1
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Idlett-Ali SL, Salazar CA, Bell MS, Short EB, Rowland NC. Neuromodulation for treatment-resistant depression: Functional network targets contributing to antidepressive outcomes. Front Hum Neurosci 2023; 17:1125074. [PMID: 36936612 PMCID: PMC10018031 DOI: 10.3389/fnhum.2023.1125074] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Non-invasive brain stimulation is designed to target accessible brain regions that underlie many psychiatric disorders. One such method, transcranial magnetic stimulation (TMS), is commonly used in patients with treatment-resistant depression (TRD). However, for non-responders, the choice of an alternative therapy is unclear and often decided empirically without detailed knowledge of precise circuit dysfunction. This is also true of invasive therapies, such as deep brain stimulation (DBS), in which responses in TRD patients are linked to circuit activity that varies in each individual. If the functional networks affected by these approaches were better understood, a theoretical basis for selection of interventions could be developed to guide psychiatric treatment pathways. The mechanistic understanding of TMS is that it promotes long-term potentiation of cortical targets, such as dorsolateral prefrontal cortex (DLPFC), which are attenuated in depression. DLPFC is highly interconnected with other networks related to mood and cognition, thus TMS likely alters activity remote from DLPFC, such as in the central executive, salience and default mode networks. When deeper structures such as subcallosal cingulate cortex (SCC) are targeted using DBS for TRD, response efficacy has depended on proximity to white matter pathways that similarly engage emotion regulation and reward. Many have begun to question whether these networks, targeted by different modalities, overlap or are, in fact, the same. A major goal of current functional and structural imaging in patients with TRD is to elucidate neuromodulatory effects on the aforementioned networks so that treatment of intractable psychiatric conditions may become more predictable and targeted using the optimal technique with fewer iterations. Here, we describe several therapeutic approaches to TRD and review clinical studies of functional imaging and tractography that identify the diverse loci of modulation. We discuss differentiating factors associated with responders and non-responders to these stimulation modalities, with a focus on mechanisms of action for non-invasive and intracranial stimulation modalities. We advance the hypothesis that non-invasive and invasive neuromodulation approaches for TRD are likely impacting shared networks and critical nodes important for alleviating symptoms associated with this disorder. We close by describing a therapeutic framework that leverages personalized connectome-guided target identification for a stepwise neuromodulation paradigm.
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Affiliation(s)
- Shaquia L. Idlett-Ali
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- *Correspondence: Shaquia L. Idlett-Ali,
| | - Claudia A. Salazar
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
| | - Marcus S. Bell
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
| | - E. Baron Short
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States
| | - Nathan C. Rowland
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
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2
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Ciaunica A, Seth A, Limanowski J, Hesp C, Friston KJ. I overthink—Therefore I am not: An active inference account of altered sense of self and agency in depersonalisation disorder. Conscious Cogn 2022; 101:103320. [PMID: 35490544 PMCID: PMC9130736 DOI: 10.1016/j.concog.2022.103320] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 03/27/2022] [Accepted: 03/29/2022] [Indexed: 12/17/2022]
Abstract
This paper examines potential mechanisms behind atypical sense of self and agency in Depersonalisation Disorder (DPD). Using Active Inference, we argue that aberrant somatosensory attenuation and precision weighting underlies DPD. Failures of somatosensory attenuation may disrupt the sense of agency and control over one’s perceptions and actions. In DPD, individuals may believe ‘another agent’ is controlling their thoughts, perceptions or actions. Unlike psychosis however, in DPD the individual maintains the full insight that the ‘other agent’ is ‘me’ (the self).
This paper considers the phenomenology of depersonalisation disorder, in relation to predictive processing and its associated pathophysiology. To do this, we first establish a few mechanistic tenets of predictive processing that are necessary to talk about phenomenal transparency, mental action, and self as subject. We briefly review the important role of ‘predicting precision’ and how this affords mental action and the loss of phenomenal transparency. We then turn to sensory attenuation and the phenomenal consequences of (pathophysiological) failures to attenuate or modulate sensory precision. We then consider this failure in the context of depersonalisation disorder. The key idea here is that depersonalisation disorder reflects the remarkable capacity to explain perceptual engagement with the world via the hypothesis that “I am an embodied perceiver, but I am not in control of my perception”. We suggest that individuals with depersonalisation may believe that ‘another agent’ is controlling their thoughts, perceptions or actions, while maintaining full insight that the ‘other agent’ is ‘me’ (the self). Finally, we rehearse the predictions of this formal analysis, with a special focus on the psychophysical and physiological abnormalities that may underwrite the phenomenology of depersonalisation.
