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Martin-Burgos B, McPherson TS, Hammonds R, Gao R, Muotri AR, Voytek B. Development of neuronal timescales in human cortical organoids and rat hippocampus dissociated cultures. J Neurophysiol 2024; 132:757-764. [PMID: 39015071 PMCID: PMC11427036 DOI: 10.1152/jn.00135.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/04/2024] [Accepted: 06/24/2024] [Indexed: 07/18/2024] Open
Abstract
To support complex cognition, neuronal circuits must integrate information across multiple temporal scales, ranging from milliseconds to decades. Neuronal timescales describe the duration over which activity within a network persists, posing a putative explanatory mechanism for how information might be integrated over multiple temporal scales. Little is known about how timescales develop in human neural circuits or other model systems, limiting insight into how the functional dynamics necessary for cognition emerge. In our work, we show that neuronal timescales develop in a nonlinear fashion in human cortical organoids, which is partially replicated in dissociated rat hippocampus cultures. We use spectral parameterization of spiking activity to extract an estimate of neuronal timescale that is unbiased by coevolving oscillations. Cortical organoid timescales begin to increase around month 6 postdifferentiation. In rodent hippocampal dissociated cultures, we see that timescales decrease from in vitro days 13-23 before stabilizing. We speculate that cortical organoid development over the duration studied here reflects an earlier stage of a generalized developmental timeline in contrast to the rodent hippocampal cultures, potentially accounting for differences in timescale developmental trajectories. The fluctuation of timescales might be an important developmental feature that reflects the changing complexity and information capacity in developing neuronal circuits.NEW & NOTEWORTHY Neuronal timescales describe the persistence of activity within a network of neurons. Timescales were found to fluctuate with development in two model systems. In cortical organoids timescales increased, peaked, and then decreased throughout development; in rat hippocampal dissociated cultures timescales decreased over development. These distinct developmental models overlap to highlight a critical window in which timescales lengthen and contract, potentially indexing changes in the information capacity of neuronal systems.
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Affiliation(s)
- Blanca Martin-Burgos
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California, United States
| | - Trevor Supan McPherson
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California, United States
| | - Ryan Hammonds
- Department of Cognitive Science, University of California, San Diego, La Jolla, California, United States
- Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, California, United States
| | - Richard Gao
- Department of Cognitive Science, University of California, San Diego, La Jolla, California, United States
| | - Alysson R Muotri
- Department of Pediatrics/Rady Children's Hospital San Diego, School of Medicine, University of California, San Diego, La Jolla, California, United States
- Department of Cellular & Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, California, United States
| | - Bradley Voytek
- Department of Cognitive Science, University of California, San Diego, La Jolla, California, United States
- Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, California, United States
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California, United States
- Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, California, United States
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2
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Le Belle JE, Condro M, Cepeda C, Oikonomou KD, Tessema K, Dudley L, Schoenfield J, Kawaguchi R, Geschwind D, Silva AJ, Zhang Z, Shokat K, Harris NG, Kornblum HI. Acute rapamycin treatment reveals novel mechanisms of behavioral, physiological, and functional dysfunction in a maternal inflammation mouse model of autism and sensory over-responsivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.08.602602. [PMID: 39026891 PMCID: PMC11257517 DOI: 10.1101/2024.07.08.602602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Maternal inflammatory response (MIR) during early gestation in mice induces a cascade of physiological and behavioral changes that have been associated with autism spectrum disorder (ASD). In a prior study and the current one, we find that mild MIR results in chronic systemic and neuro-inflammation, mTOR pathway activation, mild brain overgrowth followed by regionally specific volumetric changes, sensory processing dysregulation, and social and repetitive behavior abnormalities. Prior studies of rapamycin treatment in autism models have focused on chronic treatments that might be expected to alter or prevent physical brain changes. Here, we have focused on the acute effects of rapamycin to uncover novel mechanisms of dysfunction and related to mTOR pathway signaling. We find that within 2 hours, rapamycin treatment could rapidly rescue neuronal hyper-excitability, seizure susceptibility, functional network connectivity and brain community structure, and repetitive behaviors and sensory over-responsivity in adult offspring with persistent brain overgrowth. These CNS-mediated effects are also associated with alteration of the expression of several ASD-,ion channel-, and epilepsy-associated genes, in the same time frame. Our findings suggest that mTOR dysregulation in MIR offspring is a key contributor to various levels of brain dysfunction, including neuronal excitability, altered gene expression in multiple cell types, sensory functional network connectivity, and modulation of information flow. However, we demonstrate that the adult MIR brain is also amenable to rapid normalization of these functional changes which results in the rescue of both core and comorbid ASD behaviors in adult animals without requiring long-term physical alterations to the brain. Thus, restoring excitatory/inhibitory imbalance and sensory functional network modularity may be important targets for therapeutically addressing both primary sensory and social behavior phenotypes, and compensatory repetitive behavior phenotypes.
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3
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Fitz H, Hagoort P, Petersson KM. Neurobiological Causal Models of Language Processing. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:225-247. [PMID: 38645618 PMCID: PMC11025648 DOI: 10.1162/nol_a_00133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 12/18/2023] [Indexed: 04/23/2024]
Abstract
The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap. A neurobiological causal model is a mechanistic description of language processing that is grounded in, and constrained by, the characteristics of the neurobiological substrate. It intends to model the generators of language behavior at the level of implementational causality. We describe key features and neurobiological component parts from which causal models can be built and provide guidelines on how to implement them in model simulations. Then we outline how this approach can shed new light on the core computational machinery for language, the long-term storage of words in the mental lexicon and combinatorial processing in sentence comprehension. In contrast to cognitive theories of behavior, causal models are formulated in the "machine language" of neurobiology which is universal to human cognition. We argue that neurobiological causal modeling should be pursued in addition to existing approaches. Eventually, this approach will allow us to develop an explicit computational neurobiology of language.
