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Schilling A, Gerum R, Boehm C, Rasheed J, Metzner C, Maier A, Reindl C, Hamer H, Krauss P. Deep learning based decoding of single local field potential events. Neuroimage 2024; 297:120696. [PMID: 38909761 DOI: 10.1016/j.neuroimage.2024.120696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 06/12/2024] [Accepted: 06/18/2024] [Indexed: 06/25/2024] Open
Abstract
How is information processed in the cerebral cortex? In most cases, recorded brain activity is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. However, the brain is obviously a single-trial processor. Thus, we here demonstrate that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial basis. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both extra-cellular neural recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding.
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Affiliation(s)
- Achim Schilling
- Neuroscience Lab, University Hospital Erlangen, Germany; Cognitive Computational Neuroscience Group, University Erlangen-Nürnberg, Germany
| | - Richard Gerum
- Cognitive Computational Neuroscience Group, University Erlangen-Nürnberg, Germany; Department of Physics and Center for Vision Research, York University, Toronto, Canada
| | - Claudia Boehm
- Neuroscience Lab, University Hospital Erlangen, Germany; Cognitive Computational Neuroscience Group, University Erlangen-Nürnberg, Germany
| | - Jwan Rasheed
- Neuroscience Lab, University Hospital Erlangen, Germany; Cognitive Computational Neuroscience Group, University Erlangen-Nürnberg, Germany
| | - Claus Metzner
- Cognitive Computational Neuroscience Group, University Erlangen-Nürnberg, Germany; Pattern Recognition Lab, University Erlangen-Nürnberg, Germany
| | - Andreas Maier
- Pattern Recognition Lab, University Erlangen-Nürnberg, Germany
| | - Caroline Reindl
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Germany
| | - Hajo Hamer
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Germany
| | - Patrick Krauss
- Cognitive Computational Neuroscience Group, University Erlangen-Nürnberg, Germany; Pattern Recognition Lab, University Erlangen-Nürnberg, Germany.
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2
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Liu Y, Xu S, Deng Y, Luo J, Zhang K, Yang Y, Sha L, Hu R, Xu Z, Yin E, Xu Q, Wu Y, Cai X. SWCNTs/PEDOT:PSS nanocomposites-modified microelectrode arrays for revealing locking relations between burst and local field potential in cultured cortical networks. Biosens Bioelectron 2024; 253:116168. [PMID: 38452571 DOI: 10.1016/j.bios.2024.116168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 02/04/2024] [Accepted: 02/23/2024] [Indexed: 03/09/2024]
Abstract
Burst and local field potential (LFP) are fundamental components of brain activity, representing fast and slow rhythms, respectively. Understanding the intricate relationship between burst and LFP is crucial for deciphering the underlying mechanisms of brain dynamics. In this study, we fabricated high-performance microelectrode arrays (MEAs) using the SWCNTs/PEDOT:PSS nanocomposites, which exhibited favorable electrical properties (low impedance: 12.8 ± 2.44 kΩ) and minimal phase delay (-11.96 ± 1.64°). These MEAs enabled precise exploration of the burst-LFP interaction in cultured cortical networks. After a 14-day period of culture, we used the MEAs to monitor electrophysiological activities and revealed a time-locking relationship between burst and LFP, indicating the maturation of the neural network. To further investigate this relationship, we modulated burst firing patterns by treating the neural culture with increasing concentrations of glycine. The results indicated that glycine effectively altered burst firing patterns, with both duration and spike count increasing as the concentration rose. This was accompanied by an enhanced level of time-locking between burst and LFP but a decrease in synchrony among neurons. This study not only highlighted the pivotal role of SWCNTs/PEDOT:PSS-modified MEAs in elucidating the interaction between burst and LFP, bridging the gap between slow and fast brain rhythms in vitro but also provides valuable insights into the potential therapeutic strategies targeting neurological disorders associated with abnormal rhythm generation.
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Affiliation(s)
- Yaoyao Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Shihong Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Yu Deng
- State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Jinping Luo
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Kui Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Yan Yang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Longze Sha
- State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Ruilin Hu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Zhaojie Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Erwei Yin
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, 300450, China
| | - Qi Xu
- State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China.
| | - Yirong Wu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China.
| | - Xinxia Cai
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Science, Beijing, 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100149, China.
