1
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Wu K, Gollo LL. Dendrites contribute to the gradient of intrinsic timescales encompassing cortical and subcortical brain networks. Front Cell Neurosci 2024; 18:1404605. [PMID: 39309702 PMCID: PMC11412829 DOI: 10.3389/fncel.2024.1404605] [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: 03/21/2024] [Accepted: 08/19/2024] [Indexed: 09/25/2024] Open
Abstract
Introduction Cytoarchitectonic studies have uncovered a correlation between higher levels of cortical hierarchy and reduced dendritic size. This hierarchical organization extends to the brain's timescales, revealing longer intrinsic timescales at higher hierarchical levels. However, estimating the contribution of single-neuron dendritic morphology to the hierarchy of timescales, which is typically characterized at a macroscopic level, remains challenging. Method Here we mapped the intrinsic timescales of six functional networks using functional magnetic resonance imaging (fMRI) data, and characterized the influence of neuronal dendritic size on intrinsic timescales of brain regions, utilizing a multicompartmental neuronal modeling approach based on digitally reconstructed neurons. Results The fMRI results revealed a hierarchy of intrinsic timescales encompassing both cortical and subcortical brain regions. The neuronal modeling indicated that neurons with larger dendritic structures exhibit shorter intrinsic timescales. Together these findings highlight the contribution of dendrites at the neuronal level to the hierarchy of intrinsic timescales at the whole-brain level. Discussion This study sheds light on the intricate relationship between neuronal structure, cytoarchitectonic maps, and the hierarchy of timescales in the brain.
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Affiliation(s)
| | - Leonardo L. Gollo
- Brain Networks and Modelling Laboratory, School of Psychological Sciences, and Monash Biomedical Imaging, The Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
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2
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Hall S. Is the Papez circuit the location of the elusive episodic memory engram? IBRO Neurosci Rep 2024; 16:249-259. [PMID: 38370006 PMCID: PMC10869290 DOI: 10.1016/j.ibneur.2024.01.016] [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: 09/25/2023] [Accepted: 01/31/2024] [Indexed: 02/20/2024] Open
Abstract
All of the brain structures and white matter that make up Papez' circuit, as well as the circuit as a whole, are implicated in the literature in episodic memory formation and recall. This paper shows that Papez' circuit has the detailed structure and connectivity that is evidently required to support the episodic memory engram, and that identifying Papez' circuit as the location of the engram answers a number of long-standing questions regarding the role of medial temporal lobe structures in episodic memory. The paper then shows that the process by which the episodic memory engram may be formed is a network-wide Hebbian potentiation termed "racetrack potentiation", whose frequency corresponds to that observed in vivo in humans for memory functions. Further, by considering the microcircuits observed in the medial temporal lobe structures forming Papez' circuit, the paper establishes the neural mechanisms behind the required functions of sensory information storage and recall, pattern completion, pattern separation, and memory consolidation. The paper shows that Papez' circuit has the necessary connectivity to gather the various elements of an episodic memory occurring within Pöppel's experienced time or "quantum of experience". Finally, the paper shows how the memory engram located in Papez' circuit might be central to the formation of a duplicate engram in the cortex enabling consolidation and long-term storage of episodic memories.
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Affiliation(s)
- Steven Hall
- Department of Psychology, University of Bolton, Deane Road, Bolton BL3 5AB, UK
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3
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Liang J, Yang Z, Zhou C. Excitation-Inhibition Balance, Neural Criticality, and Activities in Neuronal Circuits. Neuroscientist 2024:10738584231221766. [PMID: 38291889 DOI: 10.1177/10738584231221766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Neural activities in local circuits exhibit complex and multilevel dynamic features. Individual neurons spike irregularly, which is believed to originate from receiving balanced amounts of excitatory and inhibitory inputs, known as the excitation-inhibition balance. The spatial-temporal cascades of clustered neuronal spikes occur in variable sizes and durations, manifested as neural avalanches with scale-free features. These may be explained by the neural criticality hypothesis, which posits that neural systems operate around the transition between distinct dynamic states. Here, we summarize the experimental evidence for and the underlying theory of excitation-inhibition balance and neural criticality. Furthermore, we review recent studies of excitatory-inhibitory networks with synaptic kinetics as a simple solution to reconcile these two apparently distinct theories in a single circuit model. This provides a more unified understanding of multilevel neural activities in local circuits, from spontaneous to stimulus-response dynamics.
