Toward a complex system understanding of bipolar disorder: A chaotic model of abnormal circadian activity rhythms in euthymic bipolar disorder

On the higher-order smallest ring-star network of Chialvo neurons under diffusive couplings

Network dynamical systems with higher-order interactions are a current trending topic, pervasive in many applied fields. However, our focus in this work is neurodynamics. We numerically study the dynamics of the smallest higher-order network of neurons arranged in a ring-star topology. The dynamics of each node in this network is governed by the Chialvo neuron map, and they interact via linear diffusive couplings. This model is perceived to imitate the nonlinear dynamical properties exhibited by a realistic nervous system where the neurons transfer information through multi-body interactions. We deploy the higher-order coupling strength as the primary bifurcation parameter. We start by analyzing our model using standard tools from dynamical systems theory: fixed point analysis, Jacobian matrix, and bifurcation patterns. We observe the coexistence of disparate chaotic attractors. We also observe an interesting route to chaos from a fixed point via period-doubling and the appearance of cyclic quasiperiodic closed invariant curves. Furthermore, we numerically observe the existence of codimension-1 bifurcation points: saddle-node, period-doubling, and Neimark-Sacker. We also qualitatively study the typical phase portraits of the system, and numerically quantify chaos and complexity using the 0-1 test and sample entropy measure, respectively. Finally, we study the synchronization behavior among the neurons using the cross correlation coefficient and the Kuramoto order parameter. We conjecture that unfolding these patterns and behaviors of the network model will help us identify different states of the nervous system, further aiding us in dealing with various neural diseases and nervous disorders.

A critical evaluation of dynamical systems models of bipolar disorder

Bipolar disorder (BD) is a mood disorder involving recurring (hypo)manic and depressive episodes. The inherently temporal nature of BD has inspired its conceptualization using dynamical systems theory, which is a mathematical framework for understanding systems that evolve over time. In this paper, we provide a critical review of the dynamical systems models of BD. Owing to the heterogeneity of methodological and experimental designs in computational modeling, we designed a structured approach that parallels the appraisal of animal models by their face, predictive, and construct validity. This tool, the validity appraisal guide for computational models (VAG-CM), is not an absolute measure of validity, but rather a guide for a more objective appraisal of models in this review. We identified 26 studies published before November 18, 2021 that proposed generative dynamical systems models of time-varying signals in BD. Two raters independently applied the VAG-CM to the included studies, obtaining a mean Cohen's κ of 0.55 (95% CI [0.45, 0.64]) prior to establishing consensus ratings. Consensus VAG-CM ratings revealed three model/study clusters: data-driven models with face validity, theory-driven models with predictive validity, and theory-driven models lacking all forms of validity. We conclude that future modeling studies should employ a hybrid approach that first operationalizes BD features of interest using empirical data to achieve face validity, followed by explanations of those features using generative models with components that are homologous to physiological or psychological systems involved in BD, to achieve construct validity. Such models would be best developed alongside long-term prospective cohort studies involving a collection of multimodal time-series data. We also encourage future studies to extend, modify, and evaluate the VAG-CM approach for a wider breadth of computational modeling studies and psychiatric disorders.

Inactograms and objective sleep measures as means to capture subjective sleep problems in patients with a bipolar disorder

BACKGROUND

Sleep problems are common in bipolar disorders (BDs). To objectively characterize these problems in BDs, further methodological development is needed to capture subjective insomnia.

AIM

To test psychometric properties of the Athens Insomnia Scale (AIS), and associations with actigraphy-derived measures, applying modifications in actigraphy data processing to capture features of perturbed sleep in patients with a BD.

METHODS

Seventy-four patients completed the AIS and the Quick Inventory of Depressive Symptomatology, self-report (QIDS-SR-16). Locomotor activity was continuously recorded by wrist actigraphy for ≥10 consecutive days. We computed the sleep onset/offset, the center of daily inactivity (CenDI), as a proxy for chronotype, and the degree of consolidation of daily inactivity (ConDI), as a proxy for sleep-wake rhythm strength.