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3
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Abstract
The QBIT theory is a recently introduced multi-disciplinary approach to the problem of consciousness. One of the main axioms of the theory is that when information-theoretic certainty of an observer about a stimulus goes beyond a certain threshold, the observer becomes conscious of that stimulus. This axiom could provide an explanation for how the brain generates consciousness.In short, the QBIT theory suggests that the brain generates consciousness by reducing the entropy of its internal representations below a critical threshold. This paper explains how the brain gradually minimizes the entropy of its internal representations and consequently generate minimum-entropy representations (also known as conscious representations or qualia). The paper also explores the consequences of this entropy-minimization process in the context of quantum information theory.
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Affiliation(s)
- Majid Beshkar
- Tehran University of Medical Sciences, Tehran, Iran.
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4
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Saunders SE, Baekey DM, Levitt ES. Fentanyl effects on respiratory neuron activity in the dorsolateral pons. J Neurophysiol 2022; 128:1117-1132. [PMID: 36197016 PMCID: PMC9621704 DOI: 10.1152/jn.00113.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 09/09/2022] [Accepted: 10/03/2022] [Indexed: 11/22/2022] Open
Abstract
Opioids suppress breathing through actions in the brainstem, including respiratory-related areas of the dorsolateral pons, which contain multiple phenotypes of respiratory patterned neurons. The discharge identity of dorsolateral pontine neurons that are impacted by opioids is unknown. To address this, single neuronal units were recorded in the dorsolateral pons of arterially perfused in situ rat preparations that were perfused with an apneic concentration of the opioid agonist fentanyl, followed by the opioid antagonist naloxone (NLX). Dorsolateral pontine neurons were categorized based on respiratory-associated discharge patterns, which were differentially affected by fentanyl. Inspiratory neurons and a subset of inspiratory/expiratory phase-spanning neurons were either silenced or had reduced firing frequency during fentanyl-induced apnea, which was reversed upon administration of naloxone. In contrast, the majority of expiratory neurons continued to fire tonically during fentanyl-induced apnea, albeit with reduced firing frequency. In addition, pontine late-inspiratory and postinspiratory neuronal activity were absent from apneustic-like breaths during the transition to fentanyl-induced apnea and the naloxone-mediated transition to recovery. Thus, opioid-induced deficits in respiratory patterning may occur due to reduced activity of pontine inspiratory neurons, whereas apnea occurs with loss of all phasic pontine activity and sustained tonic expiratory neuron activity.NEW & NOTEWORTHY Opioids can suppress breathing via actions throughout the brainstem, including the dorsolateral pons. The respiratory phenotype of dorsolateral pontine neurons inhibited by opioids is unknown. Here, we describe the effect of the highly potent opioid fentanyl on the firing activity of these dorsolateral pontine neurons. Inspiratory neurons were largely silenced by fentanyl, whereas expiratory neurons were not. We provide a framework whereby this differential sensitivity to fentanyl can contribute to respiratory pattern deficits and apnea.
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Affiliation(s)
- Sandy E Saunders
- Department of Pharmacology and Therapeutics, University of Florida, Gainesville, Florida
- Center for Respiratory Research and Rehabilitation, University of Florida, Gainesville, Florida
| | - David M Baekey
- Department of Pharmacology and Therapeutics, University of Florida, Gainesville, Florida
- Center for Respiratory Research and Rehabilitation, University of Florida, Gainesville, Florida
| | - Erica S Levitt
- Department of Pharmacology and Therapeutics, University of Florida, Gainesville, Florida
- Center for Respiratory Research and Rehabilitation, University of Florida, Gainesville, Florida
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5
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Bant JS, Hardcastle K, Ocko SA, Giocomo LM. Topography in the Bursting Dynamics of Entorhinal Neurons. Cell Rep 2021; 30:2349-2359.e7. [PMID: 32075768 DOI: 10.1016/j.celrep.2020.01.057] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 11/28/2019] [Accepted: 01/17/2020] [Indexed: 12/18/2022] Open
Abstract
Medial entorhinal cortex contains neural substrates for representing space. These substrates include grid cells that fire in repeating locations and increase in scale progressively along the dorsal-to-ventral entorhinal axis, with the physical distance between grid firing nodes increasing from tens of centimeters to several meters in rodents. Whether the temporal scale of grid cell spiking dynamics shows a similar dorsal-to-ventral organization remains unknown. Here, we report the presence of a dorsal-to-ventral gradient in the temporal spiking dynamics of grid cells in behaving mice. This gradient in bursting supports the emergence of a dorsal grid cell population with a high signal-to-noise ratio. In vitro recordings combined with a computational model point to a role for gradients in non-inactivating sodium conductances in supporting the bursting gradient in vivo. Taken together, these results reveal a complementary organization in the temporal and intrinsic properties of entorhinal cells.
