The Atlas of Social Complexity. Chapter 16: Mindfulness, Creativity

As I stated in my previous post, the second major content theme in The Atlas of Social Complexity is the Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders and then Chapter 15: Healing and the therapeutic process.

 

The focus of this post is CHAPTER 16: Mindfulness, imagination, and creativity

 

OVERVIEW OF CHAPTER:

 

The human brain is a portal between the physical world and mental life. With the brain (as its own form of structure and organisation) acting as a bridge, the two domains, the physical and the mental, are not separate but deeply intertwined, such that life and reality regularly relent to the powers of imagination and creativity, meanwhile the mind is entirely embodied, including the metaphors by which we live.

 

Humans dream of flying and traveling past the speed of light; they imagine superheroes and demons; they create gods and monsters; they envisage lives outside the laws of physics, where reality is bent to their goals and desires and their hopes and dreams. Some humans dream the sublime and beautiful, others dream disturbing nightmares. They are all still dreams to which reality and nature regularly relent.

 

As Oscar Wilde famously stated in The Decay of Lying (1891) “Paradox though it may seem – and paradoxes are always dangerous things – it is none the less true that Life imitates art far more than Art imitates life.”

 

It is at the nexus of mindfulness, imagination, and creativity that the arts and humanities collide with the complexity science study of cognition, emotion, and consciousness.

 

To explore this nexus, the focus of this chapter, we examine the five key issues that need to be addressed.

• The first is that we need to be clear what mindfulness, imagination, and creativity mean.
• The second is understanding the different levels or degrees of creativity.
• The third is the adverse impact that hyper-specialisation has on these topics.
• The fourth is the continued restriction of creativity to a mental act, which ignores emotions, as in the case of spontaneous creativity and flow.
• The fifth is how creativity draws on our embodied minds and social life.

 

We end the chapter exploring what we see as the most promising inquiry in these areas. This chapter can be read in tandem with Chapter 32 ‘The Unfinished Space’.

One examples is the work of Orion Maxted[1] . Maxted is a British theatre performance artist based presently in Amsterdam. He studied computing, music and performance art and holds an MA in theatre. His work explores hybrid forms of performance that explore the nexus between complex systems, cybernetics, computation, language, musicality, and theatre. He calls this nexus ‘algorithmic theatre’ as the computational modelling taking place is done entirely by people, mostly through the usage of language. Several examples of his algorithmic theatre, such as flocking or flow, theatre of mind and the brain, can be seen online.[2]  The Theatre of Mind is an experimental piece “to transform the theatre and the audience into a collective intelligence, aka, a mind – achieved by connecting the audience together via mobile phones in a distributed-intelligence network or swarm intelligence – and creating feedback loops between what the audience collectively write, and the ideas that come into existence live on stage”.[3] The purpose of the piece is to ask such questions as: “Do the mind and the world share a common structure? Is the world becoming an increasingly interconnected ‘global brain’? And if so, how do we get the best ideas to rise to the surface and think about the survival of the group?” [4] What makes Maxted’s work so valuable is that, as a way of expanding the focus of the science of mindfulness, imagination and creativity, which is driven to seek answers, he finds value in pushing us to also ask other or different types of critical questions – which is just as powerful.

 

 

KEY WORDS: mindfulness, creativity, imagination, complexity and art, complexity and music, humanities and complexity theory.

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[1] For more, visit https://www.artscienceforum.nl/community/orion-maxted

[2] For more on this work visit https://vimeo.com/orionmaxted/videos. See also https://ias.uva.nl/people/artists-in-residence/current-and-former-artists-in-residence/orion-maxted.html?origin=kYo1rHhER0SPcrDyBywiFg

[3] http://www.artscienceforum.nl/community/orion-maxted

[4] Ibid.

The Atlas of Social Complexity. Chapter 15: Healing and the therapeutic process

As I stated in my previous post, the second major content theme in The Atlas of Social Complexity is the Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders.

 

The focus of this post is Chapter 15: Healing and the therapeutic process.

OVERVIEW OF CHAPTER

Chapter 14 explores the question: What does complexity have to say about healing and therapeutic process?

While historical texts on healing can be found across all cultures, the emergence of therapy as a specific technique for healing has a distinct history. In terms of the complexity sciences, our story begins in the 1950s with family systems theory and with the application of dynamical systems theory to therapy.

