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Nair SS, Chakravarthy S. A Computational Model of Deep Brain Stimulation for Parkinson's Disease Tremor and Bradykinesia. Brain Sci 2024; 14:620. [PMID: 38928620 PMCID: PMC11201485 DOI: 10.3390/brainsci14060620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/05/2024] [Accepted: 06/17/2024] [Indexed: 06/28/2024] Open
Abstract
Parkinson's disease (PD) is a progressive neurological disorder that is typically characterized by a range of motor dysfunctions, and its impact extends beyond physical abnormalities into emotional well-being and cognitive symptoms. The loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) leads to an array of dysfunctions in the functioning of the basal ganglia (BG) circuitry that manifests into PD. While active research is being carried out to find the root cause of SNc cell death, various therapeutic techniques are used to manage the symptoms of PD. The most common approach in managing the symptoms is replenishing the lost dopamine in the form of taking dopaminergic medications such as levodopa, despite its long-term complications. Another commonly used intervention for PD is deep brain stimulation (DBS). DBS is most commonly used when levodopa medication efficacy is reduced, and, in combination with levodopa medication, it helps reduce the required dosage of medication, prolonging the therapeutic effect. DBS is also a first choice option when motor complications such as dyskinesia emerge as a side effect of medication. Several studies have also reported that though DBS is found to be effective in suppressing severe motor symptoms such as tremors and rigidity, it has an adverse effect on cognitive capabilities. Henceforth, it is important to understand the exact mechanism of DBS in alleviating motor symptoms. A computational model of DBS stimulation for motor symptoms will offer great insights into understanding the mechanisms underlying DBS, and, along this line, in our current study, we modeled a cortico-basal ganglia circuitry of arm reaching, where we simulated healthy control (HC) and PD symptoms as well as the DBS effect on PD tremor and bradykinesia. Our modeling results reveal that PD tremors are more correlated with the theta band, while bradykinesia is more correlated with the beta band of the frequency spectrum of the local field potential (LFP) of the subthalamic nucleus (STN) neurons. With a DBS current of 220 pA, 130 Hz, and a 100 microsecond pulse-width, we could found the maximum therapeutic effect for the pathological dynamics simulated using our model using a set of parameter values. However, the exact DBS characteristics vary from patient to patient, and this can be further studied by exploring the model parameter space. This model can be extended to study different DBS targets and accommodate cognitive dynamics in the future to study the impact of DBS on cognitive symptoms and thereby optimize the parameters to produce optimal performance effects across modalities. Combining DBS with rehabilitation is another frontier where DBS can reduce symptoms such as tremors and rigidity, enabling patients to participate in their therapy. With DBS providing instant relief to patients, a combination of DBS and rehabilitation can enhance neural plasticity. One of the key motivations behind combining DBS with rehabilitation is to expect comparable results in motor performance even with milder DBS currents.
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Affiliation(s)
| | - Srinivasa Chakravarthy
- Department of Biotechnology, Bhupat and Mehta Jyoti School of Biosciences, Chennai 600036, India;
- Department of Medical Science and Technology, Indian Institute of Technology Madras, Sardar Patel Road, Adyar, Chennai 600036, India
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2
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Cunha GM, Corso G, Lima MMS, Dos Santos Lima GZ. Electrophysiological damage to neuronal membrane alters ephaptic entrainment. Sci Rep 2023; 13:11974. [PMID: 37488148 PMCID: PMC10366241 DOI: 10.1038/s41598-023-38738-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 07/13/2023] [Indexed: 07/26/2023] Open
Abstract
The brain is commonly understood as a complex network system with a particular organization and topology that can result in specific electrophysiological patterns. Among all the dynamic elements resulting from the circuits of the brain's network, ephapticity is a cellular communication mechanism that has received little attention. To understand the network's properties of ephaptic entrainment, we start investigating the ephaptic effect on a single neuron. In this study, we used numerical simulations to examine the relationship between alterations in ephaptic neuronal entrainment and impaired electrophysiological properties of the neuronal membrane, which can occur via spike field coherence (SFC). This change in frequency band amplitude is observed in some neurodegenerative diseases, such as Parkinson's or Alzheimer's. To further investigate these phenomena, we proposed a damaged model based on the impairment of both the resistance of the ion channels and the capacitance of the lipid membrane. Therefore, we simulated ephaptic entrainment with the hybrid neural model quadratic integrate-and-fire ephaptic (QIF-E), which mimics an ephaptic entrainment generated by an LFP (simulate a neuronal group). Our results indicate a link between peak entrainment (ephapticity) preference and a shift in frequency band when damage occurs mainly in ion channels. Finally, we discuss possible relationships between ephaptic entrainment and neurodegenerative diseases associated with aging factors.
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Affiliation(s)
- Gabriel Moreno Cunha
- Departamento de Física Teórica e Experimental, Universidade Federal do Rio Grande do Norte, Natal, RN, 59078-970, Brazil
| | - Gilberto Corso
- Departamento de Física Teórica e Experimental, Universidade Federal do Rio Grande do Norte, Natal, RN, 59078-970, Brazil
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59078-970, Brazil
| | - Marcelo M S Lima
- Departamento de Fisiologia, Universidade Federal do Paraná, Curitiba, PR, 81531-980, Brazil
- Departamento de Farmacologia, Universidade Federal do Paraná, Curitiba, PR, 81531-980, Brazil
| | - Gustavo Zampier Dos Santos Lima
- Departamento de Física Teórica e Experimental, Universidade Federal do Rio Grande do Norte, Natal, RN, 59078-970, Brazil.
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59078-970, Brazil.
- Escola de Ciências e Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, RN, 59078-970, Brazil.
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Alavi SM, Mirzaei A, Valizadeh A, Ebrahimpour R. Excitatory deep brain stimulation quenches beta oscillations arising in a computational model of the subthalamo-pallidal loop. Sci Rep 2022; 12:7845. [PMID: 35552409 PMCID: PMC9098470 DOI: 10.1038/s41598-022-10084-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 03/21/2022] [Indexed: 11/30/2022] Open
Abstract
Parkinson’s disease (PD) is associated with abnormal \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β band oscillations (13–30 Hz) in the cortico-basal ganglia circuits. Abnormally increased striato-pallidal inhibition and strengthening the synaptic coupling between subthalamic nucleus (STN) and globus pallidus externa (GPe), due to the loss of dopamine, are considered as the potential sources of \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β oscillations in the basal ganglia. Deep brain stimulation (DBS) of the basal ganglia subregions is known as a way to reduce the pathological \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β oscillations and motor deficits related to PD. Despite the success of the DBS, its underlying mechanism is poorly understood and, there is controversy about the inhibitory or excitatory role of the DBS in the literature. Here, we utilized a computational network model of basal ganglia which consists of STN, GPe, globus pallidus interna, and thalamic neuronal population. This model can reproduce healthy and pathological \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β oscillations similar to what has been observed in experimental studies. Using this model, we investigated the effect of DBS to understand whether its effect is excitatory or inhibitory. Our results show that the excitatory DBS is able to quench the pathological synchrony and \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β oscillations, while, applying inhibitory DBS failed to quench the PD signs. In light of simulation results, we conclude that the effect of the DBS on its target is excitatory.
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Affiliation(s)
- Seyed Mojtaba Alavi
- Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.,School of Cognitive Sciences (SCS), Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | | | - Alireza Valizadeh
- Department of Physics, Institute for Advance Studies in Basic Sciences (IASBS), Zanjan, Iran.,School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Reza Ebrahimpour
- Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. .,School of Cognitive Sciences (SCS), Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
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Park C, Rubchinsky LL, Ahn S. Mathematical model of subthalamic nucleus neuron: Characteristic activity patterns and bifurcation analysis. CHAOS (WOODBURY, N.Y.) 2021; 31:113121. [PMID: 34881610 DOI: 10.1063/5.0059773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 10/14/2021] [Indexed: 06/13/2023]
Abstract
The subthalamic nucleus (STN) has an important role in the pathophysiology of the basal ganglia in Parkinson's disease. The ability of STN cells to generate bursting rhythms under either transient or sustained hyperpolarization may underlie the excessively synchronous beta rhythms observed in Parkinson's disease. In this study, we developed a conductance-based single compartment model of an STN neuron, which is able to generate characteristic activity patterns observed in experiments including hyperpolarization-induced bursts and post-inhibitory rebound bursts. This study focused on the role of three currents in rhythm generation: T-type calcium (CaT) current, L-type calcium (CaL) current, and hyperpolarization-activated cyclic nucleotide-gated (HCN) current. To investigate the effects of these currents in rhythm generation, we performed a bifurcation analysis using slow variables in these currents. Bifurcation analysis showed that the HCN current promotes single-spike activity patterns rather than bursting in agreement with experimental results. It also showed that the CaT current is necessary for characteristic bursting activity patterns. In particular, the CaT current enables STN neurons to generate these activity patterns under hyperpolarizing stimuli. The CaL current enriches and reinforces these characteristic activity patterns. In hyperpolarization-induced bursts or post-inhibitory rebound bursts, the CaL current allows STN neurons to generate long bursting patterns. Thus, the bifurcation analysis explained the synergistic interaction of the CaT and CaL currents, which enables STN neurons to respond to hyperpolarizing stimuli in a salient way. The results of this study implicate the importance of CaT and CaL currents in the pathophysiology of the basal ganglia in Parkinson's disease.
