Chaos and Complexity

Ehlers, Cindy L.

doi:10.1001/archpsyc.1995.03950230074010

Cited by 53 publications

(7 citation statements)

References 42 publications

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“…Despite these limitations, although preliminary, our findings surely suggest that bipolar disorder is associated with an enhanced sleep-related dysregulation of the ANS activity and the use of heartbeat complex dynamics as viable markers of pathological mental conditions. This conclusion is supported by previous evidence suggesting nonlinear analysis of physiological signals to support care in mental health 66 – 68 , thus possibly overcoming the use of scores from structured tests only.…”

Section: Discussionsupporting

confidence: 80%

Heartbeat Complexity Modulation in Bipolar Disorder during Daytime and Nighttime

Nardelli

Lanatà

Bertschy

et al. 2017

Sci Rep

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This study reports on the complexity modulation of heartbeat dynamics in patients affected by bipolar disorder. In particular, a multiscale entropy analysis was applied to the R-R interval series, that were derived from electrocardiographic (ECG) signals for a group of nineteen subjects comprised of eight patients and eleven healthy control subjects. They were monitored using a textile-based sensorized t-shirt during the day and overnight for a total of 47 diurnal and 27 nocturnal recordings. Patients showed three different mood states: depression, hypomania and euthymia. Results show a clear loss of complexity during depressive and hypomanic states as compared to euthymic and healthy control states. In addition, we observed that a more significant complexity modulation among healthy and pathological mood states occurs during the night. These findings suggest that bipolar disorder is associated with an enhanced sleep-related dysregulation of the Autonomic Nervous System (ANS) activity, and that heartbeat complex dynamics may serve as a viable marker of pathological conditions in mental health.

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Section: Discussionsupporting

confidence: 80%

Heartbeat Complexity Modulation in Bipolar Disorder during Daytime and Nighttime

Nardelli

Lanatà

Bertschy

et al. 2017

Sci Rep

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“…Short and noisy time series in biology and medicine are inherently difficult to study, but in one previous paper of bipolar patients analyses of mood recordings over extended time periods (2 years) showed evidence of underlying low-dimensional chaotic dynamics by estimation of correlation dimension [ 31 ]. However, interpretation of such findings are difficult [ 32 ], and we have not tried to use correlation dimension on the present dataset.…”

Section: Discussionmentioning

confidence: 99%

Graph theory applied to the analysis of motor activity in patients with schizophrenia and depression

Fasmer¹,

Fasmer

Berle

et al. 2018

PLoS ONE

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Depression and schizophrenia are defined only by their clinical features, and diagnostic separation between them can be difficult. Disturbances in motor activity pattern are central features of both types of disorders. We introduce a new method to analyze time series, called the similarity graph algorithm. Time series of motor activity, obtained from actigraph registrations over 12 days in depressed and schizophrenic patients, were mapped into a graph and we then applied techniques from graph theory to characterize these time series, primarily looking for changes in complexity. The most marked finding was that depressed patients were found to be significantly different from both controls and schizophrenic patients, with evidence of less regularity of the time series, when analyzing the recordings with one hour intervals. These findings support the contention that there are important differences in control systems regulating motor behavior in patients with depression and schizophrenia. The similarity graph algorithm we have described can easily be applied to the study of other types of time series.

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“…Modeling psychopathological processes with non-linear dynamic systems has been suggested by numerous scholars ( Schiepek and Tschacher, 1992 ; Barton, 1994 ; Belair et al, 1995 ; Ehlers, 1995 ; Heiby, 1995 ; Breakspear, 2006 ; Tschacher and Junghan, 2009 ; Haken and Schiepek, 2010 ; Bystritsky et al, 2012 ; Yang and Tsai, 2013 ). Non-linear dynamic systems are also an emerging field in suicidology ( Mishara, 1996 ; Ramsay, 1997 ; Rogers, 2003 ; Large, 2010 ; Rogers and Lester, 2010 ; Schiepek et al, 2011b ; Sawhney, 2012 ), contributing new perspectives on the emergence and prediction of suicide-related phenomena.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Monitoring of Non-linear Suicidal Dynamics: Methodology and a Demonstrative Case Report

et al. 2016

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In recent years, a number of different authors have stressed the usefulness of non-linear dynamic systems approach in suicide research and suicide prevention. This approach applies specific methods of time series analysis and, consequently, it requires a continuous and fine-meshed assessment of the processes under consideration. The technical means for this kind of process assessment and process analysis are now available. This paper outlines how suicidal dynamics can be monitored in high-risk patients by an Internet-based application for continuous self-assessment with integrated tools of non-linear time series analysis: the Synergetic Navigation System. This procedure is illustrated by data from a patient who attempted suicide at the end of a 90-day monitoring period. Additionally, future research topics and clinical applications of a non-linear dynamic systems approach in suicidology are discussed.

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Chaos and Complexity

Cited by 53 publications

References 42 publications

Heartbeat Complexity Modulation in Bipolar Disorder during Daytime and Nighttime

Heartbeat Complexity Modulation in Bipolar Disorder during Daytime and Nighttime

Graph theory applied to the analysis of motor activity in patients with schizophrenia and depression

Real-Time Monitoring of Non-linear Suicidal Dynamics: Methodology and a Demonstrative Case Report

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