition, with implications for the study of neuropsychiatric disorders.
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Affiliation(s)
- Michael Jacob
- Mental Health Service, San Francisco VA Healthcare System, San Francisco, CA, United States
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Judith Ford
- Mental Health Service, San Francisco VA Healthcare System, San Francisco, CA, United States
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Terrence Deacon
- Department of Anthropology, University of California, Berkeley, Berkeley, CA, United States
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58
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Libedinsky C. Comparing representations and computations in single neurons versus neural networks. Trends Cogn Sci 2023; 27:517-527. [PMID: 37005114 DOI: 10.1016/j.tics.2023.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 04/03/2023]
Abstract
Single-neuron-level explanations have been the gold standard in neuroscience for decades. Recently, however, neural-network-level explanations have become increasingly popular. This increase in popularity is driven by the fact that the analysis of neural networks can solve problems that cannot be addressed by analyzing neurons independently. In this opinion article, I argue that while both frameworks employ the same general logic to link physical and mental phenomena, in many cases the neural network framework provides better explanatory objects to understand representations and computations related to mental phenomena. I discuss what constitutes a mechanistic explanation in neural systems, provide examples, and conclude by highlighting a number of the challenges and considerations associated with the use of analyses of neural networks to study brain function.
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59
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Marques DM, Almeida AS, Oliveira CBA, Machado ACL, Lara MVS, Porciúncula LO. Delayed Outgrowth in Response to the BDNF and Altered Synaptic Proteins in Neurons From SHR Rats. Neurochem Res 2023:10.1007/s11064-023-03917-9. [PMID: 36995561 DOI: 10.1007/s11064-023-03917-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/23/2023] [Accepted: 03/21/2023] [Indexed: 03/31/2023]
Abstract
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity symptoms. Neuroimaging studies have revealed a delayed cortical and subcortical development pattern in children diagnosed with ADHD. This study followed up on the development in vitro of frontal cortical neurons from Spontaneously hypertensive rats (SHR), an ADHD rat model, and Wistar-Kyoto rats (WKY), control strain, over their time in culture, and in response to BDNF treatment at two different days in vitro (DIV). These neurons were also evaluated for synaptic proteins, brain-derived neurotrophic factor (BDNF), and related protein levels. Frontal cortical neurons from the ADHD rat model exhibited shorter dendrites and less dendritic branching over their time in culture. While pro- and mature BDNF levels were not altered, the cAMP-response element-binding (CREB) decreased at 1 DIV and SNAP-25 decreased at 5 DIV. Different from control cultures, exogenous BDNF promoted less dendritic branching in neurons from the ADHD model. Our data revealed that neurons from the ADHD model showed decreased levels of an important transcription factor at the beginning of their development, and their delayed outgrowth and maturation had consequences in the levels of SNAP-25 and may be associated with less response to BDNF. These findings provide an alternative tool for studies on synaptic dysfunctions in ADHD. They may also offer a valuable tool for investigating drug effects and new treatment opportunities.
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Affiliation(s)
- Daniela M Marques
- Departamento de Bioquímica, Programa de Pós-Graduação Em Ciências Biológicas-Bioquímica, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2600-anexo, Porto Alegre, RS, 90035-003, Brasil
| | - Amanda S Almeida
- Departamento de Bioquímica, Programa de Pós-Graduação Em Ciências Biológicas-Bioquímica, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2600-anexo, Porto Alegre, RS, 90035-003, Brasil
| | - Catiane B A Oliveira
- Departamento de Bioquímica, Programa de Pós-Graduação Em Ciências Biológicas-Bioquímica, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2600-anexo, Porto Alegre, RS, 90035-003, Brasil
| | - Ana Carolina L Machado
- Departamento de Bioquímica, Programa de Pós-Graduação Em Ciências Biológicas-Bioquímica, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2600-anexo, Porto Alegre, RS, 90035-003, Brasil
| | - Marcus Vinícius S Lara
- Departamento de Bioquímica, Programa de Pós-Graduação Em Ciências Biológicas-Bioquímica, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2600-anexo, Porto Alegre, RS, 90035-003, Brasil
| | - Lisiane O Porciúncula
- Departamento de Bioquímica, Programa de Pós-Graduação Em Ciências Biológicas-Bioquímica, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2600-anexo, Porto Alegre, RS, 90035-003, Brasil.
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60
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Jeong H, Namboodiri VMK, Jung MW, Andermann ML. Sensory cortical ensembles exhibit differential coupling to ripples in distinct hippocampal subregions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.533028. [PMID: 36993665 PMCID: PMC10055189 DOI: 10.1101/2023.03.17.533028] [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: 06/19/2023]
Abstract
Cortical neurons activated during recent experiences often reactivate with dorsal hippocampal CA1 sharp-wave ripples (SWRs) during subsequent rest. Less is known about cortical interactions with intermediate hippocampal CA1, whose connectivity, functions, and SWRs differ from those of dorsal CA1. We identified three clusters of visual cortical excitatory neurons that are excited together with either dorsal or intermediate CA1 SWRs, or suppressed before both SWRs. Neurons in each cluster were distributed across primary and higher visual cortices and co-active even in the absence of SWRs. These ensembles exhibited similar visual responses but different coupling to thalamus and pupil-indexed arousal. We observed a consistent activity sequence: (i) suppression of SWR-suppressed cortical neurons, (ii) thalamic silence, and (iii) activation of the cortical ensemble preceding and predicting intermediate CA1 SWRs. We propose that the coordinated dynamics of these ensembles relay visual experiences to distinct hippocampal subregions for incorporation into different cognitive maps.
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Affiliation(s)
- Huijeong Jeong
- Department of Neurology, University of California, San Francisco, CA 94158, USA
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
| | - Vijay Mohan K Namboodiri
- Department of Neurology, University of California, San Francisco, CA 94158, USA
- Neuroscience Graduate Program, University of California, San Francisco, CA 94158, USA
- Weill Institute for Neuroscience, Kavli Institute for Fundamental Neuroscience, Center for Integrative Neuroscience, University of California, San Francisco 94158, CA, USA
| | - Min Whan Jung
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Korea
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
| | - Mark L. Andermann
- Division of Endocrinology, Metabolism, and Diabetes, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115 USA
- Lead contact
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61
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Neuronal Cultures: Exploring Biophysics, Complex Systems, and Medicine in a Dish. BIOPHYSICA 2023. [DOI: 10.3390/biophysica3010012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Neuronal cultures are one of the most important experimental models in modern interdisciplinary neuroscience, allowing to investigate in a control environment the emergence of complex behavior from an ensemble of interconnected neurons. Here, I review the research that we have conducted at the neurophysics laboratory at the University of Barcelona over the last 15 years, describing first the neuronal cultures that we prepare and the associated tools to acquire and analyze data, to next delve into the different research projects in which we actively participated to progress in the understanding of open questions, extend neuroscience research on new paradigms, and advance the treatment of neurological disorders. I finish the review by discussing the drawbacks and limitations of neuronal cultures, particularly in the context of brain-like models and biomedicine.
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62
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Berthon B, Bergel A, Matei M, Tanter M. Decoding behavior from global cerebrovascular activity using neural networks. Sci Rep 2023; 13:3541. [PMID: 36864293 PMCID: PMC9981746 DOI: 10.1038/s41598-023-30661-5] [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: 12/03/2021] [Accepted: 02/27/2023] [Indexed: 03/04/2023] Open
Abstract
Functional Ultrasound (fUS) provides spatial and temporal frames of the vascular activity in the brain with high resolution and sensitivity in behaving animals. The large amount of resulting data is underused at present due to the lack of appropriate tools to visualize and interpret such signals. Here we show that neural networks can be trained to leverage the richness of information available in fUS datasets to reliably determine behavior, even from a single fUS 2D image after appropriate training. We illustrate the potential of this method with two examples: determining if a rat is moving or static and decoding the animal's sleep/wake state in a neutral environment. We further demonstrate that our method can be transferred to new recordings, possibly in other animals, without additional training, thereby paving the way for real-time decoding of brain activity based on fUS data. Finally, the learned weights of the network in the latent space were analyzed to extract the relative importance of input data to classify behavior, making this a powerful tool for neuroscientific research.
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Affiliation(s)
- Béatrice Berthon
- Physics for Medicine Institute, INSERM U1273, CNRS UMR 8063, ESPCI Paris, PSL Research University, Paris, France.
| | - Antoine Bergel
- Physics for Medicine Institute, INSERM U1273, CNRS UMR 8063, ESPCI Paris, PSL Research University, Paris, France
| | - Marta Matei
- Physics for Medicine Institute, INSERM U1273, CNRS UMR 8063, ESPCI Paris, PSL Research University, Paris, France
| | - Mickaël Tanter
- Physics for Medicine Institute, INSERM U1273, CNRS UMR 8063, ESPCI Paris, PSL Research University, Paris, France
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63
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Transcranial Magnetic Stimulation in Obsessive-Compulsive Disorder. Psychiatr Clin North Am 2023; 46:133-166. [PMID: 36740349 DOI: 10.1016/j.psc.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Obsessive-compulsive disorder (OCD) patients need novel therapeutic interventions since most experience residual symptoms despite treatment. Converging evidence suggest that OCD involves dysfunction of limbic cortico-striato-thalamo-cortical loops, including the medial prefrontal cortex (mPFC) and dorsal anterior cingulate cortex (dACC), that tends to normalize with successful treatment. Recently, three repetitive transcranial magnetic stimulation (rTMS) coils were FDA-cleared for treatment-refractory OCD. This review presents on-label and off-label clinical evidence and relevant physical characteristics of the three coils. The Deep TMS™ H7 Coil studies' point to efficacy of mPFC-dACC stimulation, while no clear target stems from the small heterogenous D-B80 and figure-8 coils studies.