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Affiliation(s)
- Choongseok Park
- Department of Mathematics and Statistics, North Carolina A&T State University, Greensboro, North Carolina 27411, USA
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana 46202, USA
| | - Sungwoo Ahn
- Department of Mathematics, East Carolina University, Greenville, North Carolina 27858, USA
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5
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Reis AS, Brugnago EL, Caldas IL, Batista AM, Iarosz KC, Ferrari FAS, Viana RL. Suppression of chaotic bursting synchronization in clustered scale-free networks by an external feedback signal. CHAOS (WOODBURY, N.Y.) 2021; 31:083128. [PMID: 34470231 DOI: 10.1063/5.0056672] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 08/02/2021] [Indexed: 06/13/2023]
Abstract
Oscillatory activities in the brain, detected by electroencephalograms, have identified synchronization patterns. These synchronized activities in neurons are related to cognitive processes. Additionally, experimental research studies on neuronal rhythms have shown synchronous oscillations in brain disorders. Mathematical modeling of networks has been used to mimic these neuronal synchronizations. Actually, networks with scale-free properties were identified in some regions of the cortex. In this work, to investigate these brain synchronizations, we focus on neuronal synchronization in a network with coupled scale-free networks. The networks are connected according to a topological organization in the structural cortical regions of the human brain. The neuronal dynamic is given by the Rulkov model, which is a two-dimensional iterated map. The Rulkov neuron can generate quiescence, tonic spiking, and bursting. Depending on the parameters, we identify synchronous behavior among the neurons in the clustered networks. In this work, we aim to suppress the neuronal burst synchronization by the application of an external perturbation as a function of the mean-field of membrane potential. We found that the method we used to suppress synchronization presents better results when compared to the time-delayed feedback method when applied to the same model of the neuronal network.
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Affiliation(s)
- Adriane S Reis
- Physics Institute, University of São Paulo, 05508-090 São Paulo, SP, Brazil
| | - Eduardo L Brugnago
- Physics Department, Federal University of Paraná, 81531-980 Curitiba, PR, Brazil
| | - Iberê L Caldas
- Physics Institute, University of São Paulo, 81531-980 São Paulo, SP, Brazil
| | - Antonio M Batista
- Department of Mathematics and Statistics, State University of Ponta Grossa, 84030-900 Ponta Grossa, PR, Brazil
| | - Kelly C Iarosz
- Faculty of Telêmaco Borba, 84266-010 Telêmaco Borba, PR, Brazil
| | - Fabiano A S Ferrari
- Institute of Engineering, Science and Technology, Federal University of the Valleys of Jequitinhonha and Mucuri, 39803-371 Janaúba, MG, Brazil
| | - Ricardo L Viana
- Physics Department, Federal University of Paraná, 81531-980 Curitiba, PR, Brazil
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Duchet B, Ghezzi F, Weerasinghe G, Tinkhauser G, Kühn AA, Brown P, Bick C, Bogacz R. Average beta burst duration profiles provide a signature of dynamical changes between the ON and OFF medication states in Parkinson's disease. PLoS Comput Biol 2021; 17:e1009116. [PMID: 34233347 PMCID: PMC8263069 DOI: 10.1371/journal.pcbi.1009116] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 05/26/2021] [Indexed: 11/18/2022] Open
Abstract
Parkinson's disease motor symptoms are associated with an increase in subthalamic nucleus beta band oscillatory power. However, these oscillations are phasic, and there is a growing body of evidence suggesting that beta burst duration may be of critical importance to motor symptoms. This makes insights into the dynamics of beta bursting generation valuable, in particular to refine closed-loop deep brain stimulation in Parkinson's disease. In this study, we ask the question "Can average burst duration reveal how dynamics change between the ON and OFF medication states?". Our analysis of local field potentials from the subthalamic nucleus demonstrates using linear surrogates that the system generating beta oscillations is more likely to act in a non-linear regime OFF medication and that the change in a non-linearity measure is correlated with motor impairment. In addition, we pinpoint the simplest dynamical changes that could be responsible for changes in the temporal patterning of beta oscillations between medication states by fitting to data biologically inspired models, and simpler beta envelope models. Finally, we show that the non-linearity can be directly extracted from average burst duration profiles under the assumption of constant noise in envelope models. This reveals that average burst duration profiles provide a window into burst dynamics, which may underlie the success of burst duration as a biomarker. In summary, we demonstrate a relationship between average burst duration profiles, dynamics of the system generating beta oscillations, and motor impairment, which puts us in a better position to understand the pathology and improve therapies such as deep brain stimulation.
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Affiliation(s)
- Benoit Duchet
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Filippo Ghezzi
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
| | - Gihan Weerasinghe
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Andrea A. Kühn
- Charité - Universitätsmedizin Berlin, Department of Neurology, Movement Disorder and Neuromodulation Unit, Berlin, Germany
| | - Peter Brown
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Christian Bick
- Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience - Systems & Network Neuroscience, Amsterdam, the Netherlands
- Mathematical Institute, University of Oxford, Oxford, United Kingdom
- Department of Mathematics, University of Exeter, Exeter, United Kingdom
- EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom
| | - Rafal Bogacz
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
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7
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Sand D, Rappel P, Marmor O, Bick AS, Arkadir D, Lu BL, Bergman H, Israel Z, Eitan R. Machine learning-based personalized subthalamic biomarkers predict ON-OFF levodopa states in Parkinson patients. J Neural Eng 2021; 18. [PMID: 33906182 DOI: 10.1088/1741-2552/abfc1d] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 04/27/2021] [Indexed: 01/20/2023]
Abstract
Objective.Adaptive deep brain stimulation (aDBS) based on subthalamic nucleus (STN) electrophysiology has recently been proposed to improve clinical outcomes of DBS for Parkinson's disease (PD) patients. Many current models for aDBS are based on one or two electrophysiological features of STN activity, such as beta or gamma activity. Although these models have shown interesting results, we hypothesized that an aDBS model that includes many STN activity parameters will yield better clinical results. The objective of this study was to investigate the most appropriate STN neurophysiological biomarkers, detectable over long periods of time, that can predict OFF and ON levodopa states in PD patients.Approach.Long-term local field potentials (LFPs) were recorded from eight STNs (four PD patients) during 92 recording sessions (44 OFF and 48 ON levodopa states), over a period of 3-12 months. Electrophysiological analysis included the power of frequency bands, band power ratio and burst features. A total of 140 engineered features was extracted for 20 040 epochs (each epoch lasting 5 s). Based on these engineered features, machine learning (ML) models classified LFPs as OFF vs ON levodopa states.Main results.Beta and gamma band activity alone poorly predicts OFF vs ON levodopa states, with an accuracy of 0.66 and 0.64, respectively. Group ML analysis slightly improved prediction rates, but personalized ML analysis, based on individualized engineered electrophysiological features, were markedly better, predicting OFF vs ON levodopa states with an accuracy of 0.8 for support vector machine learning models.Significance.We showed that individual patients have unique sets of STN neurophysiological biomarkers that can be detected over long periods of time. ML models revealed that personally classified engineered features most accurately predict OFF vs ON levodopa states. Future development of aDBS for PD patients might include personalized ML algorithms.
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Affiliation(s)
- Daniel Sand
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Pnina Rappel
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Odeya Marmor
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Atira S Bick
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - David Arkadir
- The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Bao-Liang Lu
- Center for Brain-like Computing and Machine Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Hagai Bergman
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel.,Functional Neurosurgery Unit, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Zvi Israel
- The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.,Functional Neurosurgery Unit, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Renana Eitan
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.,Jerusalem Mental Health Center, Hebrew University-Hadassah Medical School, Jerusalem, Israel.,Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States of America
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Zirkle J, Rubchinsky LL. Noise effect on the temporal patterns of neural synchrony. Neural Netw 2021; 141:30-39. [PMID: 33857688 DOI: 10.1016/j.neunet.2021.03.032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 03/13/2021] [Accepted: 03/22/2021] [Indexed: 01/03/2023]
Abstract
Neural synchrony in the brain is often present in an intermittent fashion, i.e., there are intervals of synchronized activity interspersed with intervals of desynchronized activity. A series of experimental studies showed that this kind of temporal patterning of neural synchronization may be very specific and may be correlated with behaviour (even if the average synchrony strength is not changed). Prior studies showed that a network with many short desynchronized intervals may be functionally different from a network with few long desynchronized intervals as it may be more sensitive to synchronizing input signals. In this study, we investigated the effect of channel noise on the temporal patterns of neural synchronization. We employed a small network of conductance-based model neurons that were mutually connected via excitatory synapses. The resulting dynamics of the network was studied using the same time-series analysis methods as used in prior experimental and computational studies. While it is well known that synchrony strength generally degrades with noise, we found that noise also affects the temporal patterning of synchrony. Noise, at a sufficient intensity (yet too weak to substantially affect synchrony strength), promotes dynamics with predominantly short (although potentially very numerous) desynchronizations. Thus, channel noise may be one of the mechanisms contributing to the short desynchronization dynamics observed in multiple experimental studies.
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Affiliation(s)
- Joel Zirkle
- Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA.
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9
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Nguyen QA, Rubchinsky LL. Temporal patterns of synchrony in a pyramidal-interneuron gamma (PING) network. CHAOS (WOODBURY, N.Y.) 2021; 31:043134. [PMID: 34251236 DOI: 10.1063/5.0042451] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 04/05/2021] [Indexed: 06/13/2023]
Abstract
Synchronization in neural systems plays an important role in many brain functions. Synchronization in the gamma frequency band (30-100 Hz) is involved in a variety of cognitive phenomena; abnormalities of the gamma synchronization are found in schizophrenia and autism spectrum disorder. Frequently, the strength of synchronization is not high, and synchronization is intermittent even on short time scales (few cycles of oscillations). That is, the network exhibits intervals of synchronization followed by intervals of desynchronization. Neural circuit dynamics may show different distributions of desynchronization durations even if the synchronization strength is fixed. We use a conductance-based neural network exhibiting pyramidal-interneuron gamma rhythm to study the temporal patterning of synchronized neural oscillations. We found that changes in the synaptic strength (as well as changes in the membrane kinetics) can alter the temporal patterning of synchrony. Moreover, we found that the changes in the temporal pattern of synchrony may be independent of the changes in the average synchrony strength. Even though the temporal patterning may vary, there is a tendency for dynamics with short (although potentially numerous) desynchronizations, similar to what was observed in experimental studies of neural synchronization in the brain. Recent studies suggested that the short desynchronizations dynamics may facilitate the formation and the breakup of transient neural assemblies. Thus, the results of this study suggest that changes of synaptic strength may alter the temporal patterning of the gamma synchronization as to make the neural networks more efficient in the formation of neural assemblies and the facilitation of cognitive phenomena.
