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The relevance of the neural code in the Basal Ganglia for the treatment of Parkinson's disease: Beyond the rate and pattern models


Andres, Daniela; Cerquetti, Daniel; Merello, Marcelo (2012). The relevance of the neural code in the Basal Ganglia for the treatment of Parkinson's disease: Beyond the rate and pattern models. In: Yoshida, Chiyo; Ito, Ami. Parkinson's Disease: Diagnosis, Treatment and Prognosis. New York, USA: Nova Science Publishers, 99-120.

Abstract

Deep Brain Stimulation (DBS) therapy refers to the electrical stimulation of specific neural centers and has been successfully applied in a number of pathologies, which include Parkinson’s disease, dystonia and tremor among others. The classic model of Parkinson’s disease, which explains the motor symptoms of the condition based on the Globus Pallidus pars interna (GPi) overactivity, has demonstrated many inconsistencies after being compared with results of functional neurosurgery in human patients. The GPi normally exerts an inhibitory influence over the motor cortex, because of what it is mostly interpreted as an inhibiting structure of motor activity. Evidence coming from patients with implanted DBS has shown that stimulation of the GPi further increments the activity of the nucleus. Even more, DBS is known to be effective both in patients with Parkinson’s disease and patients with dystonia, two pathologies that were interpreted as originating from opposite mechanisms in the classical framework. Finally, DBS is able to alleviate motor symptoms of Parkinson’s disease when applied to different parts of the Basal Ganglia, another fact that contradicts the classic box-and-arrow model. The
mentioned evidence brings to light the fact that new approaches are needed to describe and understand the physiopathology of the Basal Ganglia and Parkinson’s disease from a formal point of view beyond the rate or pattern models. In this context it becomes relevant the study of the structure of the neural code in the Basal Ganglia with new analysis tools that allow the characterization of their neuronal discharge in a more thorough and quantitative way. In this direction non-linear analysis tools have been recently applied to the study of neurophysiological signals from parkinsonian subjects with different degrees of success. Several authors have proposed that non-linear properties might be helpful to create new models of Parkinson’s disease and further understand the mechanisms underlying DBS. In previous works by our group with neuronal recordings from human patients with Parkinson’s disease, we have found similarities between the behavior of turbulent fluids and the neuronal discharge from the Basal Ganglia. In the present chapter we review current knowledge about the structure of the neural code in the Basal Ganglia. We summarize what is currently thought about mathematical features of the neuronal discharge of the Basal Ganglia under different experimental settings. Finally, we discuss the implications that the structure of the neural code has for DBS therapy and propose a simple and novel hypothesis derived from fluid dynamics that could be helpful in future models of DBS and Parkinson’s disease.

Abstract

Deep Brain Stimulation (DBS) therapy refers to the electrical stimulation of specific neural centers and has been successfully applied in a number of pathologies, which include Parkinson’s disease, dystonia and tremor among others. The classic model of Parkinson’s disease, which explains the motor symptoms of the condition based on the Globus Pallidus pars interna (GPi) overactivity, has demonstrated many inconsistencies after being compared with results of functional neurosurgery in human patients. The GPi normally exerts an inhibitory influence over the motor cortex, because of what it is mostly interpreted as an inhibiting structure of motor activity. Evidence coming from patients with implanted DBS has shown that stimulation of the GPi further increments the activity of the nucleus. Even more, DBS is known to be effective both in patients with Parkinson’s disease and patients with dystonia, two pathologies that were interpreted as originating from opposite mechanisms in the classical framework. Finally, DBS is able to alleviate motor symptoms of Parkinson’s disease when applied to different parts of the Basal Ganglia, another fact that contradicts the classic box-and-arrow model. The
mentioned evidence brings to light the fact that new approaches are needed to describe and understand the physiopathology of the Basal Ganglia and Parkinson’s disease from a formal point of view beyond the rate or pattern models. In this context it becomes relevant the study of the structure of the neural code in the Basal Ganglia with new analysis tools that allow the characterization of their neuronal discharge in a more thorough and quantitative way. In this direction non-linear analysis tools have been recently applied to the study of neurophysiological signals from parkinsonian subjects with different degrees of success. Several authors have proposed that non-linear properties might be helpful to create new models of Parkinson’s disease and further understand the mechanisms underlying DBS. In previous works by our group with neuronal recordings from human patients with Parkinson’s disease, we have found similarities between the behavior of turbulent fluids and the neuronal discharge from the Basal Ganglia. In the present chapter we review current knowledge about the structure of the neural code in the Basal Ganglia. We summarize what is currently thought about mathematical features of the neuronal discharge of the Basal Ganglia under different experimental settings. Finally, we discuss the implications that the structure of the neural code has for DBS therapy and propose a simple and novel hypothesis derived from fluid dynamics that could be helpful in future models of DBS and Parkinson’s disease.

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Contributors:Movements Disorders Section, Raul Carrea Institute for Neurological Research, Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia (FLENI), Argentina
Item Type:Book Section, not refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:July 2012
Deposited On:06 Mar 2013 08:32
Last Modified:05 Apr 2016 16:36
Publisher:Nova Science Publishers
ISBN:978-1-61942-830-0
Official URL:https://www.novapublishers.com/catalog/product_info.php?products_id=28727
Related URLs:http://opac.nebis.ch/F/?local_base=NEBIS&CON_LNG=GER&func=find-b&find_code=SYS&request=007582455

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