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Weber I, Florin E, von Papen M, Visser-Vandewalle V, Timmermann L. Characterization of information processing in the subthalamic area of Parkinson’s patients. Neuroimage 2020; 209:116518. [DOI: 10.1016/j.neuroimage.2020.116518] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 12/19/2019] [Accepted: 01/02/2020] [Indexed: 12/21/2022] Open
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Darbin O, Hatanaka N, Takara S, Kaneko N, Chiken S, Naritoku D, Martino A, Nambu A. Parkinsonism Differently Affects the Single Neuronal Activity in the Primary and Supplementary Motor Areas in Monkeys: An Investigation in Linear and Nonlinear Domains. Int J Neural Syst 2020; 30:2050010. [PMID: 32019380 DOI: 10.1142/s0129065720500100] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The changes in neuronal firing activity in the primary motor cortex (M1) and supplementary motor area (SMA) were compared in monkeys rendered parkinsonian by treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The neuronal dynamic was characterized using mathematical tools defined in different frameworks (rate, oscillations or complex patterns). Then, and for each cortical area, multivariate and discriminate analyses were further performed on these features to identify those important to differentiate between the normal and the pathological neuronal activity. Our results show a different order in the importance of the features to discriminate the pathological state in each cortical area which suggests that the M1 and the SMA exhibit dissimilarities in their neuronal alterations induced by parkinsonism. Our findings highlight the need for multiple mathematical frameworks to best characterize the pathological neuronal activity related to parkinsonism. Future translational studies are warranted to investigate the causal relationships between cortical region-specificities, dominant pathological hallmarks and symptoms.
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Affiliation(s)
- Olivier Darbin
- Department of Neurology, University South Alabama, 307 University Blvd, Mobile, AL 36688, USA
| | - Nobuhiko Hatanaka
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
| | - Sayuki Takara
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
| | - Nobuya Kaneko
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
| | - Satomi Chiken
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
| | - Dean Naritoku
- Department of Neurology, University South Alabama, 307 University Blvd, Mobile, AL 36688, USA
| | - Anthony Martino
- Department of Neurology, University South Alabama, 307 University Blvd, Mobile, AL 36688, USA
| | - Atsushi Nambu
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
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Andres D. On the Motion of Spikes: Turbulent-Like Neuronal Activity in the Human Basal Ganglia. Front Hum Neurosci 2018; 12:429. [PMID: 30405381 PMCID: PMC6207592 DOI: 10.3389/fnhum.2018.00429] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 10/02/2018] [Indexed: 12/03/2022] Open
Abstract
Neuronal signals are usually characterized in terms of their discharge rate, a description inadequate to account for the complex temporal organization of spike trains. Complex temporal properties, which are characteristic of neuronal systems, can only be described with the appropriate, complex mathematical tools. Here, I apply high order structure functions to the analysis of neuronal signals recorded from parkinsonian patients during functional neurosurgery, recovering multifractal properties. To achieve an accurate model of such multifractality is critical for understanding the basal ganglia, since other non-linear properties, such as entropy, depend on the fractal properties of complex systems. I propose a new approach to the study of neuronal signals: to study spiking activity in terms of the velocity of spikes, defining it as the inverse function of the instantaneous frequency. I introduce a neural field model that includes a non-linear gradient field, representing neuronal excitability, and a diffusive term to consider the physical properties of the electric field. Multifractality is present in the model for a range of diffusion coefficients, and multifractal temporal properties are mirrored into space. The model reproduces the behavior of human basal ganglia neurons and shows that it is like that of turbulent fluids. The results obtained from the model predict that passive electric properties of neuronal activity, including ephaptic coupling, are far more relevant to the human brain than what is usually considered: passive electric properties determine the temporal and spatial organization of neuronal activity in the neural tissue.