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3
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Ciaunica A, Pienkos E, Nakul E, Madeira L, Farmer H. Exploration of self- and world experiences in depersonalization traits. PHILOSOPHICAL PSYCHOLOGY 2022. [DOI: 10.1080/09515089.2022.2056009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Anna Ciaunica
- Institute of Philosophy, University of Porto, via Panoramica s/n 4150-564 Porto, Portugal
- Institute of Cognitive Neuroscience, University College London, WC1N 3AR London, UK
- Centre for Philosophy of Science, University of Lisbon, Campo Gra, 1749-016 Lisbon, Portugal
| | | | - Estelle Nakul
- Aix Marseille Univ, CNRS, LNC, FR3C, Marseille, France
| | - Luis Madeira
- Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Harry Farmer
- School of Human Sciences, University of Greenwich, UK
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4
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Constant A, Badcock P, Friston K, Kirmayer LJ. Integrating Evolutionary, Cultural, and Computational Psychiatry: A Multilevel Systemic Approach. Front Psychiatry 2022; 13:763380. [PMID: 35444580 PMCID: PMC9013887 DOI: 10.3389/fpsyt.2022.763380] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 02/14/2022] [Indexed: 12/21/2022] Open
Abstract
This paper proposes an integrative perspective on evolutionary, cultural and computational approaches to psychiatry. These three approaches attempt to frame mental disorders as multiscale entities and offer modes of explanations and modeling strategies that can inform clinical practice. Although each of these perspectives involves systemic thinking, each is limited in its ability to address the complex developmental trajectories and larger social systemic interactions that lead to mental disorders. Inspired by computational modeling in theoretical biology, this paper aims to integrate the modes of explanation offered by evolutionary, cultural and computational psychiatry in a multilevel systemic perspective. We apply the resulting Evolutionary, Cultural and Computational (ECC) model to Major Depressive Disorder (MDD) to illustrate how this integrative approach can guide research and practice in psychiatry.
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Affiliation(s)
- Axel Constant
- Department of Philosophy, The University of Sydney, Darlington, NSW, Australia
| | - Paul Badcock
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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5
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Kooij LH, van der Pol TM, Daams JG, Hein IM, Lindauer RJL. Common elements of evidence-based trauma therapy for children and adolescents. Eur J Psychotraumatol 2022; 13:2079845. [PMID: 35759314 PMCID: PMC9225709 DOI: 10.1080/20008198.2022.2079845] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
UNLABELLED Background: Numerous evidence-based trauma therapies for children and adolescents have been developed over several decades to minimize the negative outcomes of post-traumatic stress disorder (PTSD). However, PTSD remains a complex construct and is associated with pervasive problems and high comorbidity. To gain more insight, much could be learnt from the similarities in trauma therapies. Objective: The purpose of this study is to derive common elements from evidence-based trauma therapies for children and adolescents. Method: Therapies were selected from a literature search. Five evidence-based trauma therapies were included in this study. A common element list was created through an existing and modified Delphi method, with a diverse group of Dutch trauma therapists. An element was deemed common when it appeared in three or more of the therapies. The final list was presented to international experts on the included trauma therapies. Results: A substantial commonality of techniques and mechanisms was found across the five evidence-based trauma therapies for children and adolescents, showing a strong overlap between therapies. Conclusion: The identified elements create a basis for research and clinical practice, with regard to targeted trauma therapies tailored to each individual child and his or her support system. This promotes therapy modules that are more flexible and accessible for both therapists and clients, in every environment, from specialized psychiatric units to sites with meagre resources. With current integrated knowledge, we can enhance the effectiveness of child psychiatry and refine trauma therapies. HIGHLIGHTS Using a modified Delphi method, a substantial commonality of techniques and mechanisms is found in evidence-based trauma therapies for children and adolescents.Understanding the techniques and mechanisms of trauma therapy could be of help in refining upcoming therapies, and creates a basis for future research.Commonalities promote therapy modules that are more flexible and accessible for both therapists and clients, in environments ranging from specialized psychiatric units to sites with meagre resources.