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64
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Frisby SL, Halai AD, Cox CR, Lambon Ralph MA, Rogers TT. Decoding semantic representations in mind and brain. Trends Cogn Sci 2023; 27:258-281. [PMID: 36631371 DOI: 10.1016/j.tics.2022.12.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 01/11/2023]
Abstract
A key goal for cognitive neuroscience is to understand the neurocognitive systems that support semantic memory. Recent multivariate analyses of neuroimaging data have contributed greatly to this effort, but the rapid development of these novel approaches has made it difficult to track the diversity of findings and to understand how and why they sometimes lead to contradictory conclusions. We address this challenge by reviewing cognitive theories of semantic representation and their neural instantiation. We then consider contemporary approaches to neural decoding and assess which types of representation each can possibly detect. The analysis suggests why the results are heterogeneous and identifies crucial links between cognitive theory, data collection, and analysis that can help to better connect neuroimaging to mechanistic theories of semantic cognition.
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Affiliation(s)
- Saskia L Frisby
- Medical Research Council (MRC) Cognition and Brain Sciences Unit, Chaucer Road, Cambridge CB2 7EF, UK.
| | - Ajay D Halai
- Medical Research Council (MRC) Cognition and Brain Sciences Unit, Chaucer Road, Cambridge CB2 7EF, UK
| | - Christopher R Cox
- Department of Psychology, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Matthew A Lambon Ralph
- Medical Research Council (MRC) Cognition and Brain Sciences Unit, Chaucer Road, Cambridge CB2 7EF, UK
| | - Timothy T Rogers
- Department of Psychology, University of Wisconsin-Madison, 1202 West Johnson Street, Madison, WI 53706, USA.
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Callegari F, Brofiga M, Massobrio P. Modeling the three-dimensional connectivity of in vitro cortical ensembles coupled to Micro-Electrode Arrays. PLoS Comput Biol 2023; 19:e1010825. [PMID: 36780570 PMCID: PMC9956882 DOI: 10.1371/journal.pcbi.1010825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 02/24/2023] [Accepted: 12/17/2022] [Indexed: 02/15/2023] Open
Abstract
Nowadays, in vitro three-dimensional (3D) neuronal networks are becoming a consolidated experimental model to overcome most of the intrinsic limitations of bi-dimensional (2D) assemblies. In the 3D environment, experimental evidence revealed a wider repertoire of activity patterns, characterized by a modulation of the bursting features, than the one observed in 2D cultures. However, it is not totally clear and understood what pushes the neuronal networks towards different dynamical regimes. One possible explanation could be the underlying connectivity, which could involve a larger number of neurons in a 3D rather than a 2D space and could organize following well-defined topological schemes. Driven by experimental findings, achieved by recording 3D cortical networks organized in multi-layered structures coupled to Micro-Electrode Arrays (MEAs), in the present work we developed a large-scale computational network model made up of leaky integrate-and-fire (LIF) neurons to investigate possible structural configurations able to sustain the emerging patterns of electrophysiological activity. In particular, we investigated the role of the number of layers defining a 3D assembly and the spatial distribution of the connections within and among the layers. These configurations give rise to different patterns of activity that could be compared to the ones emerging from real in vitro 3D neuronal populations. Our results suggest that the introduction of three-dimensionality induced a global reduction in both firing and bursting rates with respect to 2D models. In addition, we found that there is a minimum number of layers necessary to obtain a change in the dynamics of the network. However, the effects produced by a 3D organization of the cells is somewhat mitigated if a scale-free connectivity is implemented in either one or all the layers of the network. Finally, the best matching of the experimental data is achieved supposing a 3D connectivity organized in structured bundles of links located in different areas of the 2D network.
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Affiliation(s)
- Francesca Callegari
- Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genova, Genova, Italy
| | - Martina Brofiga
- Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genova, Genova, Italy
- ScreenNeuroPharm, Sanremo, Italy
| | - Paolo Massobrio
- Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genova, Genova, Italy
- National Institute for Nuclear Physics (INFN), Genova, Italy
- * E-mail:
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66
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Sun F, Jiang H, Wang H, Zhong Y, Xu Y, Xing Y, Yu M, Feng LW, Tang Z, Liu J, Sun H, Wang H, Wang G, Zhu M. Soft Fiber Electronics Based on Semiconducting Polymer. Chem Rev 2023; 123:4693-4763. [PMID: 36753731 DOI: 10.1021/acs.chemrev.2c00720] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Fibers, originating from nature and mastered by human, have woven their way throughout the entire history of human civilization. Recent developments in semiconducting polymer materials have further endowed fibers and textiles with various electronic functions, which are attractive in applications such as information interfacing, personalized medicine, and clean energy. Owing to their ability to be easily integrated into daily life, soft fiber electronics based on semiconducting polymers have gained popularity recently for wearable and implantable applications. Herein, we present a review of the previous and current progress in semiconducting polymer-based fiber electronics, particularly focusing on smart-wearable and implantable areas. First, we provide a brief overview of semiconducting polymers from the viewpoint of materials based on the basic concepts and functionality requirements of different devices. Then we analyze the existing applications and associated devices such as information interfaces, healthcare and medicine, and energy conversion and storage. The working principle and performance of semiconducting polymer-based fiber devices are summarized. Furthermore, we focus on the fabrication techniques of fiber devices. Based on the continuous fabrication of one-dimensional fiber and yarn, we introduce two- and three-dimensional fabric fabricating methods. Finally, we review challenges and relevant perspectives and potential solutions to address the related problems.
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Affiliation(s)
- Fengqiang Sun
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
| | - Hao Jiang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Haoyu Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yueheng Zhong
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yiman Xu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yi Xing
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Muhuo Yu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Shanghai Key Laboratory of Lightweight Structural Composites, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Liang-Wen Feng
- Key Laboratory of Green Chemistry & Technology, Ministry of Education, College of Chemistry, Sichuan University, Chengdu 610065, China
| | - Zheng Tang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Center for Advanced Low-dimension Materials, Donghua University, Shanghai 201620, China
| | - Jun Liu
- National Key Laboratory on Electromagnetic Environment Effects and Electro-Optical Engineering, Nanjing 210007, China
| | - Hengda Sun
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Hongzhi Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Gang Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Meifang Zhu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
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67
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Nietz AK, Streng ML, Popa LS, Carter RE, Flaherty EB, Aronson JD, Ebner TJ. To be and not to be: wide-field Ca2+ imaging reveals neocortical functional segmentation combines stability and flexibility. Cereb Cortex 2023:7024718. [PMID: 36734268 DOI: 10.1093/cercor/bhac523] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 12/09/2022] [Accepted: 12/10/2022] [Indexed: 02/04/2023] Open
Abstract
The stability and flexibility of the functional parcellation of the cerebral cortex is fundamental to how familiar and novel information is both represented and stored. We leveraged new advances in Ca2+ sensors and microscopy to understand the dynamics of functional segmentation in the dorsal cerebral cortex. We performed wide-field Ca2+ imaging in head-fixed mice and used spatial independent component analysis (ICA) to identify independent spatial sources of Ca2+ fluorescence. The imaging data were evaluated over multiple timescales and discrete behaviors including resting, walking, and grooming. When evaluated over the entire dataset, a set of template independent components (ICs) were identified that were common across behaviors. Template ICs were present across a range of timescales, from days to 30 seconds, although with lower occurrence probability at shorter timescales, highlighting the stability of the functional segmentation. Importantly, unique ICs emerged at the shorter duration timescales that could act to transiently refine the cortical network. When data were evaluated by behavior, both common and behavior-specific ICs emerged. Each behavior is composed of unique combinations of common and behavior-specific ICs. These observations suggest that cerebral cortical functional segmentation exhibits considerable spatial stability over time and behaviors while retaining the flexibility for task-dependent reorganization.
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Affiliation(s)
- Angela K Nietz
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Martha L Streng
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Laurentiu S Popa
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Evelyn B Flaherty
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Justin D Aronson
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
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68
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Scangos KW, State MW, Miller AH, Baker JT, Williams LM. New and emerging approaches to treat psychiatric disorders. Nat Med 2023; 29:317-333. [PMID: 36797480 PMCID: PMC11219030 DOI: 10.1038/s41591-022-02197-0] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 12/21/2022] [Indexed: 02/18/2023]
Abstract
Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact the lives of millions of people worldwide. Although their etiological and diagnostic heterogeneity has long challenged drug discovery, an emerging circuit-based understanding of psychiatric illness is offering an important alternative to the current reliance on trial and error, both in the development and in the clinical application of treatments. Here we review new and emerging treatment approaches, with a particular emphasis on the revolutionary potential of brain-circuit-based interventions for precision psychiatry. Limitations of circuit models, challenges of bringing precision therapeutics to market and the crucial advances needed to overcome these obstacles are presented.