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Affiliation(s)
- Daniela Andres
- Science and Technology School, National University of San Martin, Buenos Aires, Argentina
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Nanni F, Andres DS. Structure Function Revisited: A Simple Tool for Complex Analysis of Neuronal Activity. Front Hum Neurosci 2017; 11:409. [PMID: 28855866 PMCID: PMC5557788 DOI: 10.3389/fnhum.2017.00409] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 07/25/2017] [Indexed: 11/13/2022] Open
Abstract
Neural systems are characterized by their complex dynamics, reflected on signals produced by neurons and neuronal ensembles. This complexity exhibits specific features in health, disease and in different states of consciousness, and can be considered a hallmark of certain neurologic and neuropsychiatric conditions. To measure complexity from neurophysiologic signals, a number of different nonlinear tools of analysis are available. However, not all of these tools are easy to implement, or able to handle clinical data, often obtained in less than ideal conditions in comparison to laboratory or simulated data. Recently, the temporal structure function emerged as a powerful tool for the analysis of complex properties of neuronal activity. The temporal structure function is efficient computationally and it can be robustly estimated from short signals. However, the application of this tool to neuronal data is relatively new, making the interpretation of results difficult. In this methods paper we describe a step by step algorithm for the calculation and characterization of the structure function. We apply this algorithm to oscillatory, random and complex toy signals, and test the effect of added noise. We show that: (1) the mean slope of the structure function is zero in the case of random signals; (2) oscillations are reflected on the shape of the structure function, but they don't modify the mean slope if complex correlations are absent; (3) nonlinear systems produce structure functions with nonzero slope up to a critical point, where the function turns into a plateau. Two characteristic numbers can be extracted to quantify the behavior of the structure function in the case of nonlinear systems: (1). the point where the plateau starts (the inflection point, where the slope change occurs), and (2). the height of the plateau. While the inflection point is related to the scale where correlations weaken, the height of the plateau is related to the noise present in the signal. To exemplify our method we calculate structure functions of neuronal recordings from the basal ganglia of parkinsonian and healthy rats, and draw guidelines for their interpretation in light of the results obtained from our toy signals.
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Affiliation(s)
| | - Daniela S. Andres
- Science and Technology School, National University of San Martin (UNSAM)San Martin, Argentina
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Darbin O, Jin X, Von Wrangel C, Schwabe K, Nambu A, Naritoku DK, Krauss JK, Alam M. Neuronal Entropy-Rate Feature of Entopeduncular Nucleus in Rat Model of Parkinson's Disease. Int J Neural Syst 2015; 26:1550038. [PMID: 26711712 DOI: 10.1142/s0129065715500380] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus, i.e. the entopeduncular nucleus (EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson's disease (PD). In both control subjects and subjects with 6-OHDA lesion of dopamine (DA) the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15 and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25 Hz. Our data establishes that the nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions such as movement disorders.