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Affiliation(s)
- Lieke H Kooij
- Department of Child and Adolescent Psychiatry, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Thimo M van der Pol
- Department of Child and Adolescent Psychiatry, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Joost G Daams
- Medical Library, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Irma M Hein
- Department of Child and Adolescent Psychiatry, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Ramón J L Lindauer
- Department of Child and Adolescent Psychiatry, Amsterdam UMC, University of Amsterdam, the Netherlands
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Goekoop R, de Kleijn R. Permutation Entropy as a Universal Disorder Criterion: How Disorders at Different Scale Levels Are Manifestations of the Same Underlying Principle. ENTROPY (BASEL, SWITZERLAND) 2021; 23:1701. [PMID: 34946007 PMCID: PMC8700347 DOI: 10.3390/e23121701] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 12/10/2021] [Accepted: 12/13/2021] [Indexed: 12/12/2022]
Abstract
What do bacteria, cells, organs, people, and social communities have in common? At first sight, perhaps not much. They involve totally different agents and scale levels of observation. On second thought, however, perhaps they share everything. A growing body of literature suggests that living systems at different scale levels of observation follow the same architectural principles and process information in similar ways. Moreover, such systems appear to respond in similar ways to rising levels of stress, especially when stress levels approach near-lethal levels. To explain such communalities, we argue that all organisms (including humans) can be modeled as hierarchical Bayesian controls systems that are governed by the same biophysical principles. Such systems show generic changes when taxed beyond their ability to correct for environmental disturbances. Without exception, stressed organisms show rising levels of 'disorder' (randomness, unpredictability) in internal message passing and overt behavior. We argue that such changes can be explained by a collapse of allostatic (high-level integrative) control, which normally synchronizes activity of the various components of a living system to produce order. The selective overload and cascading failure of highly connected (hub) nodes flattens hierarchical control, producing maladaptive behavior. Thus, we present a theory according to which organic concepts such as stress, a loss of control, disorder, disease, and death can be operationalized in biophysical terms that apply to all scale levels of organization. Given the presumed universality of this mechanism, 'losing control' appears to involve the same process anywhere, whether involving bacteria succumbing to an antibiotic agent, people suffering from physical or mental disorders, or social systems slipping into warfare. On a practical note, measures of disorder may serve as early warning signs of system failure even when catastrophic failure is still some distance away.
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Affiliation(s)
- Rutger Goekoop
- Parnassia Group, PsyQ Parnassia Academy, Department of Anxiety Disorders, Early Detection and Intervention Team (EDIT), Lijnbaan 4, 2512 VA Den Haag, The Netherlands
| | - Roy de Kleijn
- Cognitive Psychology Unit, Institute of Psychology & Leiden Institute for Brain and Cognition, Leiden University, Wassenaarseweg 52, 2333 AK Leiden, The Netherlands;
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7
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Park HJ, Eo J, Pae C, Son J, Park SM, Kang J. State-Dependent Effective Connectivity in Resting-State fMRI. Front Neural Circuits 2021; 15:719364. [PMID: 34776875 PMCID: PMC8579116 DOI: 10.3389/fncir.2021.719364] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/22/2021] [Indexed: 01/02/2023] Open
Abstract
The human brain at rest exhibits intrinsic dynamics transitioning among the multiple metastable states of the inter-regional functional connectivity. Accordingly, the demand for exploring the state-specific functional connectivity increases for a deeper understanding of mental diseases. Functional connectivity, however, lacks information about the directed causal influences among the brain regions, called effective connectivity. This study presents the dynamic causal modeling (DCM) framework to explore the state-dependent effective connectivity using spectral DCM for the resting-state functional MRI (rsfMRI). We established the sequence of brain states using the hidden Markov model with the multivariate autoregressive coefficients of rsfMRI, summarizing the functional connectivity. We decomposed the state-dependent effective connectivity using a parametric empirical Bayes scheme that models the effective connectivity of consecutive windows with the time course of the discrete states as regressors. We showed the plausibility of the state-dependent effective connectivity analysis in a simulation setting. To test the clinical applicability, we applied the proposed method to characterize the state- and subtype-dependent effective connectivity of the default mode network in children with combined-type attention deficit hyperactivity disorder (ADHD-C) compared with age-matched, typically developed children (TDC). All 88 children were subtyped according to the occupation times (i.e., dwell times) of the three dominant functional connectivity states, independently of clinical diagnosis. The state-dependent effective connectivity differences between ADHD-C and TDC according to the subtypes and those between the subtypes of ADHD-C were expressed mainly in self-inhibition, magnifying the importance of excitation inhibition balance in the subtyping. These findings provide a clear motivation for decomposing the state-dependent dynamic effective connectivity and state-dependent analysis of the directed coupling in exploring mental diseases.
