Management of Pakshaghata (Hemiplegia due to basal ganglia bleed) through Panchakarma: A case study

ABSTRACT:Background:Transtentorial herniation of large cerebral fragments is a rare phenomenon.Method:Case StudyResults:Examination of the brain of a 35-year-old male showed massive intracerebral hemorrhage resulting in displacement of basal ganglia components into the fourth ventricle.Conclusions:Sufficiently rapid intracerebral bleeding can dissect fragments of cerebrum and displace them long distances across the tentorial opening.

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Case Study: Acute Basal Ganglia Enlargement and Obsessive-Compulsive Symptoms in an Adolescent Boy

Journal of the American Academy of Child & Adolescent Psychiatry ◽

10.1097/00004583-199607000-00017 ◽

1996 ◽

Vol 35 (7) ◽

pp. 913-915 ◽

Cited By ~ 105

Author(s):

JAY N. GIEDD ◽

JUDITH L. RAPOPORT ◽

HENRIETTA L. LEONARD ◽

DANIEL RICHTER ◽

SUSAN E. SWEDO

Keyword(s):

Basal Ganglia ◽

Obsessive Compulsive ◽

Obsessive Compulsive Symptoms

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Multi-objective Evolutionary Algorithms to Investigate Neurocomputational Issues: The Case Study of Basal Ganglia Models

From Animals to Animats 11 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-15193-4_56 ◽

2010 ◽

pp. 597-606 ◽

Cited By ~ 2

Author(s):

Jean Liènard ◽

Agnès Guillot ◽

Benoît Girard

Keyword(s):

Basal Ganglia ◽

Evolutionary Algorithms ◽

Multi Objective

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Persistent denial of handicap after infarction of the right basal ganglia: a case study.

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp.51.1.112 ◽

1988 ◽

Vol 51 (1) ◽

pp. 112-115 ◽

Cited By ~ 25

Author(s):

A House ◽

J Hodges

Keyword(s):

Basal Ganglia ◽

The Right

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Insights into Parkinson’s disease from computational models of the basal ganglia

10.1101/260992 ◽

2018 ◽

Author(s):

Mark D. Humphries ◽

Jose Obeso ◽

Jakob Kisbye Dreyer

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Basal Ganglia ◽

Computational Models ◽

Neural Circuits ◽

Computational Modelling ◽

Beta Band ◽

Complex Interplay ◽

Deep Brain

AbstractMovement disorders arise from the complex interplay of multiple changes to neural circuits. Successful treatments for these disorders could interact with these complex changes in myriad ways, and as a consequence their mechanisms of action and their amelioration of symptoms are incompletely understood. Using Parkinson’s disease as a case-study, we review here how computational models are a crucial tool for taming this complexity, across causative mechanisms, consequent neural dynamics, and treatments. For mechanisms, we review models that capture the effects of losing dopamine on basal ganglia function; for dynamics, we discuss models that have transformed our understanding of how beta-band (15-30 Hz) oscillations arise in the parkinsonian basal ganglia. For treatments, we touch on the breadth of computational modelling work trying to understand the therapeutic actions of deep brain stimulation. Collectively, models from across all levels of description are providing a compelling account of the causes, symptoms, and treatments for Parkinson’s disease.

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Insights into Parkinson’s disease from computational models of the basal ganglia

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2017-315922 ◽

2018 ◽

Vol 89 (11) ◽

pp. 1181-1188 ◽

Cited By ~ 15

Author(s):

Mark D Humphries ◽

Jose Angel Obeso ◽

Jakob Kisbye Dreyer

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Basal Ganglia ◽

Computational Models ◽

Neural Circuits ◽

Computational Modelling ◽

Beta Band ◽

Complex Interplay ◽

Deep Brain

Movement disorders arise from the complex interplay of multiple changes to neural circuits. Successful treatments for these disorders could interact with these complex changes in myriad ways, and as a consequence their mechanisms of action and their amelioration of symptoms are incompletely understood. Using Parkinson’s disease as a case study, we review here how computational models are a crucial tool for taming this complexity, across causative mechanisms, consequent neural dynamics and treatments. For mechanisms, we review models that capture the effects of losing dopamine on basal ganglia function; for dynamics, we discuss models that have transformed our understanding of how beta-band (15–30 Hz) oscillations arise in the parkinsonian basal ganglia. For treatments, we touch on the breadth of computational modelling work trying to understand the therapeutic actions of deep brain stimulation. Collectively, models from across all levels of description are providing a compelling account of the causes, symptoms and treatments for Parkinson’s disease.

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