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Demeter DV, Greene DJ. The promise of precision functional mapping for neuroimaging in psychiatry. Neuropsychopharmacology 2024:10.1038/s41386-024-01941-z. [PMID: 39085426 DOI: 10.1038/s41386-024-01941-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 06/14/2024] [Accepted: 07/17/2024] [Indexed: 08/02/2024]
Abstract
Precision functional mapping (PFM) is a neuroimaging approach to reliably estimate metrics of brain function from individual people via the collection of large amounts of fMRI data (hours per person). This method has revealed much about the inter-individual variation of functional brain networks. While standard group-level studies, in which we average brain measures across groups of people, are important in understanding the generalizable neural underpinnings of neuropsychiatric disorders, many disorders are heterogeneous in nature. This heterogeneity often complicates clinical care, leading to patient uncertainty when considering prognosis or treatment options. We posit that PFM methods may help streamline clinical care in the future, fast-tracking the choice of personalized treatment that is most compatible with the individual. In this review, we provide a history of PFM studies, foundational results highlighting the benefits of PFM methods in the pursuit of an advanced understanding of individual differences in functional network organization, and possible avenues where PFM can contribute to clinical translation of neuroimaging research results in the way of personalized treatment in psychiatry.
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Affiliation(s)
- Damion V Demeter
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA.
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA.
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2
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Sohail A, Zhang L. Informing the treatment of social anxiety disorder with computational and neuroimaging data. PSYCHORADIOLOGY 2024; 4:kkae010. [PMID: 38841558 PMCID: PMC11152174 DOI: 10.1093/psyrad/kkae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/15/2024] [Accepted: 04/25/2024] [Indexed: 06/07/2024]
Affiliation(s)
- Aamir Sohail
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
| | - Lei Zhang
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
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3
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Leehr EJ, Seeger FR, Böhnlein J, Gathmann B, Straube T, Roesmann K, Junghöfer M, Schwarzmeier H, Siminski N, Herrmann MJ, Langhammer T, Goltermann J, Grotegerd D, Meinert S, Winter NR, Dannlowski U, Lueken U. Association between resting-state connectivity patterns in the defensive system network and treatment response in spider phobia-a replication approach. Transl Psychiatry 2024; 14:137. [PMID: 38453896 PMCID: PMC10920691 DOI: 10.1038/s41398-024-02799-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 01/15/2024] [Accepted: 01/18/2024] [Indexed: 03/09/2024] Open
Abstract
Although highly effective on average, exposure-based treatments do not work equally well for all patients with anxiety disorders. The identification of pre-treatment response-predicting patient characteristics may enable patient stratification. Preliminary research highlights the relevance of inhibitory fronto-limbic networks as such. We aimed to identify pre-treatment neural signatures differing between exposure treatment responders and non-responders in spider phobia and to validate results through rigorous replication. Data of a bi-centric intervention study comprised clinical phenotyping and pre-treatment resting-state functional connectivity (rsFC) data of n = 79 patients with spider phobia (discovery sample) and n = 69 patients (replication sample). RsFC data analyses were accomplished using the Matlab-based CONN-toolbox with harmonized analyses protocols at both sites. Treatment response was defined by a reduction of >30% symptom severity from pre- to post-treatment (Spider Phobia Questionnaire Score, primary outcome). Secondary outcome was defined by a reduction of >50% in a Behavioral Avoidance Test (BAT). Mean within-session fear reduction functioned as a process measure for exposure. Compared to non-responders and pre-treatment, results in the discovery sample seemed to indicate that responders exhibited stronger negative connectivity between frontal and limbic structures and were characterized by heightened connectivity between the amygdala and ventral visual pathway regions. Patients exhibiting high within-session fear reduction showed stronger excitatory connectivity within the prefrontal cortex than patients with low within-session fear reduction. Whereas these results could be replicated by another team using the same data (cross-team replication), cross-site replication of the discovery sample findings in the independent replication sample was unsuccessful. Results seem to support negative fronto-limbic connectivity as promising ingredient to enhance response rates in specific phobia but lack sufficient replication. Further research is needed to obtain a valid basis for clinical decision-making and the development of individually tailored treatment options. Notably, future studies should regularly include replication approaches in their protocols.
