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Systems level neurophysiological state characteristics for drug evaluation in an animal model of levodopa-induced dyskinesia.

Tamté, Martin LU ; Brys, Ivani LU ; Richter, Ulrike LU ; Ivica, Nela LU ; Halje, Pär LU and Petersson, Per LU (2016) In Journal of Neurophysiology 115(3). p.1713-1729
Abstract
Disorders affecting the central nervous system have proven particularly hard to treat and disappointingly few of novel therapies have reached the clinics in the last decades. A better understanding of the physiological processes in the brain underlying various symptoms could therefore greatly improve the rate of progress in this field. We here show how systems level descriptions of different brain states reliably can be obtained through a newly developed method based on large-scale recordings in distributed neural networks encompassing several different brain structures. Using this technology we characterize the neurophysiological states associated with parkinsonism and levodopa-induced dyskinesia in a rodent model of Parkinson's disease... (More)
Disorders affecting the central nervous system have proven particularly hard to treat and disappointingly few of novel therapies have reached the clinics in the last decades. A better understanding of the physiological processes in the brain underlying various symptoms could therefore greatly improve the rate of progress in this field. We here show how systems level descriptions of different brain states reliably can be obtained through a newly developed method based on large-scale recordings in distributed neural networks encompassing several different brain structures. Using this technology we characterize the neurophysiological states associated with parkinsonism and levodopa-induced dyskinesia in a rodent model of Parkinson's disease together with pharmacological interventions aimed at reducing dyskinetic symptoms. Our results show that the obtained electrophysiological data add significant information to conventional behavioral evaluations and hereby elucidates the underlying effects of treatments in greater detail. Taken together, these results potentially open up for studies of neurophysiological mechanisms underlying symptoms in a wide range of neurologic and psychiatric conditions that until now have been very hard to investigate in animal models of disease. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Neurophysiology
volume
115
issue
3
pages
1713 - 1729
publisher
American Physiological Society
external identifiers
  • PMID:26740532
  • Scopus:84984794064
ISSN
0022-3077
DOI
10.1152/jn.00868.2015
language
English
LU publication?
yes
id
5f1b59b8-a9b5-4476-8074-8b95277edfde (old id 8592864)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/26740532?dopt=Abstract
date added to LUP
2016-02-01 21:56:54
date last changed
2016-10-13 04:32:22
@misc{5f1b59b8-a9b5-4476-8074-8b95277edfde,
  abstract     = {Disorders affecting the central nervous system have proven particularly hard to treat and disappointingly few of novel therapies have reached the clinics in the last decades. A better understanding of the physiological processes in the brain underlying various symptoms could therefore greatly improve the rate of progress in this field. We here show how systems level descriptions of different brain states reliably can be obtained through a newly developed method based on large-scale recordings in distributed neural networks encompassing several different brain structures. Using this technology we characterize the neurophysiological states associated with parkinsonism and levodopa-induced dyskinesia in a rodent model of Parkinson's disease together with pharmacological interventions aimed at reducing dyskinetic symptoms. Our results show that the obtained electrophysiological data add significant information to conventional behavioral evaluations and hereby elucidates the underlying effects of treatments in greater detail. Taken together, these results potentially open up for studies of neurophysiological mechanisms underlying symptoms in a wide range of neurologic and psychiatric conditions that until now have been very hard to investigate in animal models of disease.},
  author       = {Tamté, Martin and Brys, Ivani and Richter, Ulrike and Ivica, Nela and Halje, Pär and Petersson, Per},
  issn         = {0022-3077},
  language     = {eng},
  number       = {3},
  pages        = {1713--1729},
  publisher    = {ARRAY(0x96cf728)},
  series       = {Journal of Neurophysiology},
  title        = {Systems level neurophysiological state characteristics for drug evaluation in an animal model of levodopa-induced dyskinesia.},
  url          = {http://dx.doi.org/10.1152/jn.00868.2015},
  volume       = {115},
  year         = {2016},
}