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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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Characterization of the probability distribution of amplitudes using Gamma and Rayleigh functions.(a) Probability distribution P(A) for a subject considered to be a low risk for BD at a scale s∼0.59 h, along with Gamma (black line) and Rayleigh (grey line) best-fit functions: based on AIC, the Gamma distribution yields a better fit. (b) Probability distribution P(A) at a scale of s∼3.0 h for the same subject: the fit of the Rayleigh distribution function (gray line) is superior to the Gamma function at this scale, by AIC criteria. (c) Average value of the shape parameter, , at different scales (hours) for 35 subjects considered to be low risk for BD by GBI criteria (open circles) and another 35 at high risk (filled circles).
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pone-0020650-g003: Characterization of the probability distribution of amplitudes using Gamma and Rayleigh functions.(a) Probability distribution P(A) for a subject considered to be a low risk for BD at a scale s∼0.59 h, along with Gamma (black line) and Rayleigh (grey line) best-fit functions: based on AIC, the Gamma distribution yields a better fit. (b) Probability distribution P(A) at a scale of s∼3.0 h for the same subject: the fit of the Rayleigh distribution function (gray line) is superior to the Gamma function at this scale, by AIC criteria. (c) Average value of the shape parameter, , at different scales (hours) for 35 subjects considered to be low risk for BD by GBI criteria (open circles) and another 35 at high risk (filled circles).

Mentions: To look for any scale-invariant feature in the amplitude distribution at multiple time scales, we plotted the estimated shape parameter, γ, of the Gamma distribution fit at different time scales. We found that the shape parameter exhibited multi-scale behavior (Figure 3). If the shape parameter of the individual distribution showed a constant value for time scales up to 2.0 h, this would indicate scale-invariance. However, the shape parameter decreased at short time scales and gradually increased at longer time scales. Although the long-tail distribution was a property of the data, the amplitude distribution lacked a scale-invariant feature. Since such a non-collapsed nature of the distribution may represent an abnormality of the system, we investigated plausible correlates of this multi-scale behavior to the illness of BD. To quantify the observed behavior, we integrated the shape parameter up to 2.0 h time scales for each subject as . The derived integral, termed a vulnerability index (VI), was used in hypothesis-testing analyses.


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)

Characterization of the probability distribution of amplitudes using Gamma and Rayleigh functions.(a) Probability distribution P(A) for a subject considered to be a low risk for BD at a scale s∼0.59 h, along with Gamma (black line) and Rayleigh (grey line) best-fit functions: based on AIC, the Gamma distribution yields a better fit. (b) Probability distribution P(A) at a scale of s∼3.0 h for the same subject: the fit of the Rayleigh distribution function (gray line) is superior to the Gamma function at this scale, by AIC criteria. (c) Average value of the shape parameter, , at different scales (hours) for 35 subjects considered to be low risk for BD by GBI criteria (open circles) and another 35 at high risk (filled circles).
© Copyright Policy
Related In: Results  -  Collection

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

pone-0020650-g003: Characterization of the probability distribution of amplitudes using Gamma and Rayleigh functions.(a) Probability distribution P(A) for a subject considered to be a low risk for BD at a scale s∼0.59 h, along with Gamma (black line) and Rayleigh (grey line) best-fit functions: based on AIC, the Gamma distribution yields a better fit. (b) Probability distribution P(A) at a scale of s∼3.0 h for the same subject: the fit of the Rayleigh distribution function (gray line) is superior to the Gamma function at this scale, by AIC criteria. (c) Average value of the shape parameter, , at different scales (hours) for 35 subjects considered to be low risk for BD by GBI criteria (open circles) and another 35 at high risk (filled circles).
Mentions: To look for any scale-invariant feature in the amplitude distribution at multiple time scales, we plotted the estimated shape parameter, γ, of the Gamma distribution fit at different time scales. We found that the shape parameter exhibited multi-scale behavior (Figure 3). If the shape parameter of the individual distribution showed a constant value for time scales up to 2.0 h, this would indicate scale-invariance. However, the shape parameter decreased at short time scales and gradually increased at longer time scales. Although the long-tail distribution was a property of the data, the amplitude distribution lacked a scale-invariant feature. Since such a non-collapsed nature of the distribution may represent an abnormality of the system, we investigated plausible correlates of this multi-scale behavior to the illness of BD. To quantify the observed behavior, we integrated the shape parameter up to 2.0 h time scales for each subject as . The derived integral, termed a vulnerability index (VI), was used in hypothesis-testing analyses.

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