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Affiliation(s)
- Quynh-Anh Nguyen
- Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, Indiana 46202, USA
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, Indiana 46202, USA
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10
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Vera-Ávila VP, Sevilla-Escoboza JR, Leyva I. Complex networks exhibit intermittent synchronization. CHAOS (WOODBURY, N.Y.) 2020; 30:103119. [PMID: 33138450 DOI: 10.1063/5.0020419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 09/28/2020] [Indexed: 06/11/2023]
Abstract
The path toward the synchronization of an ensemble of dynamical units goes through a series of transitions determined by the dynamics and the structure of the connections network. In some systems on the verge of complete synchronization, intermittent synchronization, a time-dependent state where full synchronization alternates with non-synchronized periods, has been observed. This phenomenon has been recently considered to have functional relevance in neuronal ensembles and other networked biological systems close to criticality. We characterize the intermittent state as a function of the network topology to show that the different structures can encourage or inhibit the appearance of early signs of intermittency. In particular, we study the local intermittency and show how the nodes incorporate to intermittency in hierarchical order, which can provide information about the node topological role even when the structure is unknown.
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Affiliation(s)
- V P Vera-Ávila
- Centro Universitario de los Lagos, Universidad de Guadalajara, Jalisco 47460, Mexico
| | - J R Sevilla-Escoboza
- Centro Universitario de los Lagos, Universidad de Guadalajara, Jalisco 47460, Mexico
| | - I Leyva
- Complex Systems Group & GISC, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain and Center for Biomedical Technology, Universidad Politécnica de Madrid, 28223 Madrid, Spain
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11
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Dos Santos Lima GZ, Targa ADS, de Freitas Cavalcante S, Rodrigues LS, Fontenele-Araújo J, Torterolo P, Andersen ML, Lima MMS. Disruption of neocortical synchronisation during slow-wave sleep in the rotenone model of Parkinson's disease. J Sleep Res 2020; 30:e13170. [PMID: 32865294 DOI: 10.1111/jsr.13170] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 07/27/2020] [Accepted: 07/28/2020] [Indexed: 12/16/2022]
Abstract
Parkinson's disease motor dysfunctions are associated with improperly organised neural oscillatory activity. The presence of such disruption at the early stages of the disease in which altered sleep is one of the main features could be a relevant predictive feature. Based on this, we aimed to investigate the neocortical synchronisation dynamics during slow-wave sleep (SWS) in the rotenone model of Parkinson's disease. After rotenone administration within the substantia nigra pars compacta, one group of male Wistar rats underwent sleep-wake recording. Considering the association between SWS oscillatory activity and memory consolidation, another group of rats underwent a memory test. The fine temporal structure of synchronisation dynamics was evaluated by a recently developed technique called first return map. We observed that rotenone administration decreased the time spent in SWS and altered the power spectrum within different frequency bands, whilst it increased the transition rate from a synchronised to desynchronised state. This neurotoxin also increased the probability of longer and decreased the probability of shorter desynchronisation events. At the same time, we observed impairment in object recognition memory. These findings depict an electrophysiological fingerprint represented by a disruption in the typical oscillatory activity within the neocortex at the early stages of Parkinson's disease, concomitant with a decrease in the time spent in SWS and impairment in recognition memory.
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Affiliation(s)
- Gustavo Zampier Dos Santos Lima
- Science and Technology School, Federal University of Rio Grande do Norte, Natal, Brazil.,Department of Biophysics and Pharmacology, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Adriano D S Targa
- Department of Physiology, Federal University of Paraná, Curitiba, Brazil.,Department of Pharmacology, Federal University of Paraná, Curitiba, Brazil.,Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Translational Research in Respiratory Medicine, Lleida, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | | | - Lais S Rodrigues
- Department of Physiology, Federal University of Paraná, Curitiba, Brazil.,Department of Pharmacology, Federal University of Paraná, Curitiba, Brazil
| | - John Fontenele-Araújo
- Department of Physiology and Behavior, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Pablo Torterolo
- Department of Physiology, University of the Republic, Montevideo, Uruguay
| | - Monica L Andersen
- Department of Psychobiology, Federal University of São Paulo, São Paulo, Brazil
| | - Marcelo M S Lima
- Department of Physiology, Federal University of Paraná, Curitiba, Brazil.,Department of Pharmacology, Federal University of Paraná, Curitiba, Brazil
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12
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Zirkle J, Rubchinsky LL. Spike-Timing Dependent Plasticity Effect on the Temporal Patterning of Neural Synchronization. Front Comput Neurosci 2020; 14:52. [PMID: 32595464 PMCID: PMC7303326 DOI: 10.3389/fncom.2020.00052] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 05/12/2020] [Indexed: 11/29/2022] Open
Abstract
Neural synchrony in the brain at rest is usually variable and intermittent, thus intervals of predominantly synchronized activity are interrupted by intervals of desynchronized activity. Prior studies suggested that this temporal structure of the weakly synchronous activity might be functionally significant: many short desynchronizations may be functionally different from few long desynchronizations even if the average synchrony level is the same. In this study, we used computational neuroscience methods to investigate the effects of spike-timing dependent plasticity (STDP) on the temporal patterns of synchronization in a simple model. We employed a small network of conductance-based model neurons that were connected via excitatory plastic synapses. The dynamics of this network was subjected to the time-series analysis methods used in prior experimental studies. We found that STDP could alter the synchronized dynamics in the network in several ways, depending on the time scale that plasticity acts on. However, in general, the action of STDP in the simple network considered here is to promote dynamics with short desynchronizations (i.e., dynamics reminiscent of that observed in experimental studies). Complex interplay of the cellular and synaptic dynamics may lead to the activity-dependent adjustment of synaptic strength in such a way as to facilitate experimentally observed short desynchronizations in the intermittently synchronized neural activity.
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Affiliation(s)
- Joel Zirkle
- Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, United States
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, United States.,Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, United States
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13
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Temporal patterns of dispersal-induced synchronization in population dynamics. J Theor Biol 2020; 490:110159. [PMID: 31954109 DOI: 10.1016/j.jtbi.2020.110159] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 01/08/2020] [Accepted: 01/10/2020] [Indexed: 11/24/2022]
Abstract
The mechanisms and properties of synchronization of oscillating ecological populations attract attention because it is a fairly common phenomenon and because spatial synchrony may elevate a risk of extinction and may lead to other environmental impacts. Conditions for stable synchronization in a system of linearly coupled predator-prey oscillators have been considered in the past. However, the spatial dispersal coupling may be relatively weak and may not necessarily lead to a stable, complete synchrony. If the coupling between oscillators is too weak to induce a stable synchrony, oscillators may be engaged into intermittent synchrony, when episodes of synchronized dynamics are interspersed with the episodes of desynchronized dynamics. In the present study we consider the temporal patterning of this kind of intermittent synchronized dynamics in a system of two dispersal-coupled Rosenzweig-MacArthur predator-prey oscillators. We consider the properties of the distributions of durations of desynchronized intervals and their dependence on the model parameters. We show that the temporal patterning of synchronous dynamics (an ecological network phenomenon) may depend on the properties of individual predator-prey patch (individual oscillator) and may vary independently of the strength of dispersal. We also show that if the dynamics of predator is slow relative to the dynamics of the prey (a situation that may promote brief but large outbreaks), dispersal-coupled predator-prey oscillating populations exhibit numerous short desynchronizations (as opposed to few long desynchronizations) and may require weaker dispersal in order to reach strong synchrony.
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14
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Malaia EA, Ahn S, Rubchinsky LL. Dysregulation of temporal dynamics of synchronous neural activity in adolescents on autism spectrum. Autism Res 2019; 13:24-31. [PMID: 31702116 DOI: 10.1002/aur.2219] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 09/04/2019] [Accepted: 09/05/2019] [Indexed: 12/20/2022]
Abstract
Autism spectrum disorder is increasingly understood to be based on atypical signal transfer among multiple interconnected networks in the brain. Relative temporal patterns of neural activity have been shown to underlie both the altered neurophysiology and the altered behaviors in a variety of neurogenic disorders. We assessed brain network dynamics variability in autism spectrum disorders (ASD) using measures of synchronization (phase-locking) strength, and timing of synchronization and desynchronization of neural activity (desynchronization ratio) across frequency bands of resting-state electroencephalography (EEG). Our analysis indicated that frontoparietal synchronization is higher in ASD but with more short periods of desynchronization. It also indicates that the relationship between the properties of neural synchronization and behavior is different in ASD and typically developing populations. Recent theoretical studies suggest that neural networks with a high desynchronization ratio have increased sensitivity to inputs. Our results point to the potential significance of this phenomenon to the autistic brain. This sensitivity may disrupt the production of an appropriate neural and behavioral responses to external stimuli. Cognitive processes dependent on the integration of activity from multiple networks maybe, as a result, particularly vulnerable to disruption. Autism Res 2020, 13: 24-31. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Parts of the brain can work together by synchronizing the activity of the neurons. We recorded the electrical activity of the brain in adolescents with autism spectrum disorder and then compared the recording to that of their peers without the diagnosis. We found that in participants with autism, there were a lot of very short time periods of non-synchronized activity between frontal and parietal parts of the brain. Mathematical models show that the brain system with this kind of activity is very sensitive to external events.
