research-article

The Recurrence Dynamics of Personalized Depression

Author:

Tuan PhamAuthors Info & Claims

ACSW '20: Proceedings of the Australasian Computer Science Week Multiconference

Article No.: 38, Pages 1 - 8

https://doi.org/10.1145/3373017.3373057

Published: 04 February 2020 Publication History

Abstract

The purpose of this study is to explore advanced methods of complex system dynamics to discover latent patterns from nonlinear time series of personalized major depression. The study was performed with methods for analysis of complex system dynamics, including fuzzy recurrence plots, fuzzy joint recurrence plots, fuzzy weighted recurrence networks, and tensor decomposition of the recurrence dynamics. Both the use of two complex network properties known as the average clustering coefficient and characteristic path length and the tensor decomposition of the fuzzy weighted recurrence plots of the depression time series suggest a critical transition as an early warning signal in the reduction of anti-depressant medication applied to a single participant. Fuzzy recurrence plots, fuzzy recurrence networks, and tensor decomposition of mental-state dynamics are useful mathematical tools for constructing patient-specific models of the dynamics of depression and detecting development of new depressive episodes over the effect of drug-dosage alteration.

References

[1]

[1] Depression. National Institute of Mental Health, https://www.nimh.nih.gov/health/topics/depression/index.shtml (2018). Accessed 16 June 2019.

[2]

[2] Depression (major depressive disorder). Mayo Clinic, https://www.mayoclinic.org/diseases-conditions/depression/symptoms-causes/syc-20356007 (2019). Accessed 16 June 2019.

[3]

[3] Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, et al. Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS Med 2013; 10:10e1001547.

[4]

[4] Bhandari S. Untreated depression. WebMD Medical Reference, https://www.webmd.com/depression/guide/untreated-depression-effects#1 (17 August 2017). Accessed 16 June 2019.

[5]

[5] Briggs R, Tobin K, Kenny RA, Kennelly SP. What is the prevalence of untreated depression and death ideation in older people? Data from the Irish Longitudinal Study on Aging. Int Psychogeriatr 2018; 30:1393-1401.

[6]

[6] Wichers M, Groot PC, Psychosystems, ESM Group, EWS Group. Critical slowing down as a personalized early warning signal for depression. Psychother Psychosom 2016; 85:114-116.

[7]

[7] Scheffer M, Bascompte J, Brock WA, Brovkin V, Carpenter SR, Dakos V, et al. Early-warning signals for critical transitions. Nature 2009; 461:53-59.

[8]

[8] Van de Leemput IA, Wichers M, Cramer AO, Borsboom D, Tuerlinckx F, Kuppens P, et al. Critical slowing down as early warning for the onset and termination of depression. Proc Natl Acad Sci USA 2014; 111: 87-92.

[9]

[9] Beard C, Millner AJ, Forgeard MJ, Fried EI, Hsu KJ, Treadway MT, et al. Network analysis of depression and anxiety symptom relationships in a psychiatric sample. Psychol Med 2016; 46:3359-3369.

[10]

[10] McElroy E, Napoleone E, Wolpert M, Patalay P. Structure and connectivity of depressive symptom networks corresponding to early treatment response. EClinicalMedicine 2019; 8:29-36.

[11]

[11] Wichers M, Wigman JT, Bringmann LF, de Jonge P. Mental disorders as networks: some cautionary reflections on a promising approach. Soc Psychiatry Psychiatr Epidemiol 2017; 52:143-145

[12]

[12] Schweren L, van Borkulo C, Fried E, Goodyear I. Assessment of symptom network density as a prognostic marker of treatment response in adolescent depression. JAMA Psychiatry 2018; 75:98-100.

[13]

[13] Groot PC. Patients can diagnose too: how continuous self-assessment aids diagnosis of, and recovery from, depression. J. Ment. Heal. 2010; 19:352-362.

[14]

[14] Kossakowski JJ, Groot PC, Haslbeck JMB, Borsboom D, Wichers M. Data from ‘Critical Slowing Down as a Personalized Early Warning Signal for Depression’. Journal of Open Psychology Data 2017; 5:1.

[15]

[15] Eckmann JP, Kamphorst SO, Ruelle D. Recurrence plots of dynamical systems. Europhysics Letters 1987; 4:973-977.

[16]

[16] Pham TD. Fuzzy recurrence plots. EPL 2016; 116:50008.

[17]

[17] Zadeh LA. Similarity relations and fuzzy orderings. Information Sciences 1971; 3: 177-200.

[18]

[18] Bezdek JC. Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Plenum Press; 1981.

[19]

[19] Pham TD. Fuzzy cross and fuzzy joint recurrence plots. Physica A, published online 04 October 2019.

[20]

[20] Romano M, Thiel M, Kurths J, von Bloh W. Multivariate recurrence plots. Physics Letters A 2004; 330:214-223.

[21]

[21] Pham TD. Fuzzy weighted recurrence networks of time series. Physica A 2019; 513:409-417.

[22]

[22] Pham TD. From fuzzy recurrence plots to scalable recurrence networks of time series. EPL 2017; 118:20003.

[23]

[23] Watts DJ, Strogatz S. Collective dynamics of “small-world” networks. Nature 1998, 393:440-442.