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Affiliation(s)
- Olivier Darbin
- 1 Department of Neurology, University South Alabama, 307 University Blvd., Mobile, AL 36688, USA.,2 Division of System Neurophysiology, National Institute for Physiological Sciences, Okazaki, 444-8585, Japan.,3 Animal Resource Program, University Alabama at Birmingham, Birmingham, AL, USA
| | - Xingxing Jin
- 4 Department of Neurosurgery, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany
| | - Christof Von Wrangel
- 4 Department of Neurosurgery, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany
| | - Kerstin Schwabe
- 4 Department of Neurosurgery, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany
| | - Atsushi Nambu
- 2 Division of System Neurophysiology, National Institute for Physiological Sciences, Okazaki, 444-8585, Japan.,5 Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), Okazaki, 444-8585, Japan
| | - Dean K Naritoku
- 1 Department of Neurology, University South Alabama, 307 University Blvd., Mobile, AL 36688, USA
| | - Joachim K Krauss
- 4 Department of Neurosurgery, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany
| | - Mesbah Alam
- 4 Department of Neurosurgery, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany
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Andres DS, Cerquetti D, Merello M. Neural code alterations and abnormal time patterns in Parkinson's disease. J Neural Eng 2015; 12:026004. [PMID: 25629221 DOI: 10.1088/1741-2560/12/2/026004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The neural code used by the basal ganglia is a current question in neuroscience, relevant for the understanding of the pathophysiology of Parkinson's disease. While a rate code is known to participate in the communication between the basal ganglia and the motor thalamus/cortex, different lines of evidence have also favored the presence of complex time patterns in the discharge of the basal ganglia. To gain insight into the way the basal ganglia code information, we studied the activity of the globus pallidus pars interna (GPi), an output node of the circuit. APPROACH We implemented the 6-hydroxydopamine model of Parkinsonism in Sprague-Dawley rats, and recorded the spontaneous discharge of single GPi neurons, in head-restrained conditions at full alertness. Analyzing the temporal structure function, we looked for characteristic scales in the neuronal discharge of the GPi. MAIN RESULTS At a low-scale, we observed the presence of dynamic processes, which allow the transmission of time patterns. Conversely, at a middle-scale, stochastic processes force the use of a rate code. Regarding the time patterns transmitted, we measured the word length and found that it is increased in Parkinson's disease. Furthermore, it showed a positive correlation with the frequency of discharge, indicating that an exacerbation of this abnormal time pattern length can be expected, as the dopamine depletion progresses. SIGNIFICANCE We conclude that a rate code and a time pattern code can co-exist in the basal ganglia at different temporal scales. However, their normal balance is progressively altered and replaced by pathological time patterns in Parkinson's disease.
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Affiliation(s)
- Daniela Sabrina Andres
- Institute of Neuroinformatics, ETH and University Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland. Institute for Neurological Research Raul Carrea, Fleni Institute, Movement Disorders section, Montañeses 2325, 1428, Buenos Aires, Argentina
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Andres DS, Cerquetti D, Merello M, Stoop R. Neuronal Entropy Depends on the Level of Alertness in the Parkinsonian Globus Pallidus in vivo. Front Neurol 2014; 5:96. [PMID: 25009529 PMCID: PMC4069479 DOI: 10.3389/fneur.2014.00096] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2014] [Accepted: 05/31/2014] [Indexed: 12/02/2022] Open
Abstract
A new working hypothesis of Parkinson's disease (PD) proposes to focus on the central role of entropy increase in the basal ganglia (BG) in movement disorders. The conditions necessary for entropy increase in vivo are, however, still not fully described. We recorded the activity of single globus pallidus pars interna neurons during the transition from deep anesthesia to full alertness in relaxed, head-restrained, control, and parkinsonian (6-hydroxydopamine-lesioned group-lesioned) rats. We found that during awakening from anesthesia, the variation of neuronal entropy was significantly higher in the parkinsonian than in the control group. This implies in our view that in PD the entropy of the output neurons of the BG varies dynamically with the input to the network, which is determined by the level of alertness. Therefore, entropy needs to be interpreted as a dynamic, emergent property that characterizes the global state of the BG neuronal network, rather than a static property of parkinsonian neurons themselves. Within the framework of the "entropy hypothesis," this implies the presence of a pathological feedback loop in the parkinsonian BG, where increasing the network input results in a further increase of neuronal entropy and a worsening of akinesia.