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Affiliation(s)
- Hartmut Fitz
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Neurobiology of Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Peter Hagoort
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Neurobiology of Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Karl Magnus Petersson
- Neurobiology of Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Faculty of Medicine and Biomedical Sciences, University of Algarve, Faro, Portugal
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4
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Yiling Y, Shapcott K, Peter A, Klon-Lipok J, Xuhui H, Lazar A, Singer W. Robust encoding of natural stimuli by neuronal response sequences in monkey visual cortex. Nat Commun 2023; 14:3021. [PMID: 37231014 DOI: 10.1038/s41467-023-38587-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 05/08/2023] [Indexed: 05/27/2023] Open
Abstract
Parallel multisite recordings in the visual cortex of trained monkeys revealed that the responses of spatially distributed neurons to natural scenes are ordered in sequences. The rank order of these sequences is stimulus-specific and maintained even if the absolute timing of the responses is modified by manipulating stimulus parameters. The stimulus specificity of these sequences was highest when they were evoked by natural stimuli and deteriorated for stimulus versions in which certain statistical regularities were removed. This suggests that the response sequences result from a matching operation between sensory evidence and priors stored in the cortical network. Decoders trained on sequence order performed as well as decoders trained on rate vectors but the former could decode stimulus identity from considerably shorter response intervals than the latter. A simulated recurrent network reproduced similarly structured stimulus-specific response sequences, particularly once it was familiarized with the stimuli through non-supervised Hebbian learning. We propose that recurrent processing transforms signals from stationary visual scenes into sequential responses whose rank order is the result of a Bayesian matching operation. If this temporal code were used by the visual system it would allow for ultrafast processing of visual scenes.
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Affiliation(s)
- Yang Yiling
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- International Max Planck Research School (IMPRS) for Neural Circuits, 60438, Frankfurt am Main, Germany
- Faculty of Biological Sciences, Goethe-University Frankfurt am Main, 60438, Frankfurt am Main, Germany
| | - Katharine Shapcott
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
| | - Alina Peter
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- International Max Planck Research School (IMPRS) for Neural Circuits, 60438, Frankfurt am Main, Germany
- Faculty of Biological Sciences, Goethe-University Frankfurt am Main, 60438, Frankfurt am Main, Germany
| | - Johanna Klon-Lipok
- Max Planck Institute for Brain Research, 60438, Frankfurt am Main, Germany
| | - Huang Xuhui
- Intelligent Science and Technology Academy, China Aerospace Science and Industry Corporation (CASIC), 100144, Beijing, China
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
| | - Andreea Lazar
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
| | - Wolf Singer
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany.
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany.
- Max Planck Institute for Brain Research, 60438, Frankfurt am Main, Germany.
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5
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Liu J, Chen D, Xiao X, Zhang H, Zhou W, Liang S, Kunz L, Schulze-Bonhage A, Axmacher N, Wang L. Multi-scale goal distance representations in human hippocampus during virtual spatial navigation. Curr Biol 2023; 33:2024-2033.e3. [PMID: 37148875 DOI: 10.1016/j.cub.2023.04.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/17/2023] [Accepted: 04/14/2023] [Indexed: 05/08/2023]
Abstract
Goal-directed navigation relies on both coarse and fine-grained coding of spatial distance between the current position of a navigating subject and a goal destination. However, the neural signatures underlying goal distance coding remain poorly understood. Using intracranial EEG recordings from the hippocampus of drug-resistant epilepsy patients who performed a virtual spatial navigation task, we found that the right hippocampal theta power was significantly modulated by goal distance and decreased with goal proximity. This modulation varied along the hippocampal longitudinal axis such that theta power in the posterior hippocampus decreased more strongly with goal proximity. Similarly, neural timescale, reflecting the duration across which information can be maintained, increased gradually from the posterior to anterior hippocampus. Taken together, this study provides empirical evidence for multi-scale spatial representations of goal distance in the human hippocampus and links the hippocampal processing of spatial information to its intrinsic temporal dynamics.
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Affiliation(s)
- Jiali Liu
- CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Rd, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, 1 Yanqihu East Rd, Beijing 101408, China
| | - Dong Chen
- CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Rd, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, 1 Yanqihu East Rd, Beijing 101408, China
| | - Xue Xiao
- CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Rd, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, 1 Yanqihu East Rd, Beijing 101408, China
| | - Hui Zhang
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, Bochum 44801, Germany
| | - Wenjing Zhou
- Department of Epilepsy Center, Tsinghua University Yuquan Hospital, 5 Shijingshan Rd, Beijing 100040, China
| | - Shuli Liang
- Functional Neurosurgery Department, Beijing Children's Hospital, Capital Medical University, 56 Nanlishi Rd, Beijing 100045, China
| | - Lukas Kunz
- Department of Biomedical Engineering, Columbia University, 1210 Amsterdam Ave, New York, NY 10027, USA
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Str. 64, Freiburg im Breisgau 79106, Germany
| | - Nikolai Axmacher
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, Bochum 44801, Germany
| | - Liang Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, 16 Lincui Rd, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, 1 Yanqihu East Rd, Beijing 101408, China.
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6
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Zeraati R, Shi YL, Steinmetz NA, Gieselmann MA, Thiele A, Moore T, Levina A, Engel TA. Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity. Nat Commun 2023; 14:1858. [PMID: 37012299 PMCID: PMC10070246 DOI: 10.1038/s41467-023-37613-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 03/24/2023] [Indexed: 04/05/2023] Open
Abstract
Intrinsic timescales characterize dynamics of endogenous fluctuations in neural activity. Variation of intrinsic timescales across the neocortex reflects functional specialization of cortical areas, but less is known about how intrinsic timescales change during cognitive tasks. We measured intrinsic timescales of local spiking activity within columns of area V4 in male monkeys performing spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales, fast and slow. The slow timescale increased when monkeys attended to the receptive fields location and correlated with reaction times. By evaluating predictions of several network models, we found that spatiotemporal correlations in V4 activity were best explained by the model in which multiple timescales arise from recurrent interactions shaped by spatially arranged connectivity, and attentional modulation of timescales results from an increase in the efficacy of recurrent interactions. Our results suggest that multiple timescales may arise from the spatial connectivity in the visual cortex and flexibly change with the cognitive state due to dynamic effective interactions between neurons.
