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Galin S, Keren H. The Predictive Potential of Heart Rate Variability for Depression. Neuroscience 2024; 546:88-103. [PMID: 38513761 DOI: 10.1016/j.neuroscience.2024.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/29/2024] [Accepted: 03/16/2024] [Indexed: 03/23/2024]
Abstract
Heart rate variability (HRV),a measure of the fluctuations in the intervals between consecutive heartbeats, is an indicator of changes in the autonomic nervous system. A chronic reduction in HRV has been repeatedly linked to clinical depression. However, the chronological and mechanistic aspects of this relationship, between the neural, physiological, and psychopathological levels, remain unclear. In this review we present evidence by which changes in HRV might precede the onset of depression. We describe several pathways that can facilitate this relationship. First, we examine a theoretical model of the impact of autonomic imbalance on HRV and its role in contributing to mood dysregulation and depression. We then highlight brain regions that are regulating both HRV and emotion, suggesting these neural regions, and the Insula in particular, as potential mediators of this relationship. We also present additional possible mediating mechanisms involving the immune system and inflammation processes. Lastly, we support this model by showing evidence that modification of HRV with biofeedback leads to an improvement in some symptoms of depression. The possibility that changes in HRV precede the onset of depression is critical to put to the test, not only because it could provide insights into the mechanisms of the illness but also because it may offer a predictive anddiagnosticphysiological marker for depression. Importantly, it could also help to develop new effective clinical interventions for treating depression.
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Affiliation(s)
- Shir Galin
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel; Gonda Interdisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel
| | - Hanna Keren
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel; Gonda Interdisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel.
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2
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Gadassi Polack R, Mollick JA, Keren H, Joormann J, Watts R. Neural responses to reward valence and magnitude from pre- to early adolescence. Neuroimage 2023; 275:120166. [PMID: 37178821 PMCID: PMC10311119 DOI: 10.1016/j.neuroimage.2023.120166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 04/04/2023] [Accepted: 05/10/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUND Neural activation during reward processing is thought to underlie critical behavioral changes that take place during the transition to adolescence (e.g., learning, risk-taking). Though literature on the neural basis of reward processing in adolescence is booming, important gaps remain. First, more information is needed regarding changes in functional neuroanatomy in early adolescence. Another gap is understanding whether sensitivity to different aspects of the incentive (e.g., magnitude and valence) changes during the transition into adolescence. We used fMRI from a large sample of preadolescent children to characterize neural responses to incentive valence vs. magnitude during anticipation and feedback, and their change over a period of two years. METHODS Data were taken from the Adolescent Cognitive and Brain DevelopmentSM (ABCD®) study release 3.0. Children completed the Monetary Incentive Delay task at baseline (ages 9-10) and year 2 follow-up (ages 11-12). Based on data from two sites (N = 491), we identified activation-based Regions of Interest (ROIs; e.g., striatum, prefrontal regions, etc.) that were sensitive to trial type (win $5, win $0.20, neutral, lose $0.20, lose $5) during anticipation and feedback phases. Then, in an independent subsample (N = 1470), we examined whether these ROIs were sensitive to valence and magnitude and whether that sensitivity changed over two years. RESULTS Our results show that most ROIs involved in reward processing (including the striatum, prefrontal cortex, and insula) are specialized, i.e., mainly sensitive to either incentive valence or magnitude, and this sensitivity was consistent over a 2-year period. The effect sizes of time and its interactions were significantly smaller (0.002≤η2≤0.02) than the effect size of trial type (0.06≤η2≤0.30). Interestingly, specialization was moderated by reward processing phase but was stable across development. Biological sex and pubertal status differences were few and inconsistent. Developmental changes were mostly evident during success feedback, where neural reactivity increased over time. CONCLUSIONS Our results suggest sub-specialization to valence vs. magnitude within many ROIs of the reward circuitry. Additionally, in line with theoretical models of adolescent development, our results suggest that the ability to benefit from success increases from pre- to early adolescence. These findings can inform educators and clinicians and facilitate empirical research of typical and atypical motivational behaviors during a critical time of development.