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Affiliation(s)
- Katherine W Scangos
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Matthew W State
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew H Miller
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Justin T Baker
- McLean Hospital Institute for Technology in Psychiatry, Belmont, MA, USA
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Mental Illness Research Education and Clinical Center (MIRECC), VA Palo Alto Health Care System, Palo Alto, CA, USA
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69
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Priming of probabilistic attentional templates. Psychon Bull Rev 2023; 30:22-39. [PMID: 35831678 DOI: 10.3758/s13423-022-02125-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/09/2022] [Indexed: 11/08/2022]
Abstract
Attentional priming has a dominating influence on vision, speeding visual search, releasing items from crowding, reducing masking effects, and during free-choice, primed targets are chosen over unprimed ones. Many accounts postulate that templates stored in working memory control what we attend to and mediate the priming. But what is the nature of these templates (or representations)? Analyses of real-world visual scenes suggest that tuning templates to exact color or luminance values would be impractical since those can vary greatly because of changes in environmental circumstances and perceptual interpretation. Tuning templates to a range of the most probable values would be more efficient. Recent evidence does indeed suggest that the visual system represents such probability, gradually encoding statistical variation in the environment through repeated exposure to input statistics. This is consistent with evidence from neurophysiology and theoretical neuroscience as well as computational evidence of probabilistic representations in visual perception. I argue that such probabilistic representations are the unit of attentional priming and that priming of, say, a repeated single-color value simply involves priming of a distribution with no variance. This "priming of probability" view can be modelled within a Bayesian framework where priming provides contextual priors. Priming can therefore be thought of as learning of the underlying probability density function of the target or distractor sets in a given continuous task.
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70
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Neuronal ensemble dynamics in social memory. Curr Opin Neurobiol 2023; 78:102654. [PMID: 36509026 DOI: 10.1016/j.conb.2022.102654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 11/08/2022] [Accepted: 11/09/2022] [Indexed: 12/14/2022]
Abstract
A large body of evidence suggests that cognitive functions rely on the coordination of ensembles of neurons across brain circuits. One example is social memory, the ability to recognize and remember other conspecifics. A broad range of brain regions have been implicated in social behaviors and memory processes. At the single-cell level, neurons from different brain areas have responded to specific social features. The coordination of these ensembles both within a region and across structures is required to support social memory and decision-making. The synchronous activation of these neuronal ensembles could allow for the integration of different aspects of a social episode into a unified representation of experience. In this review, recent results on the circuit basis and physiological mechanisms of social memory are discussed, from a systems neuroscience perspective. An integrative framework of the neuronal ensemble dynamics supporting this fundamental cognitive ability is proposed.
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71
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Galgali AR, Sahani M, Mante V. Residual dynamics resolves recurrent contributions to neural computation. Nat Neurosci 2023; 26:326-338. [PMID: 36635498 DOI: 10.1038/s41593-022-01230-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 11/08/2022] [Indexed: 01/14/2023]
Abstract
Relating neural activity to behavior requires an understanding of how neural computations arise from the coordinated dynamics of distributed, recurrently connected neural populations. However, inferring the nature of recurrent dynamics from partial recordings of a neural circuit presents considerable challenges. Here we show that some of these challenges can be overcome by a fine-grained analysis of the dynamics of neural residuals-that is, trial-by-trial variability around the mean neural population trajectory for a given task condition. Residual dynamics in macaque prefrontal cortex (PFC) in a saccade-based perceptual decision-making task reveals recurrent dynamics that is time dependent, but consistently stable, and suggests that pronounced rotational structure in PFC trajectories during saccades is driven by inputs from upstream areas. The properties of residual dynamics restrict the possible contributions of PFC to decision-making and saccade generation and suggest a path toward fully characterizing distributed neural computations with large-scale neural recordings and targeted causal perturbations.
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Affiliation(s)
- Aniruddh R Galgali
- Institute of Neuroinformatics, University of Zurich & ETH Zurich, Zurich, Switzerland.
- Neuroscience Center Zurich, University of Zurich & ETH Zurich, Zurich, Switzerland.
- Department of Experimental Psychology, University of Oxford, Oxford, UK.
| | - Maneesh Sahani
- Gatsby Computational Neuroscience Unit, University College London, London, UK
| | - Valerio Mante
- Institute of Neuroinformatics, University of Zurich & ETH Zurich, Zurich, Switzerland.
- Neuroscience Center Zurich, University of Zurich & ETH Zurich, Zurich, Switzerland.
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72
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Koren V, Bondanelli G, Panzeri S. Computational methods to study information processing in neural circuits. Comput Struct Biotechnol J 2023; 21:910-922. [PMID: 36698970 PMCID: PMC9851868 DOI: 10.1016/j.csbj.2023.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 01/09/2023] [Accepted: 01/09/2023] [Indexed: 01/13/2023] Open
Abstract
The brain is an information processing machine and thus naturally lends itself to be studied using computational tools based on the principles of information theory. For this reason, computational methods based on or inspired by information theory have been a cornerstone of practical and conceptual progress in neuroscience. In this Review, we address how concepts and computational tools related to information theory are spurring the development of principled theories of information processing in neural circuits and the development of influential mathematical methods for the analyses of neural population recordings. We review how these computational approaches reveal mechanisms of essential functions performed by neural circuits. These functions include efficiently encoding sensory information and facilitating the transmission of information to downstream brain areas to inform and guide behavior. Finally, we discuss how further progress and insights can be achieved, in particular by studying how competing requirements of neural encoding and readout may be optimally traded off to optimize neural information processing.
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Affiliation(s)
- Veronika Koren
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, Hamburg 20251, Germany
| | | | - Stefano Panzeri
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, Hamburg 20251, Germany
- Istituto Italiano di Tecnologia, Via Melen 83, Genova 16152, Italy
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73
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Electron transfer in protein modifications: from detection to imaging. Sci China Chem 2023. [DOI: 10.1007/s11426-022-1417-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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74
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Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation. J Neurosci 2023; 43:82-92. [PMID: 36400529 PMCID: PMC9838708 DOI: 10.1523/jneurosci.1104-22.2022] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 09/15/2022] [Accepted: 10/16/2022] [Indexed: 11/19/2022] Open
Abstract
Cortical computations emerge from the dynamics of neurons embedded in complex cortical circuits. Within these circuits, neuronal ensembles, which represent subnetworks with shared functional connectivity, emerge in an experience-dependent manner. Here we induced ensembles in ex vivo cortical circuits from mice of either sex by differentially activating subpopulations through chronic optogenetic stimulation. We observed a decrease in voltage correlation, and importantly a synaptic decoupling between the stimulated and nonstimulated populations. We also observed a decrease in firing rate during Up-states in the stimulated population. These ensemble-specific changes were accompanied by decreases in intrinsic excitability in the stimulated population, and a decrease in connectivity between stimulated and nonstimulated pyramidal neurons. By incorporating the empirically observed changes in intrinsic excitability and connectivity into a spiking neural network model, we were able to demonstrate that changes in both intrinsic excitability and connectivity accounted for the decreased firing rate, but only changes in connectivity accounted for the observed decorrelation. Our findings help ascertain the mechanisms underlying the ability of chronic patterned stimulation to create ensembles within cortical circuits and, importantly, show that while Up-states are a global network-wide phenomenon, functionally distinct ensembles can preserve their identity during Up-states through differential firing rates and correlations.SIGNIFICANCE STATEMENT The connectivity and activity patterns of local cortical circuits are shaped by experience. This experience-dependent reorganization of cortical circuits is driven by complex interactions between different local learning rules, external input, and reciprocal feedback between many distinct brain areas. Here we used an ex vivo approach to demonstrate how simple forms of chronic external stimulation can shape local cortical circuits in terms of their correlated activity and functional connectivity. The absence of feedback between different brain areas and full control of external input allowed for a tractable system to study the underlying mechanisms and development of a computational model. Results show that differential stimulation of subpopulations of neurons significantly reshapes cortical circuits and forms subnetworks referred to as neuronal ensembles.
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75
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Bryson A, Petrou S. SCN1A channelopathies: Navigating from genotype to neural circuit dysfunction. Front Neurol 2023; 14:1173460. [PMID: 37139072 PMCID: PMC10149698 DOI: 10.3389/fneur.2023.1173460] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 03/28/2023] [Indexed: 05/05/2023] Open
Abstract
The SCN1A gene is strongly associated with epilepsy and plays a central role for supporting cortical excitation-inhibition balance through the expression of NaV1.1 within inhibitory interneurons. The phenotype of SCN1A disorders has been conceptualized as driven primarily by impaired interneuron function that predisposes to disinhibition and cortical hyperexcitability. However, recent studies have identified SCN1A gain-of-function variants associated with epilepsy, and the presence of cellular and synaptic changes in mouse models that point toward homeostatic adaptations and complex network remodeling. These findings highlight the need to understand microcircuit-scale dysfunction in SCN1A disorders to contextualize genetic and cellular disease mechanisms. Targeting the restoration of microcircuit properties may be a fruitful strategy for the development of novel therapies.
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Affiliation(s)
- Alexander Bryson
- Ion Channels and Disease Group, The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- *Correspondence: Alexander Bryson,
| | - Steven Petrou
- Ion Channels and Disease Group, The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Praxis Precision Medicines, Inc., Cambridge, MA, United States
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76
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Monaco JD, Hwang GM. Neurodynamical Computing at the Information Boundaries of Intelligent Systems. Cognit Comput 2022; 16:1-13. [PMID: 39129840 PMCID: PMC11306504 DOI: 10.1007/s12559-022-10081-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 11/15/2022] [Indexed: 12/28/2022]
Abstract
Artificial intelligence has not achieved defining features of biological intelligence despite models boasting more parameters than neurons in the human brain. In this perspective article, we synthesize historical approaches to understanding intelligent systems and argue that methodological and epistemic biases in these fields can be resolved by shifting away from cognitivist brain-as-computer theories and recognizing that brains exist within large, interdependent living systems. Integrating the dynamical systems view of cognition with the massive distributed feedback of perceptual control theory highlights a theoretical gap in our understanding of nonreductive neural mechanisms. Cell assemblies-properly conceived as reentrant dynamical flows and not merely as identified groups of neurons-may fill that gap by providing a minimal supraneuronal level of organization that establishes a neurodynamical base layer for computation. By considering information streams from physical embodiment and situational embedding, we discuss this computational base layer in terms of conserved oscillatory and structural properties of cortical-hippocampal networks. Our synthesis of embodied cognition, based in dynamical systems and perceptual control, aims to bypass the neurosymbolic stalemates that have arisen in artificial intelligence, cognitive science, and computational neuroscience.