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Affiliation(s)
- Evie A Malaia
- Department of Communicative Disorders, University of Alabama, Tuscaloosa, Alabama
| | - Sungwoo Ahn
- Department of Mathematics, East Carolina University, Greenville, North Carolina
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences, Indiana University - Purdue University Indianapolis, Indianapolis, Indiana.,Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana
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15
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Cluster burst synchronization in a scale-free network of inhibitory bursting neurons. Cogn Neurodyn 2019; 14:69-94. [PMID: 32015768 DOI: 10.1007/s11571-019-09546-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 06/03/2019] [Accepted: 07/01/2019] [Indexed: 10/26/2022] Open
Abstract
We consider a scale-free network of inhibitory Hindmarsh-Rose (HR) bursting neurons, and make a computational study on coupling-induced cluster burst synchronization by varying the average coupling strength J 0 . For sufficiently small J 0 , non-cluster desynchronized states exist. However, when passing a critical point J c ∗ ( ≃ 0.16 ) , the whole population is segregated into 3 clusters via a constructive role of synaptic inhibition to stimulate dynamical clustering between individual burstings, and thus 3-cluster desynchronized states appear. As J 0 is further increased and passes a lower threshold J l ∗ ( ≃ 0.78 ) , a transition to 3-cluster burst synchronization occurs due to another constructive role of synaptic inhibition to favor population synchronization. In this case, HR neurons in each cluster make burstings every 3rd cycle of the instantaneous burst rate R w ( t ) of the whole population, and exhibit burst synchronization. However, as J 0 passes an intermediate threshold J m ∗ ( ≃ 5.2 ) , HR neurons fire burstings intermittently at a 4th cycle of R w ( t ) via burst skipping rather than at its 3rd cycle, and hence they begin to make intermittent hoppings between the 3 clusters. Due to such intermittent intercluster hoppings via burst skippings, the 3 clusters become broken up (i.e., the 3 clusters are integrated into a single one). However, in spite of such break-up (i.e., disappearance) of the 3-cluster states, (non-cluster) burst synchronization persists in the whole population, which is well visualized in the raster plot of burst onset times where bursting stripes (composed of burst onset times and indicating burst synchronization) appear successively. With further increase in J 0 , intercluster hoppings are intensified, and bursting stripes also become dispersed more and more due to a destructive role of synaptic inhibition to spoil the burst synchronization. Eventually, when passing a higher threshold J h ∗ ( ≃ 17.8 ) a transition to desynchronization occurs via complete overlap between the bursting stripes. Finally, we also investigate the effects of stochastic noise on both 3-cluster burst synchronization and intercluster hoppings.
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16
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Muddapu VR, Mandali A, Chakravarthy VS, Ramaswamy S. A Computational Model of Loss of Dopaminergic Cells in Parkinson's Disease Due to Glutamate-Induced Excitotoxicity. Front Neural Circuits 2019; 13:11. [PMID: 30858799 PMCID: PMC6397878 DOI: 10.3389/fncir.2019.00011] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 02/05/2019] [Indexed: 01/04/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disease associated with progressive and inexorable loss of dopaminergic cells in Substantia Nigra pars compacta (SNc). Although many mechanisms have been suggested, a decisive root cause of this cell loss is unknown. A couple of the proposed mechanisms, however, show potential for the development of a novel line of PD therapeutics. One of these mechanisms is the peculiar metabolic vulnerability of SNc cells compared to other dopaminergic clusters; the other is the SubThalamic Nucleus (STN)-induced excitotoxicity in SNc. To investigate the latter hypothesis computationally, we developed a spiking neuron network-model of SNc-STN-GPe system. In the model, prolonged stimulation of SNc cells by an overactive STN leads to an increase in ‘stress' variable; when the stress in a SNc neuron exceeds a stress threshold, the neuron dies. The model shows that the interaction between SNc and STN involves a positive-feedback due to which, an initial loss of SNc cells that crosses a threshold causes a runaway-effect, leading to an inexorable loss of SNc cells, strongly resembling the process of neurodegeneration. The model further suggests a link between the two aforementioned mechanisms of SNc cell loss. Our simulation results show that the excitotoxic cause of SNc cell loss might initiate by weak-excitotoxicity mediated by energy deficit, followed by strong-excitotoxicity, mediated by a disinhibited STN. A variety of conventional therapies were simulated to test their efficacy in slowing down SNc cell loss. Among them, glutamate inhibition, dopamine restoration, subthalamotomy and deep brain stimulation showed superior neuroprotective-effects in the proposed model.
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Affiliation(s)
| | - Alekhya Mandali
- Department of Psychiatry, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - V Srinivasa Chakravarthy
- Computational Neuroscience Lab, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT-Madras, Chennai, India
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17
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Deffains M, Bergman H. Parkinsonism-related β oscillations in the primate basal ganglia networks – Recent advances and clinical implications. Parkinsonism Relat Disord 2019; 59:2-8. [DOI: 10.1016/j.parkreldis.2018.12.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2018] [Revised: 12/12/2018] [Accepted: 12/13/2018] [Indexed: 10/27/2022]
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18
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COMT Inhibition Alters Cue-Evoked Oscillatory Dynamics during Alcohol Drinking in the Rat. eNeuro 2018; 5:eN-NWR-0326-18. [PMID: 30406194 PMCID: PMC6220588 DOI: 10.1523/eneuro.0326-18.2018] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Accepted: 09/05/2018] [Indexed: 11/21/2022] Open
Abstract
Alterations in the corticostriatal system have been implicated in numerous substance use disorders, including alcohol use disorder (AUD). Adaptations in this neural system are associated with enhanced drug-seeking behaviors following exposure to cues predicting drug availability. Therefore, understanding how potential treatments alter neural activity in this system could lead to more refined and effective approaches for AUD. Local field potentials (LFPs) were acquired simultaneously in the prefrontal cortex (PFC) and nucleus accumbens (NA) of both alcohol preferring (P) and Wistar rats engaged in a Pavlovian conditioning paradigm wherein a light cue signaled the availability of ethanol (EtOH). On test days, the catechol-o-methyl-transferase (COMT) inhibitor tolcapone was administered prior to conditioning. Stimulus-evoked voltage changes were observed following the presentation of the EtOH cue in both strains and were most pronounced in the PFC of P rats. Phase analyses of LFPs in the θ band (5–11 Hz) revealed that PFC-NA synchrony was reduced in P rats relative to Wistars but was robustly increased during drinking. Presentation of the cue resulted in a larger phase reset in the PFC of P rats but not Wistars, an effect that was attenuated by tolcapone. Additionally, tolcapone reduced cued EtOH intake in P rat but not Wistars. These results suggest a link between corticostriatal synchrony and genetic risk for excessive drinking. Moreover, inhibition of COMT within these systems may result in reduced attribution of salience to reward paired stimuli via modulation of stimulus-evoked changes to cortical oscillations in genetically susceptible populations.
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19
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Boaretto BRR, Budzinski RC, Prado TL, Kurths J, Lopes SR. Neuron dynamics variability and anomalous phase synchronization of neural networks. CHAOS (WOODBURY, N.Y.) 2018; 28:106304. [PMID: 30384616 DOI: 10.1063/1.5023878] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Accepted: 07/05/2018] [Indexed: 06/08/2023]
Abstract
Anomalous phase synchronization describes a synchronization phenomenon occurring even for the weakly coupled network and characterized by a non-monotonous dependence of the synchronization strength on the coupling strength. Its existence may support a theoretical framework to some neurological diseases, such as Parkinson's and some episodes of seizure behavior generated by epilepsy. Despite the success of controlling or suppressing the anomalous phase synchronization in neural networks applying external perturbations or inducing ambient changes, the origin of the anomalous phase synchronization as well as the mechanisms behind the suppression is not completely known. Here, we consider networks composed of N = 2000 coupled neurons in a small-world topology for two well known neuron models, namely, the Hodgkin-Huxley-like and the Hindmarsh-Rose models, both displaying the anomalous phase synchronization regime. We show that the anomalous phase synchronization may be related to the individual behavior of the coupled neurons; particularly, we identify a strong correlation between the behavior of the inter-bursting-intervals of the neurons, what we call neuron variability, to the ability of the network to depict anomalous phase synchronization. We corroborate the ideas showing that external perturbations or ambient parameter changes that eliminate anomalous phase synchronization and at the same time promote small changes in the individual dynamics of the neurons, such that an increasing individual variability of neurons implies a decrease of anomalous phase synchronization. Finally, we demonstrate that this effect can be quantified using a well known recurrence quantifier, the "determinism." Moreover, the results obtained by the determinism are based on only the mean field potential of the network, turning these measures more suitable to be used in experimental situations.
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Affiliation(s)
- B R R Boaretto
- Departamento de Física, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil
| | - R C Budzinski
- Departamento de Física, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil
| | - T L Prado
- Instituto de Engenharia, Ciência e Tecnologia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, 39440-000 Janaúba, Brazil
| | - Jürgen Kurths
- Potsdam Institute for Climate Impact Research - Telegraphenberg A 31, 14473 Potsdam, Germany
| | - S R Lopes
- Departamento de Física, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil
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20
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Kim SY, Lim W. Burst synchronization in a scale-free neuronal network with inhibitory spike-timing-dependent plasticity. Cogn Neurodyn 2018; 13:53-73. [PMID: 30728871 DOI: 10.1007/s11571-018-9505-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Revised: 08/19/2018] [Accepted: 08/28/2018] [Indexed: 01/09/2023] Open
Abstract
We are concerned about burst synchronization (BS), related to neural information processes in health and disease, in the Barabási-Albert scale-free network (SFN) composed of inhibitory bursting Hindmarsh-Rose neurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibitory spike-timing-dependent plasticity (iSTDP). In previous works without considering iSTDP, BS was found to appear in a range of noise intensities for fixed synaptic inhibition strengths. In contrast, in our present work, we take into consideration iSTDP and investigate its effect on BS by varying the noise intensity. Our new main result is to find occurrence of a Matthew effect in inhibitory synaptic plasticity: good BS gets better via LTD, while bad BS get worse via LTP. This kind of Matthew effect in inhibitory synaptic plasticity is in contrast to that in excitatory synaptic plasticity where good (bad) synchronization gets better (worse) via LTP (LTD). We note that, due to inhibition, the roles of LTD and LTP in inhibitory synaptic plasticity are reversed in comparison with those in excitatory synaptic plasticity. Moreover, emergences of LTD and LTP of synaptic inhibition strengths are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic burst onset times. Finally, in the presence of iSTDP we investigate the effects of network architecture on BS by varying the symmetric attachment degree l ∗ and the asymmetry parameter Δ l in the SFN.