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Affiliation(s)
- Reuma Gadassi Polack
- Psychology Department, Yale University, United States; Psychiatry Department, Yale University, United States; School of Behavioral Sciences, Tel Aviv-Yaffo Academic College, Israel.
| | | | - Hanna Keren
- Faculty of Medicine, Bar-Ilan University, Israel
| | | | - Richard Watts
- Psychology Department, Yale University, United States
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3
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Jangraw DC, Keren H, Sun H, Bedder RL, Rutledge RB, Pereira F, Thomas AG, Pine DS, Zheng C, Nielson DM, Stringaris A. A highly replicable decline in mood during rest and simple tasks. Nat Hum Behav 2023; 7:596-610. [PMID: 36849591 PMCID: PMC10192073 DOI: 10.1038/s41562-023-01519-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 01/04/2023] [Indexed: 03/01/2023]
Abstract
Does our mood change as time passes? This question is central to behavioural and affective science, yet it remains largely unexamined. To investigate, we intermixed subjective momentary mood ratings into repetitive psychology paradigms. Here we demonstrate that task and rest periods lowered participants' mood, an effect we call 'Mood Drift Over Time'. This finding was replicated in 19 cohorts totalling 28,482 adult and adolescent participants. The drift was relatively large (-13.8% after 7.3 min of rest, Cohen's d = 0.574) and was consistent across cohorts. Behaviour was also impacted: participants were less likely to gamble in a task that followed a rest period. Importantly, the drift slope was inversely related to reward sensitivity. We show that accounting for time using a linear term significantly improves the fit of a computational model of mood. Our work provides conceptual and methodological reasons for researchers to account for time's effects when studying mood and behaviour.
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Affiliation(s)
- David C Jangraw
- National Institute of Mental Health, Bethesda, MD, USA.
- Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, USA.
| | - Hanna Keren
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Haorui Sun
- Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, USA
| | - Rachel L Bedder
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Robb B Rutledge
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, USA
| | | | - Adam G Thomas
- National Institute of Mental Health, Bethesda, MD, USA
| | - Daniel S Pine
- National Institute of Mental Health, Bethesda, MD, USA
| | - Charles Zheng
- National Institute of Mental Health, Bethesda, MD, USA
| | | | - Argyris Stringaris
- Department of Psychiatry, National and Kapodistrian University of Athens, Athens, Greece
- Faculty of Brain Sciences, Division of Psychiatry, University College London, London, UK
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4
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Elliott MV, Johnson SL, Pearlstein JG, Muñoz Lopez DE, Keren H. Emotion-related impulsivity and risky decision-making: A systematic review and meta-regression. Clin Psychol Rev 2023; 100:102232. [PMID: 36512906 PMCID: PMC9974869 DOI: 10.1016/j.cpr.2022.102232] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 11/12/2022] [Accepted: 11/23/2022] [Indexed: 11/30/2022]
Abstract
Emotion-related impulsivity, the trait-like tendency toward regrettable behavior during states of high emotion, is a robust predictor of internalizing and externalizing psychopathology. Despite substantial evidence that emotion-related impulsivity is important transdiagnostically, relatively little is known about its cognitive correlates. This systematic review and meta-regression investigates one such candidate, risky decision-making. We analyzed 195 effect sizes from 51 studies of 14,957 total participants, including 105 newly calculated effect sizes that were not reported in the original publications. The meta-regression demonstrated evidence for a small, positive relationship of emotion-related impulsivity with behavioral indices of risky decision-making (ß = 0.086). Effects generalized across sample age, gender, Positive versus Negative Urgency, and clinical versus nonclinical samples. The average effect size varied by task type, with stronger effects for the Iowa Gambling Task and Delay Discounting Task. Experimental arousal manipulation was nearly a significant moderator, with stress and pharmacological manipulations yielding significant effect sizes. Analyses indicated that publication bias did not skew the current findings. Notwithstanding limitations, the data suggest that risky decision-making is a cognitive domain that relates to emotion-related impulsivity. We conclude with recommendations regarding the specific types of tasks and arousal inductions that will best capture emotion-related impulsivity in future experimental research.
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Affiliation(s)
- Matthew V Elliott
- University of California, Berkeley, Berkeley, CA, United States of America.
| | - Sheri L Johnson
- University of California, Berkeley, Berkeley, CA, United States of America
| | | | | | - Hanna Keren
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
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5
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Liuzzi L, Chang KK, Zheng C, Keren H, Saha D, Nielson DM, Stringaris A. Magnetoencephalographic Correlates of Mood and Reward Dynamics in Human Adolescents. Cereb Cortex 2021; 32:3318-3330. [PMID: 34921602 PMCID: PMC9340400 DOI: 10.1093/cercor/bhab417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 10/14/2021] [Accepted: 10/15/2021] [Indexed: 11/24/2022] Open
Abstract
Despite its omnipresence in everyday interactions and its importance for mental health, mood and its neuronal underpinnings are poorly understood. Computational models can help identify parameters affecting self-reported mood during mood induction tasks. Here, we test if computationally modeled dynamics of self-reported mood during monetary gambling can be used to identify trial-by-trial variations in neuronal activity. To this end, we shifted mood in healthy (N = 24) and depressed (N = 30) adolescents by delivering individually tailored reward prediction errors while recording magnetoencephalography (MEG) data. Following a pre-registered analysis, we hypothesize that the expectation component of mood would be predictive of beta-gamma oscillatory power (25–40 Hz). We also hypothesize that trial variations in the source localized responses to reward feedback would be predicted by mood and by its reward prediction error component. Through our multilevel statistical analysis, we found confirmatory evidence that beta-gamma power is positively related to reward expectation during mood shifts, with localized sources in the posterior cingulate cortex. We also confirmed reward prediction error to be predictive of trial-level variations in the response of the paracentral lobule. To our knowledge, this is the first study to harness computational models of mood to relate mood fluctuations to variations in neural oscillations with MEG.