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Affiliation(s)
- Joseph D. Monaco
- Dept of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - Grace M. Hwang
- Johns Hopkins University Applied Physics Laboratory, Laurel, MD USA
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Nomoto M, Murayama E, Ohno S, Okubo-Suzuki R, Muramatsu SI, Inokuchi K. Hippocampus as a sorter and reverberatory integrator of sensory inputs. Nat Commun 2022; 13:7413. [PMID: 36539403 PMCID: PMC9768143 DOI: 10.1038/s41467-022-35119-2] [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: 03/13/2022] [Accepted: 11/17/2022] [Indexed: 12/24/2022] Open
Abstract
The hippocampus must be capable of sorting and integrating multiple sensory inputs separately but simultaneously. However, it remains to be elucidated how the hippocampus executes these processes simultaneously during learning. Here we found that synchrony between conditioned stimulus (CS)-, unconditioned stimulus (US)- and future retrieval-responsible cells occurs in the CA1 during the reverberatory phase that emerges after sensory inputs have ceased, but not during CS and US inputs. Mutant mice lacking N-methyl-D-aspartate receptors (NRs) in CA3 showed a cued-fear memory impairment and a decrease in synchronized reverberatory activities between CS- and US-responsive CA1 cells. Optogenetic CA3 silencing at the reverberatory phase during learning impaired cued-fear memory. Thus, the hippocampus uses reverberatory activity to link CS and US inputs, and avoid crosstalk during sensory inputs.
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Affiliation(s)
- Masanori Nomoto
- grid.267346.20000 0001 2171 836XResearch Centre for Idling Brain Science, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XDepartment of Biochemistry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XCREST, JST, University of Toyama, Toyama, 930−0194 Japan
| | - Emi Murayama
- grid.267346.20000 0001 2171 836XResearch Centre for Idling Brain Science, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XDepartment of Biochemistry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XCREST, JST, University of Toyama, Toyama, 930−0194 Japan
| | - Shuntaro Ohno
- grid.267346.20000 0001 2171 836XResearch Centre for Idling Brain Science, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XDepartment of Biochemistry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XCREST, JST, University of Toyama, Toyama, 930−0194 Japan
| | - Reiko Okubo-Suzuki
- grid.267346.20000 0001 2171 836XResearch Centre for Idling Brain Science, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XDepartment of Biochemistry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XCREST, JST, University of Toyama, Toyama, 930−0194 Japan
| | - Shin-ichi Muramatsu
- grid.410804.90000000123090000Division of Neurology, Department of Medicine, Jichi Medical University, Tochigi, 329−0498 Japan ,grid.26999.3d0000 0001 2151 536XCenter for Gene and Cell Therapy, The Institute of Medical Science, The University of Tokyo, Tokyo, 108−8639 Japan
| | - Kaoru Inokuchi
- grid.267346.20000 0001 2171 836XResearch Centre for Idling Brain Science, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XDepartment of Biochemistry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, 930−0194 Japan ,grid.267346.20000 0001 2171 836XCREST, JST, University of Toyama, Toyama, 930−0194 Japan
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Adegoke MA, Teter O, Meaney DF. Flexibility of in vitro cortical circuits influences resilience from microtrauma. Front Cell Neurosci 2022; 16:991740. [PMID: 36589287 PMCID: PMC9803265 DOI: 10.3389/fncel.2022.991740] [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: 07/11/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Background Small clusters comprising hundreds to thousands of neurons are an important level of brain architecture that correlates single neuronal properties to fulfill brain function, but the specific mechanisms through which this scaling occurs are not well understood. In this study, we developed an in vitro experimental platform of small neuronal circuits (islands) to probe the importance of structural properties for their development, physiology, and response to microtrauma. Methods Primary cortical neurons were plated on a substrate patterned to promote attachment in clusters of hundreds of cells (islands), transduced with GCaMP6f, allowed to mature until 10-13 days in vitro (DIV), and monitored with Ca2+ as a non-invasive proxy for electrical activity. We adjusted two structural factors-island size and cellular density-to evaluate their role in guiding spontaneous activity and network formation in neuronal islands. Results We found cellular density, but not island size, regulates of circuit activity and network function in this system. Low cellular density islands can achieve many states of activity, while high cellular density biases islands towards a limited regime characterized by low rates of activity and high synchronization, a property we summarized as "flexibility." The injury severity required for an island to lose activity in 50% of its population was significantly higher in low-density, high flexibility islands. Conclusion Together, these studies demonstrate flexible living cortical circuits are more resilient to microtrauma, providing the first evidence that initial circuit state may be a key factor to consider when evaluating the consequences of trauma to the cortex.
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Affiliation(s)
- Modupe A. Adegoke
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, United States
| | - Olivia Teter
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, United States
| | - David F. Meaney
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, United States,Department of Neurosurgery, Penn Center for Brain Injury and Repair, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States,*Correspondence: David F. Meaney,
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79
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Serrano-Reyes M, Pérez-Ortega JE, García-Vilchis B, Laville A, Ortega A, Galarraga E, Bargas J. Dimensionality reduction and recurrence analysis reveal hidden structures of striatal pathological states. Front Syst Neurosci 2022; 16:975989. [PMID: 36741818 PMCID: PMC9893717 DOI: 10.3389/fnsys.2022.975989] [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: 06/22/2022] [Accepted: 11/09/2022] [Indexed: 12/02/2022] Open
Abstract
A pipeline is proposed here to describe different features to study brain microcircuits on a histological scale using multi-scale analyses, including the uniform manifold approximation and projection (UMAP) dimensional reduction technique and modularity algorithm to identify neuronal ensembles, Runs tests to show significant ensembles activation, graph theory to show trajectories between ensembles, and recurrence analyses to describe how regular or chaotic ensembles dynamics are. The data set includes ex-vivo NMDA-activated striatal tissue in control conditions as well as experimental models of disease states: decorticated, dopamine depleted, and L-DOPA-induced dyskinetic rodent samples. The goal was to separate neuronal ensembles that have correlated activity patterns. The pipeline allows for the demonstration of differences between disease states in a brain slice. First, the ensembles were projected in distinctive locations in the UMAP space. Second, graphs revealed functional connectivity between neurons comprising neuronal ensembles. Third, the Runs test detected significant peaks of coactivity within neuronal ensembles. Fourth, significant peaks of coactivity were used to show activity transitions between ensembles, revealing recurrent temporal sequences between them. Fifth, recurrence analysis shows how deterministic, chaotic, or recurrent these circuits are. We found that all revealed circuits had recurrent activity except for the decorticated circuits, which tended to be divergent and chaotic. The Parkinsonian circuits exhibit fewer transitions, becoming rigid and deterministic, exhibiting a predominant temporal sequence that disrupts transitions found in the controls, thus resembling the clinical signs of rigidity and paucity of movements. Dyskinetic circuits display a higher recurrence rate between neuronal ensembles transitions, paralleling clinical findings: enhancement in involuntary movements. These findings confirm that looking at neuronal circuits at the histological scale, recording dozens of neurons simultaneously, can show clear differences between control and diseased striatal states: "fingerprints" of the disease states. Therefore, the present analysis is coherent with previous ones of striatal disease states, showing that data obtained from the tissue are robust. At the same time, it adds heuristic ways to interpret circuitry activity in different states.
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Affiliation(s)
- Miguel Serrano-Reyes
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico,Departamento de Ingeniería en Sistemas Biomédicos, Centro de Ingeniería Avanzada, Facultad de Ingeniería, Universidad Nacional Autónoma de México, Mexico City, Mexico,Miguel Serrano-Reyes,
| | - Jesús Esteban Pérez-Ortega
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico,Department of Biological Sciences, Columbia University, New York, NY, United States
| | - Brisa García-Vilchis
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Antonio Laville
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Aidán Ortega
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Elvira Galarraga
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Jose Bargas
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico,*Correspondence: Jose Bargas,
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80
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Khedr EM, Elbeh K, Saber M, Abdelrady Z, Abdelwarith A. A double blind randomized clinical trial of the effectiveness of low frequency rTMS over right DLPFC or OFC for treatment of obsessive-compulsive disorder. J Psychiatr Res 2022; 156:122-131. [PMID: 36244200 DOI: 10.1016/j.jpsychires.2022.10.025] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 10/02/2022] [Accepted: 10/05/2022] [Indexed: 11/07/2022]
Abstract
We compared the effectiveness of low frequency repetitive transcranial magnetic stimulation over right dorsolateral prefrontal cortex (DLPFC), right orbitofrontal cortex (OFC) and sham for treatment of obsessive-compulsive disorder (OCD) and sought to determine possible predictors of effective treatment. Sixty OCD patients participated and were randomly allocated to one of the 3 treatment groups. Treatment was administered daily for 10 days. Assessments were made at the beginning and end of therapy as well as three months later using the Yale-Brown obsessive compulsive scale (Y-BOCS), Hamilton Anxiety Rating Scale (HAM-A), Beck Depression Inventory (BDI), and Clinical Global Impression - Severity scale (CGI-S). There were no significant demographic or clinical differences between the groups at baseline. One-way repeated measures ANOVA showed that participants in all 3 groups improved their scores on all rating scales following treatment. A two-way repeated measures ANOVA revealed a significant time and group interaction due to the fact that both active treatment groups outperformed the sham group, although there was no significant difference between the two. Percent improvement had significant negative correlations with the following factors: duration of illness, baseline Y-BOCS, HAM-A, and BDI. We conclude that rTMS over either right DLPFC or OFC has a therapeutic effect on OCD symptoms. Patients with lower Y-BOCS and fewer comorbidities responded best to rTMS.