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Affiliation(s)
- Elisabeth J Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.
| | - Fabian R Seeger
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Center for Mental Health, University Hospital of Würzburg, Würzburg, Germany
- Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - Joscha Böhnlein
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Bettina Gathmann
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
- Otto-Creutzfeld Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
| | - Kati Roesmann
- Otto-Creutzfeld Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
- Institute for Clinical Psychology and Psychotherapy, University of Siegen, Siegen, Germany
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
- Institute of Psychology, Unit of Clinical Psychology and Psychotherapy in Childhood and Adolescence, University of Osnabrück, Osnabrück, Germany
| | - Markus Junghöfer
- Otto-Creutzfeld Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Hanna Schwarzmeier
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Center for Mental Health, University Hospital of Würzburg, Würzburg, Germany
| | - Niklas Siminski
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Center for Mental Health, University Hospital of Würzburg, Würzburg, Germany
| | - Martin J Herrmann
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Center for Mental Health, University Hospital of Würzburg, Würzburg, Germany
| | - Till Langhammer
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils R Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ulrike Lueken
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Center for Mental Health, University Hospital of Würzburg, Würzburg, Germany
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
- German Center for Mental Health (DZPG), partner site Berlin/Potsdam, Berlin, Germany
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Isager PM, Lakens D, van Leeuwen T, van 't Veer AE. Exploring a formal approach to selecting studies for replication: A feasibility study in social neuroscience. Cortex 2024; 171:330-346. [PMID: 38070388 DOI: 10.1016/j.cortex.2023.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 09/12/2023] [Accepted: 10/02/2023] [Indexed: 02/12/2024]
Abstract
Replication of published results is crucial for ensuring the robustness and self-correction of research, yet replications are scarce in many fields. Replicating researchers will therefore often have to decide which of several relevant candidates to target for replication. Formal strategies for efficient study selection have been proposed, but none have been explored for practical feasibility - a prerequisite for validation. Here we move one step closer to efficient replication study selection by exploring the feasibility of a particular selection strategy that estimates replication value as a function of citation impact and sample size (Isager, van 't Veer, & Lakens, 2021). We tested our strategy on a sample of fMRI studies in social neuroscience. We first report our efforts to generate a representative candidate set of replication targets. We then explore the feasibility and reliability of estimating replication value for the targets in our set, resulting in a dataset of 1358 studies ranked on their value of prioritising them for replication. In addition, we carefully examine possible measures, test auxiliary assumptions, and identify boundary conditions of measuring value and uncertainty. We end our report by discussing how future validation studies might be designed. Our study demonstrates the importance of investigating how to implement study selection strategies in practice. Our sample and study design can be extended to explore the feasibility of other formal study selection strategies that have been proposed.
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Affiliation(s)
- Peder M Isager
- Department of Psychology, Oslo New University College, Norway
| | - Daniël Lakens
- Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, the Netherlands
| | - Thed van Leeuwen
- Centre for Science and Technology Studies, Leiden University, the Netherlands
| | - Anna E van 't Veer
- Methodology and Statistics Unit, Institute of Psychology, Leiden University, the Netherlands.
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Zugman A, Ringlein GV, Finn ES, Lewis KM, Berman E, Silverman WK, Lebowitz ER, Pine DS, Winkler AM. Brain Functional Connectivity and Anatomical Features as Predictors of Cognitive Behavioral Therapy Outcome for Anxiety in Youths. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.29.24301959. [PMID: 38352528 PMCID: PMC10862993 DOI: 10.1101/2024.01.29.24301959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/25/2024]
Abstract
Background Because pediatric anxiety disorders precede the onset of many other problems, successful prediction of response to the first-line treatment, cognitive-behavioral therapy (CBT), could have major impact. However, existing clinical models are weakly predictive. The current study evaluates whether structural and resting-state functional magnetic resonance imaging can predict post-CBT anxiety symptoms. Methods Two datasets were studied: (A) one consisted of n=54 subjects with an anxiety diagnosis, who received 12 weeks of CBT, and (B) one consisted of n=15 subjects treated for 8 weeks. Connectome Predictive Modeling (CPM) was used to predict treatment response, as assessed with the PARS; additionally we investigated models using anatomical features, instead of functional connectivity. The main analysis included network edges positively correlated with treatment outcome, and age, sex, and baseline anxiety severity as predictors. Results from alternative models and analyses also are presented. Model assessments utilized 1000 bootstraps, resulting in a 95% CI for R2, r and mean absolute error (MAE). Outcomes The main model showed a mean absolute error of approximately 3.5 (95%CI: [3.1-3.8]) points a R2 of 0.08 [-0.14 - 0.26] and r of 0.38 [0.24 - 0.511]. When testing this model in the left-out sample (B) the results were similar, with a MAE of 3.4 [2.8 - 4.7], R2-0.65 [-2.29 - 0.16] and r of 0.4 [0.24 - 0.54]. The anatomical metrics showed a similar pattern, where models rendered overall low R2. Interpretation The analysis showed that models based on earlier promising results failed to predict clinical outcomes. Despite the small sample size, the current study does not support extensive use of CPM to predict outcome in pediatric anxiety.