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Affiliation(s)
- Lucrezia Liuzzi
- Section of Clinical and Computational Psychiatry (CompΨ), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Katharine K Chang
- Department of Psychology, University of Rochester, Rochester, NY 14627, USA
| | - Charles Zheng
- Machine Learning Team, Functional Magnetic Resonance Imaging Facility, National Institutes of Health, Bethesda, MD 20892, USA
| | - Hanna Keren
- Section of Clinical and Computational Psychiatry (CompΨ), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Dipta Saha
- Section of Clinical and Computational Psychiatry (CompΨ), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Dylan M Nielson
- Section of Clinical and Computational Psychiatry (CompΨ), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Argyris Stringaris
- Section of Clinical and Computational Psychiatry (CompΨ), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
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6
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Keren H, Zheng C, Jangraw DC, Chang K, Vitale A, Rutledge RB, Pereira F, Nielson DM, Stringaris A. The temporal representation of experience in subjective mood. eLife 2021; 10:62051. [PMID: 34128464 PMCID: PMC8241441 DOI: 10.7554/elife.62051] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 06/02/2021] [Indexed: 12/24/2022] Open
Abstract
Humans refer to their mood state regularly in day-to-day as well as clinical interactions. Theoretical accounts suggest that when reporting on our mood we integrate over the history of our experiences; yet, the temporal structure of this integration remains unexamined. Here, we use a computational approach to quantitatively answer this question and show that early events exert a stronger influence on reported mood (a primacy weighting) compared to recent events. We show that a Primacy model accounts better for mood reports compared to a range of alternative temporal representations across random, consistent, or dynamic reward environments, different age groups, and in both healthy and depressed participants. Moreover, we find evidence for neural encoding of the Primacy, but not the Recency, model in frontal brain regions related to mood regulation. These findings hold implications for the timing of events in experimental or clinical settings and suggest new directions for individualized mood interventions.
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Affiliation(s)
- Hanna Keren
- Section of Clinical and Computational Psychiatry, National Institute of Mental Health, National Institutes of Health, Bethesda, United States
| | - Charles Zheng
- Machine Learning Team, National Institute of Mental Health, National Institutes of Health, Bethesda, United States
| | - David C Jangraw
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, United States
| | - Katharine Chang
- Section of Clinical and Computational Psychiatry, National Institute of Mental Health, National Institutes of Health, Bethesda, United States
| | - Aria Vitale
- Section of Clinical and Computational Psychiatry, National Institute of Mental Health, National Institutes of Health, Bethesda, United States
| | - Robb B Rutledge
- Department of Psychology, Yale University, New Haven, United States.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.,Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Francisco Pereira
- Machine Learning Team, National Institute of Mental Health, National Institutes of Health, Bethesda, United States
| | - Dylan M Nielson
- Section of Clinical and Computational Psychiatry, National Institute of Mental Health, National Institutes of Health, Bethesda, United States
| | - Argyris Stringaris
- Section of Clinical and Computational Psychiatry, National Institute of Mental Health, National Institutes of Health, Bethesda, United States
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7
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Nielson DM, Keren H, O'Callaghan G, Jackson SM, Douka I, Vidal-Ribas P, Pornpattananangkul N, Camp CC, Gorham LS, Wei C, Kirwan S, Zheng CY, Stringaris A. Great Expectations: A Critical Review of and Suggestions for the Study of Reward Processing as a Cause and Predictor of Depression. Biol Psychiatry 2021; 89:134-143. [PMID: 32797941 PMCID: PMC10726343 DOI: 10.1016/j.biopsych.2020.06.012] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 05/20/2020] [Accepted: 06/10/2020] [Indexed: 10/24/2022]
Abstract
Both human and animal studies support the relationship between depression and reward processing abnormalities, giving rise to the expectation that neural signals of these processes may serve as biomarkers or mechanistic treatment targets. Given the great promise of this research line, we scrutinized those findings and the theoretical claims that underlie them. To achieve this, we applied the framework provided by classical work on causality as well as contemporary approaches to prediction. We identified a number of conceptual, practical, and analytical challenges to this line of research and used a preregistered meta-analysis to quantify the longitudinal associations between reward processing abnormalities and depression. We also investigated the impact of measurement error on reported data. We found that reward processing abnormalities do not reach levels that would be useful for clinical prediction, yet the available evidence does not preclude a possible causal role in depression.