 

While theories of the family are endemic to social science, a systems view is distinct, getting its start when Gregory Bateson applied systems thinking to family communication patterns, thereby developing a systems approach to family therapy. Other key figures of the time were Jay Haley and John Weakland – who also worked on the Bateson project – as well as such pioneering scholars as Virginia Satir, Milton Erickson and Mara Selvini Palazzoli. Palazzoli developed the Milan model of family systems therapy,[1] which she later applied to schools, hospitals, and corporations. Theodore Lidz and colleagues,[2] advocating for the role of environmental factors, examined how schizophrenia emerges out of dysfunctional or pathological environments and emphasized – rightly so, as it still remains the case – that while biological models and psychopharmacology are of value, therapy, particularly family systems, is incredibly successful. Other major schools of thought include the Palo Alto Mental Research Institute, structural family therapy, and the intergenerational therapies of Murray Bowen, Ivan Boszormenyi-Nagy, and James Framo, which explore how the pathology of family life is passed down across generations.[3]

 

Somewhat distinct from family systems theory – but certainly in concert with its ‘systems’ view of psychopathology, including the role of familial and contextual forces, as well as the importance of social interaction, particularly between a therapist and client – is the formal application of dynamical systems theory to therapy. This approach starts with the complexity turn in social science. Here the heavy emphasis is on the value of dynamical systems theory, as a set of methodological tools, for modelling and doing therapy. While this includes a variety of computational modelling approaches, including simulation, genetic algorithms and complex networks, it is primarily grounded in the mathematics of dynamical systems theory. As readers may recall, the Swiss psychologist, Wolfgang Tschacher was (and remains) a key figure in application of dynamical systems theory to therapy.[4] Starting in the 1990s with his work on time and self-organisation, and then continuing onward to the study of embodiment and synchrony in the therapeutic process, Tschacher has been pivotal to the field’s development. Later, in the early aughties, he began working with Hermann Haken on the application of synergetics (a theory of nonlinear complex systems) to the dynamics of cognition, psychology and therapy[5] – all points we will get to later. Another key figure is the American psychologist, Adele Hayes. In particular is her 1998 publication, “Dynamic systems theory as a paradigm for the study of change in psychotherapy: an application to cognitive therapy for depression”.[6] Her work is central to the development of a dynamical systems approach to change in therapy, with particular emphasis on cognitive-behavioural therapy, associative networks, system flexibility, destabilization of pathological patterns, and the development of new patterns or attractors. Other key scholars include John Mordechai Gottman,[7] Helmut Schöller,[8] Fred Hasselman,[9] Günter Schiepek[10] and David Pincus.[11]

Despite their significant differences, these scholars (be they family systems theory or otherwise) variously embrace the following assumptions about the healing and therapeutic process. For our review, we will constrain ourselves to the therapeutic process, as the variety of settings and situations in which mental health healing takes place would require a level of detail beyond what we can address here. The majority of the literature also tends to focus on therapy (be it in an office, clinic, or hospital) as it provides a somewhat controlled setting for exploring the healing and therapeutic process.

 

Here are the topics we review in the chapter:

• the role of time in healing
• how therapy takes place within complex social systems
• the dynamics, nonlinearities, initial conditions and feedback loops in the therapeutic process
• embodiment and synchrony in therapy
• therapeutic process as both stochastic and deterministic
• self-organisation and attractors
• the stability of mental disorders
• how therapy is both time varying and time-invariant; symptom targeting; and therapeutic synergetics.

 

 

 

KEY WORDS: Synergetics in therapy, dynamical systems theory, synchrony in therapy, family systems theory, family therapy, psychotherapy.

 

 

 

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[1] Boscolo, Luigi, Gianfranco Cecchin, Lynn Hoffman, and Peggy Penn. Milan systemic family therapy: Conversations in theory and practice. Basic Books, 1987.

[2] Lidz, Theodore. "Schizophrenia and the family." Psychiatry 21, no. 1 (1958): 21-27.

[3] See footnote 4. See also Sexton, T. L., & Lebow, J. (Eds.). Handbook of family therapy. Routledge 2016.

[4] Wolfgang Tschacher, ‘Time and Embodiment in the Process of Psychotherapy: A Dynamical Systems Perspective’, in Time and Body, ed. Christian Tewes and Giovanni Stanghellini, 1st ed. (Cambridge University Press, 2020), 104–16.

[5] Wolfgang Tschacher and Hermann Haken, ‘Causation and Chance: Detection of Deterministic and Stochastic Ingredients in Psychotherapy Processes’, Psychotherapy Research 30, no. 8 (16 November 2020): 1075–87.