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Affiliation(s)
- Eman M Khedr
- Department of Neurology and Psychiatry, Assiut University, Assiut, Egypt; Department of Neuropsychiatry, Aswan University, Aswan, Egypt.
| | - Khaled Elbeh
- Department of Neurology and Psychiatry, Assiut University, Assiut, Egypt
| | - Mostafa Saber
- Department of Neuropsychiatry, Aswan University, Aswan, Egypt
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81
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Erofeev A, Antifeev I, Bolshakova A, Bezprozvanny I, Vlasova O. In Vivo Penetrating Microelectrodes for Brain Electrophysiology. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22239085. [PMID: 36501805 PMCID: PMC9735502 DOI: 10.3390/s22239085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/14/2022] [Accepted: 11/22/2022] [Indexed: 05/13/2023]
Abstract
In recent decades, microelectrodes have been widely used in neuroscience to understand the mechanisms behind brain functions, as well as the relationship between neural activity and behavior, perception and cognition. However, the recording of neuronal activity over a long period of time is limited for various reasons. In this review, we briefly consider the types of penetrating chronic microelectrodes, as well as the conductive and insulating materials for microelectrode manufacturing. Additionally, we consider the effects of penetrating microelectrode implantation on brain tissue. In conclusion, we review recent advances in the field of in vivo microelectrodes.
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Affiliation(s)
- Alexander Erofeev
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Correspondence: (A.E.); (O.V.)
| | - Ivan Antifeev
- Laboratory of Methods and Instruments for Genetic and Immunoassay Analysis, Institute for Analytical Instrumentation of the Russian Academy of Sciences, 198095 Saint Petersburg, Russia
| | - Anastasia Bolshakova
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
| | - Ilya Bezprozvanny
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Department of Physiology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390, USA
| | - Olga Vlasova
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Correspondence: (A.E.); (O.V.)
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82
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Goshi N, Girardi G, da Costa Souza F, Gardner A, Lein PJ, Seker E. Influence of microchannel geometry on device performance and electrophysiological recording fidelity during long-term studies of connected neural populations. LAB ON A CHIP 2022; 22:3961-3975. [PMID: 36111641 PMCID: PMC9639432 DOI: 10.1039/d2lc00683a] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Compartmentalized microfluidic neural cell culture platforms, which physically separate axons from the neural soma using a series of microchannels, have been used for studying a wide range of pathological conditions and basic neuroscience questions. While each study has different experimental needs, the fundamental design of these devices has largely remained unchanged and a systematic study to establish long-term neural cultures in this format is lacking. Here, we investigate the influence of microchannel geometry and cell seeding density on device performance particularly in the context of long-term studies of synaptically-connected, yet fluidically-isolated neural populations of neurons and glia. Of the different experimental parameters, the microchannel height was the principal determinant of device performance, where the other parameters offer additional degrees of freedom in customizing such devices for specific applications. We condense the effects of these parameters into design rules and demonstrate their utility in engineering a microfluidic neural culture platform with integrated microelectrode arrays. The engineered device successfully recorded from primary rat cortical cells for 59 days in vitro with more than on order of magnitude enhancement in signal-to-noise ratio in the microchannels.
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Affiliation(s)
- Noah Goshi
- Department of Biomedical Engineering, University of California - Davis, Davis, CA 95616, USA
| | - Gregory Girardi
- Department of Biomedical Engineering, University of California - Davis, Davis, CA 95616, USA
| | - Felipe da Costa Souza
- Department of Molecular Biosciences, University of California - Davis, Davis, CA 95616, USA
| | - Alexander Gardner
- Department of Electrical and Computer Engineering, University of California - Davis, Davis, CA 95616, USA.
| | - Pamela J Lein
- Department of Molecular Biosciences, University of California - Davis, Davis, CA 95616, USA
| | - Erkin Seker
- Department of Electrical and Computer Engineering, University of California - Davis, Davis, CA 95616, USA.
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83
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Pandey B, Pachitariu M, Brunton BW, Harris KD. Structured random receptive fields enable informative sensory encodings. PLoS Comput Biol 2022; 18:e1010484. [PMID: 36215307 PMCID: PMC9584455 DOI: 10.1371/journal.pcbi.1010484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 10/20/2022] [Accepted: 08/11/2022] [Indexed: 11/10/2022] Open
Abstract
Brains must represent the outside world so that animals survive and thrive. In early sensory systems, neural populations have diverse receptive fields structured to detect important features in inputs, yet significant variability has been ignored in classical models of sensory neurons. We model neuronal receptive fields as random, variable samples from parameterized distributions and demonstrate this model in two sensory modalities using data from insect mechanosensors and mammalian primary visual cortex. Our approach leads to a significant theoretical connection between the foundational concepts of receptive fields and random features, a leading theory for understanding artificial neural networks. The modeled neurons perform a randomized wavelet transform on inputs, which removes high frequency noise and boosts the signal. Further, these random feature neurons enable learning from fewer training samples and with smaller networks in artificial tasks. This structured random model of receptive fields provides a unifying, mathematically tractable framework to understand sensory encodings across both spatial and temporal domains.
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Affiliation(s)
- Biraj Pandey
- Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America
| | - Marius Pachitariu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Bingni W. Brunton
- Department of Biology, University of Washington, Seattle, Washington, United States of America
| | - Kameron Decker Harris
- Department of Computer Science, Western Washington University, Bellingham, Washington, United States of America
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84
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Xue Y. Computational optics for high-throughput imaging of neural activity. NEUROPHOTONICS 2022; 9:041408. [PMID: 35607516 PMCID: PMC9122092 DOI: 10.1117/1.nph.9.4.041408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 04/19/2022] [Indexed: 06/15/2023]
Abstract
Optical microscopy offers a noninvasive way to image neural activity in the mouse brain. To simultaneously record neural activity across a large population of neurons, optical systems that have high spatiotemporal resolution and can access a large volume are necessary. The throughput of a system, that is, the number of resolvable spots acquired by the system at a given time, is usually limited by optical hardware. To overcome this limitation, computation optics that designs optical hardware and computer software jointly becomes a new approach that achieves micronscale resolution, millimeter-scale field-of-view, and hundreds of hertz imaging speed at the same time. This review article summarizes recent advances in computational optics for high-throughput imaging of neural activity, highlighting technologies for three-dimensional parallelized excitation and detection. Computational optics can substantially accelerate the study of neural circuits with previously unattainable precision and speed.
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Affiliation(s)
- Yi Xue
- University of California, Davis, Department of Biomedical Engineering, Davis, California, United States
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85
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Mishchenko TA, Yarkov RS, Saviuk MO, Krivonosov MI, Perenkov AD, Gudkov SV, Vedunova MV. Unravelling Contributions of Astrocytic Connexin 43 to the Functional Activity of Brain Neuron-Glial Networks under Hypoxic State In Vitro. MEMBRANES 2022; 12:948. [PMID: 36295708 PMCID: PMC9609249 DOI: 10.3390/membranes12100948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/25/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
Brain hypoxia remains an Achilles' heel for public health that must be urgently addressed. Hypoxic damage affects both neurons and glial cells, particularly astrocytes, which are in close dynamic bi-directional communication, and are organized in plastic and tightly regulated networks. However, astroglial networks have received limited attention regarding their influence on the adaptive functional rearrangements of neural networks to oxygen deficiency. Herein, against the background of astrocytic Cx43 gap junction blockade by the selective blocker Gap19, we evaluated the features of spontaneous calcium activity and network characteristics of cells in primary cultures of the cerebral cortex, as well as the expression levels of metabotropic glutamate receptors 2 (mGluR2) and 5 (mGluR5) in the early and late periods after simulated hypoxia in vitro. We showed that, under normoxic conditions, blockade of Cx43 leads to an increase in the expression of metabotropic glutamate receptors mGluR2 and mGluR5 and long-term modulation of spontaneous calcium activity in primary cortical cultures, primarily expressed in the restructuring of the functional architectonics of neuron-glial networks through reducing the level of correlation between cells in the network and the percentage of existing correlated connections between cells. Blocking Cx43 during hypoxic injury has a pronounced neuroprotective effect. Together with the increased expression of mGluR5 receptors, a decrease in mGluR2 expression to the physiological level was found, which suggests the triggering of alternative molecular mechanisms of cell adaptation to hypoxia. Importantly, the blockade of Cx43 in hypoxic damage contributed to the maintenance of both the main parameters of the spontaneous calcium activity of primary cortical cultures and the functional architectonics of neuron-glial networks while maintaining the profile of calcium oscillations and calcium signal communications between cells at a highly correlated level. Our results demonstrate the crucial importance of astrocytic networks in functional brain adaptation to hypoxic damage and could be a promising target for the development of rational anti-hypoxic therapy.