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Affiliation(s)
- Sang-Yoon Kim
- Institute for Computational Neuroscience and Department of Science Education, Daegu National University of Education, Daegu, 42411 Korea
| | - Woochang Lim
- Institute for Computational Neuroscience and Department of Science Education, Daegu National University of Education, Daegu, 42411 Korea
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21
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Deffains M, Iskhakova L, Katabi S, Israel Z, Bergman H. Longer β oscillatory episodes reliably identify pathological subthalamic activity in Parkinsonism. Mov Disord 2018; 33:1609-1618. [PMID: 30145811 DOI: 10.1002/mds.27418] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Revised: 03/20/2018] [Accepted: 03/23/2018] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND The efficacy of deep brain stimulation (DBS) - primarily of the subthalamic nucleus (STN) - for advanced Parkinson's disease (PD) is commonly attributed to the suppression of pathological synchronous β oscillations along the cortico-thalamo-basal ganglia network. Conventional continuous high-frequency DBS indiscriminately influences pathological and normal neural activity. The DBS protocol would therefore be more effective if stimulation was only applied when necessary (closed-loop adaptive DBS). OBJECTIVES AND METHODS Our study aimed to identify a reliable biomarker of the pathological neuronal activity in parkinsonism that could be used as a trigger for adaptive DBS. To this end, we examined the oscillatory features of paired spiking activities recorded in three distinct nodes of the basal ganglia network of 2 African green monkeys before and after induction of parkinsonism (by MPTP intoxication). RESULTS Parkinsonism-related basal ganglia β oscillations consisted of synchronized time-limited episodes, rather than a continuous stretch, of β oscillatory activity. Episodic basal ganglia β oscillatory activity, although prolonged in parkinsonism, was not necessarily pathological given that short β episodes could also be detected in the healthy state. Importantly, prolongation of the basal ganglia β episodes was more pronounced than their intensification in the parkinsonian state-especially in the STN. Hence, deletion of longer β episodes was more effective than deletion of stronger β episodes in reducing parkinsonian STN synchronized oscillatory activity. CONCLUSIONS Prolonged STN β episodes are pathological in parkinsonism and can be used as optimal trigger for future adaptive DBS applications. © 2018 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Marc Deffains
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel
| | - Liliya Iskhakova
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel
| | - Shiran Katabi
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Zvi Israel
- Department of Neurosurgery, Hadassah University Hospital, Jerusalem, Israel
| | - Hagai Bergman
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel.,Department of Neurosurgery, Hadassah University Hospital, Jerusalem, Israel
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22
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Neural synchronization: Average strength vs. temporal patterning. Clin Neurophysiol 2018; 129:842-844. [PMID: 29486414 DOI: 10.1016/j.clinph.2018.01.063] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 01/13/2018] [Accepted: 01/18/2018] [Indexed: 11/24/2022]
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23
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Tinkhauser G, Pogosyan A, Tan H, Herz DM, Kühn AA, Brown P. Beta burst dynamics in Parkinson's disease OFF and ON dopaminergic medication. Brain 2017; 140:2968-2981. [PMID: 29053865 PMCID: PMC5667742 DOI: 10.1093/brain/awx252] [Citation(s) in RCA: 208] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Accepted: 08/05/2017] [Indexed: 01/23/2023] Open
Abstract
Exaggerated basal ganglia beta activity (13–35 Hz) is commonly
found in patients with Parkinson’s disease and can be suppressed by
dopaminergic medication, with the degree of suppression being correlated with
the improvement in motor symptoms. Importantly, beta activity is not
continuously elevated, but fluctuates to give beta bursts. The percentage number
of longer beta bursts in a given interval is positively correlated with clinical
impairment in Parkinson’s disease patients. Here we determine whether the
characteristics of beta bursts are dependent on dopaminergic state. Local field
potentials were recorded from the subthalamic nucleus of eight
Parkinson’s disease patients during temporary lead externalization during
surgery for deep brain stimulation. The recordings took place with the patient
quietly seated following overnight withdrawal of levodopa and after
administration of levodopa. Beta bursts were defined by applying a common
amplitude threshold and burst characteristics were compared between the two drug
conditions. The amplitude of beta bursts, indicative of the degree of local
neural synchronization, progressively increased with burst duration. Treatment
with levodopa limited this evolution leading to a relative increase of shorter,
lower amplitude bursts. Synchronization, however, was not limited to local
neural populations during bursts, but also, when such bursts were cotemporaneous
across the hemispheres, was evidenced by bilateral phase synchronization. The
probability of beta bursts and the proportion of cotemporaneous bursts were
reduced by levodopa. The percentage number of longer beta bursts in a given
interval was positively related to motor impairment, while the opposite was true
for the percentage number of short duration beta bursts. Importantly, the
decrease in burst duration was also correlated with the motor improvement. In
conclusion, we demonstrate that long duration beta bursts are associated with an
increase in local and interhemispheric synchronization. This may compromise
information coding capacity and thereby motor processing. Dopaminergic activity
limits this uncontrolled beta synchronization by terminating long duration beta
bursts, with positive consequences on network state and motor symptoms.
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Affiliation(s)
- Gerd Tinkhauser
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.,Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - Alek Pogosyan
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Damian M Herz
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Andrea A Kühn
- Department of Neurology, Charitè, Universitätsmedizin Berlin, Germany
| | - Peter Brown
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
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24
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Ratnadurai-Giridharan S, Cheung CC, Rubchinsky LL. Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia. IEEE Trans Neural Syst Rehabil Eng 2017; 25:2188-2195. [DOI: 10.1109/tnsre.2017.2712418] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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25
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Ahn S, Rubchinsky LL. Potential Mechanisms and Functions of Intermittent Neural Synchronization. Front Comput Neurosci 2017; 11:44. [PMID: 28611618 PMCID: PMC5447717 DOI: 10.3389/fncom.2017.00044] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 05/15/2017] [Indexed: 11/26/2022] Open
Abstract
Neural synchronization is believed to play an important role in different brain functions. Synchrony in cortical and subcortical circuits is frequently variable in time and not perfect. Few long intervals of desynchronized dynamics may be functionally different from many short desynchronized intervals although the average synchrony may be the same. Recent analysis of imperfect synchrony in different neural systems reported one common feature: neural oscillations may go out of synchrony frequently, but primarily for a short time interval. This study explores potential mechanisms and functional advantages of this short desynchronizations dynamics using computational neuroscience techniques. We show that short desynchronizations are exhibited in coupled neurons if their delayed rectifier potassium current has relatively large values of the voltage-dependent activation time-constant. The delayed activation of potassium current is associated with generation of quickly-rising action potential. This “spikiness” is a very general property of neurons. This may explain why very different neural systems exhibit short desynchronization dynamics. We also show how the distribution of desynchronization durations may be independent of the synchronization strength. Finally, we show that short desynchronization dynamics requires weaker synaptic input to reach a pre-set synchrony level. Thus, this dynamics allows for efficient regulation of synchrony and may promote efficient formation of synchronous neural assemblies.
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Affiliation(s)
- Sungwoo Ahn
- Department of Mathematical Sciences, Indiana University Purdue University IndianapolisIndianapolis, IN, United States
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences, Indiana University Purdue University IndianapolisIndianapolis, IN, United States.,Stark Neurosciences Research Institute, Indiana University School of MedicineIndianapolis, IN, United States
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Yan H, Wang J. Quantification of motor network dynamics in Parkinson's disease by means of landscape and flux theory. PLoS One 2017; 12:e0174364. [PMID: 28350890 PMCID: PMC5370118 DOI: 10.1371/journal.pone.0174364] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Accepted: 03/08/2017] [Indexed: 01/18/2023] Open
Abstract
The basal ganglia neural circuit plays an important role in motor control. Despite the significant efforts, the understanding of the principles and underlying mechanisms of this modulatory circuit and the emergence of abnormal synchronized oscillations in movement disorders is still challenging. Dopamine loss has been proved to be responsible for Parkinson's disease. We quantitatively described the dynamics of the basal ganglia-thalamo-cortical circuit in Parkinson's disease in terms of the emergence of both abnormal firing rates and firing patterns in the circuit. We developed a potential landscape and flux framework for exploring the modulatory circuit. The driving force of the circuit can be decomposed into a gradient of the potential, which is associated with the steady-state probability distributions, and the curl probability flux term. We uncovered the underlying potential landscape as a Mexican hat-shape closed ring valley where abnormal oscillations emerge due to dopamine depletion. We quantified the global stability of the network through the topography of the landscape in terms of the barrier height, which is defined as the potential difference between the maximum potential inside the ring and the minimum potential along the ring. Both a higher barrier and a larger flux originated from detailed balance breaking result in more stable oscillations. Meanwhile, more energy is consumed to support the increasing flux. Global sensitivity analysis on the landscape topography and flux indicates how changes in underlying neural network regulatory wirings and external inputs influence the dynamics of the system. We validated two of the main hypotheses(direct inhibition hypothesis and output activation hypothesis) on the therapeutic mechanism of deep brain stimulation (DBS). We found GPe appears to be another effective stimulated target for DBS besides GPi and STN. Our approach provides a general way to quantitatively explore neural networks and may help for uncovering more efficacious therapies for movement disorders.
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Affiliation(s)
- Han Yan
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, P.R.China
| | - Jin Wang
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, P.R.China
- Department of Chemistry and Physics, State University of New York at Stony Brook, Stony Brook, New York, United States of America
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Ahn S, Zauber SE, Worth RM, Rubchinsky LL. Synchronized Beta-Band Oscillations in a Model of the Globus Pallidus-Subthalamic Nucleus Network under External Input. Front Comput Neurosci 2016; 10:134. [PMID: 28066222 PMCID: PMC5167737 DOI: 10.3389/fncom.2016.00134] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 11/30/2016] [Indexed: 11/13/2022] Open
Abstract
Hypokinetic symptoms of Parkinson's disease are usually associated with excessively strong oscillations and synchrony in the beta frequency band. The origin of this synchronized oscillatory dynamics is being debated. Cortical circuits may be a critical source of excessive beta in Parkinson's disease. However, subthalamo-pallidal circuits were also suggested to be a substantial component in generation and/or maintenance of Parkinsonian beta activity. Here we study how the subthalamo-pallidal circuits interact with input signals in the beta frequency band, representing cortical input. We use conductance-based models of the subthalamo-pallidal network and two types of input signals: artificially-generated inputs and input signals obtained from recordings in Parkinsonian patients. The resulting model network dynamics is compared with the dynamics of the experimental recordings from patient's basal ganglia. Our results indicate that the subthalamo-pallidal model network exhibits multiple resonances in response to inputs in the beta band. For a relatively broad range of network parameters, there is always a certain input strength, which will induce patterns of synchrony similar to the experimentally observed ones. This ability of the subthalamo-pallidal network to exhibit realistic patterns of synchronous oscillatory activity under broad conditions may indicate that these basal ganglia circuits are directly involved in the expression of Parkinsonian synchronized beta oscillations. Thus, Parkinsonian synchronized beta oscillations may be promoted by the simultaneous action of both cortical (or some other) and subthalamo-pallidal network mechanisms. Hence, these mechanisms are not necessarily mutually exclusive.