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Affiliation(s)
- Daniela Sabrina Andres
- Institute of Neuroinformatics, ETH Zurich and University of Zurich, Zurich, Switzerland
- Movement Disorders Section, Institute for Neurological Research Raul Carrea, Fleni Institute, Buenos Aires, Argentina
- Society in Science, The Branco-Weiss Fellowship, ETH Zurich, Zurich, Switzerland
| | - Daniel Cerquetti
- Movement Disorders Section, Institute for Neurological Research Raul Carrea, Fleni Institute, Buenos Aires, Argentina
| | - Marcelo Merello
- Movement Disorders Section, Institute for Neurological Research Raul Carrea, Fleni Institute, Buenos Aires, Argentina
| | - Ruedi Stoop
- Institute of Neuroinformatics, ETH Zurich and University of Zurich, Zurich, Switzerland
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Wang R, Wang J, Deng B, Liu C, Wei X, Tsang KM, Chan WL. A combined method to estimate parameters of the thalamocortical model from a heavily noise-corrupted time series of action potential. CHAOS (WOODBURY, N.Y.) 2014; 24:013128. [PMID: 24697390 DOI: 10.1063/1.4867658] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
A combined method composing of the unscented Kalman filter (UKF) and the synchronization-based method is proposed for estimating electrophysiological variables and parameters of a thalamocortical (TC) neuron model, which is commonly used for studying Parkinson's disease for its relay role of connecting the basal ganglia and the cortex. In this work, we take into account the condition when only the time series of action potential with heavy noise are available. Numerical results demonstrate that not only this method can estimate model parameters from the extracted time series of action potential successfully but also the effect of its estimation is much better than the only use of the UKF or synchronization-based method, with a higher accuracy and a better robustness against noise, especially under the severe noise conditions. Considering the rather important role of TC neuron in the normal and pathological brain functions, the exploration of the method to estimate the critical parameters could have important implications for the study of its nonlinear dynamics and further treatment of Parkinson's disease.
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Affiliation(s)
- Ruofan Wang
- Department of Electrical and Automation Engineering, Tianjin University, Tianjin, China
| | - Jiang Wang
- Department of Electrical and Automation Engineering, Tianjin University, Tianjin, China
| | - Bin Deng
- Department of Electrical and Automation Engineering, Tianjin University, Tianjin, China
| | - Chen Liu
- Department of Electrical and Automation Engineering, Tianjin University, Tianjin, China
| | - Xile Wei
- Department of Electrical and Automation Engineering, Tianjin University, Tianjin, China
| | - K M Tsang
- Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - W L Chan
- Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong
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Liu C, Wang J, Chen YY, Deng B, Wei XL, Li HY. Closed-loop control of the thalamocortical relay neuron's Parkinsonian state based on slow variable. Int J Neural Syst 2013; 23:1350017. [PMID: 23746290 DOI: 10.1142/s0129065713500172] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
A novel closed-loop control strategy is proposed to control Parkinsonian state based on a computational model. By modeling thalamocortical relay neurons under external electric field, a slow variable feedback control is applied to restore its relay functionality. Qualitative and quantitative analysis demonstrates the performance of feedback controller based on slow variable is more efficient compared with traditional feedback control based on fast variable. These findings point to the potential value of model-based design of feedback controllers for Parkinson's disease.
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Affiliation(s)
- Chen Liu
- School of Electrical Engineering and Automation, Tianjin University, Tianjin, China.
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An entropy-based model for basal ganglia dysfunctions in movement disorders. BIOMED RESEARCH INTERNATIONAL 2013; 2013:742671. [PMID: 23762856 PMCID: PMC3671275 DOI: 10.1155/2013/742671] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Accepted: 05/06/2013] [Indexed: 11/18/2022]
Abstract
During this last decade, nonlinear analyses have been used to characterize the irregularity that exists in the neuronal data stream of the basal ganglia. In comparison to linear parameters for disparity (i.e., rate, standard deviation, and oscillatory activities), nonlinear analyses focus on complex patterns that are composed of groups of interspike intervals with matching lengths but not necessarily contiguous in the data stream. In light of recent animal and clinical studies, we present a review and commentary on the basal ganglia neuronal entropy in the context of movement disorders.
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Ortiz-Rosario A, Adeli H. Brain-computer interface technologies: from signal to action. Rev Neurosci 2013; 24:537-52. [PMID: 24077619 DOI: 10.1515/revneuro-2013-0032] [Citation(s) in RCA: 123] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2013] [Accepted: 08/21/2013] [Indexed: 01/08/2023]
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