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Affiliation(s)
- Roxana Zeraati
- International Max Planck Research School for the Mechanisms of Mental Function and Dysfunction, University of Tübingen, Tübingen, Germany
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Yan-Liang Shi
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | - Marc A Gieselmann
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Alexander Thiele
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Tirin Moore
- Department of Neurobiology and Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Anna Levina
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
- Department of Computer Science, University of Tübingen, Tübingen, Germany.
- Bernstein Center for Computational Neuroscience Tübingen, Tübingen, Germany.
| | - Tatiana A Engel
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
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7
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Pinto L, Tank DW, Brody CD. Multiple timescales of sensory-evidence accumulation across the dorsal cortex. eLife 2022; 11:e70263. [PMID: 35708483 PMCID: PMC9203055 DOI: 10.7554/elife.70263] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
Cortical areas seem to form a hierarchy of intrinsic timescales, but the relevance of this organization for cognitive behavior remains unknown. In particular, decisions requiring the gradual accrual of sensory evidence over time recruit widespread areas across this hierarchy. Here, we tested the hypothesis that this recruitment is related to the intrinsic integration timescales of these widespread areas. We trained mice to accumulate evidence over seconds while navigating in virtual reality and optogenetically silenced the activity of many cortical areas during different brief trial epochs. We found that the inactivation of all tested areas affected the evidence-accumulation computation. Specifically, we observed distinct changes in the weighting of sensory evidence occurring during and before silencing, such that frontal inactivations led to stronger deficits on long timescales than posterior cortical ones. Inactivation of a subset of frontal areas also led to moderate effects on behavioral processes beyond evidence accumulation. Moreover, large-scale cortical Ca2+ activity during task performance displayed different temporal integration windows. Our findings suggest that the intrinsic timescale hierarchy of distributed cortical areas is an important component of evidence-accumulation mechanisms.
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Affiliation(s)
- Lucas Pinto
- Department of Neuroscience, Northwestern UniversityChicagoUnited States
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - David W Tank
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton UniversityPrincetonUnited States
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8
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Heo JS, Kim EK, Kim SY, Song IG, Yoon YM, Cho H, Lee ES, Shin SH, Oh BM, Shin HI, Kim HS. Direct swallowing training and oral sensorimotor stimulation in preterm infants: a randomised controlled trial. Arch Dis Child Fetal Neonatal Ed 2022; 107:166-173. [PMID: 34281934 DOI: 10.1136/archdischild-2021-321945] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 06/21/2021] [Indexed: 12/26/2022]
Abstract
OBJECTIVE To evaluate the effects of direct swallowing training (DST) alone and combined with oral sensorimotor stimulation (OSMS) on oral feeding ability in very preterm infants. DESIGN Blinded, parallel group, randomised controlled trial (1:1:1). SETTING Neonatal intensive care unit of a South Korean tertiary hospital. PARTICIPANTS Preterm infants born at <32 weeks of gestation who achieved full tube feeding. INTERVENTIONS Two sessions per day were provided according to the randomly assigned groups (control: two times per day sham intervention; DST: DST and sham interventions, each once a day; DST+OSMS: DST and OSMS interventions, each once a day). PRIMARY OUTCOME Time from start to independent oral feeding (IOF). RESULTS Analyses were conducted in 186 participants based on modified intention-to-treat (63 control; 63 DST; 60 DST+OSMS). The mean time from start to IOF differed significantly between the control, DST and DST+OSMS groups (21.1, 17.2 and 14.8 days, respectively, p=0.02). Compared with non-intervention, DST+OSMS significantly shortened the time from start to IOF (effect size: -0.49; 95% CI: -0.86 to -0.14; p=0.02), whereas DST did not. The proportion of feeding volume taken during the initial 5 min, an index of infants' actual feeding ability when fatigue is minimal, increased earlier in the DST+OSMS than in the DST. CONCLUSIONS In very preterm infants, DST+OSMS led to the accelerated attainment of IOF compared with non-intervention, whereas DST alone did not. The effect of DST+OSMS on oral feeding ability appeared earlier than that of DST alone. TRIAL REGISTRATION NUMBER ClinicalTrials.gov Registry (NCT02508571).
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Affiliation(s)
- Ju Sun Heo
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of).,Department of Paediatrics, Korea University Anam Hospital, Seoul, Korea (the Republic of)
| | - Ee-Kyung Kim
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of)
| | - Sae Yun Kim
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of).,Department of Paediatrics, Catholic University of Korea Yeouido Saint Mary's Hospital, Seoul, Korea (the Republic of)
| | - In Gyu Song
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of).,Department of Paediatrics, Korea University Guro Hospital, Seoul, Korea (the Republic of)
| | - Young Mi Yoon
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of).,Department of Paediatrics, Jeju National University Hospital, Jeju, Korea (the Republic of)
| | - Hannah Cho
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of).,Department of Paediatrics, Korea University Anam Hospital, Seoul, Korea (the Republic of)
| | - Eun Sun Lee
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of).,Department of Paediatrics, Chung-Ang University Hospital, Seoul, Korea (the Republic of)
| | - Seung Han Shin
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of)
| | - Byung-Mo Oh
- Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, Korea (the Republic of).,Department of Rehabilitation Medicine, National Traffic Injury Rehabilitation Hospital, Yangpyeong, Korea (the Republic of).,Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea (the Republic of)
| | - Hyung-Ik Shin
- Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, Korea (the Republic of).,Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea (the Republic of)
| | - Han-Suk Kim
- Department of Paediatrics, Seoul National University College of Medicine, Seoul, Korea (the Republic of)
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9
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Barbero-Castillo A, Mateos-Aparicio P, Dalla Porta L, Camassa A, Perez-Mendez L, Sanchez-Vives MV. Impact of GABA A and GABA B Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States. J Neurosci 2021; 41:5029-5044. [PMID: 33906901 PMCID: PMC8197642 DOI: 10.1523/jneurosci.1837-20.2021] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 03/20/2021] [Accepted: 04/01/2021] [Indexed: 11/21/2022] Open
Abstract
Quantitative estimations of spatiotemporal complexity of cortical activity patterns are used in the clinic as a measure of consciousness levels, but the cortical mechanisms involved are not fully understood. We used a version of the perturbational complexity index (PCI) adapted to multisite recordings from the ferret (either sex) cerebral cortex in vitro (sPCI) to investigate the role of GABAergic inhibition in cortical complexity. We studied two dynamical states: slow-wave activity (synchronous state) and desynchronized activity, that express low and high causal complexity respectively. Progressive blockade of GABAergic inhibition during both regimes revealed its impact on the emergent cortical activity and on sPCI. Gradual GABAA receptor blockade resulted in higher synchronization, being able to drive the network from a desynchronized to a synchronous state, with a progressive decrease of complexity (sPCI). Blocking GABAB receptors also resulted in a reduced sPCI, in particular when in a synchronous, slow wave state. Our findings demonstrate that physiological levels of inhibition contribute to the generation of dynamical richness and spatiotemporal complexity. However, if inhibition is diminished or enhanced, cortical complexity decreases. Using a computational model, we explored a larger parameter space in this relationship and demonstrate a link between excitatory/inhibitory balance and the complexity expressed by the cortical network.SIGNIFICANCE STATEMENT The spatiotemporal complexity of the activity expressed by the cerebral cortex is a highly revealing feature of the underlying network's state. Complexity varies with physiological brain states: it is higher during awake than during sleep states. But it also informs about pathologic states: in disorders of consciousness, complexity is lower in an unresponsive wakefulness syndrome than in a minimally conscious state. What are the network parameters that modulate complexity? Here we investigate how inhibition, mediated by either GABAA or GABAA receptors, influences cortical complexity. And we do this departing from two extreme functional states: a highly synchronous, slow-wave state, and a desynchronized one that mimics wakefulness. We find that there is an optimal level of inhibition in which complexity is highest.