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Affiliation(s)
- Hae-Jeong Park
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea.,Department of Psychiatry, Yonsei University College of Medicine, Seoul, South Korea.,Brain Korea 21 Project, Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea.,Center for Systems and Translational Brain Science, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, South Korea.,Department of Cognitive Science, Yonsei University, Seoul, South Korea
| | - Jinseok Eo
- Brain Korea 21 Project, Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea.,Center for Systems and Translational Brain Science, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, South Korea
| | - Chongwon Pae
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea.,Department of Psychiatry, Yonsei University College of Medicine, Seoul, South Korea.,Brain Korea 21 Project, Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea.,Center for Systems and Translational Brain Science, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, South Korea
| | - Junho Son
- Brain Korea 21 Project, Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea.,Center for Systems and Translational Brain Science, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, South Korea
| | - Sung Min Park
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea.,Department of Psychiatry, Yonsei University College of Medicine, Seoul, South Korea
| | - Jiyoung Kang
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea.,Department of Psychiatry, Yonsei University College of Medicine, Seoul, South Korea.,Brain Korea 21 Project, Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea.,Center for Systems and Translational Brain Science, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, South Korea
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8
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Bohlen L, Shaw R, Cerritelli F, Esteves JE. Osteopathy and Mental Health: An Embodied, Predictive, and Interoceptive Framework. Front Psychol 2021; 12:767005. [PMID: 34777176 PMCID: PMC8578726 DOI: 10.3389/fpsyg.2021.767005] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 10/06/2021] [Indexed: 11/13/2022] Open
Abstract
Globally, mental and musculoskeletal disorders present with high prevalence, disease burden, and comorbidity. In order to improve the quality of care for patients with persistent physical and comorbid mental health conditions, person-centered care approaches addressing psychosocial factors are currently advocated. Central to successful person-centered care is a multidisciplinary collaboration between mental health and musculoskeletal specialists underpinned by a robust therapeutic alliance. Such a collaborative approach might be found in osteopathy, which is typically utilized to treat patients with musculoskeletal disorders but may arguably also benefit mental health outcomes. However, research and practice exploring the reputed effect of osteopathy on patients with mental health problems lack a robust framework. In this hypothesis and theory article, we build upon research from embodied cognition, predictive coding, interoception, and osteopathy to propose an embodied, predictive and interoceptive framework that underpins osteopathic person-centered care for individuals with persistent physical and comorbid mental health problems. Based on the premise that, for example, chronic pain and comorbid depression are underlined by overly precise predictions or imprecise sensory information, we hypothesize that osteopathic treatment may generate strong interoceptive prediction errors that update the generative model underpinning the experience of pain and depression. Thus, physical and mental symptoms may be reduced through active and perceptual inference. We discuss how these theoretical perspectives can inform future research into osteopathy and mental health to reduce the burden of comorbid psychological factors in patients with persistent physical symptoms and support person-centered multidisciplinary care in mental health.
