Nature heals: An informational entropy account of self-organization and change in field psychotherapy

IF 13.7 1区 生物学 Q1 BIOLOGY Physics of Life Reviews Pub Date : 2024-09-06 DOI:10.1016/j.plrev.2024.09.005
Pietro Sarasso , Wolfgang Tschacher , Felix Schoeller , Gianni Francesetti , Jan Roubal , Michela Gecele , Katiuscia Sacco , Irene Ronga
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Abstract

This paper reviews biophysical models of psychotherapeutic change based on synergetics and the free energy principle. These models suggest that introducing sensory surprise into the patient-therapist system can lead to self-organization and the formation of new attractor states, disrupting entrenched patterns of thoughts, emotions, and behaviours. We propose that the therapist can facilitate this process by cultivating epistemic trust and modulating embodied attention to allow surprising affective states to enter shared awareness. Transient increases in free energy enable the update of generative models, expanding the range of experiences available within the patient-therapist phenomenal field. We hypothesize that patterns of disorganization at behavioural and physiological levels, indexed by increased entropy, complexity, and lower determinism, are key markers and predictors of psychotherapeutic gains. Future research should investigate how the therapist's openness to novelty shapes therapeutic outcomes.

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自然治愈:对现场心理疗法中的自组织和变化的信息熵解释
本文回顾了基于协同学和自由能原理的心理治疗变化生物物理模型。这些模型表明,在患者-治疗师系统中引入感官惊喜可以导致自组织和新吸引子状态的形成,破坏根深蒂固的思想、情感和行为模式。我们建议,治疗师可以通过培养认识上的信任和调节体现注意力来促进这一过程,从而让令人惊讶的情感状态进入共同意识。自由能量的瞬时增加能够更新生成模型,扩大患者-治疗师现象场中可用的体验范围。我们假设,以熵增加、复杂性和决定性降低为指标的行为和生理层面的混乱模式是心理治疗收益的关键标志和预测因素。未来的研究应调查治疗师对新奇事物的开放性如何影响治疗结果。
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来源期刊
Physics of Life Reviews
Physics of Life Reviews 生物-生物物理
CiteScore
20.30
自引率
14.50%
发文量
52
审稿时长
8 days
期刊介绍: Physics of Life Reviews, published quarterly, is an international journal dedicated to review articles on the physics of living systems, complex phenomena in biological systems, and related fields including artificial life, robotics, mathematical bio-semiotics, and artificial intelligent systems. Serving as a unifying force across disciplines, the journal explores living systems comprehensively—from molecules to populations, genetics to mind, and artificial systems modeling these phenomena. Inviting reviews from actively engaged researchers, the journal seeks broad, critical, and accessible contributions that address recent progress and sometimes controversial accounts in the field.
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