9 results on '"Jackob Keynan"'
Search Results
2. Reduction of Beta Band Activity in the Dorsolateral Prefrontal Cortex and Subgenual Anterior Cingulate Cortex After Stanford Neuromodulation Therapy in Treatment-Resistant Depression
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Masataka Wada, Anna Chaiken, Derrick Buchanan, Jennifer Lissemore, Eleanor Cole, Claudia Tischler, Jackob Keynan, Cammie Rolle, and Nolan Williams
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Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Published
- 2025
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3. Heart-brain coupling in a randomized controlled trial of Stanford Neuromodulation Therapy: preliminary results and future directions.
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John Coetzee, Hanneke van Dijk, Martin Tik, Clive Veerapal, Andrew Geoly, T.J. Ford, Haroon Musleh, Irakli Kaloiani, Jackob Keynan, Martijn Arns, and Nolan Williams
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Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Published
- 2023
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4. Predictors of real-time fMRI neurofeedback performance and improvement – A machine learning mega-analysis
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Amelie Haugg, Fabian M. Renz, Andrew A. Nicholson, Cindy Lor, Sebastian J. Götzendorfer, Ronald Sladky, Stavros Skouras, Amalia McDonald, Cameron Craddock, Lydia Hellrung, Matthias Kirschner, Marcus Herdener, Yury Koush, Marina Papoutsi, Jackob Keynan, Talma Hendler, Kathrin Cohen Kadosh, Catharina Zich, Simon H. Kohl, Manfred Hallschmid, Jeff MacInnes, R. Alison Adcock, Kathryn C. Dickerson, Nan-Kuei Chen, Kymberly Young, Jerzy Bodurka, Michael Marxen, Shuxia Yao, Benjamin Becker, Tibor Auer, Renate Schweizer, Gustavo Pamplona, Ruth A. Lanius, Kirsten Emmert, Sven Haller, Dimitri Van De Ville, Dong-Youl Kim, Jong-Hwan Lee, Theo Marins, Fukuda Megumi, Bettina Sorger, Tabea Kamp, Sook-Lei Liew, Ralf Veit, Maartje Spetter, Nikolaus Weiskopf, Frank Scharnowski, and David Steyrl
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Neurofeedback ,Functional MRI ,Mega-analysis ,Machine learning ,Real-time fMRI ,Learning ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments.With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.
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- 2021
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5. Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors
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Nimrod Jackob Keynan, Ziv Ben-Zion, Pinchas Halpern, Talma Hendler, Haggai Sharon, Yoav Zeevi, Arieh Y. Shalev, Roee Admon, Tal Kozlovski, Israel Liberzon, and Yoav Benjamini
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Adult ,Psychometrics ,Article ,lcsh:RC321-571 ,Stress Disorders, Post-Traumatic ,Young Adult ,Cellular and Molecular Neuroscience ,Humans ,Medicine ,Survivors ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,Biological Psychiatry ,Depression (differential diagnoses) ,Post-traumatic stress disorder (PTSD) ,business.industry ,Cognitive flexibility ,Cognition ,Middle Aged ,medicine.disease ,Anxiety Disorders ,Magnetic Resonance Imaging ,Cognitive test ,Psychiatry and Mental health ,Anxiety ,Female ,medicine.symptom ,Psychiatric disorders ,business ,Insula ,Biomarkers ,Neuroscience ,Clinical psychology - Abstract
Contemporary symptom-based diagnosis of post-traumatic stress disorder (PTSD) largely overlooks related neurobehavioral mechanisms and relies entirely on subjective interpersonal reporting. Previous studies associating biomarkers with PTSD have mostly used symptom-based diagnosis as the main outcome measure, disregarding the wide variability and richness of PTSD phenotypical features. Here, we aimed to computationally derive potential biomarkers that could efficiently differentiate PTSD subtypes among recent trauma survivors. A three-staged semi-unsupervised method (“3C”) was used to firstly categorize individuals by current PTSD symptom severity, then derive clusters based on clinical features related to PTSD (e.g. anxiety and depression), and finally to classify participants’ cluster membership using objective multi-domain features. A total of 256 features were extracted from psychometrics, cognitive functioning, and both structural and functional MRI data, obtained from 101 adult civilians (age = 34.80 ± 11.95; 51 females) evaluated within 1 month of trauma exposure. The features that best differentiated cluster membership were assessed by importance analysis, classification tree, and ANOVA. Results revealed that entorhinal and rostral anterior cingulate cortices volumes (structural MRI domain), in-task amygdala’s functional connectivity with the insula and thalamus (functional MRI domain), executive function and cognitive flexibility (cognitive testing domain) best differentiated between two clusters associated with PTSD severity. Cross-validation established the results’ robustness and consistency within this sample. The neural and cognitive potential biomarkers revealed by the 3C analytics offer objective classifiers of post-traumatic morbidity shortly following trauma. They also map onto previously documented neurobehavioral mechanisms associated with PTSD and demonstrate the usefulness of standardized and objective measurements as differentiating clinical sub-classes shortly after trauma.
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- 2020
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6. Hippocampal-Amygdala Resting State Functional Connectivity Serves as Resilience Factor for Short- and Long-Term Stress Exposure
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Talma Henlder, Ziv Ben-Zion, Pinchas Halpern, Israel Liberzon, Haggai Sharon, Arieh Y. Shalev, Nimrod Jackob Keynan, and Roee Admon
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medicine.anatomical_structure ,Resting state fMRI ,Functional connectivity ,Long term stress ,medicine ,Hippocampal formation ,Resilience (network) ,Psychology ,Amygdala ,Neuroscience ,Biological Psychiatry - Published
- 2020
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7. Neurobehavioral moderators of post-traumatic stress disorder (PTSD) trajectories: study protocol of a prospective MRI study of recent trauma survivors
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Pinchas Halpern, Talma Hendler, Ziv Ben-Zion, Nimrod Jackob Keynan, Naomi B. Fine, Roee Admon, Israel Liberzon, and Arieh Y. Shalev
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050103 clinical psychology ,Longitudinal study ,lcsh:RC435-571 ,Magnetic Resonance Imaging (MRI) ,Poison control ,behavioral disciplines and activities ,Study Protocol ,03 medical and health sciences ,纵向研究 ,0302 clinical medicine ,lcsh:Psychiatry ,mental disorders ,medicine ,0501 psychology and cognitive sciences ,Trastorno de Estrés Postraumático (TEPT) ,Trayectorias de los síntomas ,磁共振成像(MRI) ,• The protocol of a multimodal longitudinal study of recent trauma survivors is presented.• The study evaluates the evolving relationships between PTSD symptoms, neurocognitive functioning, and brain imaging parameters (structural and functional).• The study rationale, methodology, and design are reported.• Technical and conceptual challenges to performing longitudinal multimodal studies of recent PTSD are discussed.• Study design elements that addresses these challenges (e.g., changes in PTSD diagnostic template, optimal assessments’ timing, and minimizing subject loss) are discussed ,Depression (differential diagnoses) ,Post-traumatic stress disorder (PTSD) ,business.industry ,05 social sciences ,longitudinal study ,Cognitive flexibility ,Moderadores neuroconductuales ,Post-Traumatic Stress Disorder (PTSD) ,Executive functions ,medicine.disease ,Imagen por Resonancia Magnética (MRI) ,estudio longitudinal ,030227 psychiatry ,3. Good health ,symptom trajectories ,Traumatic injury ,症状轨迹 ,neurobehavioral moderators ,神经行为调节效应 ,Anxiety ,medicine.symptom ,business ,创伤后应激障碍(PTSD) ,Clinical psychology - Abstract
Background: Post-traumatic stress disorder (PTSD) is triggered by distinct events and is therefore amenable to studies of its early pathogenesis. Longitudinal studies during the year that follows trauma exposure revealed typical symptom trajectories leading to either recovery or protracted PTSD. Thezneurobehavioral correlates of early PTSD symptoms’ trajectories have not been longitudinally explored. Objective: To present the rationale and design of a longitudinal study exploring the relationship between evolving PTSD symptoms and co-occurring cognitive functioning and structural and functional brain imaging parameters. Method: Adult civilians consecutively admitted to a general hospital emergency room (ER) for traumatic injury will be screened for early PTSD symptoms suggestive of chronic PTSD risk, and consecutively evaluated 1, 6 and 14 months following the traumatic event. Consecutive assessments will include structured clinical interviews for PTSD and comorbid disorders, self-reported depression and anxiety symptoms, a web-based assessment of cognitive domains previously linked with PTSD (e.g., memory, executive functions, cognitive flexibility), high-resolution structural MRI of both grey and white matter, functional resting-state connectivity, and fMRI tasks examining emotional reactivity and regulation, as well as motivation processing and sensitivity to risk and reward. Data analyses will explore putative cognitive predictors of non-remitting PTSD, and brain structural and functional correlates of PTSD persistence or recovery. Conclusion: This work will longitudinally document patterns of brain structures, connectivity, and functioning, predictive of (or associated with) emerging PTSD during the critical first year of after the traumatic event. It will thereby inform our understanding of the disorder’s pathogenesis and underlying neuropathology. Challenges to longitudinal MRI studies of recent survivors, and methodological choices used to optimize the study’s design are discussed.
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- 2019
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8. Potential Neurocognitive Biomarkers for Post Traumatic Stress Disorder (PTSD) Severity in Recent Trauma Survivors
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Nimrod Jackob Keynan, Ziv Ben-Zion, Haggai Sharon, Pinchas Halpern, Tal Kozlovski, Yoav Benjamini, Israel Liberzon, Talma Hendler, Yoav Zeevi, Roee Admon, and Arieh Y. Shalev
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Psychometrics ,business.industry ,Functional neuroimaging ,Cognitive flexibility ,Medicine ,Cognition ,business ,medicine.disease ,Neurocognitive ,Insula ,Psychopathology ,Clinical psychology ,Post-traumatic stress disorder (PTSD) - Abstract
Contemporary symptom-based diagnosis of Post-traumatic Stress Disorder (PTSD) largely overlooks related neurobehavioral findings and rely entirely on subjective interpersonal reporting. Previous studies associating objective biomarkers with PTSD have mostly used the disorder’s symptom-based diagnosis as main outcome measure, overlooking the actual clustering and richness of phenotypical features associated with PTSD. Here, we aimed to computationally derive potential neurocognitive biomarkers that could efficiently differentiate PTSD subtypes, based on an observational cohort study of recent trauma survivors. A three-staged semi-unsupervised method (“3C”) was used to categorize trauma survivors based on current PTSD diagnostics, derive clusters of PTSD based on features related to symptom load, and to classify participants’ cluster membership using objective features. A total of 256 features were extracted from psychometrics, cognitive, structural and functional neuroimaging data, obtained from 101 adult civilians (age=34.80±11.95, 51 females) evaluated within a month of trauma exposure. Multi-domain features that best differentiated cluster membership were indicated by using importance analysis, classification trees, and ANOVA. Results revealed that entorhinal and rostral anterior cingulate cortices volumes (structural domain), in-task amygdala’s functional connectivity with the insula and thalamus (functional domain), executive function and cognitive flexibility (cognitive domain) best differentiated between two clusters related to PTSD severity. Cross-validation established the results’ robustness and consistency within this sample. Multi-domain biomarkers revealed by the 3C analytics offer objective classifiers of post-traumatic morbidity shortly following trauma. They also map onto previously documented neurobehavioral PTSD features, supporting the future use of standardized and objective measurements to more precisely identify psychopathology subgroups shortly after trauma.
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- 2019
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9. Cognitive Flexibility Predicts PTSD Symptoms: Observational and Interventional Studies
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Ziv Ben-Zion, Naomi B. Fine, Nimrod Jackob Keynan, Roee Admon, Nili Green, Mor Halevi, Greg A. Fonzo, Michal Achituv, Ofer Merin, Haggai Sharon, Pinchas Halpern, Israel Liberzon, Amit Etkin, Talma Hendler, and Arieh Y. Shalev
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lcsh:RC435-571 ,Psychological intervention ,cognitive flexibility ,03 medical and health sciences ,0302 clinical medicine ,cognitive training intervention ,lcsh:Psychiatry ,Intervention (counseling) ,medicine ,risk factors ,Cognitive skill ,Post-traumatic stress disorder (PTSD) ,Original Research ,Psychiatry ,resilience factors ,business.industry ,Cognitive flexibility ,medicine.disease ,Post-Traumatic Stress Disorder (PTSD) ,030227 psychiatry ,3. Good health ,Psychiatry and Mental health ,neurocognitive functioning ,Observational study ,business ,Neurocognitive ,030217 neurology & neurosurgery ,Clinical psychology ,Psychopathology - Abstract
Introduction: Post-Traumatic Stress Disorder (PTSD) is a prevalent, severe and tenacious psychopathological consequence of traumatic events. Neurobehavioral mechanisms underlying PTSD pathogenesis have been identified, and may serve as risk-resilience factors during the early aftermath of trauma exposure. Longitudinally documenting the neurobehavioral dimensions of early responses to trauma may help characterize survivors at risk and inform mechanism-based interventions. We present two independent longitudinal studies that repeatedly probed clinical symptoms and neurocognitive domains in recent trauma survivors. We hypothesized that better neurocognitive functioning shortly after trauma will be associated with less severe PTSD symptoms a year later, and that an early neurocognitive intervention will improve cognitive functioning and reduce PTSD symptoms. Methods: Participants in both studies were adult survivors of traumatic events admitted to two general hospitals' emergency departments (EDs) in Israel. The studies used identical clinical and neurocognitive tools, which included assessment of PTSD symptoms and diagnosis, and a battery of neurocognitive tests. The first study evaluated 181 trauma-exposed individuals one-, six-, and 14 months following trauma exposure. The second study evaluated 97 trauma survivors 1 month after trauma exposure, randomly allocated to 30 days of web-based neurocognitive intervention (n = 50) or control tasks (n = 47), and re-evaluated all subjects three- and 6 months after trauma exposure. Results: In the first study, individuals with better cognitive flexibility at 1 month post-trauma showed significantly less severe PTSD symptoms after 13 months (p = 0.002). In the second study, the neurocognitive training group showed more improvement in cognitive flexibility post-intervention (p = 0.019), and lower PTSD symptoms 6 months post-trauma (p = 0.017), compared with controls. Intervention- induced improvement in cognitive flexibility positively correlated with clinical improvement (p = 0.002). Discussion: Cognitive flexibility, shortly after trauma exposure, emerged as a significant predictor of PTSD symptom severity. It was also ameliorated by a neurocognitive intervention and associated with a better treatment outcome. These findings support further research into the implementation of mechanism-driven neurocognitive preventive interventions for PTSD.
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- 2018
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