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Affiliation(s)
- Tatiana A. Mishchenko
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 119991 Moscow, Russia
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Roman S. Yarkov
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Mariia O. Saviuk
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Mikhail I. Krivonosov
- Institute of Information, Technology, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Alexey D. Perenkov
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Sergey V. Gudkov
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 119991 Moscow, Russia
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
| | - Maria V. Vedunova
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 119991 Moscow, Russia
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., 603022 Nizhny Novgorod, Russia
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Vaccari FE, Diomedi S, Filippini M, Hadjidimitrakis K, Fattori P. New insights on single-neuron selectivity in the era of population-level approaches. Front Integr Neurosci 2022; 16:929052. [PMID: 36249900 PMCID: PMC9554653 DOI: 10.3389/fnint.2022.929052] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 09/02/2022] [Indexed: 11/13/2022] Open
Abstract
In the past, neuroscience was focused on individual neurons seen as the functional units of the nervous system, but this approach fell short over time to account for new experimental evidence, especially for what concerns associative and motor cortices. For this reason and thanks to great technological advances, a part of modern research has shifted the focus from the responses of single neurons to the activity of neural ensembles, now considered the real functional units of the system. However, on a microscale, individual neurons remain the computational components of these networks, thus the study of population dynamics cannot prescind from studying also individual neurons which represent their natural substrate. In this new framework, ideas such as the capability of single cells to encode a specific stimulus (neural selectivity) may become obsolete and need to be profoundly revised. One step in this direction was made by introducing the concept of “mixed selectivity,” the capacity of single cells to integrate multiple variables in a flexible way, allowing individual neurons to participate in different networks. In this review, we outline the most important features of mixed selectivity and we also present recent works demonstrating its presence in the associative areas of the posterior parietal cortex. Finally, in discussing these findings, we present some open questions that could be addressed by future studies.
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Affiliation(s)
| | - Stefano Diomedi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Matteo Filippini
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, Bologna, Italy
- *Correspondence: Patrizia Fattori
| | | | - Patrizia Fattori
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, Bologna, Italy
- Matteo Filippini
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87
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Miehl C, Onasch S, Festa D, Gjorgjieva J. Formation and computational implications of assemblies in neural circuits. J Physiol 2022. [PMID: 36068723 DOI: 10.1113/jp282750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 08/22/2022] [Indexed: 11/08/2022] Open
Abstract
In the brain, patterns of neural activity represent sensory information and store it in non-random synaptic connectivity. A prominent theoretical hypothesis states that assemblies, groups of neurons that are strongly connected to each other, are the key computational units underlying perception and memory formation. Compatible with these hypothesised assemblies, experiments have revealed groups of neurons that display synchronous activity, either spontaneously or upon stimulus presentation, and exhibit behavioural relevance. While it remains unclear how assemblies form in the brain, theoretical work has vastly contributed to the understanding of various interacting mechanisms in this process. Here, we review the recent theoretical literature on assembly formation by categorising the involved mechanisms into four components: synaptic plasticity, symmetry breaking, competition and stability. We highlight different approaches and assumptions behind assembly formation and discuss recent ideas of assemblies as the key computational unit in the brain. Abstract figure legend Assembly Formation. Assemblies are groups of strongly connected neurons formed by the interaction of multiple mechanisms and with vast computational implications. Four interacting components are thought to drive assembly formation: synaptic plasticity, symmetry breaking, competition and stability. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Christoph Miehl
- Computation in Neural Circuits, Max Planck Institute for Brain Research, 60438, Frankfurt, Germany.,School of Life Sciences, Technical University of Munich, 85354, Freising, Germany
| | - Sebastian Onasch
- Computation in Neural Circuits, Max Planck Institute for Brain Research, 60438, Frankfurt, Germany.,School of Life Sciences, Technical University of Munich, 85354, Freising, Germany
| | - Dylan Festa
- Computation in Neural Circuits, Max Planck Institute for Brain Research, 60438, Frankfurt, Germany.,School of Life Sciences, Technical University of Munich, 85354, Freising, Germany
| | - Julijana Gjorgjieva
- Computation in Neural Circuits, Max Planck Institute for Brain Research, 60438, Frankfurt, Germany.,School of Life Sciences, Technical University of Munich, 85354, Freising, Germany
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88
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Grienberger C, Giovannucci A, Zeiger W, Portera-Cailliau C. Two-photon calcium imaging of neuronal activity. NATURE REVIEWS. METHODS PRIMERS 2022; 2:67. [PMID: 38124998 PMCID: PMC10732251 DOI: 10.1038/s43586-022-00147-1] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/07/2022] [Indexed: 12/23/2023]
Abstract
In vivo two-photon calcium imaging (2PCI) is a technique used for recording neuronal activity in the intact brain. It is based on the principle that, when neurons fire action potentials, intracellular calcium levels rise, which can be detected using fluorescent molecules that bind to calcium. This Primer is designed for scientists who are considering embarking on experiments with 2PCI. We provide the reader with a background on the basic concepts behind calcium imaging and on the reasons why 2PCI is an increasingly powerful and versatile technique in neuroscience. The Primer explains the different steps involved in experiments with 2PCI, provides examples of what ideal preparations should look like and explains how data are analysed. We also discuss some of the current limitations of the technique, and the types of solutions to circumvent them. Finally, we conclude by anticipating what the future of 2PCI might look like, emphasizing some of the analysis pipelines that are being developed and international efforts for data sharing.
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Affiliation(s)
- Christine Grienberger
- Department of Biology and Volen National Center for Complex Systems, Brandeis University, Waltham, MA, USA
| | - Andrea Giovannucci
- Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - William Zeiger
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Carlos Portera-Cailliau
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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89
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Lara-González E, Padilla-Orozco M, Fuentes-Serrano A, Bargas J, Duhne M. Translational neuronal ensembles: Neuronal microcircuits in psychology, physiology, pharmacology and pathology. Front Syst Neurosci 2022; 16:979680. [PMID: 36090187 PMCID: PMC9449457 DOI: 10.3389/fnsys.2022.979680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 07/27/2022] [Indexed: 11/23/2022] Open
Abstract
Multi-recording techniques show evidence that neurons coordinate their firing forming ensembles and that brain networks are made by connections between ensembles. While “canonical” microcircuits are composed of interconnected principal neurons and interneurons, it is not clear how they participate in recorded neuronal ensembles: “groups of neurons that show spatiotemporal co-activation”. Understanding synapses and their plasticity has become complex, making hard to consider all details to fill the gap between cellular-synaptic and circuit levels. Therefore, two assumptions became necessary: First, whatever the nature of the synapses these may be simplified by “functional connections”. Second, whatever the mechanisms to achieve synaptic potentiation or depression, the resultant synaptic weights are relatively stable. Both assumptions have experimental basis cited in this review, and tools to analyze neuronal populations are being developed based on them. Microcircuitry processing followed with multi-recording techniques show temporal sequences of neuronal ensembles resembling computational routines. These sequences can be aligned with the steps of behavioral tasks and behavior can be modified upon their manipulation, supporting the hypothesis that they are memory traces. In vitro, recordings show that these temporal sequences can be contained in isolated tissue of histological scale. Sequences found in control conditions differ from those recorded in pathological tissue obtained from animal disease models and those recorded after the actions of clinically useful drugs to treat disease states, setting the basis for new bioassays to test drugs with potential clinical use. These findings make the neuronal ensembles theoretical framework a dynamic neuroscience paradigm.
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Affiliation(s)
- Esther Lara-González
- División Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Montserrat Padilla-Orozco
- División Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Alejandra Fuentes-Serrano
- División Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - José Bargas
- División Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
- *Correspondence: José Bargas,
| | - Mariana Duhne
- División Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, Mexico City, Mexico
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
- Mariana Duhne,
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90
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Ma S, Wu T, Chen X, Wang Y, Ma J, Chen H, Riaud A, Wan J, Xu Z, Chen L, Ren J, Zhang DW, Zhou P, Chai Y, Bao W. A 619-pixel machine vision enhancement chip based on two-dimensional semiconductors. SCIENCE ADVANCES 2022; 8:eabn9328. [PMID: 35921422 PMCID: PMC9348785 DOI: 10.1126/sciadv.abn9328] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 06/21/2022] [Indexed: 06/09/2023]
Abstract
The rapid development of machine vision applications demands hardware that can sense and process visual information in a single monolithic unit to avoid redundant data transfer. Here, we design and demonstrate a monolithic vision enhancement chip with light-sensing, memory, digital-to-analog conversion, and processing functions by implementing a 619-pixel with 8582 transistors and physical dimensions of 10 mm by 10 mm based on a wafer-scale two-dimensional (2D) monolayer molybdenum disulfide (MoS2). The light-sensing function with analog MoS2 transistor circuits offers low noise and high photosensitivity. Furthermore, we adopt a MoS2 analog processing circuit to dynamically adjust the photocurrent of individual imaging sensor, which yields a high dynamic light-sensing range greater than 90 decibels. The vision chip allows the applications for contrast enhancement and noise reduction of image processing. This large-scale monolithic chip based on 2D semiconductors shows multiple functions with light sensing, memory, and processing for artificial machine vision applications, exhibiting the potentials of 2D semiconductors for future electronics.