RESULTS

AIS showed good psychometric properties (Cronbach's alpha = 0.84; test-retest correlation = 0.84, P<.001). Subjective sleep problems correlated moderately with a later sleep phase (CenDI with AIS rho = 0.34, P = .003), lower consolidation (ConDI with AIS rho = -0.22, P = .05; with QIDS-SR-16 rho = -0.27, P = .019), later timing of sleep offset (with AIS rho = 0.49, P = ≤.001, with QIDS-SR-16 rho = 0.36, P = .002), and longer total sleep (with AIS rho = 0.29, P = .012, with QIDS-SR-16 rho = 0.41, P = ≤.001). While AIS was psychometrically more solid, correlations with objective sleep were more consistent across time for QIDS-SR-16.

CONCLUSIONS

AIS and QIDS-SR-16 are suitable for clinical screening of sleep problems among patients with a BD. Subjective insomnia associated with objective measures. For clinical and research purposes, actigraphy and data visualization on inactograms are useful for accurate longitudinal characterization of sleep patterns.

Measuring circadian function in bipolar disorders: Empirical and conceptual review of physiological, actigraphic, and self-report approaches

BACKGROUND

Interest in biological clock pathways in bipolar disorders (BD) continues to grow, but there has yet to be an audit of circadian measurement tools for use in BD research and practice.

PROCEDURE

The International Society for Bipolar Disorders Chronobiology Task Force conducted a critical integrative review of circadian methods that have real-world applicability. Consensus discussion led to the selection of three domains to review-melatonin assessment, actigraphy, and self-report.

RESULTS

Measurement approaches used to quantify circadian function in BD are described in sufficient detail for researchers and clinicians to make pragmatic decisions about their use. A novel integration of the measurement literature is offered in the form of a provisional taxonomy distinguishing between circadian measures (the instruments and methods used to quantify circadian function, such as dim light melatonin onset) and circadian constructs (the biobehavioral processes to be measured, such as circadian phase).

CONCLUSIONS

Circadian variables are an important target of measurement in clinical practice and biomarker research. To improve reproducibility and clinical application of circadian constructs, an informed systematic approach to measurement is required. We trust that this review will decrease ambiguity in the literature and support theory-based consideration of measurement options.

Transition of Neural Activity From the Chaotic Bipolar-Disorder State to the Periodic Healthy State Using External Feedback Signals

Chronotherapy is a treatment for mood disorders, including major depressive disorder, mania, and bipolar disorder (BD). Neurotransmitters associated with the pathology of mood disorders exhibit circadian rhythms. A functional deficit in the neural circuits related to mood disorders disturbs the circadian rhythm; chronotherapy is an intervention that helps resynchronize the patient's biological clock with the periodic daily cycle, leading to amelioration of symptoms. In previous reports, Hadaeghi et al. proposed a non-linear dynamic model composed of the frontal and sensory cortical neural networks and the hypothalamus to explain the relationship between deficits in neural function in the frontal cortex and the disturbed circadian rhythm/mood transitions in BD (hereinafter referred to as the Hadaeghi model). In this model, neural activity in the frontal and sensory lobes exhibits periodic behavior in the healthy state; while in BD, this neural activity is in a state of chaos-chaos intermittency; this temporal departure from the healthy periodic state disturbs the circadian pacemaker in the hypothalamus. In this study, we propose an intervention based on a feedback method called the “reduced region of orbit” (RRO) method to facilitate the transition of the disturbed frontal cortical neural activity underlying BD to healthy periodic activity. Our simulation was based on the Hadaeghi model. We used an RRO feedback signal based on the return-map structure of the simulated frontal and sensory lobes to induce synchronization with a relatively weak periodic signal corresponding to the healthy condition by applying feedback of appropriate strength. The RRO feedback signal induces chaotic resonance, which facilitates the transition to healthy, periodic frontal neural activity, although this synchronization is restricted to a relatively low frequency of the periodic input signal. Additionally, applying an appropriate strength of the RRO feedback signal lowered the amplitude of the periodic input signal required to induce a synchronous state compared with the periodic signal applied alone. In conclusion, through a chaotic-resonance effect induced by the RRO feedback method, the state of the disturbed frontal neural activity characteristic of BD was transformed into a state close to healthy periodic activity by relatively weak periodic perturbations. Thus, RRO feedback-modulated chronotherapy might be an innovative new type of minimally invasive chronotherapy.