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Affiliation(s)
- Junhao Liang
- Eberhard Karls University of Tübingen and Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Zhuda Yang
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Life Science Imaging Centre, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Research Centre, Hong Kong Baptist University Institute of Research and Continuing Education, Shenzhen, China
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4
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Navarro P, Oweiss K. Compressive sensing of functional connectivity maps from patterned optogenetic stimulation of neuronal ensembles. PATTERNS (NEW YORK, N.Y.) 2023; 4:100845. [PMID: 37876895 PMCID: PMC10591201 DOI: 10.1016/j.patter.2023.100845] [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: 11/26/2022] [Revised: 04/04/2023] [Accepted: 08/25/2023] [Indexed: 10/26/2023]
Abstract
Mapping functional connectivity between neurons is an essential step toward probing the neural computations mediating behavior. Accurately determining synaptic connectivity maps in populations of neurons is challenging in terms of yield, accuracy, and experimental time. Here, we developed a compressive sensing approach to reconstruct synaptic connectivity maps based on random two-photon cell-targeted optogenetic stimulation and membrane voltage readout of many putative postsynaptic neurons. Using a biophysical network model of interconnected populations of excitatory and inhibitory neurons, we characterized mapping recall and precision as a function of network observability, sparsity, number of neurons stimulated, off-target stimulation, synaptic reliability, propagation latency, and network topology. We found that mapping can be achieved with far fewer measurements than the standard pairwise sequential approach, with network sparsity and synaptic reliability serving as primary determinants of the performance. Our results suggest a rapid and efficient method to reconstruct functional connectivity of sparsely connected neuronal networks.
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Affiliation(s)
- Phillip Navarro
- Electrical and Computer Engineering Department, University of Florida, Gainesville, FL 32611, USA
| | - Karim Oweiss
- Electrical and Computer Engineering Department, University of Florida, Gainesville, FL 32611, USA
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
- Department of Neurology, University of Florida, Gainesville, FL 32611, USA
- Department of Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, FL 32611, USA
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5
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Liu S, Li F, Wan F. Distance to Criticality Undergoes Critical Transition Before Epileptic Seizure Attacks. Brain Res Bull 2023:110684. [PMID: 37353038 DOI: 10.1016/j.brainresbull.2023.110684] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/03/2023] [Accepted: 06/10/2023] [Indexed: 06/25/2023]
Abstract
Epilepsy is a common neurological disorder characterized by recurring seizures, but its underlying mechanisms remain poorly understood. Despite extensive research, there are still gaps in our knowledge about the relationship between brain dynamics and seizures. In this study, our aim is to address these gaps by proposing a novel approach to assess the role of brain network dynamics in the onset of seizures. Specifically, we investigate the relationship between brain dynamics and seizures by tracking the distance to criticality. Our hypothesis is that this distance plays a crucial role in brain state changes and that seizures may be related to critical transitions of this distance. To test this hypothesis, we develop a method to measure the evolution of the brain network's distance to the critical dynamic systems (i.e., the distance to the tipping point, DTP) using dynamic network biomarker theory and random matrix theory. The results show that the DTP of the brain decreases significantly immediately after onset of an epileptic seizure, suggesting that the brain loses its well-defined quasi-critical state during seizures. We refer to this phenomenon as the "criticality of the criticality" (COC). Furthermore, we observe that DTP exhibits a shape transition before and after the onset of the seizures. This phenomenon suggests the possibility of early warning signal (EWS) identification in the dynamic sequence of DTP, which could be utilized for seizure prediction. Our results show that the Hurst exponent, skewness, kurtosis, autocorrelation, and variance of the DTP sequence are potential EWS features. This study advances our understanding of the relationship between brain dynamics and seizures and highlights the potential for using criticality-based measures to predict and prevent seizures.
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Affiliation(s)
- Shun Liu
- The Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau; The Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau; The Centre for Artificial Intelligence and Robotics, Institute of Collaborative Innovation, University of Macau, Macau
| | - Fali Li
- The Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau; The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuro-information, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, the Center for Information in Bio-Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng Wan
- The Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau; The Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau; The Centre for Artificial Intelligence and Robotics, Institute of Collaborative Innovation, University of Macau, Macau.
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6
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D'Angelo E, Jirsa V. The quest for multiscale brain modeling. Trends Neurosci 2022; 45:777-790. [PMID: 35906100 DOI: 10.1016/j.tins.2022.06.007] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/20/2022] [Accepted: 06/21/2022] [Indexed: 01/07/2023]
Abstract
Addressing the multiscale organization of the brain, which is fundamental to the dynamic repertoire of the organ, remains challenging. In principle, it should be possible to model neurons and synapses in detail and then connect them into large neuronal assemblies to explain the relationship between microscopic phenomena, large-scale brain functions, and behavior. It is more difficult to infer neuronal functions from ensemble measurements such as those currently obtained with brain activity recordings. In this article we consider theories and strategies for combining bottom-up models, generated from principles of neuronal biophysics, with top-down models based on ensemble representations of network activity and on functional principles. These integrative approaches are hoped to provide effective multiscale simulations in virtual brains and neurorobots, and pave the way to future applications in medicine and information technologies.