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Affiliation(s)
- Sungwoo Ahn
- Department of Mathematics, East Carolina University Greenville, NC, USA
| | - S Elizabeth Zauber
- Department of Neurology, Indiana University School of Medicine Indianapolis, IN, USA
| | - Robert M Worth
- Department of Mathematical Sciences, Indiana University-Purdue University IndianapolisIndianapolis, IN, USA; Department of Neurosurgery, Indiana University School of MedicineIndianapolis, IN, USA
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences, Indiana University-Purdue University IndianapolisIndianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of MedicineIndianapolis, IN, USA
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Effect of network architecture on burst and spike synchronization in a scale-free network of bursting neurons. Neural Netw 2016; 79:53-77. [DOI: 10.1016/j.neunet.2016.03.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Revised: 03/07/2016] [Accepted: 03/22/2016] [Indexed: 11/22/2022]
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Haidar I, Pasillas-Lépine W, Chaillet A, Panteley E, Palfi S, Senova S. Closed-loop firing rate regulation of two interacting excitatory and inhibitory neural populations of the basal ganglia. BIOLOGICAL CYBERNETICS 2016; 110:55-71. [PMID: 26837751 DOI: 10.1007/s00422-015-0678-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2015] [Accepted: 12/21/2015] [Indexed: 05/28/2023]
Abstract
This paper develops a new closed-loop firing rate regulation strategy for a population of neurons in the subthalamic nucleus, derived using a model-based analysis of the basal ganglia. The system is described using a firing rate model, in order to analyse the generation of beta-band oscillations. On this system, a proportional regulation of the firing rate reduces the gain of the subthalamo-pallidal loop in the parkinsonian case, thus impeding pathological oscillation generation. A filter with a well-chosen frequency is added to this proportional scheme, in order to avoid a potential instability of the feedback loop due to actuation and measurement delays. Our main result is a set of conditions on the parameters of the stimulation strategy that guarantee both its stability and a prescribed delay margin. A discussion on the applicability of the proposed method and a complete set of mathematical proofs is included.
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Affiliation(s)
- Ihab Haidar
- Laboratoire des signaux et systèmes, CNRS - CentraleSupélec - Univ. Paris Sud, Gif-sur-Yvette, France
| | - William Pasillas-Lépine
- Laboratoire des signaux et systèmes, CNRS - CentraleSupélec - Univ. Paris Sud, Gif-sur-Yvette, France.
| | - Antoine Chaillet
- Laboratoire des signaux et systèmes, CNRS - CentraleSupélec - Univ. Paris Sud, Gif-sur-Yvette, France
| | - Elena Panteley
- Laboratoire des signaux et systèmes, CNRS - CentraleSupélec - Univ. Paris Sud, Gif-sur-Yvette, France
- ITMO University, Saint Petersburg, Russia
| | - Stéphane Palfi
- AP-HP, Hôpital H. Mondor, Service de Neurochirurgie, Créteil, France
- IMRB, Inserm, U955, Equipe 14, Créteil, France
- Faculté de médecine, Université Paris Est, Créteil, France
| | - Suhan Senova
- AP-HP, Hôpital H. Mondor, Service de Neurochirurgie, Créteil, France
- IMRB, Inserm, U955, Equipe 14, Créteil, France
- Faculté de médecine, Université Paris Est, Créteil, France
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Kucewicz MT, Michael Berry B, Bower MR, Cimbalnik J, Svehlik V, Matt Stead S, Worrell GA. Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task. IEEE Trans Biomed Eng 2016; 63:67-75. [DOI: 10.1109/tbme.2015.2451596] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Rubchinsky LL, Ahn S. Short desynchronization epochs in neural synchronization: detection, mechanisms, and functions. BMC Neurosci 2015. [PMCID: PMC4697597 DOI: 10.1186/1471-2202-16-s1-p3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Temporal patterning of neural synchrony in the basal ganglia in Parkinson's disease. Clin Neurophysiol 2015; 127:1743-1745. [PMID: 26433255 DOI: 10.1016/j.clinph.2015.09.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2015] [Revised: 09/11/2015] [Accepted: 09/11/2015] [Indexed: 11/23/2022]
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Ahn S, Zauber SE, Worth RM, Witt T, Rubchinsky LL. Interaction of synchronized dynamics in cortex and basal ganglia in Parkinson's disease. Eur J Neurosci 2015; 42:2164-71. [PMID: 26154341 DOI: 10.1111/ejn.12980] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2014] [Revised: 05/26/2015] [Accepted: 06/05/2015] [Indexed: 01/24/2023]
Abstract
Parkinson's disease pathophysiology is marked by increased oscillatory and synchronous activity in the beta frequency band in cortical and basal ganglia circuits. This study explores the functional connections between synchronized dynamics of cortical areas and synchronized dynamics of subcortical areas in Parkinson's disease. We simultaneously recorded neuronal units (spikes) and local field potentials (LFP) from subthalamic nucleus (STN) and electroencephalograms (EEGs) from the scalp in parkinsonian patients, and analysed the correlation between the time courses of the spike-LFP synchronization and inter-electrode EEG synchronization. We found the (non-invasively obtained) time course of the synchrony strength between EEG electrodes and the (invasively obtained) time course of the synchrony between spiking units and LFP in STN to be weakly, but significantly, correlated with each other. This correlation is largest for the bilateral motor EEG synchronization, followed by bilateral frontal EEG synchronization. Our observations suggest that there may be multiple functional modes by which the cortical and basal ganglia circuits interact with each other in Parkinson's disease: not only may synchronization be observed between some areas in cortex and the basal ganglia, but also synchronization within cortex and within basal ganglia may be related, suggesting potentially a more global functional interaction. More coherent dynamics in one brain region may modulate or activate the dynamics of another brain region in a more powerful way, causing correlations between changes in synchrony strength in the two regions.
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Affiliation(s)
- Sungwoo Ahn
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA
| | - S Elizabeth Zauber
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Robert M Worth
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA.,Department of Neurosurgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Thomas Witt
- Department of Neurosurgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA.,Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
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Mandali A, Rengaswamy M, Chakravarthy VS, Moustafa AA. A spiking Basal Ganglia model of synchrony, exploration and decision making. Front Neurosci 2015; 9:191. [PMID: 26074761 PMCID: PMC4444758 DOI: 10.3389/fnins.2015.00191] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Accepted: 05/12/2015] [Indexed: 12/31/2022] Open
Abstract
To make an optimal decision we need to weigh all the available options, compare them with the current goal, and choose the most rewarding one. Depending on the situation an optimal decision could be to either “explore” or “exploit” or “not to take any action” for which the Basal Ganglia (BG) is considered to be a key neural substrate. In an attempt to expand this classical picture of BG function, we had earlier hypothesized that the Indirect Pathway (IP) of the BG could be the subcortical substrate for exploration. In this study we build a spiking network model to relate exploration to synchrony levels in the BG (which are a neural marker for tremor in Parkinson's disease). Key BG nuclei such as the Sub Thalamic Nucleus (STN), Globus Pallidus externus (GPe) and Globus Pallidus internus (GPi) were modeled as Izhikevich spiking neurons whereas the Striatal output was modeled as Poisson spikes. The model is cast in reinforcement learning framework with the dopamine signal representing reward prediction error. We apply the model to two decision making tasks: a binary action selection task (similar to one used by Humphries et al., 2006) and an n-armed bandit task (Bourdaud et al., 2008). The model shows that exploration levels could be controlled by STN's lateral connection strength which also influenced the synchrony levels in the STN-GPe circuit. An increase in STN's lateral strength led to a decrease in exploration which can be thought as the possible explanation for reduced exploratory levels in Parkinson's patients. Our simulations also show that on complete removal of IP, the model exhibits only Go and No-Go behaviors, thereby demonstrating the crucial role of IP in exploration. Our model provides a unified account for synchronization, action section, and explorative behavior.
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Affiliation(s)
- Alekhya Mandali
- Computational Neuroscience Lab, Department of Biotechnology, Bhupat and Mehta School of BioSciences, Indian Institute of Technology Madras Chennai, India
| | - Maithreye Rengaswamy
- Computational Neuroscience Lab, Department of Biotechnology, Bhupat and Mehta School of BioSciences, Indian Institute of Technology Madras Chennai, India
| | - V Srinivasa Chakravarthy
- Computational Neuroscience Lab, Department of Biotechnology, Bhupat and Mehta School of BioSciences, Indian Institute of Technology Madras Chennai, India
| | - Ahmed A Moustafa
- Marcs Institute for Brain and Behaviour and School of Social Sciences and Psychology, University of Western Sydney Sydney, NSW, Australia
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Ferrari FAS, Viana RL, Lopes SR, Stoop R. Phase synchronization of coupled bursting neurons and the generalized Kuramoto model. Neural Netw 2015; 66:107-18. [PMID: 25828961 DOI: 10.1016/j.neunet.2015.03.003] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2014] [Revised: 02/24/2015] [Accepted: 03/03/2015] [Indexed: 11/30/2022]
Abstract
Bursting neurons fire rapid sequences of action potential spikes followed by a quiescent period. The basic dynamical mechanism of bursting is the slow currents that modulate a fast spiking activity caused by rapid ionic currents. Minimal models of bursting neurons must include both effects. We considered one of these models and its relation with a generalized Kuramoto model, thanks to the definition of a geometrical phase for bursting and a corresponding frequency. We considered neuronal networks with different connection topologies and investigated the transition from a non-synchronized to a partially phase-synchronized state as the coupling strength is varied. The numerically determined critical coupling strength value for this transition to occur is compared with theoretical results valid for the generalized Kuramoto model.