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Affiliation(s)
- Shunli Ma
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Tianxiang Wu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Xinyu Chen
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Yin Wang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Jingyi Ma
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Honglei Chen
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Antoine Riaud
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Jing Wan
- State Key Laboratory of ASIC and System, School of Information Science and Technology, Fudan University, Shanghai 200433, China
| | - Zihan Xu
- Shenzhen Sixcarbon Technology, 188 Jiangshi Road, Shenzhen 518106, China
| | - Lin Chen
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Junyan Ren
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - David Wei Zhang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Peng Zhou
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Yang Chai
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Wenzhong Bao
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
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91
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Liu J, Qi J, Chen X, Li Z, Hong B, Ma H, Li G, Shen L, Liu D, Kong Y, Zhai H, Xie Q, Han H, Yang Y. Fear memory-associated synaptic and mitochondrial changes revealed by deep learning-based processing of electron microscopy data. Cell Rep 2022; 40:111151. [PMID: 35926462 DOI: 10.1016/j.celrep.2022.111151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 05/20/2022] [Accepted: 07/11/2022] [Indexed: 11/03/2022] Open
Abstract
Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demanding but still highly informative. We thus developed a region-CNN-based deep learning method to identify, segment, and reconstruct synapses and mitochondria to explore the structural plasticity of synapses and mitochondria in the auditory cortex of mice subjected to fear conditioning. Upon reconstructing over 135,000 mitochondria and 160,000 synapses, we find that fear conditioning significantly increases the number of mitochondria but decreases their size and promotes formation of multi-contact synapses, comprising a single axonal bouton and multiple postsynaptic sites from different dendrites. Modeling indicates that such multi-contact configuration increases the information storage capacity of new synapses by over 50%. With high accuracy and speed in reconstruction, our method yields structural and functional insight into cellular plasticity associated with fear learning.
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Affiliation(s)
- Jing Liu
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, School of Future Technology, University of the Chinese Academy of Sciences, Beijing 101408, China
| | - Junqian Qi
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China; Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Xi Chen
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Zhenchen Li
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, School of Future Technology, University of the Chinese Academy of Sciences, Beijing 101408, China
| | - Bei Hong
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, School of Future Technology, University of the Chinese Academy of Sciences, Beijing 101408, China
| | - Hongtu Ma
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Guoqing Li
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Lijun Shen
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Danqian Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yu Kong
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Hao Zhai
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, School of Future Technology, University of the Chinese Academy of Sciences, Beijing 101408, China
| | - Qiwei Xie
- Research Base of Beijing Modern Manufacturing Development, Beijing University of Technology, Beijing 100124, China.
| | - Hua Han
- National Laboratory of Pattern Recognition, Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, School of Future Technology, University of the Chinese Academy of Sciences, Beijing 101408, China; Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Yang Yang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
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92
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Song S, Regan B, Ereifej ES, Chan ER, Capadona JR. Neuroinflammatory Gene Expression Analysis Reveals Pathways of Interest as Potential Targets to Improve the Recording Performance of Intracortical Microelectrodes. Cells 2022; 11:2348. [PMID: 35954192 PMCID: PMC9367362 DOI: 10.3390/cells11152348] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/22/2022] [Accepted: 07/26/2022] [Indexed: 02/04/2023] Open
Abstract
Intracortical microelectrodes are a critical component of brain-machine interface (BMI) systems. The recording performance of intracortical microelectrodes used for both basic neuroscience research and clinical applications of BMIs decreases over time, limiting the utility of the devices. The neuroinflammatory response to the microelectrode has been identified as a significant contributing factor to its performance. Traditionally, pathological assessment has been limited to a dozen or so known neuroinflammatory proteins, and only a few groups have begun to explore changes in gene expression following microelectrode implantation. Our initial characterization of gene expression profiles of the neuroinflammatory response to mice implanted with non-functional intracortical probes revealed many upregulated genes that could inform future therapeutic targets. Emphasis was placed on the most significant gene expression changes and genes involved in multiple innate immune sets, including Cd14, C3, Itgam, and Irak4. In previous studies, inhibition of Cluster of Differentiation 14 (Cd14) improved microelectrode performance for up to two weeks after electrode implantation, suggesting CD14 can be explored as a potential therapeutic target. However, all measures of improvements in signal quality and electrode performance lost statistical significance after two weeks. Therefore, the current study investigated the expression of genes in the neuroinflammatory pathway at the tissue-microelectrode interface in Cd14-/- mice to understand better how Cd14 inhibition was connected to temporary improvements in recording quality over the initial 2-weeks post-surgery, allowing for the identification of potential co-therapeutic targets that may work synergistically with or after CD14 inhibition to improve microelectrode performance.
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Affiliation(s)
- Sydney Song
- Department of Biomedical Engineering, Case Western Reserve University, 2071 Martin Luther King Jr. Drive, Cleveland, OH 44106, USA; (S.S.); (E.S.E.)
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, USA
| | - Brianna Regan
- Veteran Affairs Ann Arbor Healthcare System, Ann Arbor, MI 48105, USA;
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Evon S. Ereifej
- Department of Biomedical Engineering, Case Western Reserve University, 2071 Martin Luther King Jr. Drive, Cleveland, OH 44106, USA; (S.S.); (E.S.E.)
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, USA
- Veteran Affairs Ann Arbor Healthcare System, Ann Arbor, MI 48105, USA;
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA
| | - E. Ricky Chan
- Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, USA;
| | - Jeffrey R. Capadona
- Department of Biomedical Engineering, Case Western Reserve University, 2071 Martin Luther King Jr. Drive, Cleveland, OH 44106, USA; (S.S.); (E.S.E.)
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, USA
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93
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Hennig MH. The sloppy relationship between neural circuit structure and function. J Physiol 2022. [PMID: 35876720 DOI: 10.1113/jp282757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/20/2022] [Indexed: 11/08/2022] Open
Abstract
Investigating and describing the relationships between the structure of a circuit and its function has a long tradition in neuroscience. Since neural circuits acquire their structure through sophisticated developmental programmes, and memories and experiences are maintained through synaptic modification, it is to be expected that structure is closely linked to function. Recent findings challenge this hypothesis from three different angles: Function does not strongly constrain circuit parameters, many parameters in neural circuits are irrelevant and contribute little to function, and circuit parameters are unstable and subject to constant random drift. At the same time however, recent work also showed that dynamics in neural circuit activity that is related to function are robust over time and across individuals. Here this apparent contradiction is addressed by considering the properties of neural manifolds that restrict circuit activity to functionally relevant subspaces, and it will be suggested that degenerate, anisotropic and unstable parameter spaces are a closely related to the structure and implementation of functionally relevant neural manifolds. Abstract figure legend What are the relationships between noisy and highly variable microscopic neural circuit variables on the one hand and the generation of behaviour on the other? Here it is proposed that an intermediate level of description exists where this relationship can be understood in terms of low-dimensional dynamics. Recordings of neural activity during unconstrained behaviour and the development of new machine learning methods will help to uncover these links. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Matthias H Hennig
- Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh
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94
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Dard RF, Leprince E, Denis J, Rao Balappa S, Suchkov D, Boyce R, Lopez C, Giorgi-Kurz M, Szwagier T, Dumont T, Rouault H, Minlebaev M, Baude A, Cossart R, Picardo MA. The rapid developmental rise of somatic inhibition disengages hippocampal dynamics from self-motion. eLife 2022; 11:e78116. [PMID: 35856497 PMCID: PMC9363116 DOI: 10.7554/elife.78116] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 07/19/2022] [Indexed: 11/25/2022] Open
Abstract
Early electrophysiological brain oscillations recorded in preterm babies and newborn rodents are initially mostly driven by bottom-up sensorimotor activity and only later can detach from external inputs. This is a hallmark of most developing brain areas, including the hippocampus, which, in the adult brain, functions in integrating external inputs onto internal dynamics. Such developmental disengagement from external inputs is likely a fundamental step for the proper development of cognitive internal models. Despite its importance, the developmental timeline and circuit basis for this disengagement remain unknown. To address this issue, we have investigated the daily evolution of CA1 dynamics and underlying circuits during the first two postnatal weeks of mouse development using two-photon calcium imaging in non-anesthetized pups. We show that the first postnatal week ends with an abrupt shift in the representation of self-motion in CA1. Indeed, most CA1 pyramidal cells switch from activated to inhibited by self-generated movements at the end of the first postnatal week, whereas the majority of GABAergic neurons remain positively modulated throughout this period. This rapid switch occurs within 2 days and follows the rapid anatomical and functional surge of local somatic GABAergic innervation. The observed change in dynamics is consistent with a two-population model undergoing a strengthening of inhibition. We propose that this abrupt developmental transition inaugurates the emergence of internal hippocampal dynamics.
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Affiliation(s)
- Robin F Dard
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Erwan Leprince
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Julien Denis
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Shrisha Rao Balappa
- Turing Centre for Living systems, Aix-Marseille University, Université de Toulon, CNRS, CPT (UMR 7332)MarseilleFrance
| | - Dmitrii Suchkov
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Richard Boyce
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Catherine Lopez
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Marie Giorgi-Kurz
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Tom Szwagier
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
- Mines ParisTech, PSL Research UniversityParisFrance
| | - Théo Dumont
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
- Mines ParisTech, PSL Research UniversityParisFrance
| | - Hervé Rouault
- Turing Centre for Living systems, Aix-Marseille University, Université de Toulon, CNRS, CPT (UMR 7332)MarseilleFrance
| | - Marat Minlebaev
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Agnès Baude
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Rosa Cossart
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
| | - Michel A Picardo
- Turing Centre for Living systems, Aix-Marseille University, INSERM, INMED U1249MarseilleFrance
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95
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Rojvirat CP, Berlin JR, Nguyen TD. Evaluating spatial and network properties of NMDA-dependent neuronal connectivity in mixed cortical cultures. Brain Res 2022; 1787:147919. [PMID: 35436447 DOI: 10.1016/j.brainres.2022.147919] [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: 01/17/2022] [Revised: 04/08/2022] [Accepted: 04/11/2022] [Indexed: 11/24/2022]
Abstract
A technique combining fluorescence imaging with Ca2+ indicators and single-cell laser scanning photostimulation of caged glutamate (LSPS) allowed identification of functional connections between individual neurons in mixed cultures of rat neocortical cells as well as observation of synchronous spontaneous activity among neurons. LSPS performed on large numbers of neurons yielded maps of functional connections between neurons and allowed calculation of neuronal network parameters. LSPS also provided an indirect measure of excitability of neurons targeted for photostimulation. By repeating LSPS sessions with the same neurons, stability of connections and change in the number and strength of connections were also determined. Experiments were conducted in the presence of bicuculline to study in detail the properties of excitatory neurotransmission. The AMPA receptor inhibitor, 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX), abolished synchronous neuronal activity but had no effect on connections mapped by LSPS. In contrast, the NMDA receptor inhibitor, 2-Amino-5-phosphono-pentanoic acid (APV), dramatically decreased the number of functional connections between neurons while also affecting synchronous spontaneous activity. Functional connections were also decreased by increasing extracellular Mg2+ concentration. These data demonstrated that LSPS mapping interrogates NMDA receptor-dependent connectivity between neurons in the network. In addition, a GluN2A-specific inhibitor, NVP-AAM077, decreased the number and strength of connections between neurons as well as neuron excitability. Conversely, the GluN2A-specific positive modulator, GNE-0723, increased these same properties. These data showed that LSPS can be used to directly study perturbations in the properties of NMDA receptor-dependent connectivity in neuronal networks. This approach should be applicable in a wide variety of in vitro and in vivo experimental preparations.
