Use of methods from chaos theory to quantify a fundamental dysfunction in the behavioral organization of schizophrenic patients

Paulus, Martin P.; Ma, Geyer; Dl, Braff

doi:10.1176/ajp.153.5.714

Cited by 79 publications

(9 citation statements)

References 12 publications

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“…Several investigators have examined complexity in psychotic disorders. More predictable (i.e., decreased complexity) behavior in a consecutive binary choice task has been reported in SZ (Paulus et al, 1996). Decreased nonlinear complexity has been observed during REM and wake periods while undergoing sleep polysomnography in first episode SZ patients (Keshavan et al, 2004).…”

Section: Introductionmentioning

confidence: 79%

Neural complexity as a potential translational biomarker for psychosis

Hager

Yang

Brady

et al. 2017

Journal of Affective Disorders

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Background The adaptability of the human brain to the constantly changing environment is reduced in patients with psychotic disorders, leading to impaired cognitive functions. Brain signal complexity, which may reflect adaptability, can be readily quantified via resting-state functional magnetic resonance imaging (fMRI) signals. We hypothesized that resting-state brain signal complexity is altered in psychotic disorders, and is correlated with cognitive impairment. Methods We assessed 156 healthy controls (HC) and 330 probands, including 125 patients with psychotic bipolar disorder (BP), 107 patients with schizophrenia (SZ), 98 patients with schizoaffective disorder (SAD) and 230 of their unaffected first-degree relatives (76 BPR, 79 SADR, and 75 SZR) from four sites of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium. Using multi-scale entropy analysis, we determined whether patients and/or relatives had pathologic differences in complexity of resting-state fMRI signals toward regularity (reduced entropy in all time scales), or toward uncorrelated randomness (increased entropy in fine time scales that decays as the time scale increases) and how these complexity differences might be associated with cognitive impairment. Results Compared to HC subjects, proband groups showed either decreased complexity toward regularity or toward randomness. SZ probands showed decreased complexity toward regular signal in hypothalamus, and BP probands in left inferior occipital, right precentral and left superior parietal regions, whereas no brain region with decreased complexity toward regularity was found in SAD probands. All proband groups showed significantly increased brain signal randomness in dorsal and ventral prefrontal cortex (PFC), and unaffected relatives showed no complexity differences in PFC regions. SZ had the largest area of involvement in both dorsal and ventral PFC. BP and SAD probands shared increased brain signal randomness in ventral medial PFC, BP and SZ probands shared increased brain signal randomness in ventral lateral PFC, whereas SAD and SZ probands shared increased brain signal randomness in dorsal medial PFC. Only SZ showed increased brain signal randomness in dorsal lateral PFC. The increased brain signal randomness in dorsal or ventral PFC was weakly associated with reduced cognitive performance in psychotic probands. Conclusion These observations support the loss of brain complexity hypothesis in psychotic probands. Furthermore, we found significant differences as well as overlaps of pathologic brain signal complexity between psychotic probands by DSM diagnoses, thus suggesting a biological approach to categorizing psychosis based on functional neuroimaging data.

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Section: Introductionmentioning

confidence: 79%

Neural complexity as a potential translational biomarker for psychosis

Hager

Yang

Brady

et al. 2017

Journal of Affective Disorders

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“…A variety of versions of activity chambers have been created and have become more sophisticated with regard to (1) relying on the use of cameras and infrared beams to automatically track behavior and (2) developing more specific measures to quantify quality and organization of behavior. An example is the rodent behavioral pattern monitor (BPM) developed by Geyer and colleagues (Geyer, Russo, & Masten, 1986; Paulus, Geyer, & Braff, 1996; Young et al, 2007). The BPM is a chamber with rearing touchplates on the walls and holes in the floors and walls.…”

Section: Animal Paradigmsmentioning

confidence: 99%

“…Locomotor movement and exploratory behavior (head dipping) is recorded via infrared beams and locomotor activity is characterized in terms of hierarchical and geometric organization. Specifically, spatial d measures the extent to which movement is one- versus two-dimensional; dynamical entropy h measures the extent to which movement is ordered versus disordered (calculated by comparing movements to preceding movement sequences); and spatial coefficient of variation (CV) measures variation in the pattern of transitions among BPM field sectors (Geyer et al, 1986; Paulus et al, 1996; Young et al, 2007). Decreased exploratory activity, rather than overall motor activity, may be associated with anxiety-related responses.…”