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Affiliation(s)
- Jason S Bant
- Department of Neurobiology, Stanford University School of Medicine, Stanford CA 94305, USA
| | - Kiah Hardcastle
- Department of Neurobiology, Stanford University School of Medicine, Stanford CA 94305, USA
| | - Samuel A Ocko
- Department of Applied Physics, Stanford University, Stanford CA 94305, USA
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University School of Medicine, Stanford CA 94305, USA.
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6
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Hao W, Liu S, Liu H, Mu X, Chen K, Xin Q, Zhang XD. In Vivo Neuroelectrophysiological Monitoring of Atomically Precise Au 25 Clusters at an Ultrahigh Injected Dose. ACS OMEGA 2020; 5:24537-24545. [PMID: 33015471 PMCID: PMC7528291 DOI: 10.1021/acsomega.0c03005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 09/04/2020] [Indexed: 05/14/2023]
Abstract
Atomically precise Au25(SG)18 clusters have shown great promise in near-infrared II cerebrovascular imaging, X-ray imaging, and cancer radiotherapy due to their high atomic number, unique molecular-like electronic structure, and renal clearable properties. Therefore, it is important to study the in vivo toxicity of Au25 clusters. Unfortunately, previous toxicological investigations focused on low injected doses (<100 mg kg-1) and routine research methods, such as blood chemistry and biochemistry, which cannot reflect neurotoxicity or tiny changes in neural activity. In this work, in vivo neuroelectrophysiology of Au25 clusters at ultrahigh injected doses (200, 300, and 500 mg kg-1) was investigated. Local field potential showed that the Au25-treated mice showed a spike in delta rhythm and moved to lower frequency over time. The power spectrum showed a 38.3% reduction in the peak value at 10 h post-injection of Au25 clusters compared with 3 h post-injection, which gradually became close to the normal level, indicating no permanent damage to the nervous system. Moreover, no significant structural changes were found in both neurons and glial cells at the histological level. These results of in vivo neuroelectrophysiology will encourage scientists to make more exciting discoveries on nervous system diseases by employing Au25 clusters even at ultrahigh injected doses.
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Affiliation(s)
- Wenting Hao
- Tianjin
International Joint Research Center for Neural Engineering, Academy
of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China
| | - Shuangjie Liu
- Tianjin
International Joint Research Center for Neural Engineering, Academy
of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China
| | - Haile Liu
- Tianjin
Key Laboratory of Low Dimensional Materials Physics and Preparing
Technology, Institute of Advanced Materials Physics, School of Sciences, Tianjin University, Tianjin 300350, China
| | - Xiaoyu Mu
- Tianjin
Key Laboratory of Low Dimensional Materials Physics and Preparing
Technology, Institute of Advanced Materials Physics, School of Sciences, Tianjin University, Tianjin 300350, China
| | - Ke Chen
- Tianjin
Key Laboratory of Low Dimensional Materials Physics and Preparing
Technology, Institute of Advanced Materials Physics, School of Sciences, Tianjin University, Tianjin 300350, China
| | - Qi Xin
- Tianjin
International Joint Research Center for Neural Engineering, Academy
of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China
- Department
of Pathology, Tianjin Third Central Hospital, Tianjin Key Laboratory
of Extracorporeal Life Support for Critical Diseases, Tianjin Third Central Hospital affiliated to Nankai University, Tianjin 300170, China
| | - Xiao-Dong Zhang
- Tianjin
International Joint Research Center for Neural Engineering, Academy
of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China
- Tianjin
Key Laboratory of Low Dimensional Materials Physics and Preparing
Technology, Institute of Advanced Materials Physics, School of Sciences, Tianjin University, Tianjin 300350, China
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7