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Affiliation(s)
- Almudena Barbero-Castillo
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Pedro Mateos-Aparicio
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Leonardo Dalla Porta
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Alessandra Camassa
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Lorena Perez-Mendez
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
| | - Maria V Sanchez-Vives
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 08036
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain 08010
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10
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Pickler RH, Meinzen-Derr J, Moore M, Sealschott S, Tepe K. Effect of Tactile Experience During Preterm Infant Feeding on Clinical Outcomes. Nurs Res 2021; 69:S21-S28. [PMID: 32555011 PMCID: PMC7483367 DOI: 10.1097/nnr.0000000000000453] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Although the survival rate of very preterm infants has improved, rates of subsequent neurobehavioral disabilities remain high. One factor implicated in poor neurobehavioral and developmental outcomes is hospitalization and inconsistent caregiving patterns in the neonatal intensive care unit. Although much underlying brain damage occurs in utero or shortly after birth, neuroprotective strategies may stop progression of damage, particularly when these strategies are used during the most sensitive periods of neural plasticity 2-3 months before term age. OBJECTIVE The purpose of this analysis was to test the effect of a patterned feeding experience involving a tactile component (touch and/or holding) provided during feedings on preterm infants' clinical outcomes, measured by oral feeding progress, as an early indicator of neurodevelopment. METHODS We used an experimental, longitudinal, two-group random assignment design. Preterm infants (n = 120) were enrolled within the first week of life and randomized to an experimental group receiving a patterned feeding experience or to a control group receiving usual feeding care. RESULTS Analysis of data from 91 infants showed that infants receiving touch at more than 25% of early gavage feedings achieved full oral feeding more quickly; as touch exposure increased, time from first oral to full oral feeding decreased. There was no association between holding during early gavage feedings or touch during transition feedings and time to full oral feeding. DISCUSSION Neurological expectation during critical periods of development is important for infants. However, a preterm infant's environment is not predictable: Caregivers change regularly, medical procedures dictate touch and holding, and care provision based on infant cues is limited. Current knowledge supports caregiving that occurs with a naturally occurring sensation (i.e., hunger), is provided in a manner that is congruent with the expectation of the neurological system, and occurs with enough regularity to enhance neuronal and synaptic development. In this study, we modeled an experience infants would "expect" if they were not in the neonatal intensive care unit and demonstrated a shorter time from first oral feeding to full oral feeding, an important clinical outcome with neurodevelopmental implications. We recommend further research to determine the effect of patterned caregiving experiences on other areas of neurodevelopment, particularly those that may occur later in life.
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Affiliation(s)
- Rita H Pickler
- Rita H. Pickler, PhD, RN, FAAN, is FloAnn Sours Easton Professor of Child and Adolescent Health, College of Nursing, The Ohio State University, Columbus. Jareen Meinzen-Derr, PhD, MPH, is Professor, Department of Pediatrics, University of Cincinnati College of Medicine, and Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Ohio. Margo Moore, MS, RN, is Research Nurse III, Division of Infectious Disease, Cincinnati Children's Hospital Medical Center, Ohio. Stephanie Sealschott, MS, RN, is PhD Candidate, College of Nursing, The Ohio State University, Columbus. Karin Tepe, BS, RN, is Research Nurse in Neonatology, Cincinnati Children's Hospital Medical Center, Ohio
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11
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Berberian N, Ross M, Chartier S. Embodied working memory during ongoing input streams. PLoS One 2021; 16:e0244822. [PMID: 33400724 PMCID: PMC7785253 DOI: 10.1371/journal.pone.0244822] [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: 06/18/2020] [Accepted: 12/16/2020] [Indexed: 11/18/2022] Open
Abstract
Sensory stimuli endow animals with the ability to generate an internal representation. This representation can be maintained for a certain duration in the absence of previously elicited inputs. The reliance on an internal representation rather than purely on the basis of external stimuli is a hallmark feature of higher-order functions such as working memory. Patterns of neural activity produced in response to sensory inputs can continue long after the disappearance of previous inputs. Experimental and theoretical studies have largely invested in understanding how animals faithfully maintain sensory representations during ongoing reverberations of neural activity. However, these studies have focused on preassigned protocols of stimulus presentation, leaving out by default the possibility of exploring how the content of working memory interacts with ongoing input streams. Here, we study working memory using a network of spiking neurons with dynamic synapses subject to short-term and long-term synaptic plasticity. The formal model is embodied in a physical robot as a companion approach under which neuronal activity is directly linked to motor output. The artificial agent is used as a methodological tool for studying the formation of working memory capacity. To this end, we devise a keyboard listening framework to delineate the context under which working memory content is (1) refined, (2) overwritten or (3) resisted by ongoing new input streams. Ultimately, this study takes a neurorobotic perspective to resurface the long-standing implication of working memory in flexible cognition.