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Affiliation(s)
- Lucas Bohlen
- Osteopathic Research Institute, Osteopathie Schule Deutschland, Hamburg, Germany
| | - Robert Shaw
- Scandinavian College of Osteopathy, Gothenburg, Sweden
- Australian Research Centre in Complementary and Integrative Medicine (ARCCIM), University of Technology Sydney, Ultimo, NSW, Australia
| | - Francesco Cerritelli
- Australian Research Centre in Complementary and Integrative Medicine (ARCCIM), University of Technology Sydney, Ultimo, NSW, Australia
- Clinical-based Human Research Department, Foundation COME Collaboration, Pescara, Italy
| | - Jorge E. Esteves
- Clinical-based Human Research Department, Foundation COME Collaboration, Pescara, Italy
- Research Department, University College of Osteopathy, London, United Kingdom
- International College of Osteopathic Medicine, Malta, Italy
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9
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Kirsch LP, Mathys C, Papadaki C, Talelli P, Friston K, Moro V, Fotopoulou A. Updating beliefs beyond the here-and-now: the counter-factual self in anosognosia for hemiplegia. Brain Commun 2021; 3:fcab098. [PMID: 34151264 PMCID: PMC8209286 DOI: 10.1093/braincomms/fcab098] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/12/2021] [Indexed: 11/13/2022] Open
Abstract
The syndrome of anosognosia for hemiplegia, or the lack of awareness for one’s paralysis following right hemisphere stroke, can provide unique insights into the neurocognitive mechanisms of self-awareness. Yet it remains unclear whether anosognosia for hemiplegia is a modality-specific deficit of sensorimotor monitoring, or whether domain-general processes of attention and belief-updating converge to cause anosognosia for hemiplegia. Using a Bayesian learning framework, we formalized and empirically investigated the hypothesis that failures to update anosognosic beliefs can be explained by abnormalities in the relative uncertainty (i.e. precision) ascribed to prior beliefs versus sensory information in different contexts. We designed a new motor belief-updating task that manipulated both the temporal (prospective and retrospective) and spatial (hemispace most affected by inattention and hemispace less affected by inattention) conditions in which beliefs had to be updated, and we validated its sensitivity to anosognosia for hemiplegia in 26 patients with right hemisphere stroke. We then computed and empirically tested two different Bayesian predictors of prospective beliefs using two proxies for precision in anosognosia for hemiplegia patients: (i) standardized, neuropsychological measures of objective attention abilities, i.e. visuospatial neglect scores and (ii) subjective uncertainty reports, i.e. confidence ratings. Our results suggest that while neglect does not affect local, sensorimotor error monitoring, it does seem to affect the degree to which observed errors are used to update more general, prospective beliefs about counterfactual motor abilities in anosognosia for hemiplegia. Difficulties in such ‘counterfactual’ belief-updating were associated with disruptions in tracts of the ventral attentional network (i.e. superior longitudinal fasciculus connecting the temporo-parietal junction and ventral frontal cortex) and associated lesions to the insula, inferior parietal cortex and superior temporal regions. These results suggest that self-awareness extends beyond local, retrospective monitoring, requiring also salience-based, convergence of beliefs about the self that go beyond the ‘here-and-now’ of sensorimotor experience.
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Affiliation(s)
- Louise P Kirsch
- Institut des Systèmes Intelligents et de Robotique, Sorbonne Université, Paris 75005, France.,Department of Clinical, Educational and Health Psychology, University College London, London WC1E 6BT, UK
| | - Christoph Mathys
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste 34136, Italy.,Interacting Minds Centre, Aarhus University, Aarhus 8000, Denmark.,Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich 8032, Switzerland
| | - Christina Papadaki
- Department of Clinical, Educational and Health Psychology, University College London, London WC1E 6BT, UK
| | | | - Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Valentina Moro
- NPSY.Lab-VR, Department of Human Sciences, University of Verona, Verona 37129, Italy
| | - Aikaterini Fotopoulou
- Department of Clinical, Educational and Health Psychology, University College London, London WC1E 6BT, UK
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10
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Han KM, Ham BJ, Kim YK. Development of Neuroimaging-Based Biomarkers in Major Depression. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:85-99. [PMID: 33834396 DOI: 10.1007/978-981-33-6044-0_6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
A leading goal in the field of biological psychiatry for depression is to find a promising diagnostic biomarker and selection of specific psychiatric treatment mode that is most likely to benefit patients with depression. Recent neuroimaging studies have characterized the pathophysiology of major depressive disorder (MDD) with functional and structural alterations in the neural circuitry involved in emotion or reward processing. Particularly, structural and functional magnetic resonance imaging (MRI) studies have reported that the brain structures deeply involved in emotion regulation or reward processing including the amygdala, prefrontal cortex (PFC), anterior cingulate cortex (ACC), ventral striatum, and hippocampus are key regions that provide useful information about diagnosis and treatment outcome prediction in MDD. For example, it has been consistently reported that elevated activity of the ACC is associated with better antidepressant response in patients with MDD. This chapter will discuss a growing body of evidence that suggests that diagnosis or prediction of outcome for specific treatment can be assisted by a neuroimaging-based biomarker in MDD.