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Mouchati PR, Kloc ML, Holmes GL, White SL, Barry JM. Optogenetic "low-theta" pacing of the septohippocampal circuit is sufficient for spatial goal finding and is influenced by behavioral state and cognitive demand. Hippocampus 2020; 30:1167-1193. [PMID: 32710688 DOI: 10.1002/hipo.23248] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 06/04/2020] [Accepted: 06/20/2020] [Indexed: 12/21/2022]
Abstract
Hippocampal theta oscillations show prominent changes in frequency and amplitude depending on behavioral state or cognitive demands. How these dynamic changes in theta oscillations contribute to the spatial and temporal organization of hippocampal cells, and ultimately behavior, remain unclear. We used low-theta frequency optogenetic stimulation to pace coordination of cellular and network activity between the medial septum (MS) and hippocampus during baseline and MS stimulation while rats were at rest or performing a spatial accuracy task with a visible or hidden goal zone. Hippocampal receptivity to pan-neuronal septal stimulation at low-theta frequency was primarily determined by speed and secondarily by task demands. Competition between artificial and endogenous field potentials at theta frequency attenuated hippocampal phase preference relative to local theta, but the spike-timing activity of hippocampal pyramidal cells was effectively driven by artificial septal output, particularly during the hidden goal task. Notwithstanding temporal reorganization by artificial theta stimulation, place field properties were unchanged and alterations to spatial behavior were limited to goal zone approximation. Our results indicate that even a low-theta frequency timing signal in the septohippocampal circuit is sufficient for spatial goal finding behavior. The results also advance a mechanistic understanding of how endogenous or artificial somatodendritic timing signals relate to displacement computations during navigation and spatial memory.
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Affiliation(s)
- Philippe R Mouchati
- Epilepsy Cognition and Development Group, Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, Vermont, USA
| | - Michelle L Kloc
- Epilepsy Cognition and Development Group, Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, Vermont, USA
| | - Gregory L Holmes
- Epilepsy Cognition and Development Group, Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, Vermont, USA
| | - Sheryl L White
- Epilepsy Cognition and Development Group, Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, Vermont, USA
| | - Jeremy M Barry
- Epilepsy Cognition and Development Group, Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, Vermont, USA
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8
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Abstract
The entorhinal cortex (EC) is a critical element of the hippocampal formation located within the medial temporal lobe (MTL) in primates. The EC has historically received attention for being the primary mediator of cortical information going into and coming from the hippocampus proper. In this review, we highlight the significance of the EC as a major player in memory processing, along with other associated structures in the primate MTL. The complex, convergent topographies of cortical and subcortical input to the EC, combined with short-range intrinsic connectivity and the selective targeting of EC efferents to the hippocampus, provide evidence for subregional specialization and integration of information beyond what would be expected if this structure were a simple conduit of information for the hippocampus. Lesion studies of the EC provide evidence implicating this region as critical for memory and the flexible use of complex relational associations between experienced events. The physiology of this structure's constituent principal cells mirrors the complexity of its anatomy. EC neurons respond preferentially to aspects of memory-dependent paradigms including object, place, and time. EC neurons also show striking spatial representations as primates explore visual space, similar to those identified in rodents navigating physical space. In this review, we highlight the great strides that have been made toward furthering our understanding of the primate EC, and we identify paths forward for future experiments to provide additional insight into the role of this structure in learning and memory.