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Affiliation(s)
- Andre Zugman
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Grace V. Ringlein
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Emily S. Finn
- Psychological and Brain Sciences, Dartmouth College, 3 Maynard St, Hanover, NH, 03755, USA
| | - Krystal M. Lewis
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Erin Berman
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Wendy K. Silverman
- Child Study Center, Yale University, 230 South Frontage Rd., New Haven, CT 06520, USA
| | - Eli R. Lebowitz
- Child Study Center, Yale University, 230 South Frontage Rd., New Haven, CT 06520, USA
| | - Daniel S. Pine
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Anderson M. Winkler
- Division of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, 1 West University Blvd, Brownsville, TX 78520, USA
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Liu J, Xie S, Hu Y, Ding Y, Zhang X, Liu W, Zhang L, Ma C, Kang Y, Jin S, Xia Y, Hu Z, Liu Z, Cheng W, Yang Z. Age-dependent alterations in the coordinated development of subcortical regions in adolescents with social anxiety disorder. Eur Child Adolesc Psychiatry 2024; 33:51-64. [PMID: 36542201 DOI: 10.1007/s00787-022-02118-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 12/02/2022] [Indexed: 12/24/2022]
Abstract
Subcortical brain regions play essential roles in the pathology of social anxiety disorder (SAD). While adolescence is the peak period of SAD, the relationships between altered development of the subcortical regions during this period and SAD are still unclear. This study investigated the age-dependent alterations in structural co-variance among subcortical regions and between subcortical and cortical regions, aiming to reflect aberrant coordination during development in the adolescent with SAD. High-resolution T1-weighted images were obtained from 76 adolescents with SAD and 67 healthy controls (HC), ranging from 11 to 17.9 years. Symptom severity was evaluated with the Social Anxiety Scale for Children (SASC) and the Depression Self Rating Scale for Children (DSRS-C). Structural co-variance and sliding age-window analyses were used to detect age-dependent group differences in inter-regional coordination patterns among subcortical regions and between subcortical and cortical regions. The volume of the striatum significantly correlated with SAD symptom severity. The SAD group exhibited significantly enhanced structural co-variance among key regions of the striatum (putamen and caudate). While the co-variance decreased with age in healthy adolescents, the co-variance in SAD adolescents stayed high, leading to more apparent group differences in middle adolescence. Moreover, the striatum's mean structural co-variance with cortical regions decreased with age in HC but increased with age in SAD. Adolescents with SAD suffer aberrant developmental coordination among the key regions of the striatum and between the striatum and cortical regions. The degree of incoordination is age-dependent, which may represent a neurodevelopmental trait of SAD.
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Affiliation(s)
- Jingjing Liu
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Shuqi Xie
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Yang Hu
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Yue Ding
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Xiaochen Zhang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Wenjing Liu
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Lei Zhang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Changminghao Ma
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Yinzhi Kang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Shuyu Jin
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Yufeng Xia
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Zhishan Hu
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Zhen Liu
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China
| | - Wenhong Cheng
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China.
| | - Zhi Yang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 South Wanping Road, Shanghai, 200013, China.
- Institute of Psychological and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China.
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China.
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Zhang Z, Gewandter JS, Geha P. Brain Imaging Biomarkers for Chronic Pain. Front Neurol 2022; 12:734821. [PMID: 35046881 PMCID: PMC8763372 DOI: 10.3389/fneur.2021.734821] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 12/08/2021] [Indexed: 12/14/2022] Open
Abstract
The prevalence of chronic pain has reached epidemic levels. In addition to personal suffering chronic pain is associated with psychiatric and medical co-morbidities, notably substance misuse, and a huge a societal cost amounting to hundreds of billions of dollars annually in medical cost, lost wages, and productivity. Chronic pain does not have a cure or quantitative diagnostic or prognostic tools. In this manuscript we provide evidence that this situation is about to change. We first start by summarizing our current understanding of the role of the brain in the pathogenesis of chronic pain. We particularly focus on the concept of learning in the emergence of chronic pain, and the implication of the limbic brain circuitry and dopaminergic signaling, which underly emotional learning and decision making, in this process. Next, we summarize data from our labs and from other groups on the latest brain imaging findings in different chronic pain conditions focusing on results with significant potential for translation into clinical applications. The gaps in the study of chronic pain and brain imaging are highlighted in throughout the overview. Finally, we conclude by discussing the costs and benefits of using brain biomarkers of chronic pain and compare to other potential markers.
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Affiliation(s)
- Zhengwu Zhang
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jennifer S Gewandter
- Anesthesiology and Perioperative Medicine, School of Medicine and Dentistry, University of Rochester, Rochester, NY, United States
| | - Paul Geha
- Department of Psychiatry, School of Medicine and Dentistry, University of Rochester, Rochester, NY, United States.,Department of Neurology, School of Medicine and Dentistry, University of Rochester, Rochester, NY, United States.,Del Monte Neuroscience Institute, University of Rochester, Rochester, NY, United States
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