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Affiliation(s)
- Egidio D'Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, and Brain Connectivity Center, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Mondino Foundation, Pavia, Italy.
| | - Viktor Jirsa
- Institut National de la Santé et de la Recherche Médicale (INSERM) Unité 1106, Centre National de la Recherche Scientifique (CNRS), and University of Aix-Marseille, Marseille, France
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7
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Dunham CS, Mackenzie ME, Nakano H, Kim AR, Juda MB, Nakano A, Stieg AZ, Gimzewski JK. Pacemaker translocations and power laws in 2D stem cell-derived cardiomyocyte cultures. PLoS One 2022; 17:e0263976. [PMID: 35286321 PMCID: PMC8920264 DOI: 10.1371/journal.pone.0263976] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 02/01/2022] [Indexed: 11/18/2022] Open
Abstract
Power laws are of interest to several scientific disciplines because they can provide important information about the underlying dynamics (e.g. scale invariance and self-similarity) of a given system. Because power laws are of increasing interest to the cardiac sciences as potential indicators of cardiac dysfunction, it is essential that rigorous, standardized analytical methods are employed in the evaluation of power laws. This study compares the methods currently used in the fields of condensed matter physics, geoscience, neuroscience, and cardiology in order to provide a robust analytical framework for evaluating power laws in stem cell-derived cardiomyocyte cultures. One potential power law-obeying phenomenon observed in these cultures is pacemaker translocations, or the spatial and temporal instability of the pacemaker region, in a 2D cell culture. Power law analysis of translocation data was performed using increasingly rigorous methods in order to illustrate how differences in analytical robustness can result in misleading power law interpretations. Non-robust methods concluded that pacemaker translocations adhere to a power law while robust methods convincingly demonstrated that they obey a doubly truncated power law. The results of this study highlight the importance of employing comprehensive methods during power law analysis of cardiomyocyte cultures.
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Affiliation(s)
- Christopher S. Dunham
- Department of Chemistry and Biochemistry, University of California, Los Angeles, California, United States of America
| | - Madelynn E. Mackenzie
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, California, United States of America
| | - Haruko Nakano
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, California, United States of America
| | - Alexis R. Kim
- Department of Chemistry and Biochemistry, University of California, Los Angeles, California, United States of America
| | - Michal B. Juda
- Molecular Biology Institute, University of California, Los Angeles, California, United States of America
| | - Atsushi Nakano
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, California, United States of America
- Molecular Biology Institute, University of California, Los Angeles, California, United States of America
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, California, United States of America
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, California, United States of America
- Department of Cell Physiology, The Jikei University, Tokyo, Japan
| | - Adam Z. Stieg
- California NanoSystems Institute, University of California, Los Angeles, California, United States of America
- International Center for Materials Nanoarchitectonics (MANA), National Institute of Materials Science, Tsukuba, Japan
| | - James K. Gimzewski
- Department of Chemistry and Biochemistry, University of California, Los Angeles, California, United States of America
- California NanoSystems Institute, University of California, Los Angeles, California, United States of America
- International Center for Materials Nanoarchitectonics (MANA), National Institute of Materials Science, Tsukuba, Japan
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8
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Beekhof GC, Osório C, White JJ, van Zoomeren S, van der Stok H, Xiong B, Nettersheim IH, Mak WA, Runge M, Fiocchi FR, Boele HJ, Hoebeek FE, Schonewille M. Differential spatiotemporal development of Purkinje cell populations and cerebellum-dependent sensorimotor behaviors. eLife 2021; 10:63668. [PMID: 33973524 PMCID: PMC8195607 DOI: 10.7554/elife.63668] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 05/10/2021] [Indexed: 12/17/2022] Open
Abstract
Distinct populations of Purkinje cells (PCs) with unique molecular and connectivity features are at the core of the modular organization of the cerebellum. Previously, we showed that firing activity of PCs differs between ZebrinII-positive and ZebrinII-negative cerebellar modules (Zhou et al., 2014; Wu et al., 2019). Here, we investigate the timing and extent of PC differentiation during development in mice. We found that several features of PCs, including activity levels, dendritic arborization, axonal shape and climbing fiber input, develop differentially between nodular and anterior PC populations. Although all PCs show a particularly rapid development in the second postnatal week, anterior PCs typically have a prolonged physiological and dendritic maturation. In line herewith, younger mice exhibit attenuated anterior-dependent eyeblink conditioning, but faster nodular-dependent compensatory eye movement adaptation. Our results indicate that specific cerebellar regions have unique developmental timelines which match with their related, specific forms of cerebellum-dependent behaviors.