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Affiliation(s)
- Nareg Berberian
- Laboratory for Computational Neurodynamics and Cognition, School of Psychology, University of Ottawa, Ottawa, Ontario, Canada
| | - Matt Ross
- Laboratory for Computational Neurodynamics and Cognition, School of Psychology, University of Ottawa, Ottawa, Ontario, Canada
| | - Sylvain Chartier
- Laboratory for Computational Neurodynamics and Cognition, School of Psychology, University of Ottawa, Ottawa, Ontario, Canada
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12
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Gao R, van den Brink RL, Pfeffer T, Voytek B. Neuronal timescales are functionally dynamic and shaped by cortical microarchitecture. eLife 2020; 9:e61277. [PMID: 33226336 PMCID: PMC7755395 DOI: 10.7554/elife.61277] [Citation(s) in RCA: 104] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 11/22/2020] [Indexed: 12/21/2022] Open
Abstract
Complex cognitive functions such as working memory and decision-making require information maintenance over seconds to years, from transient sensory stimuli to long-term contextual cues. While theoretical accounts predict the emergence of a corresponding hierarchy of neuronal timescales, direct electrophysiological evidence across the human cortex is lacking. Here, we infer neuronal timescales from invasive intracranial recordings. Timescales increase along the principal sensorimotor-to-association axis across the entire human cortex, and scale with single-unit timescales within macaques. Cortex-wide transcriptomic analysis shows direct alignment between timescales and expression of excitation- and inhibition-related genes, as well as genes specific to voltage-gated transmembrane ion transporters. Finally, neuronal timescales are functionally dynamic: prefrontal cortex timescales expand during working memory maintenance and predict individual performance, while cortex-wide timescales compress with aging. Thus, neuronal timescales follow cytoarchitectonic gradients across the human cortex and are relevant for cognition in both short and long terms, bridging microcircuit physiology with macroscale dynamics and behavior.
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Affiliation(s)
- Richard Gao
- Department of Cognitive Science, University of California, San DiegoLa JollaUnited States
| | - Ruud L van den Brink
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Thomas Pfeffer
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu FabraBarcelonaSpain
| | - Bradley Voytek
- Department of Cognitive Science, University of California, San DiegoLa JollaUnited States
- Halıcıoğlu Data Science Institute, University of California, San DiegoLa JollaUnited States
- Neurosciences Graduate Program, University of California, San DiegoLa JollaUnited States
- Kavli Institute for Brain and Mind, University of California, San DiegoLa JollaUnited States
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13
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Mahjoory K, Schoffelen JM, Keitel A, Gross J. The frequency gradient of human resting-state brain oscillations follows cortical hierarchies. eLife 2020; 9:e53715. [PMID: 32820722 PMCID: PMC7476753 DOI: 10.7554/elife.53715] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 08/20/2020] [Indexed: 12/20/2022] Open
Abstract
The human cortex is characterized by local morphological features such as cortical thickness, myelin content, and gene expression that change along the posterior-anterior axis. We investigated if some of these structural gradients are associated with a similar gradient in a prominent feature of brain activity - namely the frequency of oscillations. In resting-state MEG recordings from healthy participants (N = 187) using mixed effect models, we found that the dominant peak frequency in a brain area decreases significantly along the posterior-anterior axis following the global hierarchy from early sensory to higher order areas. This spatial gradient of peak frequency was significantly anticorrelated with that of cortical thickness, representing a proxy of the cortical hierarchical level. This result indicates that the dominant frequency changes systematically and globally along the spatial and hierarchical gradients and establishes a new structure-function relationship pertaining to brain oscillations as a core organization that may underlie hierarchical specialization in the brain.
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Affiliation(s)
- Keyvan Mahjoory
- Institute for Biomagnetism and Biosignalanalysis (IBB), University of MuensterMuensterGermany
| | - Jan-Mathijs Schoffelen
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and BehaviourNijmegenNetherlands
| | - Anne Keitel
- Psychology, University of Dundee, Scrymgeour BuildingDundeeUnited Kingdom
| | - Joachim Gross
- Institute for Biomagnetism and Biosignalanalysis (IBB), University of MuensterMuensterGermany
- Centre for Cognitive Neuroimaging (CCNi), University of GlasgowGlasgowUnited Kingdom
- Otto-Creutzfeldt-Center for Cognitive and Behavioral Neuroscience, University of MuensterMuensterGermany
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14
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Kosciessa JQ, Kloosterman NA, Garrett DD. Standard multiscale entropy reflects neural dynamics at mismatched temporal scales: What's signal irregularity got to do with it? PLoS Comput Biol 2020; 16:e1007885. [PMID: 32392250 PMCID: PMC7241858 DOI: 10.1371/journal.pcbi.1007885] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 05/21/2020] [Accepted: 04/18/2020] [Indexed: 01/10/2023] Open
Abstract
Multiscale Entropy (MSE) is used to characterize the temporal irregularity of neural time series patterns. Due to its' presumed sensitivity to non-linear signal characteristics, MSE is typically considered a complementary measure of brain dynamics to signal variance and spectral power. However, the divergence between these measures is often unclear in application. Furthermore, it is commonly assumed (yet sparingly verified) that entropy estimated at specific time scales reflects signal irregularity at those precise time scales of brain function. We argue that such assumptions are not tenable. Using simulated and empirical electroencephalogram (EEG) data from 47 younger and 52 older adults, we indicate strong and previously underappreciated associations between MSE and spectral power, and highlight how these links preclude traditional interpretations of MSE time scales. Specifically, we show that the typical definition of temporal patterns via "similarity bounds" biases coarse MSE scales-that are thought to reflect slow dynamics-by high-frequency dynamics. Moreover, we demonstrate that entropy at fine time scales-presumed to indicate fast dynamics-is highly sensitive to broadband spectral power, a measure dominated by low-frequency contributions. Jointly, these issues produce counterintuitive reflections of frequency-specific content on MSE time scales. We emphasize the resulting inferential problems in a conceptual replication of cross-sectional age differences at rest, in which scale-specific entropy age effects could be explained by spectral power differences at mismatched temporal scales. Furthermore, we demonstrate how such problems may be alleviated, resulting in the indication of scale-specific age differences in rhythmic irregularity. By controlling for narrowband contributions, we indicate that spontaneous alpha rhythms during eyes open rest transiently reduce broadband signal irregularity. Finally, we recommend best practices that may better permit a valid estimation and interpretation of neural signal irregularity at time scales of interest.