[6] Adele M. Hayes and Jennifer L. Strauss, ‘Dynamic Systems Theory as a Paradigm for the Study of Change in Psychotherapy: An Application to Cognitive Therapy for Depression.’, Journal of Consulting and Clinical Psychology 66, no. 6 (1998): 939.

[7] Gottman, John M., et al. The mathematics of marriage: Dynamic nonlinear models. MIT Press, 2005.

[8] Schöller, Helmut, et al. "Personality development in psychotherapy: a synergetic model of state-trait dynamics." Cognitive Neurodynamics 12 (2018): 441-459.

[9] Hasselman, Fred, and Anna MT Bosman. "Studying complex adaptive systems with internal states: A recurrence network approach to the analysis of multivariate time-series data representing self-reports of human experience." Frontiers in Applied Mathematics and Statistics 6 (2020): 9.

[10] Schiepek, Günter K., et al. "Psychotherapy is chaotic—(not only) in a computational world." Frontiers in Psychology 8 (2017): 379.

[11] Pincus, David, and Annette Metten. "Nonlinear dynamics in biopsychosocial resilience." Nonlinear dynamics, psychology, and life sciences 14, no. 4 (2010): 353.

MethodsNET Workshop Louvain 2024. COMPLEX-IT: A computational platform for non-experts to explore complex data

I want to thank Benoît Rihoux and the MethodsNET team for the opportunity to run a workshop on COMPLEX-IT at this year's first MethodsNET Conference and Workshop series at Université catholique de Louvain. The workshop was a three hour intensive, so thanks to all of those who attended for your brilliant questions and also for staying engaged over such a long period of time. I must say I got back to my hotel totally exhausted! LOL!

 

A QUICK OVERVIEW OF THE COMPLEX-IT WORKSHOP

COMPLEX-IT: A computational, multi-methods platform for non-experts to explore complex social science and health data

 

ABSTRACT

While the complexity sciences offer a new approach to thinking about social and health data, making use of their computational methods can be considerably challenging for non-experts – particularly postgraduate students, applied researchers, policy evaluators and civil servants. There is a solution! This workshop will introduce COMPLEX-IT, a free online R-platform designed for non-experts to employ the latest developments in machine learning, data visualisation, participatory systems mapping, network analysis, simulation, data forecasting, and cluster analysis. For our workshop, we will explore a real-world data set to walk through the steps of using COMPLEX-IT and the concepts of complexity science to show how these tools can help attendees gain new insights into social and health data. The goal is for participants to leave with a new methods platform they can use in their own work.

 

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For those who attended or simply might be interested, here are some links to the material from the day.

CLICK HERE for a link to the PowerPoint from the Workshop.

CLICK HERE for a link to COMPLEX-IT.

CLICK HERE for a link to the dataset we explored. NOTE: The dataset is a CSV (comma separated) file, created in EXCEL. It is just a sample to function as an example. It contains several public health indicators (e.g., access to health services, fuel poverty, crime, teen pregnancies, etc) for 100 authority districts in England, UK.

The Atlas of Social Complexity. Chapter 14: Psychopathology of mental disorders

As I stated in my previous post, the second major content theme in The Atlas of Social Complexity is the Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13).

 

The focus of this post is Chapter 14: Psychopathology of mental disorders.

 

 

OVERVIEW OF CHAPTER

Chapter 14 explores the question: What is a mental disorder and how best should we assess it in terms of social complexity? 

 

The field of psychopathology (also sometimes referred to as abnormal psychology) is the formal term for the study of mental disorders. Subfields include developmental, child, adolescent, and adult psychopathology. The general focus across all these sub-fields is on ‘abnormal’ states of thinking, feeling and behaving, particularly within a clinical context – with an awareness that our conceptualisation of what is ‘abnormal’ is deeply connected to our interpersonal relationships, community, culture and sociohistorical context. 

 

There is general agreement that, when it comes to psychopathology, what matters most is that a person is legitimately troubled by their emotional, cognitive, behavioural or social difficulties. In short, they are suffering.

 

There is less agreement, however, on what constitutes a mental disorder. For example, are a person’s psychological difficulties a brain disease or latent psychological construct? Or are they a scientific classification that points to the clustering of sets of psychological symptoms that have no fundamental underlying biological existence? The former view has historically dominated. The latter – referred to as the new science of mental disorders – is fast becoming the major alternative, with the potential to override the former.  