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Affiliation(s)
- Kyu-Man Han
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Yong-Ku Kim
- Department of Psychiatry, Korea University Ansan Hospital, College of Medicine, Ansan, Republic of Korea.
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11
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van Leeuwen TM, Sauer A, Jurjut AM, Wibral M, Uhlhaas PJ, Singer W, Melloni L. Perceptual Gains and Losses in Synesthesia and Schizophrenia. Schizophr Bull 2020; 47:722-730. [PMID: 33150444 PMCID: PMC8084450 DOI: 10.1093/schbul/sbaa162] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Individual differences in perception are widespread. Considering inter-individual variability, synesthetes experience stable additional sensations; schizophrenia patients suffer perceptual deficits in, eg, perceptual organization (alongside hallucinations and delusions). Is there a unifying principle explaining inter-individual variability in perception? There is good reason to believe perceptual experience results from inferential processes whereby sensory evidence is weighted by prior knowledge about the world. Perceptual variability may result from different precision weighting of sensory evidence and prior knowledge. We tested this hypothesis by comparing visibility thresholds in a perceptual hysteresis task across medicated schizophrenia patients (N = 20), synesthetes (N = 20), and controls (N = 26). Participants rated the subjective visibility of stimuli embedded in noise while we parametrically manipulated the availability of sensory evidence. Additionally, precise long-term priors in synesthetes were leveraged by presenting either synesthesia-inducing or neutral stimuli. Schizophrenia patients showed increased visibility thresholds, consistent with overreliance on sensory evidence. In contrast, synesthetes exhibited lowered thresholds exclusively for synesthesia-inducing stimuli suggesting high-precision long-term priors. Additionally, in both synesthetes and schizophrenia patients explicit, short-term priors-introduced during the hysteresis experiment-lowered thresholds but did not normalize perception. Our results imply that perceptual variability might result from differences in the precision afforded to prior beliefs and sensory evidence, respectively.
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Affiliation(s)
- Tessa M van Leeuwen
- Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany,Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany,Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands
| | - Andreas Sauer
- Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany,Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Anna-Maria Jurjut
- Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
| | - Michael Wibral
- Magnetoencephalography Unit, Brain Imaging Center, Johann Wolfgang Goethe University, Frankfurt am Main, Germany
| | - Peter J Uhlhaas
- Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany,Institute of Neuroscience and Psychology, University of Glasgow, Scotland,Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Wolf Singer
- Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany,Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany,Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe University, Frankfurt am Main, Germany
| | - Lucia Melloni
- Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany,Department of Neurology, New York University School of Medicine, New York, NY,Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany,To whom correspondence should be addressed; Max-Planck-Institute for Empirical Aesthetics, Department of Neuroscience, Grüneburgweg 14, 60322 Frankfurt am Main, Germany. tel: +49 (0)69-8300479-330, fax: +49 69 8300 479 399, e-mail:
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12
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Demekas D, Parr T, Friston KJ. An Investigation of the Free Energy Principle for Emotion Recognition. Front Comput Neurosci 2020; 14:30. [PMID: 32390817 PMCID: PMC7189749 DOI: 10.3389/fncom.2020.00030] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Accepted: 03/23/2020] [Indexed: 01/23/2023] Open
Abstract
This paper offers a prospectus of what might be achievable in the development of emotional recognition devices. It provides a conceptual overview of the free energy principle; including Markov blankets, active inference, and-in particular-a discussion of selfhood and theory of mind, followed by a brief explanation of how these concepts can explain both neural and cultural models of emotional inference. The underlying hypothesis is that emotion recognition and inference devices will evolve from state-of-the-art deep learning models into active inference schemes that go beyond marketing applications and become adjunct to psychiatric practice. Specifically, this paper proposes that a second wave of emotion recognition devices will be equipped with an emotional lexicon (or the ability to epistemically search for one), allowing the device to resolve uncertainty about emotional states by actively eliciting responses from the user and learning from these responses. Following this, a third wave of emotional devices will converge upon the user's generative model, resulting in the machine and human engaging in a reciprocal, prosocial emotional interaction, i.e., sharing a generative model of emotional states.