Section: Animal Paradigmsmentioning

confidence: 99%

Animal to human translational paradigms relevant for approach avoidance conflict decision making

Kirlić

Young

Aupperle

2017

Behaviour Research and Therapy

104

112

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Avoidance behavior in clinical anxiety disorders is often a decision made in response to approach-avoidance conflict, resulting in a sacrifice of potential rewards to avoid potential negative affective consequences. Animal research has a long history of relying on paradigms related to approach-avoidance conflict to model anxiety-relevant behavior. This approach includes punishment-based conflict, exploratory, and social interaction tasks. There has been a recent surge of interest in the translation of paradigms from animal to human, in efforts to increase generalization of findings and support the development of more effective mental health treatments. This article briefly reviews animal tests related to approach-avoidance conflict and results from lesion and pharmacologic studies utilizing these tests. We then provide a description of translational human paradigms that have been developed to tap into related constructs, summarizing behavioral and neuroimaging findings. Similarities and differences in findings from analogous animal and human paradigms are discussed. Lastly, we highlight opportunities for future research and paradigm development that will support the clinical utility of this translational work.

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“…Bauer and Whybrow (1995) found that while participants with bipolar disorder showed some brief periods of fairly well defined cycling in mood, their overall pattern of mood changes were less complex than controls. Paulus et al compared patients with schizophrenia to healthy individuals in a binary choice study, and found that participants with schizophrenia showed a simpler and more predictable pattern of response, apparently reflecting decreased adaptability in cognitive processing (Paulus & Braff, 2003; Paulus, Geyer, & Braff, 1996). A study of laterality in electrodermal activity found decreased activity and complexity in the left hand, compared with the right, among depressed patients, and decreased activity and complexity in the right hand, compared with the left, among patients with schizophrenia, while there were no laterality differences among healthy individuals (Bob, 2007).…”

Section: Mental Illnessmentioning

confidence: 99%

Dynamic Processes in Regulation and Some Implications for Biofeedback and Biobehavioral Interventions

Lehrer

Eddie

2013

Appl Psychophysiol Biofeedback

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Systems theory has long been applied in psychology, biology, and sociology. This paper applies newer methods of control systems modeling to the assessment of system stability in health and disease. Control systems can be characterized as open or closed systems with feedback loops. Feedback produces oscillatory activity, and the complexity of naturally occurring oscillatory patterns reflects the multiplicity of feedback mechanisms, such that many mechanisms operate simultaneously to control the system. Unstable systems, often associated with poor health, are characterized by absence of oscillation, random noise, or a very simple pattern of oscillation. This modeling approach can be applied to a diverse range of phenomena, including cardiovascular and brain activity, mood and thermal regulation, and social system stability. External system stressors such as disease, psychological stress, injury, or interpersonal conflict may perturb a system, yet simultaneously stimulate oscillatory processes and exercise control mechanisms. Resonance can occur in systems with negative feedback loops, causing high-amplitude oscillations at a single frequency. Resonance effects can be used to strengthen modulatory oscillations, but may obscure other information and control mechanisms, and weaken system stability. Positive as well as negative feedback loops are important for system function and stability. Examples are presented of oscillatory processes in heart rate variability, and regulation of autonomic, thermal, pancreatic and central nervous system processes, as well as in social/organizational systems such as marriages and business organizations. Resonance in negative feedback loops can help stimulate oscillations and exercise control reflexes, but also can deprive the system of important information. Empirical hypotheses derived from this approach are presented, including that moderate stress may enhance health and functioning.

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Use of methods from chaos theory to quantify a fundamental dysfunction in the behavioral organization of schizophrenic patients

Cited by 79 publications

References 12 publications

Neural complexity as a potential translational biomarker for psychosis

Neural complexity as a potential translational biomarker for psychosis

Animal to human translational paradigms relevant for approach avoidance conflict decision making

Dynamic Processes in Regulation and Some Implications for Biofeedback and Biobehavioral Interventions

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