Systems level neurophysiological state characteristics for drug evaluation in an animal model of levodopa-induced dyskinesia.
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8592864
- author
- Tamté, Martin LU ; Brys, Ivani LU ; Richter, Ulrike LU ; Ivica, Nedjeljka LU ; Halje, Pär LU and Petersson, Per LU
- organization
- publishing date
- 2016
- 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
- pmid:26740532
- scopus:84984794064
- wos:000376057400049
- 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
- 2016-04-04 09:32:12
- date last changed
- 2022-05-09 05:29:34
@article{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, Nedjeljka and Halje, Pär and Petersson, Per}},
issn = {{0022-3077}},
language = {{eng}},
number = {{3}},
pages = {{1713--1729}},
publisher = {{American Physiological Society}},
series = {{Journal of Neurophysiology}},
title = {{Systems level neurophysiological state characteristics for drug evaluation in an animal model of levodopa-induced dyskinesia.}},
url = {{https://lup.lub.lu.se/search/files/27488018/5350550_.pdf}},
doi = {{10.1152/jn.00868.2015}},
volume = {{115}},
year = {{2016}},
}