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Affiliation(s)
- Aaron D Garcia
- Graduate Program in Neuroscience, University of Washington, Seattle, Washington 98195, USA.,Department of Physiology and Biophysics, School of Medicine, University of Washington, Seattle, Washington 98195, USA;
| | - Elizabeth A Buffalo
- Department of Physiology and Biophysics, School of Medicine, University of Washington, Seattle, Washington 98195, USA; .,Washington National Primate Research Center, University of Washington, Seattle, Washington 98195, USA
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9
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Ghosh S, Mondal A, Ji P, Mishra A, Dana SK, Antonopoulos CG, Hens C. Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling. Front Comput Neurosci 2020; 14:49. [PMID: 32581757 PMCID: PMC7294985 DOI: 10.3389/fncom.2020.00049] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 05/04/2020] [Indexed: 11/21/2022] Open
Abstract
In this paper, we focus on the emergence of diverse neuronal oscillations arising in a mixed population of neurons with different excitability properties. These properties produce mixed mode oscillations (MMOs) characterized by the combination of large amplitudes and alternate subthreshold or small amplitude oscillations. Considering the biophysically plausible, Izhikevich neuron model, we demonstrate that various MMOs, including MMBOs (mixed mode bursting oscillations) and synchronized tonic spiking appear in a randomly connected network of neurons, where a fraction of them is in a quiescent (silent) state and the rest in self-oscillatory (firing) states. We show that MMOs and other patterns of neural activity depend on the number of oscillatory neighbors of quiescent nodes and on electrical coupling strengths. Our results are verified by constructing a reduced-order network model and supported by systematic bifurcation diagrams as well as for a small-world network. Our results suggest that, for weak couplings, MMOs appear due to the de-synchronization of a large number of quiescent neurons in the networks. The quiescent neurons together with the firing neurons produce high frequency oscillations and bursting activity. The overarching goal is to uncover a favorable network architecture and suitable parameter spaces where Izhikevich model neurons generate diverse responses ranging from MMOs to tonic spiking.
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Affiliation(s)
- Subrata Ghosh
- Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata, India
| | - Argha Mondal
- Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata, India
| | - Peng Ji
- The Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Arindam Mishra
- Department of Mathematics, Centre for Mathematical Biology and Ecology, Jadavpur University, Kolkata, India
| | - Syamal K Dana
- Department of Mathematics, Centre for Mathematical Biology and Ecology, Jadavpur University, Kolkata, India.,Division of Dynamics, Faculty of Mechanical Engineering, Lodz University of Technology, Lodz, Poland
| | - Chris G Antonopoulos
- Department of Mathematical Sciences, University of Essex, Colchester, United Kingdom
| | - Chittaranjan Hens
- Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata, India
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10
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Hussin AT, Leonard TK, Hoffman KL. Sharp-wave ripple features in macaques depend on behavioral state and cell-type specific firing. Hippocampus 2018; 30:50-59. [PMID: 30371963 PMCID: PMC7004038 DOI: 10.1002/hipo.23046] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 09/24/2018] [Accepted: 10/17/2018] [Indexed: 12/20/2022]
Abstract
Sharp-wave ripples (SWRs) are spontaneous, synchronized neural population events in the hippocampus widely thought to play a role in memory consolidation and retrieval. They occur predominantly in sleep and quiet immobility, and in primates, they also appear during active visual exploration. Typical measures of SWRs in behaving rats include changes in the rate of occurrence, or in the incidence of specific neural ensemble activity contained within the categorical SWR event. Much less is known about the relevance of spatiotemporal SWR features, though they may index underlying activity of specific cell types including ensemble-specific internally generated sequences. Furthermore, changes in SWR features during active exploratory states are unknown. In this study, we recorded hippocampal local-field potentials and single-units during periods of quiescence and as macaques performed a memory-guided visual search task. We observed that (a) ripples during quiescence have greater amplitudes and larger postripple waves (PRW) compared to those in task epochs, and (b) during "remembered" trials, ripples have larger amplitudes than during "forgotten" trials, with no change in duration or PRWs. We further found that spiking activity influences SWR features as a function of cell type and ripple timing. As expected, larger ripple amplitudes were associated with putative pyramidal or putative basket interneuron (IN) activity, even when the spikes in question exceed the duration of the ripple. In contrast, the PRW was attenuated with activity from low firing rate cells and enhanced with activity from high firing rate cells, with putative IN spikes during ripples leading to the most prominent PRW peaks. The selective changes in SWR features as a function of time window, cell type, and cognitive/vigilance states suggest that this mesoscopic field event can offer additional information about the local network and animal's state than would be appreciated from SWR event rates alone.