Which actigraphic variables optimally characterize the sleep-wake cycle of individuals with bipolar disorders?

OBJECTIVE

To examine which combination of objectively measured actigraphy parameters best characterizes the sleep-wake cycle of euthymic individuals with bipolar disorder (BD) compared with healthy controls (HC).

METHODS

Sixty-one BD cases and 61 matched HC undertook 21 consecutive days of actigraphy. Groups were compared using discriminant function analyses (DFA) that explored dimensions derived from mean values of sleep parameters (Model 1); variability of sleep parameters (2); daytime activity (3); and combined sleep and activity parameters (4). Exploratory within-group analyses examined characteristics associated with misclassification.

RESULTS

After controlling for depressive symptoms, the combined model (4) correctly classified 75% cases, while the sleep models (1 and 2) correctly classified 87% controls. The area under the curve favored the combined model (0.86). Age was significantly associated with misclassification among HC, while a diagnosis of BD-II was associated with an increased risk of misclassifications of cases.

CONCLUSION

Including sleep variability and activity parameters alongside measures of sleep quantity improves the characterization of cases of euthymic BD and helps distinguish them from HC. If replicated, the findings indicate that traditional approaches to actigraphy (examining mean values for the standard set of sleep parameters) may represent a suboptimal approach to understanding sleep-wake cycles in BD.

Circadian modulation of human reward function: Is there an evidentiary signal in existing neuroimaging studies?

Reward functioning in animals is modulated by the circadian system, but such effects are poorly understood in the human case. The aim of this study was to address this deficit via a systematic review of human fMRI studies measuring one or more proxies for circadian function and a neural reward outcome. A narrative synthesis of 15 studies meeting inclusion criteria identified 13 studies that show a circadian impact on the human reward system, with four types of proxy (circadian system biology, downstream circadian rhythms, circadian challenge, and time of day) associated with neural reward activation. Specific reward-related regions/networks subserving this effect included the medial prefrontal cortex, ventral striatum, putamen and default mode network. The circadian effect was observed in measures of both reward anticipation and reward receipt, with more consistent evidence for the latter. Findings are limited by marked heterogeneity across study designs. We encourage a systematic program of research investigating circadian-reward interactions as an adapted biobehavioural feature and as an aetiological mechanism in reward-related pathologies.

Critical slowing down as an early warning of transitions in episodes of bipolar disorder: A simulation study based on a computational model of circadian activity rhythms

Bipolar disorder is characterized by repeated episodes of mania and depression, and can be understood as pathological complex system behaviour involving cognitive, affective and psychomotor disturbance. Accurate prediction of episode transitions in the long-term pattern of mood changes in bipolar disorder could improve the management of the disorder by providing an objective early warning of relapse. In particular, circadian activity changes measured via actigraphy may contain clinically relevant signals of imminent systemic dysregulation. In this study, we propose a mathematical index to investigate the correlation between apparently irregular circadian activity rhythms and critical transitions in episodes of bipolar disorder. Not only does the proposed index illuminate the effects of pharmacological and psychological therapies in control over the state, but it also provides a framework to understand the dynamic (or state-dependent) control strategies. Modelling analyses using our new approach suggest that key clinical goals are minimizing side effects of mood stabilizers as well as increasing the efficiency of other therapeutic strategies.