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Affiliation(s)
- Daphne Demekas
- Department of Mathematics, University College London, London, United Kingdom
| | - Thomas Parr
- Department of Mathematics, University College London, London, United Kingdom
| | - Karl J. Friston
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
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13
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Linson A, Friston K. Reframing PTSD for computational psychiatry with the active inference framework. Cogn Neuropsychiatry 2019; 24:347-368. [PMID: 31564212 PMCID: PMC6816477 DOI: 10.1080/13546805.2019.1665994] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 09/04/2019] [Indexed: 11/25/2022]
Abstract
Introduction: Recent advances in research on stress and, respectively, on disorders of perception, learning, and behaviour speak to a promising synthesis of current insights from (i) neurobiology, cognitive neuroscience and psychology of stress and post-traumatic stress disorder (PTSD), and (ii) computational psychiatry approaches to pathophysiology (e.g. of schizophrenia and autism). Methods: Specifically, we apply this synthesis to PTSD. The framework of active inference offers an embodied and embedded lens through which to understand neuronal mechanisms, structures, and processes of cognitive function and dysfunction. In turn, this offers an explanatory model of how healthy mental functioning can go awry due to psychopathological conditions that impair inference about our environment and our bodies. In this context, auditory phenomena-known to be especially relevant to studies of PTSD and schizophrenia-and traditional models of auditory function can be viewed from an evolutionary perspective based on active inference. Results: We assess and contextualise a range of evidence on audition, stress, psychosis, and PTSD, and bring some existing partial models of PTSD into multilevel alignment. Conclusions: The novel perspective on PTSD we present aims to serve as a basis for new experimental designs and therapeutic interventions that integrate fundamentally biological, cognitive, behavioural, and environmental factors.
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Affiliation(s)
- Adam Linson
- Faculty of Natural Sciences & Faculty of Arts and Humanities, University of Stirling, Stirling, UK
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, UCL, London, UK
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14
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Perrykkad K, Hohwy J. Modelling Me, Modelling You: the Autistic Self. REVIEW JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS 2019. [DOI: 10.1007/s40489-019-00173-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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15
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Parr T, Friston KJ. The Anatomy of Inference: Generative Models and Brain Structure. Front Comput Neurosci 2018; 12:90. [PMID: 30483088 PMCID: PMC6243103 DOI: 10.3389/fncom.2018.00090] [Citation(s) in RCA: 77] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Accepted: 10/25/2018] [Indexed: 01/02/2023] Open
Abstract
To infer the causes of its sensations, the brain must call on a generative (predictive) model. This necessitates passing local messages between populations of neurons to update beliefs about hidden variables in the world beyond its sensory samples. It also entails inferences about how we will act. Active inference is a principled framework that frames perception and action as approximate Bayesian inference. This has been successful in accounting for a wide range of physiological and behavioral phenomena. Recently, a process theory has emerged that attempts to relate inferences to their neurobiological substrates. In this paper, we review and develop the anatomical aspects of this process theory. We argue that the form of the generative models required for inference constrains the way in which brain regions connect to one another. Specifically, neuronal populations representing beliefs about a variable must receive input from populations representing the Markov blanket of that variable. We illustrate this idea in four different domains: perception, planning, attention, and movement. In doing so, we attempt to show how appealing to generative models enables us to account for anatomical brain architectures. Ultimately, committing to an anatomical theory of inference ensures we can form empirical hypotheses that can be tested using neuroimaging, neuropsychological, and electrophysiological experiments.