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Affiliation(s)
| | - Catarina Osório
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands
| | - Joshua J White
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands
| | | | | | - Bilian Xiong
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands
| | | | | | - Marit Runge
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands
| | | | - Henk-Jan Boele
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands.,Princeton Neuroscience Institute, Princeton, United States
| | - Freek E Hoebeek
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands.,Department for Developmental Origins of Disease, University Medical Center Utrecht Brain Center and Wilhelmina Children's Hospital, Utrecht, Netherlands
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9
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Zhou X, Ma N, Song B, Wu Z, Liu G, Liu L, Yu L, Feng J. Optimal Organization of Functional Connectivity Networks for Segregation and Integration With Large-Scale Critical Dynamics in Human Brains. Front Comput Neurosci 2021; 15:641335. [PMID: 33867963 PMCID: PMC8044315 DOI: 10.3389/fncom.2021.641335] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 02/23/2021] [Indexed: 12/04/2022] Open
Abstract
The optimal organization for functional segregation and integration in brain is made evident by the “small-world” feature of functional connectivity (FC) networks and is further supported by the loss of this feature that has been described in many types of brain disease. However, it remains unknown how such optimally organized FC networks arise from the brain's structural constrains. On the other hand, an emerging literature suggests that brain function may be supported by critical neural dynamics, which is believed to facilitate information processing in brain. Though previous investigations have shown that the critical dynamics plays an important role in understanding the relation between whole brain structural connectivity and functional connectivity, it is not clear if the critical dynamics could be responsible for the optimal FC network configuration in human brains. Here, we show that the long-range temporal correlations (LRTCs) in the resting state fMRI blood-oxygen-level-dependent (BOLD) signals are significantly correlated with the topological matrices of the FC brain network. Using structure-dynamics-function modeling approach that incorporates diffusion tensor imaging (DTI) data and simple cellular automata dynamics, we showed that the critical dynamics could optimize the whole brain FC network organization by, e.g., maximizing the clustering coefficient while minimizing the characteristic path length. We also demonstrated with a more detailed excitation-inhibition neuronal network model that loss of local excitation-inhibition (E/I) balance causes failure of critical dynamics, therefore disrupting the optimal FC network organization. The results highlighted the crucial role of the critical dynamics in forming an optimal organization of FC networks in the brain and have potential application to the understanding and modeling of abnormal FC configurations in neuropsychiatric disorders.
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Affiliation(s)
- Xinchun Zhou
- Key Laboratory of Theoretical Physics of Gansu Province, Lanzhou Center for Theoretical Physics, Lanzhou University, Lanzhou, China
| | - Ningning Ma
- School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai, China
| | - Benseng Song
- Key Laboratory of Theoretical Physics of Gansu Province, Lanzhou Center for Theoretical Physics, Lanzhou University, Lanzhou, China
| | - Zhixi Wu
- Key Laboratory of Theoretical Physics of Gansu Province, Lanzhou Center for Theoretical Physics, Lanzhou University, Lanzhou, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Liwei Liu
- College of Electrical Engineering, Northwest University for Nationalities, Lanzhou, China
| | - Lianchun Yu
- Key Laboratory of Theoretical Physics of Gansu Province, Lanzhou Center for Theoretical Physics, Lanzhou University, Lanzhou, China
| | - Jianfeng Feng
- School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai, China.,School of Mathematical Sciences, School of Life Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China
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10
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Kirch C, Gollo LL. Single-neuron dynamical effects of dendritic pruning implicated in aging and neurodegeneration: towards a measure of neuronal reserve. Sci Rep 2021; 11:1309. [PMID: 33446683 PMCID: PMC7809359 DOI: 10.1038/s41598-020-78815-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 11/13/2020] [Indexed: 12/13/2022] Open
Abstract
Aging is a main risk factor for neurodegenerative disorders including Alzheimer's disease. It is often accompanied by reduced cognitive functions, gray-matter volume, and dendritic integrity. Although age-related brain structural changes have been observed across multiple scales, their functional implications remain largely unknown. Here we simulate the aging effects on neuronal morphology as dendritic pruning and characterize its dynamical implications. Utilizing a detailed computational modeling approach, we simulate the dynamics of digitally reconstructed neurons obtained from Neuromorpho.org. We show that dendritic pruning affects neuronal integrity: firing rate is reduced, causing a reduction in energy consumption, energy efficiency, and dynamic range. Pruned neurons require less energy but their function is often impaired, which can explain the diminished ability to distinguish between similar experiences (pattern separation) in older people. Our measures indicate that the resilience of neuronal dynamics is neuron-specific, heterogeneous, and strongly affected by dendritic topology and the position of the soma. Based on the emergent neuronal dynamics, we propose to classify the effects of dendritic deterioration, and put forward a topological measure of “neuronal reserve” that quantifies the resilience of neuronal dynamics to dendritic pruning. Moreover, our findings suggest that increasing dendritic excitability could partially mitigate the dynamical effects of aging.