Mental Health Symptom Networks

The network science of psychopathology got its start in the Psychology Department at the University of Amsterdam with the publication of two key articles. The first, in 2008, was Denny Borsboom’s Psychometric perspectives on diagnostic system. While breaking new ground, the concept of networks remained unarticulated in it. A more complete statement arrived with the second publication, in 2010, led by Angélique Cramer.[1] It is at this point that this approach really takes off.

 

It is fitting that the title of Cramer and colleagues’ article is Comorbidity: A network perspective, as symptom overlap is one of the primary reasons the network approach was created. As Robinaugh and colleagues state, “The network approach to psychopathology began a decade ago with a simple hypothesis: symptoms may cohere as syndromes because of causal relations among the symptoms themselves”.[2] From this perspective, they explain, “symptoms are not passive indicators of a latent ‘common cause’; they are agents in a causal system”. [3] Despite the significant advance over the last 13 years, the idea of mental disorders being a collection of symptoms, many of which are shared by or part of the symptom networks of other mental disorders, remains central for this approach. There is no underlying latent construct and no single-cause explanation for any mental health diagnostic category. There are only symptoms.

 

During the next thirteen years, the network approach would quickly become a major contender for the definition and diagnosis of psychopathology as well as a counterpoint to conventional approaches in psychometrics, with articles being published widely. Symptom network analysis has been applied to depression, schizophrenia, post-traumatic stress disorder, anxiety, psychosis, sleep disorders, autism, bipolar disorder, and a variety of comorbid mental health conditions.

 

This widespread adoption is demonstrated well by the fact that Cramer and colleagues published a second article in Behavioral and Brain Sciences in 2019[4].

 

Controversies, Challenges and an Agenda for Moving Forward

 

When the symptom network approach to psychopathology first emerged, its novelty was its virtue. Here, suddenly, was a way to use the latest advances in complex network analysis to think about mental disorders that felt authentic to clinical intuitions and experience.  Research collided with practice, a rare event.

 Nevertheless, there are a list of challenges that need to be addressed. Here is a list of the topics addressed in Chapter 14.

1. Statistical equivalence.

2. The limits of centrality measures.

3. Symptoms can be latent variables.

4. The problem of reductionism.

5. Where is the social?

6. Timing, dynamics and time scales.

7. Reproducibility and replicability.

8. Therapeutically targeting symptoms.

 

Why Embrace this Approach?

 

Within the soft transdiagnostic camp, the symptom network approach is, for us, the more viable route for those interested in the study of social complexity. And we say this despite the fact that this approach has some considerable challenges to address – which we just listed. Here is our rationale:

 

First and foremost, given its grounding in the complexity sciences, the network approach to psychopathology fits with the theoretical synthesis we have so far stitched together.

 

Second, this approach avoids the trap that the hierarchical latent variable approach falls into, given that the latter is still, ironically enough, in search of a more fundamental set of causal factors to explain mental disorders.

 

Third, while we appreciate the hard transdiagnostic camp’s attempt to revolutionise diagnostic nomenclature, its argument is doomed. It will never happen.

 

Finally, despite the flaws of the network approach, we will show that its problems can be fixed, oddly enough, by making better use of complex networks.

 

Our approach in Chapter 14 is to sidestep the theoretical shallowness of symptom networks by embracing a hierarchical network approach, which stiches together not only the biological and neuropsychological levels of human psychology but also, moving into the next major section of the Atlas, the social.

 

Still, despite the advances made by the symptom network literature, the social is still deafeningly missing from everyone’s work. Transdiagnostic approaches need to stop treating the social as a trigger for psychopathology, and see it, instead, as core to its formation. 

 

 

 

KEY WORDS: symptom networks, psychopathology, network theory, psychometrics, transdiagnostic psychiatry and psychology, network science of mental disorders.

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[1] Angélique O. J. Cramer et al., ‘Comorbidity: A Network Perspective’, Behavioral and Brain Sciences 33, no. 2–3 (June 2010): 137–50.

[2] Donald J. Robinaugh et al., ‘The Network Approach to Psychopathology: A Review of the Literature 2008–2018 and an Agenda for Future Research’, Psychological Medicine 50, no. 3 (February 2020), .p. 353.

[3] Ibid., p. 353.

[4] In reality, the paper was accepted for publication in 2017, and the commentaries and paper were collected and published online by Cambridge University Press: 24 January 2018, e2, but the final formal version was 2019.