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Affiliation(s)
- F A S Ferrari
- Department of Physics, Federal University of Paraná, 81531-990 Curitiba, Paraná, Brazil
| | - R L Viana
- Department of Physics, Federal University of Paraná, 81531-990 Curitiba, Paraná, Brazil.
| | - S R Lopes
- Department of Physics, Federal University of Paraná, 81531-990 Curitiba, Paraná, Brazil
| | - R Stoop
- Institute of Neuroinformatics, University of Zürich and Eidgenössische Technische Hochschule Zürich, 8057 Zürich, Switzerland
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Montaseri G, Yazdanpanah MJ, Bahrami F. Designing a deep brain stimulator to suppress pathological neuronal synchrony. Neural Netw 2015; 63:282-92. [PMID: 25601718 DOI: 10.1016/j.neunet.2014.12.008] [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: 03/05/2014] [Revised: 12/15/2014] [Accepted: 12/19/2014] [Indexed: 10/24/2022]
Abstract
Some of neuropathologies are believed to be related to abnormal synchronization of neurons. In the line of therapy, designing effective deep brain stimulators to suppress the pathological synchrony among neuronal ensembles is a challenge of high clinical relevance. The stimulation should be able to disrupt the synchrony in the presence of latencies due to imperfect knowledge about parameters of a neuronal ensemble and stimulation impacts on the ensemble. We propose an adaptive desynchronizing deep brain stimulator capable of dealing with these uncertainties. We analyze the collective behavior of the stimulated neuronal ensemble and show that, using the designed stimulator, the resulting asynchronous state is stable. Simulation results reveal the efficiency of the proposed technique.
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Affiliation(s)
- Ghazal Montaseri
- Advanced Control Systems Laboratory, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran; Department of Systems Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany.
| | - Mohammad Javad Yazdanpanah
- Advanced Control Systems Laboratory, Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| | - Fariba Bahrami
- Human Motor Control and Computational Neuroscience Laboratory, Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
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Kumar G, Ching S. Maximizing relaxation time in oscillator networks with implications for neurostimulation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2014:6589-92. [PMID: 25571506 DOI: 10.1109/embc.2014.6945138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
High frequency deep brain stimulation (HF-DBS) is a pervasive clinical neurostimulation paradigm in which rapid (> 100Hz) pulses of electrical current are invasively delivered to the brain. Here, we use dynamical systems analysis to provide hypotheses regarding the frequency-specificity of the therapeutic effects of HF-DBS. Using phase oscillator-based models, we study the relaxation time of a synchronized network following impulsive stimulation. In particular, by approximating a standard DBS pulse by a finite-energy (Dirac) delta function, we show the existence of a minimum bound on the frequency of stimulation necessary to keep the network in a desynchronized regime. If, as evidence suggests, pathological synchronization is central to the pathology in DBS-responsive disorders, then the analysis gives conceptual insight into why lower frequency and/or randomized stimulation therapy is less effective, and provides a way to study alternative design strategies.
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Wang M, Li M, Geng X, Song Z, Albers HE, Yang M, Zhang X, Xie J, Qu Q, He T. Altered neuronal activity in the primary motor cortex and globus pallidus after dopamine depletion in rats. J Neurol Sci 2015; 348:231-40. [DOI: 10.1016/j.jns.2014.12.014] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2014] [Revised: 11/09/2014] [Accepted: 12/10/2014] [Indexed: 10/24/2022]
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Bour LJ, Ackermans L, Foncke EMJ, Cath D, van der Linden C, Visser Vandewalle V, Tijssen MA. Tic related local field potentials in the thalamus and the effect of deep brain stimulation in Tourette syndrome: Report of three cases. Clin Neurophysiol 2014; 126:1578-88. [PMID: 25435514 DOI: 10.1016/j.clinph.2014.10.217] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2014] [Revised: 10/14/2014] [Accepted: 10/31/2014] [Indexed: 10/24/2022]
Abstract
OBJECTIVE Three patients with intractable Tourette syndrome (TS) underwent thalamic deep brain stimulation (DBS). To investigate the role of thalamic electrical activity in tic generation, local field potentials (LFP), EEG and EMG simultaneously were recorded. METHODS Event related potentials and event related spectral perturbations of EEG and LFP, event related cross-coherences between EEG/LFP and LFP/LFP were analyzed. As time locking events, the tic onsets were used. Spontaneous tics were compared to voluntary tic mimicking. The effect of tic suppression and DBS on thalamic LFPs was evaluated. RESULTS All three patients showed time-locked and prior to onset of spontaneous motor tics thalamic synchronization and thalamo-cortical cross-coherence. Also in three patients, not time-locked to motor tics, increased intra-thalamic coherences in the 1-8Hz frequency band were found. In one patient it was demonstrated that voluntary mimicked tics were preceded by premotor cortical and thalamic potentials. In this patient unilateral thalamic DBS contralaterally decreased the background thalamic activity. CONCLUSIONS The present study in three cases with TS shows that spontaneous tics in TS are preceded by repetitive coherent thalamo-cortical discharges, indicating that preceding a tic the basal ganglia circuits are "charged up", ultimately leading to a motor tic. SIGNIFICANCE Thalamic LFP recording may lead to more insight in underlying pathophysiological mechanisms in TS.
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Affiliation(s)
- L J Bour
- Department of Neurology and Clinical Neurophysiology of the Academic Medical Center, University of Amsterdam, The Netherlands.
| | - L Ackermans
- Department of Neurosurgery, Maastricht University Medical Center, The Netherlands; MIND (Maastricht Institute for Neuromodulative Development), The Netherlands
| | - E M J Foncke
- Department of Neurology of the Free University of Amsterdam, The Netherlands
| | - D Cath
- Department of Clinical and Health Psychology, Utrecht University/Altrecht, Anxiety Outpatient Program, Utrecht, The Netherlands
| | - C van der Linden
- Center for Movement Disorders, St. Lucas Hospital Ghent, Ghent, Belgium
| | - V Visser Vandewalle
- Department of Stereotactic and Functional Neurosurgery, University of Cologne, Germany
| | - M A Tijssen
- Department of Neurology, University of Groningen, The Netherlands
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Herrojo Ruiz M, Rusconi M, Brücke C, Haynes JD, Schönecker T, Kühn AA. Encoding of sequence boundaries in the subthalamic nucleus of patients with Parkinson's disease. ACTA ACUST UNITED AC 2014; 137:2715-30. [PMID: 25031238 DOI: 10.1093/brain/awu191] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Sequential behaviour is widespread not only in humans but also in animals, ranging in different degrees of complexity from locomotion to birdsong or music performance. The capacity to learn new motor sequences relies on the integrity of basal ganglia-cortical loops. In Parkinson's disease the execution of habitual action sequences as well as the acquisition of novel sequences is impaired partly due to a deficiency in being able to generate internal cues to trigger movement sequences. In addition, patients suffering from Parkinson's disease have difficulty initiating or terminating a self-paced sequence of actions. Direct recordings from the basal ganglia in these patients show an increased level of beta (14-30 Hz) band oscillatory activity associated with impairment in movement initiation. In this framework, the current study aims to evaluate in patients with Parkinson's disease the neuronal activity in the subthalamic nucleus related to the encoding of sequence boundaries during the explicit learning of sensorimotor sequences. We recorded local field potential activity from the subthalamic nucleus of 12 patients who underwent deep brain stimulation for the treatment of advanced Parkinson's disease, while the patients in their usual medicated state practiced sequences of finger movements on a digital piano with corresponding auditory feedback. Our results demonstrate that variability in performance during an early phase of sequence acquisition correlates across patients with changes in the pattern of subthalamic beta-band oscillations; specifically, an anticipatory suppression of beta-band activity at sequence boundaries is linked to better performance. By contrast, a more compromised performance is related to attenuation of beta-band activity before within-sequence elements. Moreover, multivariate pattern classification analysis reveals that differential information about boundaries and within-sequence elements can be decoded at least 100 ms before the keystroke from the amplitude of oscillations of subthalamic nucleus activity across different frequency bands, not just from the beta-band. Additional analysis was performed to assess the strength of how much the putative signal encoding class of ordinal position (boundaries, within-sequence elements) is reflected in each frequency band. This analysis demonstrates that suppression of power in the beta-band contains the most class-related information, whereas enhancement of gamma band (31-100 Hz) activity is the second main contributor to the encoding. Our findings support the hypothesis that subthalamic nucleus-mediated gating of salient boundary elements during sequence encoding may be a prerequisite for the adequate acquisition of action sequences and the transition to habitual behaviour.
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Affiliation(s)
- María Herrojo Ruiz
- 1 Department of Neurology, Campus Virchow, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Marco Rusconi
- 2 Bernstein Centre for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christof Brücke
- 1 Department of Neurology, Campus Virchow, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - John-Dylan Haynes
- 2 Bernstein Centre for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany 3 Berlin Centre for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Berlin, Germany 4 Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany 5 Excellence Cluster NeuroCure, Charité-Universitätsmedizin Berlin, Berlin, Germany 6 Department of Psychology, Humboldt Universität zu Berlin, Berlin, Germany
| | - Thomas Schönecker
- 1 Department of Neurology, Campus Virchow, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Andrea A Kühn
- 1 Department of Neurology, Campus Virchow, Charité-Universitätsmedizin Berlin, Berlin, Germany 4 Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany 5 Excellence Cluster NeuroCure, Charité-Universitätsmedizin Berlin, Berlin, Germany
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Ahn S, Solfest J, Rubchinsky LL. Fine temporal structure of cardiorespiratory synchronization. Am J Physiol Heart Circ Physiol 2014; 306:H755-63. [DOI: 10.1152/ajpheart.00314.2013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Cardiac and respiratory rhythms are known to exhibit a modest degree of phase synchronization, which is affected by age, diseases, and other factors. We study the fine temporal structure of this synchrony in healthy young, healthy elderly, and elderly subjects with coronary artery disease. We employ novel time-series analysis to explore how phases of oscillations go in and out of the phase-locked state at each cycle of oscillations. For the first time we show that cardiorespiratory system is engaged in weakly synchronized dynamics with a very specific temporal pattern of synchrony: the oscillations go out of synchrony frequently, but return to the synchronous state very quickly (usually within just 1 cycle of oscillations). Properties of synchrony depended on the age and disease status. Healthy subjects exhibited more synchrony at the higher (1:4) frequency-locking ratio between respiratory and cardiac rhythms, whereas subjects with coronary artery disease exhibited relatively more 1:2 synchrony. However, multiple short desynchronization episodes prevailed regardless of the age and disease status. The same average synchrony level could be alternatively achieved with few long desynchronizations, but this was not observed in the data. This implies functional importance of short desynchronization dynamics. These dynamics suggest that a synchronous state is easy to create if needed but is also easy to break. Short desynchronization dynamics may facilitate the mutual coordination of cardiac and respiratory rhythms by creating intermittent synchronous episodes. It may be an efficient background dynamics to promote adaptation of cardiorespiratory coordination to various external and internal factors.