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Affiliation(s)
- Julian Q. Kosciessa
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Niels A. Kloosterman
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Douglas D. Garrett
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
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15
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Kastanenka KV, Moreno-Bote R, De Pittà M, Perea G, Eraso-Pichot A, Masgrau R, Poskanzer KE, Galea E. A roadmap to integrate astrocytes into Systems Neuroscience. Glia 2020; 68:5-26. [PMID: 31058383 PMCID: PMC6832773 DOI: 10.1002/glia.23632] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 04/08/2019] [Accepted: 04/09/2019] [Indexed: 12/14/2022]
Abstract
Systems neuroscience is still mainly a neuronal field, despite the plethora of evidence supporting the fact that astrocytes modulate local neural circuits, networks, and complex behaviors. In this article, we sought to identify which types of studies are necessary to establish whether astrocytes, beyond their well-documented homeostatic and metabolic functions, perform computations implementing mathematical algorithms that sub-serve coding and higher-brain functions. First, we reviewed Systems-like studies that include astrocytes in order to identify computational operations that these cells may perform, using Ca2+ transients as their encoding language. The analysis suggests that astrocytes may carry out canonical computations in a time scale of subseconds to seconds in sensory processing, neuromodulation, brain state, memory formation, fear, and complex homeostatic reflexes. Next, we propose a list of actions to gain insight into the outstanding question of which variables are encoded by such computations. The application of statistical analyses based on machine learning, such as dimensionality reduction and decoding in the context of complex behaviors, combined with connectomics of astrocyte-neuronal circuits, is, in our view, fundamental undertakings. We also discuss technical and analytical approaches to study neuronal and astrocytic populations simultaneously, and the inclusion of astrocytes in advanced modeling of neural circuits, as well as in theories currently under exploration such as predictive coding and energy-efficient coding. Clarifying the relationship between astrocytic Ca2+ and brain coding may represent a leap forward toward novel approaches in the study of astrocytes in health and disease.
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Affiliation(s)
- Ksenia V. Kastanenka
- Department of Neurology, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital and Harvard Medical School, Massachusetts 02129, USA
| | - Rubén Moreno-Bote
- Department of Information and Communications Technologies, Center for Brain and Cognition and Universitat Pompeu Fabra, 08018 Barcelona, Spain
- ICREA, 08010 Barcelona, Spain
| | | | | | - Abel Eraso-Pichot
- Departament de Bioquímica, Institut de Neurociències i Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain
| | - Roser Masgrau
- Departament de Bioquímica, Institut de Neurociències i Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain
| | - Kira E. Poskanzer
- Department of Biochemistry & Biophysics, Neuroscience Graduate Program, and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, California 94143, USA
- Equally contributing authors
| | - Elena Galea
- ICREA, 08010 Barcelona, Spain
- Departament de Bioquímica, Institut de Neurociències i Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain
- Equally contributing authors
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16
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Zajzon B, Mahmoudian S, Morrison A, Duarte R. Passing the Message: Representation Transfer in Modular Balanced Networks. Front Comput Neurosci 2019; 13:79. [PMID: 31920605 PMCID: PMC6915101 DOI: 10.3389/fncom.2019.00079] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 10/29/2019] [Indexed: 01/08/2023] Open
Abstract
Neurobiological systems rely on hierarchical and modular architectures to carry out intricate computations using minimal resources. A prerequisite for such systems to operate adequately is the capability to reliably and efficiently transfer information across multiple modules. Here, we study the features enabling a robust transfer of stimulus representations in modular networks of spiking neurons, tuned to operate in a balanced regime. To capitalize on the complex, transient dynamics that such networks exhibit during active processing, we apply reservoir computing principles and probe the systems' computational efficacy with specific tasks. Focusing on the comparison of random feed-forward connectivity and biologically inspired topographic maps, we find that, in a sequential set-up, structured projections between the modules are strictly necessary for information to propagate accurately to deeper modules. Such mappings not only improve computational performance and efficiency, they also reduce response variability, increase robustness against interference effects, and boost memory capacity. We further investigate how information from two separate input streams is integrated and demonstrate that it is more advantageous to perform non-linear computations on the input locally, within a given module, and subsequently transfer the result downstream, rather than transferring intermediate information and performing the computation downstream. Depending on how information is integrated early on in the system, the networks achieve similar task-performance using different strategies, indicating that the dimensionality of the neural responses does not necessarily correlate with nonlinear integration, as predicted by previous studies. These findings highlight a key role of topographic maps in supporting fast, robust, and accurate neural communication over longer distances. Given the prevalence of such structural feature, particularly in the sensory systems, elucidating their functional purpose remains an important challenge toward which this work provides relevant, new insights. At the same time, these results shed new light on important requirements for designing functional hierarchical spiking networks.