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Affiliation(s)
- Thomas Parr
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, United Kingdom
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16
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Hong CCH, Fallon JH, Friston KJ, Harris JC. Rapid Eye Movements in Sleep Furnish a Unique Probe Into Consciousness. Front Psychol 2018; 9:2087. [PMID: 30429814 PMCID: PMC6220670 DOI: 10.3389/fpsyg.2018.02087] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 10/10/2018] [Indexed: 01/07/2023] Open
Abstract
The neural correlates of rapid eye movements (REMs) in sleep are extraordinarily robust; including REM-locked multisensory-motor integration and accompanying activation in the retrosplenial cortex, the supplementary eye field and areas encompassing cholinergic basal nucleus (Hong et al., 2009). The phenomenology of REMs speaks to the notion that perceptual experience in both sleep and wakefulness is a constructive process - in which we generate predictions of sensory inputs and then test those predictions through actively sampling the sensorium with eye movements. On this view, REMs during sleep may index an internalized active sampling or 'scanning' of self-generated visual constructs that are released from the constraints of visual input. If this view is correct, it renders REMs an ideal probe to study consciousness as "an exclusively internal affair" (Metzinger, 2009). In other words, REMs offer a probe of active inference - in the sense of predictive coding - when the brain is isolated from the sensorium in virtue of the natural blockade of sensory afferents during REM sleep. Crucially, REMs are temporally precise events that enable powerful inferences based on time series analyses. As a natural, task-free probe, (REMs) could be used in non-compliant subjects, including infants and animals. In short, REMs constitute a promising probe to study the ontogenetic and phylogenetic development of consciousness and perhaps the psychopathology of schizophrenia and autism, which have been considered in terms of aberrant predictive coding.
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Affiliation(s)
- Charles C.-H. Hong
- Patuxent Institution, Correctional Mental Health Center — Jessup, Jessup, MD, United States
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins Hospital, Baltimore, MD, United States
| | - James H. Fallon
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA, United States
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States
| | - Karl J. Friston
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom
| | - James C. Harris
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins Hospital, Baltimore, MD, United States
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17
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Parr T, Benrimoh DA, Vincent P, Friston KJ. Precision and False Perceptual Inference. Front Integr Neurosci 2018; 12:39. [PMID: 30294264 PMCID: PMC6158318 DOI: 10.3389/fnint.2018.00039] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 08/30/2018] [Indexed: 12/24/2022] Open
Abstract
Accurate perceptual inference fundamentally depends upon accurate beliefs about the reliability of sensory data. In this paper, we describe a Bayes optimal and biologically plausible scheme that refines these beliefs through a gradient descent on variational free energy. To illustrate this, we simulate belief updating during visual foraging and show that changes in estimated sensory precision (i.e., confidence in visual data) are highly sensitive to prior beliefs about the contents of a visual scene. In brief, confident prior beliefs induce an increase in estimated precision when consistent with sensory evidence, but a decrease when they conflict. Prior beliefs held with low confidence are rapidly updated to posterior beliefs, determined by sensory data. These induce much smaller changes in beliefs about sensory precision. We argue that pathologies of scene construction may be due to abnormal priors, and show that these can induce a reduction in estimated sensory precision. Having previously associated this precision with cholinergic signaling, we note that several neurodegenerative conditions are associated with visual disturbances and cholinergic deficits; notably, the synucleinopathies. On relating the message passing in our model to the functional anatomy of the ventral visual stream, we find that simulated neuronal loss in temporal lobe regions induces confident, inaccurate, empirical prior beliefs at lower levels in the visual hierarchy. This provides a plausible, if speculative, computational mechanism for the loss of cholinergic signaling and the visual disturbances associated with temporal lobe Lewy body pathology. This may be seen as an illustration of the sorts of hypotheses that may be expressed within this computational framework.
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Affiliation(s)
- Thomas Parr
- Institute of Neurology, Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - David A Benrimoh
- Institute of Neurology, Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Peter Vincent
- Institute of Neurology, Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Karl J Friston
- Institute of Neurology, Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
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