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Affiliation(s)
- Sungwoo Ahn
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana; and
| | - Jessica Solfest
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana; and
| | - Leonid L. Rubchinsky
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana; and
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana
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Zauber SE, Ahn S, Worth RM, Rubchinsky LL. Oscillatory neural activity of anteromedial globus pallidus internus in Tourette syndrome. Clin Neurophysiol 2014; 125:1923-4. [PMID: 24484872 DOI: 10.1016/j.clinph.2014.01.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2013] [Revised: 12/11/2013] [Accepted: 01/03/2014] [Indexed: 11/18/2022]
Affiliation(s)
- S Elizabeth Zauber
- Department of Neurology, Indiana University School of Medicine, 355 W 16th St., Suite 4700, Indianapolis, IN 46202, USA.
| | - Sungwoo Ahn
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
| | - Robert M Worth
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA; Department of Neurosurgery, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leonid L Rubchinsky
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, 402 N. Blackford St., Indianapolis, IN 46202, USA.
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An improved method to calculate phase locking value based on Hilbert–Huang transform and its application. Neural Comput Appl 2013. [DOI: 10.1007/s00521-013-1510-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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44
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Guo Y, Park C, Worth RM, Rubchinsky LL. Basal ganglia modulation of thalamocortical relay in Parkinson's disease and dystonia. Front Comput Neurosci 2013; 7:124. [PMID: 24046745 PMCID: PMC3763197 DOI: 10.3389/fncom.2013.00124] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2013] [Accepted: 08/17/2013] [Indexed: 11/13/2022] Open
Abstract
Basal ganglia dysfunction has being implied in both Parkinson's disease and dystonia. While these disorders probably involve different cellular and circuit pathologies within and beyond basal ganglia, there may be some shared neurophysiological pathways. For example, pallidotomy and pallidal Deep Brain Stimulation (DBS) are used in symptomatic treatment of both disorders. Both conditions are marked by alterations of rhythmicity of neural activity throughout basal ganglia-thalamocortical circuits. Increased synchronized oscillatory activity in beta band is characteristic of Parkinson's disease, while different frequency bands, theta and alpha, are involved in dystonia. We compare the effect of the activity of GPi, the output nuclei of the basal ganglia, on information processing in the downstream neural circuits of thalamus in Parkinson's disease and dystonia. We use a data-driven computational approach, a computational model of the thalamocortical (TC) cell modulated by experimentally recorded data, to study the differences and similarities of thalamic dynamics in dystonia and Parkinson's disease. Our analysis shows no substantial differences in TC relay between the two conditions. Our results suggest that, similar to Parkinson's disease, a disruption of thalamic processing could also be involved in dystonia. Moreover, the degree to which TC relay fidelity is impaired is approximately the same in both conditions. While Parkinson's disease and dystonia may have different pathologies and differ in the oscillatory content of neural discharge, our results suggest that the effect of patterning of pallidal discharge is similar in both conditions. Furthermore, these results suggest that the mechanisms of GPi DBS in dystonia may involve improvement of TC relay fidelity.
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Affiliation(s)
- Yixin Guo
- Department of Mathematics, Drexel University Philadelphia, PA, USA
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Ahn S, Rubchinsky LL. Fine temporal structure of neural synchronization. BMC Neurosci 2013. [PMCID: PMC3704817 DOI: 10.1186/1471-2202-14-s1-p336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Ahn S, Rubchinsky LL, Lapish CC. Dynamical Reorganization of Synchronous Activity Patterns in Prefrontal Cortex-Hippocampus Networks During Behavioral Sensitization. Cereb Cortex 2013; 24:2553-61. [DOI: 10.1093/cercor/bht110] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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47
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Ahn S, Rubchinsky LL. Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms. CHAOS (WOODBURY, N.Y.) 2013; 23:013138. [PMID: 23556975 PMCID: PMC3606233 DOI: 10.1063/1.4794793] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these synchronization/desynchronization patterns. We employ recently developed techniques to analyze the fine temporal structure of phase-locking to study the temporal patterning of synchrony of the human brain rhythms. We study neural oscillations recorded by electroencephalograms in α and β frequency bands in healthy human subjects at rest and during the execution of a task. While the phase-locking strength depends on many factors, dynamics of synchrony has a very specific temporal pattern: synchronous states are interrupted by frequent, but short desynchronization episodes. The probability for a desynchronization episode to occur decreased with its duration. The transition matrix between synchronized and desynchronized states has eigenvalues close to 0 and 1 where eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution between these states is perturbed, the system converges back to the stationary distribution very fast. The qualitative similarity of this patterning across different subjects, brain states and electrode locations suggests that this may be a general type of dynamics for the brain. Earlier studies indicate that not all oscillatory networks have this kind of patterning of synchronization/desynchronization dynamics. Thus, the observed prevalence of short (but potentially frequent) desynchronization events (length of one cycle of oscillations) may have important functional implications for the brain. Numerous short desynchronizations (as opposed to infrequent, but long desynchronizations) may allow for a quick and efficient formation and break-up of functionally significant neuronal assemblies.
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Affiliation(s)
- Sungwoo Ahn
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University Purdue University Indianapolis, Indiana 46032, USA.
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Failure of delayed feedback deep brain stimulation for intermittent pathological synchronization in Parkinson's disease. PLoS One 2013; 8:e58264. [PMID: 23469272 PMCID: PMC3585780 DOI: 10.1371/journal.pone.0058264] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2012] [Accepted: 02/01/2013] [Indexed: 11/19/2022] Open
Abstract
Suppression of excessively synchronous beta-band oscillatory activity in the brain is believed to suppress hypokinetic motor symptoms of Parkinson's disease. Recently, a lot of interest has been devoted to desynchronizing delayed feedback deep brain stimulation (DBS). This type of synchrony control was shown to destabilize the synchronized state in networks of simple model oscillators as well as in networks of coupled model neurons. However, the dynamics of the neural activity in Parkinson's disease exhibits complex intermittent synchronous patterns, far from the idealized synchronous dynamics used to study the delayed feedback stimulation. This study explores the action of delayed feedback stimulation on partially synchronized oscillatory dynamics, similar to what one observes experimentally in parkinsonian patients. We employ a computational model of the basal ganglia networks which reproduces experimentally observed fine temporal structure of the synchronous dynamics. When the parameters of our model are such that the synchrony is unphysiologically strong, the feedback exerts a desynchronizing action. However, when the network is tuned to reproduce the highly variable temporal patterns observed experimentally, the same kind of delayed feedback may actually increase the synchrony. As network parameters are changed from the range which produces complete synchrony to those favoring less synchronous dynamics, desynchronizing delayed feedback may gradually turn into synchronizing stimulation. This suggests that delayed feedback DBS in Parkinson's disease may boost rather than suppress synchronization and is unlikely to be clinically successful. The study also indicates that delayed feedback stimulation may not necessarily exhibit a desynchronization effect when acting on a physiologically realistic partially synchronous dynamics, and provides an example of how to estimate the stimulation effect.
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Joundi RA, Brittain JS, Green AL, Aziz TZ, Brown P, Jenkinson N. Persistent suppression of subthalamic beta-band activity during rhythmic finger tapping in Parkinson’s disease. Clin Neurophysiol 2013; 124:565-73. [DOI: 10.1016/j.clinph.2012.07.029] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2012] [Revised: 07/17/2012] [Accepted: 07/18/2012] [Indexed: 10/27/2022]
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Park C, Rubchinsky LL. Potential mechanisms for imperfect synchronization in parkinsonian basal ganglia. PLoS One 2012; 7:e51530. [PMID: 23284707 PMCID: PMC3526636 DOI: 10.1371/journal.pone.0051530] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2012] [Accepted: 11/05/2012] [Indexed: 11/18/2022] Open
Abstract
Neural activity in the brain of parkinsonian patients is characterized by the intermittently synchronized oscillatory dynamics. This imperfect synchronization, observed in the beta frequency band, is believed to be related to the hypokinetic motor symptoms of the disorder. Our study explores potential mechanisms behind this intermittent synchrony. We study the response of a bursting pallidal neuron to different patterns of synaptic input from subthalamic nucleus (STN) neuron. We show how external globus pallidus (GPe) neuron is sensitive to the phase of the input from the STN cell and can exhibit intermittent phase-locking with the input in the beta band. The temporal properties of this intermittent phase-locking show similarities to the intermittent synchronization observed in experiments. We also study the synchronization of GPe cells to synaptic input from the STN cell with dependence on the dopamine-modulated parameters. Earlier studies showed how the strengthening of dopamine-modulated coupling may lead to transitions from non-synchronized to partially synchronized dynamics, typical in Parkinson's disease. However, dopamine also affects the cellular properties of neurons. We show how the changes in firing patterns of STN neuron due to the lack of dopamine may lead to transition from a lower to a higher coherent state, roughly matching the synchrony levels observed in basal ganglia in normal and parkinsonian states. The intermittent nature of the neural beta band synchrony in Parkinson's disease is achieved in the model due to the interplay of the timing of STN input to pallidum and pallidal neuronal dynamics, resulting in sensitivity of pallidal output to the phase of the arriving STN input. Thus the mechanism considered here (the change in firing pattern of subthalamic neurons through the dopamine-induced change of membrane properties) may be one of the potential mechanisms responsible for the generation of the intermittent synchronization observed in Parkinson's disease.
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Affiliation(s)
- Choongseok Park
- Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA.
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