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Affiliation(s)
- Ahmed T Hussin
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario, Canada
| | - Timothy K Leonard
- Department of Psychology, Centre for Vision Research, York University, Toronto, Ontario, Canada
| | - Kari L Hoffman
- Department of Psychology, Centre for Vision Research, York University, Toronto, Ontario, Canada.,Department of Psychology, Center for Integrative and Cognitive Neuroscience, Vanderbilt Vision Research Center, Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee
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11
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Maidana Capitán MB, Kropff E, Samengo I. Information-Theoretical Analysis of the Neural Code in the Rodent Temporal Lobe. ENTROPY 2018; 20:e20080571. [PMID: 33265660 PMCID: PMC7513095 DOI: 10.3390/e20080571] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 07/12/2018] [Accepted: 07/25/2018] [Indexed: 11/20/2022]
Abstract
In the study of the neural code, information-theoretical methods have the advantage of making no assumptions about the probabilistic mapping between stimuli and responses. In the sensory domain, several methods have been developed to quantify the amount of information encoded in neural activity, without necessarily identifying the specific stimulus or response features that instantiate the code. As a proof of concept, here we extend those methods to the encoding of kinematic information in a navigating rodent. We estimate the information encoded in two well-characterized codes, mediated by the firing rate of neurons, and by the phase-of-firing with respect to the theta-filtered local field potential. In addition, we also consider a novel code, mediated by the delta-filtered local field potential. We find that all three codes transmit significant amounts of kinematic information, and informative neurons tend to employ a combination of codes. Cells tend to encode conjunctions of kinematic features, so that most of the informative neurons fall outside the traditional cell types employed to classify spatially-selective units. We conclude that a broad perspective on the candidate stimulus and response features expands the repertoire of strategies with which kinematic information is encoded.
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Affiliation(s)
- Melisa B. Maidana Capitán
- Departament of Medical Physics, Centro Atómico Bariloche and Instituto Balseiro, Comisión Nacional de Energía Atómica, Consejo Nacional de Investigaciones Científicas y Técnicas, 8400 San Carlos de Bariloche, Argentina
| | - Emilio Kropff
- Fundación Instituto Leloir, Consejo Nacional de Investigaciones Científicas y Técnicas, 1425 Buenos Aires, Argentina
| | - Inés Samengo
- Departament of Medical Physics, Centro Atómico Bariloche and Instituto Balseiro, Comisión Nacional de Energía Atómica, Consejo Nacional de Investigaciones Científicas y Técnicas, 8400 San Carlos de Bariloche, Argentina
- Correspondence: ; Tel.: +54-294-444-5100
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12
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Zeldenrust F, Wadman WJ, Englitz B. Neural Coding With Bursts-Current State and Future Perspectives. Front Comput Neurosci 2018; 12:48. [PMID: 30034330 PMCID: PMC6043860 DOI: 10.3389/fncom.2018.00048] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Accepted: 06/06/2018] [Indexed: 12/11/2022] Open
Abstract
Neuronal action potentials or spikes provide a long-range, noise-resistant means of communication between neurons. As point processes single spikes contain little information in themselves, i.e., outside the context of spikes from other neurons. Moreover, they may fail to cross a synapse. A burst, which consists of a short, high frequency train of spikes, will more reliably cross a synapse, increasing the likelihood of eliciting a postsynaptic spike, depending on the specific short-term plasticity at that synapse. Both the number and the temporal pattern of spikes in a burst provide a coding space that lies within the temporal integration realm of single neurons. Bursts have been observed in many species, including the non-mammalian, and in brain regions that range from subcortical to cortical. Despite their widespread presence and potential relevance, the uncertainties of how to classify bursts seems to have limited the research into the coding possibilities for bursts. The present series of research articles provides new insights into the relevance and interpretation of bursts across different neural circuits, and new methods for their analysis. Here, we provide a succinct introduction to the history of burst coding and an overview of recent work on this topic.
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Affiliation(s)
- Fleur Zeldenrust
- Department of Neurophysiology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Wytse J Wadman
- Cellular and Systems Neurobiology Lab, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Bernhard Englitz
- Department of Neurophysiology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands
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