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Affiliation(s)
- Barna Zajzon
- Jülich Research Centre, Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
| | - Sepehr Mahmoudian
- Department of Data-Driven Analysis of Biological Networks, Campus Institute for Dynamics of Biological Networks, Georg August University Göttingen, Göttingen, Germany
- MEG Unit, Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Abigail Morrison
- Jülich Research Centre, Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich, Germany
- Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr-University Bochum, Bochum, Germany
| | - Renato Duarte
- Jülich Research Centre, Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich, Germany
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17
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van den Heuvel MP, Scholtens LH, Kahn RS. Multiscale Neuroscience of Psychiatric Disorders. Biol Psychiatry 2019; 86:512-522. [PMID: 31320130 DOI: 10.1016/j.biopsych.2019.05.015] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Revised: 05/16/2019] [Accepted: 05/17/2019] [Indexed: 12/11/2022]
Abstract
The human brain comprises a multiscale network with multiple levels of organization. Neurons with dendritic and axonal connections form the microscale fabric of brain circuitry, and macroscale brain regions and white matter connections form the infrastructure for system-level brain communication and information integration. In this review, we discuss the emerging trend of multiscale neuroscience, the multidisciplinary field that brings together data from these different levels of nervous system organization to form a better understanding of between-scale relationships of brain structure, function, and behavior in health and disease. We provide a broad overview of this developing field and discuss recent findings of exemplary multiscale neuroscience studies that illustrate the importance of studying cross-scale interactions among the genetic, molecular, cellular, and macroscale levels of brain circuitry and connectivity and behavior. We particularly consider a central, overarching goal of these multiscale neuroscience studies of human brain connectivity: to obtain insight into how disease-related alterations at one level of organization may underlie alterations observed at other scales of brain network organization in mental disorders. We conclude by discussing the current limitations, challenges, and future directions of the field.
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Affiliation(s)
- Martijn P van den Heuvel
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands; Department of Clinical Genetics, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Lianne H Scholtens
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - René S Kahn
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
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18
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Hilgetag CC, Beul SF, van Albada SJ, Goulas A. An architectonic type principle integrates macroscopic cortico-cortical connections with intrinsic cortical circuits of the primate brain. Netw Neurosci 2019; 3:905-923. [PMID: 31637331 PMCID: PMC6777964 DOI: 10.1162/netn_a_00100] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 06/07/2019] [Indexed: 12/31/2022] Open
Abstract
The connections linking neurons within and between cerebral cortical areas form a multiscale network for communication. We review recent work relating essential features of cortico-cortical connections, such as their existence and laminar origins and terminations, to fundamental structural parameters of cortical areas, such as their distance, similarity in cytoarchitecture, defined by lamination or neuronal density, and other macroscopic and microscopic structural features. These analyses demonstrate the presence of an architectonic type principle. Across species and cortices, the essential features of cortico-cortical connections vary consistently and strongly with the cytoarchitectonic similarity of cortical areas. By contrast, in multivariate analyses such relations were not found consistently for distance, similarity of cortical thickness, or cellular morphology. Gradients of laminar cortical differentiation, as reflected in overall neuronal density, also correspond to regional variations of cellular features, forming a spatially ordered natural axis of concerted architectonic and connectional changes across the cortical sheet. The robustness of findings across mammalian brains allows cross-species predictions of the existence and laminar patterns of projections, including estimates for the human brain that are not yet available experimentally. The architectonic type principle integrates cortical connectivity and architecture across scales, with implications for computational explorations of cortical physiology and developmental mechanisms.
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Affiliation(s)
- Claus C Hilgetag
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Germany
| | - Sarah F Beul
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Germany
| | - Sacha J van Albada
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), and JARA-Institute of Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Germany
| | - Alexandros Goulas
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Germany
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19
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Lagzi F, Atay FM, Rotter S. Bifurcation analysis of the dynamics of interacting subnetworks of a spiking network. Sci Rep 2019; 9:11397. [PMID: 31388027 PMCID: PMC6684592 DOI: 10.1038/s41598-019-47190-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 07/10/2019] [Indexed: 12/04/2022] Open
Abstract
We analyze the collective dynamics of hierarchically structured networks of densely connected spiking neurons. These networks of sub-networks may represent interactions between cell assemblies or different nuclei in the brain. The dynamical activity pattern that results from these interactions depends on the strength of synaptic coupling between them. Importantly, the overall dynamics of a brain region in the absence of external input, so called ongoing brain activity, has been attributed to the dynamics of such interactions. In our study, two different network scenarios are considered: a system with one inhibitory and two excitatory subnetworks, and a network representation with three inhibitory subnetworks. To study the effect of synaptic strength on the global dynamics of the network, two parameters for relative couplings between these subnetworks are considered. For each case, a bifurcation analysis is performed and the results have been compared to large-scale network simulations. Our analysis shows that Generalized Lotka-Volterra (GLV) equations, well-known in predator-prey studies, yield a meaningful population-level description for the collective behavior of spiking neuronal interaction, which have a hierarchical structure. In particular, we observed a striking equivalence between the bifurcation diagrams of spiking neuronal networks and their corresponding GLV equations. This study gives new insight on the behavior of neuronal assemblies, and can potentially suggest new mechanisms for altering the dynamical patterns of spiking networks based on changing the synaptic strength between some groups of neurons.
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Affiliation(s)
- Fereshteh Lagzi
- Bernstein Center Freiburg, Freiburg, Germany. .,Faculty of Biology, University of Freiburg, Freiburg, Germany.
| | - Fatihcan M Atay
- Department of Mathematics, Bilkent University, Ankara, Turkey
| | - Stefan Rotter
- Bernstein Center Freiburg, Freiburg, Germany.,Faculty of Biology, University of Freiburg, Freiburg, Germany
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20
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Seeholzer A, Deger M, Gerstner W. Stability of working memory in continuous attractor networks under the control of short-term plasticity. PLoS Comput Biol 2019; 15:e1006928. [PMID: 31002672 PMCID: PMC6493776 DOI: 10.1371/journal.pcbi.1006928] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Revised: 05/01/2019] [Accepted: 03/04/2019] [Indexed: 12/02/2022] Open
Abstract
Continuous attractor models of working-memory store continuous-valued information in continuous state-spaces, but are sensitive to noise processes that degrade memory retention. Short-term synaptic plasticity of recurrent synapses has previously been shown to affect continuous attractor systems: short-term facilitation can stabilize memory retention, while short-term depression possibly increases continuous attractor volatility. Here, we present a comprehensive description of the combined effect of both short-term facilitation and depression on noise-induced memory degradation in one-dimensional continuous attractor models. Our theoretical description, applicable to rate models as well as spiking networks close to a stationary state, accurately describes the slow dynamics of stored memory positions as a combination of two processes: (i) diffusion due to variability caused by spikes; and (ii) drift due to random connectivity and neuronal heterogeneity. We find that facilitation decreases both diffusion and directed drifts, while short-term depression tends to increase both. Using mutual information, we evaluate the combined impact of short-term facilitation and depression on the ability of networks to retain stable working memory. Finally, our theory predicts the sensitivity of continuous working memory to distractor inputs and provides conditions for stability of memory. The ability to transiently memorize positions in the visual field is crucial for behavior. Models and experiments have shown that such memories can be maintained in networks of cortical neurons with a continuum of possible activity states, that reflects the continuum of positions in the environment. However, the accuracy of positions stored in such networks will degrade over time due to the noisiness of neuronal signaling and imperfections of the biological substrate. Previous work in simplified models has shown that synaptic short-term plasticity could stabilize this degradation by dynamically up- or down-regulating the strength of synaptic connections, thereby “pinning down” memorized positions. Here, we present a general theory that accurately predicts the extent of this “pinning down” by short-term plasticity in a broad class of biologically plausible network models, thereby untangling the interplay of varying biological sources of noise with short-term plasticity. Importantly, our work provides a novel theoretical link from the microscopic substrate of working memory—neurons and synaptic connections—to observable behavioral correlates, for example the susceptibility to distracting stimuli.