[24]

[24] Barrat A, Barthelemy M, Pastor-Satorras R, Vespignani A. The architecture of complex weighted networks. Proceedings of the National Academy of Sciences 2004; 101:3747-3752.

[25]

[25] Albert R, Barabasi AL. Statistical mechanics of complex networks. Rev. Mod. Phys. 2002; 74:47-97.

[26]

[26] Fagiolo G. Clustering in complex directed networks. Phys Rev. E. 2007; 76:026107.

[27]

[27] Cichocki A, et al. Tensor decompositions for signal processing applications: From two-way to multiway component analysis. IEEE Signal Processing Magazine 2015; 32:145-163.

[28]

[28] Harshman RA. Foundations of the PARAFAC procedure: Models and conditions for an “explanatory” multi-modal factor analysis. UCLA Working Papers in Phonetics 1970; 16:1-84.

[29]

[29] Bro R. PARAFAC. Tutorial and applications. Chemometrics and Intelligent Laboratory Systems 1997; 38:149-171.

[30]

[30] Pham TD, Yan H. Tensor decomposition of gait dynamics in Parkinson’s disease. IEEE Trans Biomedical Engineering 2018; 65:1820-1827.

[31]

[31] Andersson CA, Bro R. The N-way Toolbox for MATLAB. Chemometrics and Intelligent Laboratory Systems 2000; 52:1-4.

Cited By

Pham T(2022)Identifying critical transitions in major depression with fuzzy recurrence entropyAll Life10.1080/26895293.2022.213201715:1(1086-1100)Online publication date: 11-Oct-2022
https://doi.org/10.1080/26895293.2022.2132017
Pham TAl Anezi F(2021)Fuzzy Cross Recurrence Analysis and Tensor Decomposition of Major-Depression Time-Series DataInternational Conference on Data Science, E-learning and Information Systems 202110.1145/3460620.3460626(28-34)Online publication date: 5-Apr-2021
https://dl.acm.org/doi/10.1145/3460620.3460626
Pham T(2021)Fusion of Momentary Moods in Major Depression with Fuzzy Recurrence Analysis and Tensor Decomposition2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)10.1109/ICECET52533.2021.9698467(1-6)Online publication date: 9-Dec-2021
https://doi.org/10.1109/ICECET52533.2021.9698467
Show More Cited By

Recommendations

Fuzzy Cross Recurrence Analysis and Tensor Decomposition of Major-Depression Time-Series Data
DATA'21: International Conference on Data Science, E-learning and Information Systems 2021

The mechanism underlying the complex behavior of major or clinical depression has been hypothesized as a dynamical system. This study presents an analysis of mood self-assessment in major depression using the method of fuzzy cross recurrence plots and ...
Complex dynamics in one-dimensional CNNs: Research Articles
Special Issue on CNN Technology (Part 1)

The effect of boundary conditions on the global dynamics of cellular neural networks (CNNs) is investigated. As a case study one-dimensional template CNNs are considered. It is shown that if the off-diagonal template elements have opposite sign, then ...
A combinatorial approach to a general two-term recurrence

We provide combinatorial proofs of explicit formulas for some sequences satisfying particular cases of the general recurrence |nk|=(@a(n-1)+@bk+@c)|n-1k|+(@a^'(n-1)+@b^'k+@c^')|n-1k-1|+[n=k=0], which have been previously shown using other methods. Many ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

ACSW '20: Proceedings of the Australasian Computer Science Week Multiconference

February 2020

367 pages

ISBN:9781450376976

DOI:10.1145/3373017

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 February 2020

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

ACSW '20

ACSW '20: Australasian Computer Science Week 2020

February 4 - 6, 2020

VIC, Melbourne, Australia

Acceptance Rates

Overall Acceptance Rate 61 of 141 submissions, 43%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
162
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)1

Reflects downloads up to 26 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Pham T(2022)Identifying critical transitions in major depression with fuzzy recurrence entropyAll Life10.1080/26895293.2022.213201715:1(1086-1100)Online publication date: 11-Oct-2022
https://doi.org/10.1080/26895293.2022.2132017
Pham TAl Anezi F(2021)Fuzzy Cross Recurrence Analysis and Tensor Decomposition of Major-Depression Time-Series DataInternational Conference on Data Science, E-learning and Information Systems 202110.1145/3460620.3460626(28-34)Online publication date: 5-Apr-2021
https://dl.acm.org/doi/10.1145/3460620.3460626
Pham T(2021)Fusion of Momentary Moods in Major Depression with Fuzzy Recurrence Analysis and Tensor Decomposition2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)10.1109/ICECET52533.2021.9698467(1-6)Online publication date: 9-Dec-2021
https://doi.org/10.1109/ICECET52533.2021.9698467
Olthof MHasselman FLichtwarck-Aschoff A(2020)Complexity in psychological self-ratings: implications for research and practiceBMC Medicine10.1186/s12916-020-01727-218:1Online publication date: 8-Oct-2020
https://doi.org/10.1186/s12916-020-01727-2
Pham T(2020)Visual Computing of Causality in Personalized Depression2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)10.1109/EMBC44109.2020.9176637(5510-5513)Online publication date: Jul-2020
https://doi.org/10.1109/EMBC44109.2020.9176637

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten