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Danböck SK, Duek O, Ben-Zion Z, Korem N, Amen SL, Kelmendi B, Wilhelm FH, Levy I, Harpaz-Rotem I. Effects of a dissociative drug on fronto-limbic resting-state functional connectivity in individuals with posttraumatic stress disorder: a randomized controlled pilot study. Psychopharmacology (Berl) 2024; 241:243-252. [PMID: 37872291 PMCID: PMC10806226 DOI: 10.1007/s00213-023-06479-4] [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: 12/13/2022] [Accepted: 10/07/2023] [Indexed: 10/25/2023]
Abstract
RATIONALE A subanesthetic dose of ketamine, a non-competitive N-methyl-D-aspartate glutamate receptor (NMDAR) antagonist, elicits dissociation in individuals with posttraumatic stress disorder (PTSD), who also often suffer from chronic dissociative symptoms in daily life. These debilitating symptoms have not only been linked to worse PTSD trajectories, but also to increased resting-state functional connectivity (RSFC) between medial prefrontal cortex (mPFC) and amygdala, supporting the conceptualization of dissociation as emotion overmodulation. Yet, as studies were observational, causal evidence is lacking. OBJECTIVES The present randomized controlled pilot study examines the effect of ketamine, a dissociative drug, on RSFC between mPFC subregions and amygdala in individuals with PTSD. METHODS Twenty-six individuals with PTSD received either ketamine (0.5mg/kg; n = 12) or the control drug midazolam (0.045mg/kg; n = 14) during functional magnetic resonance imaging (fMRI). RSFC between amygdala and mPFC subregions, i.e., ventromedial PFC (vmPFC), dorsomedial PFC (dmPFC) and anterior-medial PFC (amPFC), was assessed at baseline and during intravenous drug infusion. RESULTS Contrary to pre-registered predictions, ketamine did not promote a greater increase in RSFC between amygdala and mPFC subregions from baseline to infusion compared to midazolam. Instead, ketamine elicited a stronger transient decrease in vmPFC-amygdala RSFC compared to midazolam. CONCLUSIONS A dissociative drug did not increase fronto-limbic RSFC in individuals with PTSD. These preliminary experimental findings contrast with prior correlative findings and call for further exploration and, potentially, a more differentiated view on the neurobiological underpinning of dissociative phenomena in PTSD.
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Affiliation(s)
- Sarah K Danböck
- Department of Psychology, Paris Lodron University of Salzburg, Salzburg, Austria.
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA.
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany.
| | - Or Duek
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- VA Connecticut Healthcare System, Clinical Neurosciences Division, National Center for Posttraumatic Stress Disorder, U.S. Department of Veterans Affairs, West Haven, CT, USA
- Department of Epidemiology, Biostatistics and Community Health Sciences, School of Public Health, Ben-Gurion University of The Negev, Be'er-Sheva, Israel
| | - Ziv Ben-Zion
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- VA Connecticut Healthcare System, Clinical Neurosciences Division, National Center for Posttraumatic Stress Disorder, U.S. Department of Veterans Affairs, West Haven, CT, USA
- Departments of Comparative Medicine and Neuroscience, School of Medicine, Yale University, New Haven, CT, USA
| | - Nachshon Korem
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- VA Connecticut Healthcare System, Clinical Neurosciences Division, National Center for Posttraumatic Stress Disorder, U.S. Department of Veterans Affairs, West Haven, CT, USA
| | - Shelley L Amen
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- VA Connecticut Healthcare System, Clinical Neurosciences Division, National Center for Posttraumatic Stress Disorder, U.S. Department of Veterans Affairs, West Haven, CT, USA
| | - Ben Kelmendi
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- VA Connecticut Healthcare System, Clinical Neurosciences Division, National Center for Posttraumatic Stress Disorder, U.S. Department of Veterans Affairs, West Haven, CT, USA
| | - Frank H Wilhelm
- Department of Psychology, Paris Lodron University of Salzburg, Salzburg, Austria
| | - Ifat Levy
- Departments of Comparative Medicine and Neuroscience, School of Medicine, Yale University, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - Ilan Harpaz-Rotem
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- VA Connecticut Healthcare System, Clinical Neurosciences Division, National Center for Posttraumatic Stress Disorder, U.S. Department of Veterans Affairs, West Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
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Betzel RF, Faskowitz J, Sporns O. Living on the edge: network neuroscience beyond nodes. Trends Cogn Sci 2023; 27:1068-1084. [PMID: 37716895 PMCID: PMC10592364 DOI: 10.1016/j.tics.2023.08.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/14/2023] [Accepted: 08/10/2023] [Indexed: 09/18/2023]
Abstract
Network neuroscience has emphasized the connectional properties of neural elements - cells, populations, and regions. This has come at the expense of the anatomical and functional connections that link these elements to one another. A new perspective - namely one that emphasizes 'edges' - may prove fruitful in addressing outstanding questions in network neuroscience. We highlight one recently proposed 'edge-centric' method and review its current applications, merits, and limitations. We also seek to establish conceptual and mathematical links between this method and previously proposed approaches in the network science and neuroimaging literature. We conclude by presenting several avenues for future work to extend and refine existing edge-centric analysis.
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Affiliation(s)
- Richard F Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA.
| | - Joshua Faskowitz
- Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA
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Kirk PA, Holmes AJ, Robinson OJ. Anxiety Shapes Amygdala-Prefrontal Dynamics During Movie Watching. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:409-417. [PMID: 37519469 PMCID: PMC10382705 DOI: 10.1016/j.bpsgos.2022.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 03/11/2022] [Accepted: 03/16/2022] [Indexed: 10/18/2022] Open
Abstract
Background A well-characterized amygdala-dorsomedial prefrontal circuit is thought to be crucial for threat vigilance during anxiety. However, engagement of this circuitry within relatively naturalistic paradigms remains unresolved. Methods Using an open functional magnetic resonance imaging dataset (Cambridge Centre for Ageing Neuroscience; n = 630), we sought to investigate whether anxiety correlates with dynamic connectivity between the amygdala and dorsomedial prefrontal cortex during movie watching. Results Using an intersubject representational similarity approach, we saw no effect of anxiety when comparing pairwise similarities of dynamic connectivity across the entire movie. However, preregistered analyses demonstrated a relationship between anxiety, amygdala-prefrontal dynamics, and anxiogenic features of the movie (canonical suspense ratings). Our results indicated that amygdala-prefrontal circuitry was modulated by suspense in low-anxiety individuals but was less sensitive to suspense in high-anxiety individuals. We suggest that this could also be related to slowed habituation or amplified anticipation. Moreover, a measure of threat-relevant attentional bias (accuracy/reaction time to fearful faces) demonstrated an association with connectivity and suspense. Conclusions Overall, this study demonstrated the presence of anxiety-relevant differences in connectivity during movie watching, varying with anxiogenic features of the movie. Mechanistically, exactly how and when these differences arise remains an opportunity for future research.
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Affiliation(s)
- Peter A. Kirk
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
- Experimental Psychology, University College London, London, United Kingdom
- Departments of Psychology and Psychiatry, Yale University, New Haven, Connecticut
| | - Avram J. Holmes
- Departments of Psychology and Psychiatry, Yale University, New Haven, Connecticut
- Wu Tsai Institute, Yale University, New Haven, Connecticut
| | - Oliver J. Robinson
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
- Clinical, Educational and Health Psychology, University College London, London, United Kingdom
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4
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Zhang R, Wang J, Lin H, Turk-Browne NB, Cai Q. Neural signatures of second language proficiency in narrative processing. Cereb Cortex 2023:7143624. [PMID: 37100085 DOI: 10.1093/cercor/bhad133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 03/22/2023] [Accepted: 03/23/2023] [Indexed: 04/28/2023] Open
Abstract
Making sense of speech in a second language relies on multiple abilities. Differences in brain activity related to proficiency in language tasks have often been attributed to processing demands. However, during naturalistic narrative comprehension, listeners at different proficiency levels may form different representations of the same speech. We hypothesized that the intersubject synchronization of these representations could be used to measure second-language proficiency. Using a searchlight-shared response model, we found highly proficient participants showed synchronization in regions similar to those of native speakers, including in the default mode network and the lateral prefrontal cortex. In contrast, participants with low proficiency showed more synchronization in auditory cortex and word-level semantic processing areas in the temporal lobe. Moderate proficiency showed the greatest neural diversity, suggesting lower consistency in the source of this partial proficiency. Based on these synchronization differences, we were able to classify the proficiency level or predict behavioral performance on an independent English test in held-out participants, suggesting the identified neural systems represented proficiency-sensitive information that was generalizable to other individuals. These findings suggest higher second-language proficiency leads to more native-like neural processing of naturalistic language, including in systems beyond the cognitive control network or the core language network.
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Affiliation(s)
- Ruiqing Zhang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
- Shanghai Key Laboratory of Artificial Intelligence in Learning and Cognitive Science, LAIX Inc, Shanghai 200090, China
| | - Jing Wang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201210, China
| | - Hui Lin
- Shanghai Key Laboratory of Artificial Intelligence in Learning and Cognitive Science, LAIX Inc, Shanghai 200090, China
| | - Nicholas B Turk-Browne
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - Qing Cai
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201210, China
- NYU-ECNU Institute of Brain and Cognitive Science, New York University Shanghai, Shanghai 200126, China
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Meyer ML. Don't You Forget About Me: The Importance of Studying the Brain Basis of Real-world Interpersonal Memory. J Cogn Neurosci 2023; 35:149-157. [PMID: 36306251 DOI: 10.1162/jocn_a_01926] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Despite the fact that humans are a highly social species, we know relatively little about how people remember the rich interpersonal information filling their social lives. This gap is surprising: One function of memory has been suggested to be relationship maintenance [Neisser, U. Time present and time past. Practical Aspects of Memory: Current Research and Issues, 2, 545-560, 1988]. A major barrier to understanding the brain basis of interpersonal memory is that traditional brain imaging methods are not ideally suited to study memory for the nuanced interpersonal experiences comprising our social lives. Yet, recent and rapidly developing advances in the analysis of brain responses to naturalistic social information can help researchers surpass this methodological barrier. This perspective piece articulates the importance of studying the brain basis of real-world social memories and suggests new directions in interpersonal memory research. This includes investigating the brain mechanisms that represent the content and structure of real-world interpersonal memories as well as how they are altered in mental health conditions associated with social memory biases.
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Rodriguez RX, Noble S, Tejavibulya L, Scheinost D. Leveraging edge-centric networks complements existing network-level inference for functional connectomes. Neuroimage 2022; 264:119742. [PMID: 36368501 PMCID: PMC9838718 DOI: 10.1016/j.neuroimage.2022.119742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 11/04/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022] Open
Abstract
The human connectome is modular with distinct brain regions clustering together to form large-scale communities, or networks. This concept has recently been leveraged in novel inferencing procedures by averaging the edge-level statistics within networks to induce more powerful inferencing at the network level. However, these networks are constructed based on the similarity between pairs of nodes. Emerging work has described novel edge-centric networks, which instead use the similarity between pairs of edges to construct networks. In this work, we use these edge-centric networks in a network-level inferencing procedure and compare this novel method to traditional inferential procedures and the network-level procedure using node-centric networks. We use data from the Human Connectome Project, the Healthy Brain Network, and the Philadelphia Neurodevelopmental Cohort and use a resampling technique with various sample sizes (n=40, 80, 120) to probe the power and specificity of each method. Across datasets and sample sizes, using the edge-centric networks outperforms using node-centric networks for inference as well as edge-level FDR correction and NBS. Additionally, the edge-centric networks were found to be more consistent in clustering effect sizes of similar values as compared to node-centric networks, although node-centric networks often had a lower average within-network effect size variability. Together, these findings suggest that using edge-centric networks for network-level inference can procure relatively powerful results while remaining similarly accurate to the underlying edge-level effects across networks, complementing previous inferential methods.