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Affiliation(s)
- Alexander Seeholzer
- School of Computer and Communication Sciences and School of Life Sciences, Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Moritz Deger
- School of Computer and Communication Sciences and School of Life Sciences, Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Institute for Zoology, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
| | - Wulfram Gerstner
- School of Computer and Communication Sciences and School of Life Sciences, Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- * E-mail:
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21
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Duarte R, Morrison A. Leveraging heterogeneity for neural computation with fading memory in layer 2/3 cortical microcircuits. PLoS Comput Biol 2019; 15:e1006781. [PMID: 31022182 PMCID: PMC6504118 DOI: 10.1371/journal.pcbi.1006781] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 05/07/2019] [Accepted: 01/09/2019] [Indexed: 11/24/2022] Open
Abstract
Complexity and heterogeneity are intrinsic to neurobiological systems, manifest in every process, at every scale, and are inextricably linked to the systems' emergent collective behaviours and function. However, the majority of studies addressing the dynamics and computational properties of biologically inspired cortical microcircuits tend to assume (often for the sake of analytical tractability) a great degree of homogeneity in both neuronal and synaptic/connectivity parameters. While simplification and reductionism are necessary to understand the brain's functional principles, disregarding the existence of the multiple heterogeneities in the cortical composition, which may be at the core of its computational proficiency, will inevitably fail to account for important phenomena and limit the scope and generalizability of cortical models. We address these issues by studying the individual and composite functional roles of heterogeneities in neuronal, synaptic and structural properties in a biophysically plausible layer 2/3 microcircuit model, built and constrained by multiple sources of empirical data. This approach was made possible by the emergence of large-scale, well curated databases, as well as the substantial improvements in experimental methodologies achieved over the last few years. Our results show that variability in single neuron parameters is the dominant source of functional specialization, leading to highly proficient microcircuits with much higher computational power than their homogeneous counterparts. We further show that fully heterogeneous circuits, which are closest to the biophysical reality, owe their response properties to the differential contribution of different sources of heterogeneity.
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Affiliation(s)
- Renato Duarte
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1 / INM-10), Jülich Research Centre, Jülich, Germany
- Bernstein Center Freiburg, Albert-Ludwig University of Freiburg, Freiburg im Breisgau, Germany
- Faculty of Biology, Albert-Ludwig University of Freiburg, Freiburg im Breisgau, Germany
- Institute of Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Abigail Morrison
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1 / INM-10), Jülich Research Centre, Jülich, Germany
- Bernstein Center Freiburg, Albert-Ludwig University of Freiburg, Freiburg im Breisgau, Germany
- Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr-University Bochum, Bochum, Germany
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22
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Abstract
The primate cerebral cortex displays a hierarchy that extends from primary sensorimotor to association areas, supporting increasingly integrated function underpinned by a gradient of heterogeneity in the brain's microcircuits. The extent to which these hierarchical gradients are unique to primate or may reflect a conserved mammalian principle of brain organization remains unknown. Here we report the topographic similarity of large-scale gradients in cytoarchitecture, gene expression, interneuron cell densities, and long-range axonal connectivity, which vary from primary sensory to prefrontal areas of mouse cortex, highlighting an underappreciated spatial dimension of mouse cortical specialization. Using the T1-weighted:T2-weighted (T1w:T2w) magnetic resonance imaging map as a common spatial reference for comparison across species, we report interspecies agreement in a range of large-scale cortical gradients, including a significant correspondence between gene transcriptional maps in mouse cortex with their human orthologs in human cortex, as well as notable interspecies differences. Our results support the view of systematic structural variation across cortical areas as a core organizational principle that may underlie hierarchical specialization in mammalian brains.
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Affiliation(s)
- Ben D Fulcher
- School of Physics, Sydney University, Sydney, NSW 2006, Australia;
| | - John D Murray
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511
| | - Valerio Zerbi
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, 8057 Zürich, Switzerland
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, NY 10003;
- Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai 201210, China
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Himberger KD, Chien HY, Honey CJ. Principles of Temporal Processing Across the Cortical Hierarchy. Neuroscience 2018; 389:161-174. [PMID: 29729293 DOI: 10.1016/j.neuroscience.2018.04.030] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2017] [Revised: 04/17/2018] [Accepted: 04/19/2018] [Indexed: 12/20/2022]
Abstract
The world is richly structured on multiple spatiotemporal scales. In order to represent spatial structure, many machine-learning models repeat a set of basic operations at each layer of a hierarchical architecture. These iterated spatial operations - including pooling, normalization and pattern completion - enable these systems to recognize and predict spatial structure, while robust to changes in the spatial scale, contrast and noisiness of the input signal. Because our brains also process temporal information that is rich and occurs across multiple time scales, might the brain employ an analogous set of operations for temporal information processing? Here we define a candidate set of temporal operations, and we review evidence that they are implemented in the mammalian cerebral cortex in a hierarchical manner. We conclude that multiple consecutive stages of cortical processing can be understood to perform temporal pooling, temporal normalization and temporal pattern completion.
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Affiliation(s)
- Kevin D Himberger
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
| | - Hsiang-Yun Chien
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
| | - Christopher J Honey
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, United States.
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