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Affiliation(s)
- Christoph Kirch
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.,The Queensland University of Technology, Brisbane, Australia
| | - Leonardo L Gollo
- QIMR Berghofer Medical Research Institute, Brisbane, Australia. .,The Queensland University of Technology, Brisbane, Australia. .,The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash Biomedical Imaging, Monash University, Melbourne, Australia.
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11
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Khaledi-Nasab A, Chauhan K, Tass PA, Neiman AB. Information processing in tree networks of excitable elements. Phys Rev E 2021; 103:012308. [PMID: 33601542 DOI: 10.1103/physreve.103.012308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 12/27/2020] [Indexed: 11/07/2022]
Abstract
We study the collective response of small random tree networks of diffusively coupled excitable elements to stimuli applied to leaf nodes. Such networks model the morphology of certain sensory neurons that possess branched myelinated dendrites with excitable nodes of Ranvier at every branch point and at leaf nodes. Leaf nodes receive random inputs along with a stimulus and initiate action potentials that propagate through the tree. We quantify the collective response registered at the central node using mutual information. We show that in the strong-coupling limit, the statistics of the number of nodes and leaves determines the mutual information. At the same time, the collective response is insensitive to particular node connectivity and distribution of stimulus over leaf nodes. However, for intermediate coupling, the mutual information may strongly depend on the stimulus distribution among leaf nodes. We identify a mechanism behind the competition of leaf nodes that leads to nonmonotonous dependence of mutual information on coupling strength. We show that a localized stimulus given to a tree branch can be occluded by the background firing of unstimulated branches, thus suppressing mutual information. Nonetheless, the mutual information can be enhanced by a proper stimulus localization and tuning of coupling strength.
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Affiliation(s)
- Ali Khaledi-Nasab
- Department of Neurosurgery, Stanford University, Stanford, California 94305, USA
| | - Kanishk Chauhan
- Department of Physics and Astronomy, Ohio University, Athens, Ohio 45701, USA
| | - Peter A Tass
- Department of Neurosurgery, Stanford University, Stanford, California 94305, USA
| | - Alexander B Neiman
- Department of Physics and Astronomy, Ohio University, Athens, Ohio 45701, USA
- Neuroscience Program, Ohio University, Athens, Ohio 45701, USA
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12
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Kirch C, Gollo LL. Spatially resolved dendritic integration: towards a functional classification of neurons. PeerJ 2020; 8:e10250. [PMID: 33282551 PMCID: PMC7694565 DOI: 10.7717/peerj.10250] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 10/06/2020] [Indexed: 01/19/2023] Open
Abstract
The vast tree-like dendritic structure of neurons allows them to receive and integrate input from many neurons. A wide variety of neuronal morphologies exist, however, their role in dendritic integration, and how it shapes the response of the neuron, is not yet fully understood. Here, we study the evolution and interactions of dendritic spikes in excitable neurons with complex real branch structures. We focus on dozens of digitally reconstructed illustrative neurons from the online repository NeuroMorpho.org, which contains over 130,000 neurons. Yet, our methods can be promptly extended to any other neuron. This approach allows us to estimate and map specific and heterogeneous patterns of activity observed across extensive dendritic trees with thousands of compartments. We propose a classification of neurons based on the location of the soma (centrality) and the number of branches connected to the soma. These are key topological factors in determining the neuron's energy consumption, firing rate, and the dynamic range, which quantifies the range in synaptic input rate that can be reliably encoded by the neuron's firing rate. Moreover, we find that bifurcations, the structural building blocks of complex dendrites, play a major role in increasing the dynamic range of neurons. Our results provide a better understanding of the effects of neuronal morphology in the diversity of neuronal dynamics and function.
