Abstract
In rodents, detection and quantification of motor impairments is difficult. The traction test (inverted grid with mice clinging to the underside) currently has no objective rating system. We here developed and validated the semi-automatic MATLAB script TracMouse for unbiased detection of video-recorded movement patterns. High precision videos were analyzed by: (i) principal identification of anatomical paw details frame-by-frame by an experimentally blinded rater; (ii) automatic retrieval of proxies by TracMouse for individual paws. The basic states of Hold and Step were discriminated as duration and frequency, and these principle parameters were converted into static and dynamic endpoints and their discriminating power assessed in a dopaminergic lesion model. Relative to hind paws, forepaws performed ~4 times more steps, they were ~20% longer, and Hold duration was ~5 times shorter in normal C57Bl/6 mice. Thus, forepaw steps were classified as exploratory, hind paw movement as locomotive. Multiple novel features pertaining to paw sequence, step lengths and exploratory touches were accessible through TracMouse and revealed subtle Parkinsonian phenotypes. Novel proxies using TracMouse revealed previously unidentified features of movement and may aid the understanding of (i) brain circuits related to motor planning and execution, and (ii) phenotype detection in experimental models of movement disorders.
| Original language | English |
|---|---|
| Article number | 39331 |
| Journal | Scientific Reports |
| Volume | 6 |
| DOIs | |
| Publication status | Published - 16 Dec 2016 |
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Keywords
- neurological disorders
- neuroscience
Cite this
TracMouse : A computer aided movement analysis script for the mouse inverted horizontal grid test. / Niewiadomski, W; Palasz, E; Skupinska, M; Zylinski, M; Steczkowska, M; Gasiorowska, A; Niewiadomska, G; Riedel, G.
In: Scientific Reports, Vol. 6, 39331, 16.12.2016.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - TracMouse
T2 - A computer aided movement analysis script for the mouse inverted horizontal grid test
AU - Niewiadomski, W
AU - Palasz, E
AU - Skupinska, M
AU - Zylinski, M
AU - Steczkowska, M
AU - Gasiorowska, A
AU - Niewiadomska, G
AU - Riedel, G
N1 - This work was funded by NCN grant 2014/15/B/NZ4/05041 and TauRx Therapeutics/WisTa Laboratories Ltd., Singapore and by statutory funds from the Nencki Institute of Experimental Biology.
PY - 2016/12/16
Y1 - 2016/12/16
N2 - In rodents, detection and quantification of motor impairments is difficult. The traction test (inverted grid with mice clinging to the underside) currently has no objective rating system. We here developed and validated the semi-automatic MATLAB script TracMouse for unbiased detection of video-recorded movement patterns. High precision videos were analyzed by: (i) principal identification of anatomical paw details frame-by-frame by an experimentally blinded rater; (ii) automatic retrieval of proxies by TracMouse for individual paws. The basic states of Hold and Step were discriminated as duration and frequency, and these principle parameters were converted into static and dynamic endpoints and their discriminating power assessed in a dopaminergic lesion model. Relative to hind paws, forepaws performed ~4 times more steps, they were ~20% longer, and Hold duration was ~5 times shorter in normal C57Bl/6 mice. Thus, forepaw steps were classified as exploratory, hind paw movement as locomotive. Multiple novel features pertaining to paw sequence, step lengths and exploratory touches were accessible through TracMouse and revealed subtle Parkinsonian phenotypes. Novel proxies using TracMouse revealed previously unidentified features of movement and may aid the understanding of (i) brain circuits related to motor planning and execution, and (ii) phenotype detection in experimental models of movement disorders.
AB - In rodents, detection and quantification of motor impairments is difficult. The traction test (inverted grid with mice clinging to the underside) currently has no objective rating system. We here developed and validated the semi-automatic MATLAB script TracMouse for unbiased detection of video-recorded movement patterns. High precision videos were analyzed by: (i) principal identification of anatomical paw details frame-by-frame by an experimentally blinded rater; (ii) automatic retrieval of proxies by TracMouse for individual paws. The basic states of Hold and Step were discriminated as duration and frequency, and these principle parameters were converted into static and dynamic endpoints and their discriminating power assessed in a dopaminergic lesion model. Relative to hind paws, forepaws performed ~4 times more steps, they were ~20% longer, and Hold duration was ~5 times shorter in normal C57Bl/6 mice. Thus, forepaw steps were classified as exploratory, hind paw movement as locomotive. Multiple novel features pertaining to paw sequence, step lengths and exploratory touches were accessible through TracMouse and revealed subtle Parkinsonian phenotypes. Novel proxies using TracMouse revealed previously unidentified features of movement and may aid the understanding of (i) brain circuits related to motor planning and execution, and (ii) phenotype detection in experimental models of movement disorders.
KW - neurological disorders
KW - neuroscience
U2 - 10.1038/srep39331
DO - 10.1038/srep39331
M3 - Article
C2 - 27982134
VL - 6
JO - Scientific Reports
JF - Scientific Reports
SN - 2045-2322
M1 - 39331
ER -