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Scaling behavior of human locomotor activity amplitude: association with bipolar disorder.

Indic P, Salvatore P, Maggini C, Ghidini S, Ferraro G, Baldessarini RJ, Murray G - PLoS ONE (2011)

Bottom Line: Scale invariance is a feature of complex biological systems, and abnormality of multi-scale behaviour may serve as an indicator of pathology.The hypothalamic suprachiasmatic nucleus (SCN) is a major node in central neural networks responsible for regulating multi-scale behaviour in measures of human locomotor activity.A proposed index of scaling behaviour (Vulnerability Index [VI]) derived from such data distinguished between: [i] healthy subjects at high versus low risk of mood disorders; [ii] currently clinically stable BD patients versus matched controls; and [iii] among clinical states in BD patients.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America. Premananda.Indic@umassmed.edu

ABSTRACT
Scale invariance is a feature of complex biological systems, and abnormality of multi-scale behaviour may serve as an indicator of pathology. The hypothalamic suprachiasmatic nucleus (SCN) is a major node in central neural networks responsible for regulating multi-scale behaviour in measures of human locomotor activity. SCN also is implicated in the pathophysiology of bipolar disorder (BD) or manic-depressive illness, a severe, episodic disorder of mood, cognition and behaviour. Here, we investigated scaling behaviour in actigraphically recorded human motility data for potential indicators of BD, particularly its manic phase. A proposed index of scaling behaviour (Vulnerability Index [VI]) derived from such data distinguished between: [i] healthy subjects at high versus low risk of mood disorders; [ii] currently clinically stable BD patients versus matched controls; and [iii] among clinical states in BD patients.

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Estimated predominant component of motility data.(a) The raw data in arbitrary units (a.u). (b) The estimated circadian rhythm (black line) with its amplitude (blue line). (c) The estimated circadian period (red line) in hours. Due to the non-stationary nature of the data, the estimated amplitude and the period show cycle-to-cycle variability. (d) Normalized scalogram at a specific time of 32 hr. The peak power occurred at a period of 23 h
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pone-0020650-g005: Estimated predominant component of motility data.(a) The raw data in arbitrary units (a.u). (b) The estimated circadian rhythm (black line) with its amplitude (blue line). (c) The estimated circadian period (red line) in hours. Due to the non-stationary nature of the data, the estimated amplitude and the period show cycle-to-cycle variability. (d) Normalized scalogram at a specific time of 32 hr. The peak power occurred at a period of 23 h

Mentions: To check whether vulnerability to BD would typically be inferred from more common analyses of ∼24-hour (circadian) features of actigraphic data, we estimated the predominant component using wavelet transform along with a ridge extraction algorithm [30]. Figure 5 represents an example of the estimated predominant amplitude and the period from a representative human subject. The predominant component of motility data was in the circadian range. However the predominant amplitude in arbitrary units (mean ± SD ranked for low risk: 446±150, versus high risk: 411±145 subjects, BD patients: 332±132, versus healthy controls: 435±146) and the predominant period in hours (mean ± SD ranked for low risk subjects: 24.0±0.20, high risk subjects: 23.9±0.3, BD patients: 24.0±0.05, healthy controls: 24.0±0.1) of the circadian component did not show significant differences among the subject-groups.


Scaling behavior of human locomotor activity amplitude: association with bipolar disorder.

Indic P, Salvatore P, Maggini C, Ghidini S, Ferraro G, Baldessarini RJ, Murray G - PLoS ONE (2011)

Estimated predominant component of motility data.(a) The raw data in arbitrary units (a.u). (b) The estimated circadian rhythm (black line) with its amplitude (blue line). (c) The estimated circadian period (red line) in hours. Due to the non-stationary nature of the data, the estimated amplitude and the period show cycle-to-cycle variability. (d) Normalized scalogram at a specific time of 32 hr. The peak power occurred at a period of 23 h
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3105113&req=5

pone-0020650-g005: Estimated predominant component of motility data.(a) The raw data in arbitrary units (a.u). (b) The estimated circadian rhythm (black line) with its amplitude (blue line). (c) The estimated circadian period (red line) in hours. Due to the non-stationary nature of the data, the estimated amplitude and the period show cycle-to-cycle variability. (d) Normalized scalogram at a specific time of 32 hr. The peak power occurred at a period of 23 h
Mentions: To check whether vulnerability to BD would typically be inferred from more common analyses of ∼24-hour (circadian) features of actigraphic data, we estimated the predominant component using wavelet transform along with a ridge extraction algorithm [30]. Figure 5 represents an example of the estimated predominant amplitude and the period from a representative human subject. The predominant component of motility data was in the circadian range. However the predominant amplitude in arbitrary units (mean ± SD ranked for low risk: 446±150, versus high risk: 411±145 subjects, BD patients: 332±132, versus healthy controls: 435±146) and the predominant period in hours (mean ± SD ranked for low risk subjects: 24.0±0.20, high risk subjects: 23.9±0.3, BD patients: 24.0±0.05, healthy controls: 24.0±0.1) of the circadian component did not show significant differences among the subject-groups.

Bottom Line: Scale invariance is a feature of complex biological systems, and abnormality of multi-scale behaviour may serve as an indicator of pathology.The hypothalamic suprachiasmatic nucleus (SCN) is a major node in central neural networks responsible for regulating multi-scale behaviour in measures of human locomotor activity.A proposed index of scaling behaviour (Vulnerability Index [VI]) derived from such data distinguished between: [i] healthy subjects at high versus low risk of mood disorders; [ii] currently clinically stable BD patients versus matched controls; and [iii] among clinical states in BD patients.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America. Premananda.Indic@umassmed.edu

ABSTRACT
Scale invariance is a feature of complex biological systems, and abnormality of multi-scale behaviour may serve as an indicator of pathology. The hypothalamic suprachiasmatic nucleus (SCN) is a major node in central neural networks responsible for regulating multi-scale behaviour in measures of human locomotor activity. SCN also is implicated in the pathophysiology of bipolar disorder (BD) or manic-depressive illness, a severe, episodic disorder of mood, cognition and behaviour. Here, we investigated scaling behaviour in actigraphically recorded human motility data for potential indicators of BD, particularly its manic phase. A proposed index of scaling behaviour (Vulnerability Index [VI]) derived from such data distinguished between: [i] healthy subjects at high versus low risk of mood disorders; [ii] currently clinically stable BD patients versus matched controls; and [iii] among clinical states in BD patients.

Show MeSH
Related in: MedlinePlus