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Affiliation(s)
- Christoph Kirch
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Queensland University of Technology, Brisbane, QLD, Australia
| | - Leonardo L. Gollo
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Queensland University of Technology, Brisbane, QLD, Australia
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
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13
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Modelling brain-wide neuronal morphology via rooted Cayley trees. Sci Rep 2018; 8:15666. [PMID: 30353025 PMCID: PMC6199272 DOI: 10.1038/s41598-018-34050-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 10/05/2018] [Indexed: 12/16/2022] Open
Abstract
Neuronal morphology is an essential element for brain activity and function. We take advantage of current availability of brain-wide neuron digital reconstructions of the Pyramidal cells from a mouse brain, and analyze several emergent features of brain-wide neuronal morphology. We observe that axonal trees are self-affine while dendritic trees are self-similar. We also show that tree size appear to be random, independent of the number of dendrites within single neurons. Moreover, we consider inhomogeneous branching model which stochastically generates rooted 3-Cayley trees for the brain-wide neuron topology. Based on estimated order-dependent branching probability from actual axonal and dendritic trees, our inhomogeneous model quantitatively captures a number of topological features including size and shape of both axons and dendrites. This sheds lights on a universal mechanism behind the topological formation of brain-wide axonal and dendritic trees.
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14
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Zhang R, Pei S. Dynamic range maximization in excitable networks. CHAOS (WOODBURY, N.Y.) 2018; 28:013103. [PMID: 29390628 DOI: 10.1063/1.4997254] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
We study the strategy to optimally maximize the dynamic range of excitable networks by removing the minimal number of links. A network of excitable elements can distinguish a broad range of stimulus intensities and has its dynamic range maximized at criticality. In this study, we formulate the activation propagation in excitable networks as a message passing process in which a critical state is reached when the largest eigenvalue of the weighted non-backtracking matrix is close to one. By considering the impact of single link removal on the largest eigenvalue, we develop an efficient algorithm that aims to identify the optimal set of links whose removal will drive the system to the critical state. Comparisons with other competing heuristics on both synthetic and real-world networks indicate that the proposed method can maximize the dynamic range by removing the smallest number of links, and at the same time maintaining the largest size of the giant connected component.
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Affiliation(s)
- Renquan Zhang
- School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China
| | - Sen Pei
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, USA
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15
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Gollo LL. Coexistence of critical sensitivity and subcritical specificity can yield optimal population coding. J R Soc Interface 2017; 14:20170207. [PMID: 28954848 PMCID: PMC5636266 DOI: 10.1098/rsif.2017.0207] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2017] [Accepted: 08/17/2017] [Indexed: 11/12/2022] Open
Abstract
The vicinity of phase transitions selectively amplifies weak stimuli, yielding optimal sensitivity to distinguish external input. Along with this enhanced sensitivity, enhanced levels of fluctuations at criticality reduce the specificity of the response. Given that the specificity of the response is largely compromised when the sensitivity is maximal, the overall benefit of criticality for signal processing remains questionable. Here, it is shown that this impasse can be solved by heterogeneous systems incorporating functional diversity, in which critical and subcritical components coexist. The subnetwork of critical elements has optimal sensitivity, and the subnetwork of subcritical elements has enhanced specificity. Combining segregated features extracted from the different subgroups, the resulting collective response can maximize the trade-off between sensitivity and specificity measured by the dynamic-range-to-noise ratio. Although numerous benefits can be observed when the entire system is critical, our results highlight that optimal performance is obtained when only a small subset of the system is at criticality.
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Affiliation(s)
- Leonardo L Gollo
- Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- The University of Queensland, Centre for Clinical Research, Brisbane, Australia
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16
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Kromer J, Khaledi-Nasab A, Schimansky-Geier L, Neiman AB. Emergent stochastic oscillations and signal detection in tree networks of excitable elements. Sci Rep 2017. [PMID: 28638071 PMCID: PMC5479816 DOI: 10.1038/s41598-017-04193-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
We study the stochastic dynamics of strongly-coupled excitable elements on a tree network. The peripheral nodes receive independent random inputs which may induce large spiking events propagating through the branches of the tree and leading to global coherent oscillations in the network. This scenario may be relevant to action potential generation in certain sensory neurons, which possess myelinated distal dendritic tree-like arbors with excitable nodes of Ranvier at peripheral and branching nodes and exhibit noisy periodic sequences of action potentials. We focus on the spiking statistics of the central node, which fires in response to a noisy input at peripheral nodes. We show that, in the strong coupling regime, relevant to myelinated dendritic trees, the spike train statistics can be predicted from an isolated excitable element with rescaled parameters according to the network topology. Furthermore, we show that by varying the network topology the spike train statistics of the central node can be tuned to have a certain firing rate and variability, or to allow for an optimal discrimination of inputs applied at the peripheral nodes.