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Affiliation(s)
- Raimundo X. Rodriguez
- Interdepartmental Neuroscience Program, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA,Corresponding author. (R.X. Rodriguez)
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 330 Cedar Street, New Haven, CT 06520, USA
| | - Link Tejavibulya
- Interdepartmental Neuroscience Program, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA,Department of Radiology and Biomedical Imaging, Yale School of Medicine, 330 Cedar Street, New Haven, CT 06520, USA,Department of Biomedical Engineering, Yale School of Engineering and Applied Science, 17 Hillhouse Avenue, New Haven, CT 06511, USA,Department of Statistics and Data Science, Yale University, 24 Hillhouse Avenue, New Haven, CT 06511, USA,Child Study Center, Yale School of Medicine, 230 South Frontage Road, New Haven, CT 06519, USA,Wu Tsai Institute, Yale University, 100 College Street, New Haven, CT 06510, USA
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7
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Geniesse C, Chowdhury S, Saggar M. NeuMapper: A scalable computational framework for multiscale exploration of the brain's dynamical organization. Netw Neurosci 2022; 6:467-498. [PMID: 35733428 PMCID: PMC9207992 DOI: 10.1162/netn_a_00229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 01/04/2022] [Indexed: 11/04/2022] Open
Abstract
For better translational outcomes, researchers and clinicians alike demand novel tools to distill complex neuroimaging data into simple yet behaviorally relevant representations at the single-participant level. Recently, the Mapper approach from topological data analysis (TDA) has been successfully applied on noninvasive human neuroimaging data to characterize the entire dynamical landscape of whole-brain configurations at the individual level without requiring any spatiotemporal averaging at the outset. Despite promising results, initial applications of Mapper to neuroimaging data were constrained by (1) the need for dimensionality reduction and (2) lack of a biologically grounded heuristic for efficiently exploring the vast parameter space. Here, we present a novel computational framework for Mapper-designed specifically for neuroimaging data-that removes limitations and reduces computational costs associated with dimensionality reduction and parameter exploration. We also introduce new meta-analytic approaches to better anchor Mapper-generated representations to neuroanatomy and behavior. Our new NeuMapper framework was developed and validated using multiple fMRI datasets where participants engaged in continuous multitask experiments that mimic "ongoing" cognition. Looking forward, we hope our framework will help researchers push the boundaries of psychiatric neuroimaging toward generating insights at the single-participant level across consortium-size datasets.
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Affiliation(s)
- Caleb Geniesse
- Biophysics Program, Stanford University, Stanford, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Samir Chowdhury
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Manish Saggar
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
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Rodríguez Villar AJ. A Neuroscientific and Cognitive Literary Approach to the Treatment of Time in Calderón's Autos sacramentales. Front Integr Neurosci 2022; 16:780701. [PMID: 35418840 PMCID: PMC8996133 DOI: 10.3389/fnint.2022.780701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 02/24/2022] [Indexed: 11/14/2022] Open
Abstract
Time processing is a fundamental subject in cognitive sciences and neuroscience. Current research is deepening how our brains process time, revealing its essential role in human functionality and survival. In his autos sacramentales, Early Modern Spanish playwright Pedro Calderón de la Barca portrays the relationships between human inner workings and the Christian concept of time. These plays portray the experience of the present, the perception of the flow of time, the measure of time raging from seconds to eternity, and the mental travel necessary to inhabit the past and future with the help of memory and imagination. Calderón explores how the dramatic form can portray all these temporal phenomena and how that portrait of time can constrain the dramatic structure. The different parts of the brain in charge of executive decisions, projections, memories, computation, and calibration are the basis that leads these characters to make the choices that will take them to the future they have cast for themselves. This paper analyzes how the processes that Calderón ascribed to the soul of his characters in the 17th century relate to ongoing cognitive and neuroscientific findings.
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Faskowitz J, Betzel RF, Sporns O. Edges in brain networks: Contributions to models of structure and function. Netw Neurosci 2022; 6:1-28. [PMID: 35350585 PMCID: PMC8942607 DOI: 10.1162/netn_a_00204] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 08/02/2021] [Indexed: 11/16/2022] Open
Abstract
Network models describe the brain as sets of nodes and edges that represent its distributed organization. So far, most discoveries in network neuroscience have prioritized insights that highlight distinct groupings and specialized functional contributions of network nodes. Importantly, these functional contributions are determined and expressed by the web of their interrelationships, formed by network edges. Here, we underscore the important contributions made by brain network edges for understanding distributed brain organization. Different types of edges represent different types of relationships, including connectivity and similarity among nodes. Adopting a specific definition of edges can fundamentally alter how we analyze and interpret a brain network. Furthermore, edges can associate into collectives and higher order arrangements, describe time series, and form edge communities that provide insights into brain network topology complementary to the traditional node-centric perspective. Focusing on the edges, and the higher order or dynamic information they can provide, discloses previously underappreciated aspects of structural and functional network organization.
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Affiliation(s)
- Joshua Faskowitz
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Richard F. Betzel
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Indiana University Network Science Institute, Indiana University, Bloomington, IN, USA
- Cognitive Science Program, Indiana University, Bloomington, IN, USA
| | - Olaf Sporns
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Indiana University Network Science Institute, Indiana University, Bloomington, IN, USA
- Cognitive Science Program, Indiana University, Bloomington, IN, USA
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