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Affiliation(s)
- Catherine P Rojvirat
- Department of Pharmacology, Physiology and Neuroscience, New Jersey Medical School, Rutgers University, 185 South Orange Avenue, Newark, NJ 07101-1709, United States; School of Graduate Studies, Rutgers Biomedical and Health Sciences Campus-Newark, Rutgers University, 185 South Orange Avenue, Newark, NJ 07101-1709, United States.
| | - Joshua R Berlin
- Department of Pharmacology, Physiology and Neuroscience, New Jersey Medical School, Rutgers University, 185 South Orange Avenue, Newark, NJ 07101-1709, United States.
| | - Tuan D Nguyen
- Department of Physics, The College of New Jersey, 2000 Pennington Rd., Ewing, NJ 08628, United States.
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96
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Avitan L, Stringer C. Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas. Neuron 2022; 110:3064-3075. [PMID: 35863344 DOI: 10.1016/j.neuron.2022.06.019] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 06/20/2022] [Accepted: 06/22/2022] [Indexed: 11/27/2022]
Abstract
Sensory areas are spontaneously active in the absence of sensory stimuli. This spontaneous activity has long been studied; however, its functional role remains largely unknown. Recent advances in technology, allowing large-scale neural recordings in the awake and behaving animal, have transformed our understanding of spontaneous activity. Studies using these recordings have discovered high-dimensional spontaneous activity patterns, correlation between spontaneous activity and behavior, and dissimilarity between spontaneous and sensory-driven activity patterns. These findings are supported by evidence from developing animals, where a transition toward these characteristics is observed as the circuit matures, as well as by evidence from mature animals across species. These newly revealed characteristics call for the formulation of a new role for spontaneous activity in neural sensory computation.
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Affiliation(s)
- Lilach Avitan
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
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97
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Varley TF, Hoel E. Emergence as the conversion of information: a unifying theory. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2022; 380:20210150. [PMID: 35599561 PMCID: PMC9131462 DOI: 10.1098/rsta.2021.0150] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/24/2021] [Indexed: 05/25/2023]
Abstract
Is reduction always a good scientific strategy? The existence of the special sciences above physics suggests not. Previous research has shown that dimensionality reduction (macroscales) can increase the dependency between elements of a system (a phenomenon called 'causal emergence'). Here, we provide an umbrella mathematical framework for emergence based on information conversion. We show evidence that coarse-graining can convert information from one 'type' to another. We demonstrate this using the well-understood mutual information measure applied to Boolean networks. Using partial information decomposition, the mutual information can be decomposed into redundant, unique and synergistic information atoms. Then by introducing a novel measure of the synergy bias of a given decomposition, we are able to show that the synergy component of a Boolean network's mutual information can increase at macroscales. This can occur even when there is no difference in the total mutual information between a macroscale and its underlying microscale, proving information conversion. We relate this broad framework to previous work, compare it to other theories, and argue it complexifies any notion of universal reduction in the sciences, since such reduction would likely lead to a loss of synergistic information in scientific models. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.
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Affiliation(s)
- Thomas F. Varley
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA
| | - Erik Hoel
- Allen Discovery Center, Tufts University, Medford, MA, USA
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98
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Herry C, Jercog D. Decoding defensive systems. Curr Opin Neurobiol 2022; 76:102600. [PMID: 35809501 DOI: 10.1016/j.conb.2022.102600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/21/2022] [Accepted: 05/30/2022] [Indexed: 11/26/2022]
Abstract
Our understanding of the neuronal circuits and mechanisms of defensive systems has been primarily dominated by studies focusing on the contribution of individual cells in the processing of threat-predictive cues, defensive responses, the extinction of such responses and the contextual modulation of threat-related behavior. These studies have been key in establishing threat-related circuits and mechanisms. Yet, they fall short in answering long-standing questions related to the integrative processing of distinct threatening cues, behavioral states induced by threat-related events, or the bridging from sensory processing of threat-related cues to specific defensive responses. Recent conceptual and technical developments has allowed the monitoring of large populations of neurons, which in addition to advanced analytic tools, have improved our understanding of how collective neuronal activity supports threat-related behaviors. In this review, we discuss the current knowledge of neuronal population codes within threat-related networks, in the context of aversive motivated behavior and the study of defensive systems.
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Affiliation(s)
- Cyril Herry
- INSERM, Neurocentre Magendie, U1215, 146 Rue Léo-Saignat, 33077 Bordeaux, France; Univ. Bordeaux, Neurocentre Magendie, U1215, 146 Rue Léo-Saignat, 33077 Bordeaux, France.
| | - Daniel Jercog
- INSERM, Neurocentre Magendie, U1215, 146 Rue Léo-Saignat, 33077 Bordeaux, France; Univ. Bordeaux, Neurocentre Magendie, U1215, 146 Rue Léo-Saignat, 33077 Bordeaux, France.
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99
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Rabadan MA, De La Cruz ED, Rao SB, Chen Y, Gong C, Crabtree G, Xu B, Markx S, Gogos JA, Yuste R, Tomer R. An in vitro model of neuronal ensembles. Nat Commun 2022; 13:3340. [PMID: 35680927 PMCID: PMC9184643 DOI: 10.1038/s41467-022-31073-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 06/01/2022] [Indexed: 11/28/2022] Open
Abstract
Advances in 3D neuronal cultures, such as brain spheroids and organoids, are allowing unprecedented in vitro access to some of the molecular, cellular and developmental mechanisms underlying brain diseases. However, their efficacy in recapitulating brain network properties that encode brain function remains limited, thereby precluding development of effective in vitro models of complex brain disorders like schizophrenia. Here, we develop and characterize a Modular Neuronal Network (MoNNet) approach that recapitulates specific features of neuronal ensemble dynamics, segregated local-global network activities and a hierarchical modular organization. We utilized MoNNets for quantitative in vitro modelling of schizophrenia-related network dysfunctions caused by highly penetrant mutations in SETD1A and 22q11.2 risk loci. Furthermore, we demonstrate its utility for drug discovery by performing pharmacological rescue of alterations in neuronal ensembles stability and global network synchrony. MoNNets allow in vitro modelling of brain diseases for investigating the underlying neuronal network mechanisms and systematic drug discovery.
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Affiliation(s)
- M Angeles Rabadan
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | | | - Sneha B Rao
- Mortimer B. Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
| | - Yannan Chen
- Department of Biological Sciences, Columbia University, New York, NY, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Cheng Gong
- Department of Biological Sciences, Columbia University, New York, NY, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Gregg Crabtree
- Mortimer B. Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
| | - Bin Xu
- Department of Psychiatry, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Sander Markx
- Department of Psychiatry, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Joseph A Gogos
- Mortimer B. Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
- Department of Physiology, Columbia University, New York, NY, USA
- Department of Neuroscience, Columbia University, New York, NY, USA
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Rafael Yuste
- Department of Biological Sciences, Columbia University, New York, NY, USA
- NeuroTechnology Center, Columbia University, New York, NY, USA
| | - Raju Tomer
- Department of Biological Sciences, Columbia University, New York, NY, USA.
- Mortimer B. Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA.
- Department of Biomedical Engineering, Columbia University, New York, NY, USA.
- NeuroTechnology Center, Columbia University, New York, NY, USA.
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100
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Abstract
Voluntary attention selects behaviorally relevant signals for further processing while filtering out distracter signals. Neural correlates of voluntary visual attention have been reported across multiple areas of the primate visual processing streams, with the earliest and strongest effects isolated in the prefrontal cortex. In this article, I review evidence supporting the hypothesis that signals guiding the allocation of voluntary attention emerge in areas of the prefrontal cortex and reach upstream areas to modulate the processing of incoming visual information according to its behavioral relevance. Areas located anterior and dorsal to the arcuate sulcus and the frontal eye fields produce signals that guide the allocation of spatial attention. Areas located anterior and ventral to the arcuate sulcus produce signals for feature-based attention. Prefrontal microcircuits are particularly suited to supporting voluntary attention because of their ability to generate attentional template signals and implement signal gating and their extensive connectivity with the rest of the brain. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Julio Martinez-Trujillo
- Department of Physiology, Pharmacology and Psychiatry, Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada;
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