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Affiliation(s)
- Justus Kromer
- Center for Advancing Electronics Dresden, TU Dresden, Mommsenstrasse 15, 01069, Dresden, Germany
| | - Ali Khaledi-Nasab
- Department of Physics and Astronomy, Ohio University, Athens, Ohio, 45701, USA
| | - Lutz Schimansky-Geier
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstrasse 15, 12489, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Alexander B Neiman
- Department of Physics and Astronomy, Ohio University, Athens, Ohio, 45701, USA. .,Neuroscience Program, Ohio University, Athens, Ohio, 45701, USA.
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17
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Relationship in Pacemaker Neurons Between the Long-Term Correlations of Membrane Voltage Fluctuations and the Corresponding Duration of the Inter-Spike Interval. J Membr Biol 2017; 250:249-257. [PMID: 28417145 DOI: 10.1007/s00232-017-9956-z] [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: 09/06/2016] [Accepted: 04/07/2017] [Indexed: 10/19/2022]
Abstract
Several studies of the behavior in the voltage and frequency fluctuations of the neural electrical activity have been performed. Here, we explored the particular association between behavior of the voltage fluctuations in the inter-spike segment (VFIS) and the inter-spike intervals (ISI) of F1 pacemaker neurons from H. aspersa, by disturbing the intracellular calcium handling with cadmium and caffeine. The scaling exponent α of the VFIS, as provided by detrended fluctuations analysis, in conjunction with the corresponding duration of ISI to estimate the determination coefficient R 2 (48-50 intervals per neuron, N = 5) were all evaluated. The time-varying scaling exponent α(t) of VFIS was also studied (20 segments per neuron, N = 11). The R 2 obtained in control conditions was 0.683 ([0.647 0.776] lower and upper quartiles), 0.405 [0.381 0.495] by using cadmium, and 0.151 [0.118 0.222] with caffeine (P < 0.05). A non-uniform scaling exponent α(t) showing a profile throughout the duration of the VFIS was further identified. A significant reduction of long-term correlations by cadmium was confirmed in the first part of this profile (P = 0.0001), but no significant reductions were detected by using caffeine. Our findings endorse that the behavior of the VFIS appears associated to the activation of different populations of ionic channels, which establish the neural membrane potential and are mediated by the intracellular calcium handling. Thus, we provide evidence to consider that the behavior of the VFIS, as determined by the scaling exponent α, conveys insights into mechanisms regulating the excitability of pacemaker neurons.
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18
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Zhou X, Tang N, Kuang Y, Liu Z. An approach to variable-order prediction via multiple distal dendrites of neurons. Neural Comput Appl 2016. [DOI: 10.1007/s00521-016-2518-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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19
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Gollo LL, Copelli M, Roberts JA. Diversity improves performance in excitable networks. PeerJ 2016; 4:e1912. [PMID: 27168961 PMCID: PMC4860327 DOI: 10.7717/peerj.1912] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2015] [Accepted: 03/17/2016] [Indexed: 11/20/2022] Open
Abstract
As few real systems comprise indistinguishable units, diversity is a hallmark of nature. Diversity among interacting units shapes properties of collective behavior such as synchronization and information transmission. However, the benefits of diversity on information processing at the edge of a phase transition, ordinarily assumed to emerge from identical elements, remain largely unexplored. Analyzing a general model of excitable systems with heterogeneous excitability, we find that diversity can greatly enhance optimal performance (by two orders of magnitude) when distinguishing incoming inputs. Heterogeneous systems possess a subset of specialized elements whose capability greatly exceeds that of the nonspecialized elements. We also find that diversity can yield multiple percolation, with performance optimized at tricriticality. Our results are robust in specific and more realistic neuronal systems comprising a combination of excitatory and inhibitory units, and indicate that diversity-induced amplification can be harnessed by neuronal systems for evaluating stimulus intensities.
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Affiliation(s)
- Leonardo L Gollo
- Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; Centre for Integrative Brain Function, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Mauro Copelli
- Departamento de Física, Universidade Federal de Pernambuco , Recife PE , Brazil
| | - James A Roberts
- Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; Centre for Integrative Brain Function, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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20
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Iyer KK, Roberts JA, Hellström-Westas L, Wikström S, Hansen Pupp I, Ley D, Vanhatalo S, Breakspear M. Cortical burst dynamics predict clinical outcome early in extremely preterm infants. Brain 2015; 138:2206-18. [PMID: 26001723 DOI: 10.1093/brain/awv129] [Citation(s) in RCA: 74] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2014] [Accepted: 03/19/2015] [Indexed: 01/15/2023] Open
Abstract
Intermittent bursts of electrical activity are a ubiquitous signature of very early brain activity. Previous studies have largely focused on assessing the amplitudes of these transient cortical bursts or the intervals between them. Recent advances in basic neuroscience have identified the presence of scale-free 'avalanche' processes in bursting patterns of cortical activity in other clinical contexts. Here, we hypothesize that cortical bursts in human preterm infants also exhibit scale-free properties, providing new insights into the nature, temporal evolution, and prognostic value of spontaneous brain activity in the days immediately following preterm birth. We examined electroencephalographic recordings from 43 extremely preterm infants (gestational age 22-28 weeks) and demonstrated that their cortical bursts exhibit scale-free properties as early as 12 h after birth. The scaling relationships of cortical bursts correlate significantly with later mental development-particularly within the first 12 h of life. These findings show that early preterm brain activity is characterized by scale-free dynamics which carry developmental significance, hence offering novel means for rapid and early clinical prediction of neurodevelopmental outcomes.
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Affiliation(s)
- Kartik K Iyer
- 1 Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia 2 School of Medicine, Faculty of Medicine and Biomedical Sciences, University of Queensland, Australia
| | - James A Roberts
- 1 Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Sverre Wikström
- 4 Department of Paediatrics, Karlstad Central Hospital, Sweden
| | - Ingrid Hansen Pupp
- 5 Department of Paediatrics, Institute for Clinical Sciences, Lund University, Lund, Sweden
| | - David Ley
- 5 Department of Paediatrics, Institute for Clinical Sciences, Lund University, Lund, Sweden
| | - Sampsa Vanhatalo
- 6 Department of Children's Clinical Neurophysiology, HUS Medical Imaging Centre, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland 7 Department of Paediatrics, Children's Hospital, University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Michael Breakspear
- 1 Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia 8 The Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
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21
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Williams-García RV, Moore M, Beggs JM, Ortiz G. Quasicritical brain dynamics on a nonequilibrium Widom line. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2014; 90:062714. [PMID: 25615136 DOI: 10.1103/physreve.90.062714] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2014] [Indexed: 06/04/2023]
Abstract
Is the brain really operating at a critical point? We study the nonequilibrium properties of a neural network which models the dynamics of the neocortex and argue for optimal quasicritical dynamics on the Widom line where the correlation length and information transmission are optimized. We simulate the network and introduce an analytical mean-field approximation, characterize the nonequilibrium phase transitions, and present a nonequilibrium phase diagram, which shows that in addition to an ordered and disordered phase, the system exhibits a "quasiperiodic" phase corresponding to synchronous activity in simulations, which may be related to the pathological synchronization associated with epilepsy.
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Affiliation(s)
| | - Mark Moore
- Department of Physics, Indiana University, Bloomington, Indiana 47405, USA
| | - John M Beggs
- Department of Physics, Indiana University, Bloomington, Indiana 47405, USA
| | - Gerardo Ortiz
- Department of Physics, Indiana University, Bloomington, Indiana 47405, USA
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22
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Seseña-Rubfiaro A, Echeverría JC, Godínez-Fernández JR. Fractal-like correlations of the fluctuating inter-spike membrane potential of a Helix aspersa pacemaker neuron. Comput Biol Med 2014; 53:258-64. [PMID: 25189698 DOI: 10.1016/j.compbiomed.2014.08.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2014] [Revised: 08/02/2014] [Accepted: 08/10/2014] [Indexed: 10/24/2022]
Abstract
We analyzed the voltage fluctuations of the membrane potential manifested along the inter-spike segment of a pacemaker neuron. Time series of intracellular inter-spike voltage fluctuations were obtained in the current-clamp configuration from the F1 neuron of 12 Helix aspersa specimens. To assess the dynamic or stochastic nature of the voltage fluctuations these series were analyzed by Detrended Fluctuation Analysis (DFA), providing the scaling exponent α. The median α result obtained for the inter-spike segments was 0.971 ([0.963, 0.995] lower and upper quartiles). Our results indicate a critical-like dynamic behavior in the inter-spike membrane potential that, far from being random, shows long-term correlations probably linked to the dynamics of the mechanisms involved in the regulation of the membrane potential, thereby endorsing the occurrence of critical-like phenomena at a single-neuron level.
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Affiliation(s)
- Alberto Seseña-Rubfiaro
- Electrical Engineering Department, Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco No. 186, Col. Vicentina, C.P. 09340 Iztapalapa, Mexico City, Mexico.
| | - Juan Carlos Echeverría
- Electrical Engineering Department, Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco No. 186, Col. Vicentina, C.P. 09340 Iztapalapa, Mexico City, Mexico.
| | - Jose Rafael Godínez-Fernández
- Electrical Engineering Department, Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco No. 186, Col. Vicentina, C.P. 09340 Iztapalapa, Mexico City, Mexico.
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