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Affiliation(s)
- Dylan M Nielson
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Hanna Keren
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Georgia O'Callaghan
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Sarah M Jackson
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Ioanna Douka
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Pablo Vidal-Ribas
- Social and Behavioral Science Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | | | - Christopher C Camp
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Lisa S Gorham
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Christine Wei
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Stuart Kirwan
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Charles Y Zheng
- Machine Learning Team, Functional Magnetic Resonance Imaging Facility, National Institutes of Health, Bethesda, Maryland
| | - Argyris Stringaris
- Section on Clinical and Computational Psychiatry (CompΨ), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland.
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8
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Bauermeister C, Keren H, Braun J. Unstructured network topology begets order-based representation by privileged neurons. Biol Cybern 2020; 114:113-135. [PMID: 32107622 PMCID: PMC7062672 DOI: 10.1007/s00422-020-00819-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Accepted: 02/01/2020] [Indexed: 06/10/2023]
Abstract
How spiking activity reverberates through neuronal networks, how evoked and spontaneous activity interacts and blends, and how the combined activities represent external stimulation are pivotal questions in neuroscience. We simulated minimal models of unstructured spiking networks in silico, asking whether and how gentle external stimulation might be subsequently reflected in spontaneous activity fluctuations. Consistent with earlier findings in silico and in vitro, we observe a privileged subpopulation of 'pioneer neurons' that, by their firing order, reliably encode previous external stimulation. We also confirm that pioneer neurons are 'sensitive' in that they are recruited by small fluctuations of population activity. We show that order-based representations rely on a 'chain' of pioneer neurons with different degrees of sensitivity and thus constitute an emergent property of collective dynamics. The forming of such representations is greatly favoured by a broadly heterogeneous connection topology-a broad 'middle class' in degree of connectedness. In conclusion, we offer a minimal model for the representational role of pioneer neurons, as observed experimentally in vitro. In addition, we show that broadly heterogeneous connectivity enhances the representational capacity of unstructured networks.
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Affiliation(s)
- Christoph Bauermeister
- Institute of Biology, Otto-von-Guericke University, Leipziger Str. 44, Haus 91, 39120, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Hanna Keren
- Network Biology Research Laboratory, Electrical Engineering, Technion-Israel Institute of Technology, 3200003, Haifa, Israel
| | - Jochen Braun
- Institute of Biology, Otto-von-Guericke University, Leipziger Str. 44, Haus 91, 39120, Magdeburg, Germany.
- Center for Behavioral Brain Sciences, Leipziger Str. 44, 39120, Magdeburg, Germany.
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9
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Vidal-Ribas P, Benson B, Vitale AD, Keren H, Harrewijn A, Fox NA, Pine DS, Stringaris A. Bidirectional Associations Between Stress and Reward Processing in Children and Adolescents: A Longitudinal Neuroimaging Study. Biol Psychiatry Cogn Neurosci Neuroimaging 2019; 4:893-901. [PMID: 31324591 DOI: 10.1016/j.bpsc.2019.05.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 05/01/2019] [Accepted: 05/21/2019] [Indexed: 01/22/2023]
Abstract
BACKGROUND Aberrations in both neural reward processing and stress reactivity are associated with increased risk for mental illness; yet, how these two factors relate to each other remains unclear. Several studies suggest that stress exposure impacts reward function, thus increasing risk for psychopathology. However, the alternative hypothesis, in which reward dysfunction impacts stress reactivity, has been rarely examined. The current study aimed to test both hypotheses using a longitudinal design. METHODS Participants were 38 children (23 girls; 61%) from a prospective cohort study. A standard stress-exposure measure was collected at 7 years of age. Children performed a well-validated imaging reward paradigm at age 10, and a standardized acute psychological stress laboratory protocol was administered both at age 10 and at age 13. Structural equation modeling was used to examine bidirectional associations between stress and neural response to reward anticipation. RESULTS Higher exposure to stressful life events at age 7 predicted lower neural response to reward anticipation in regions of the basal ganglia at age 10, which included ventral caudate, nucleus accumbens, putamen, and globus pallidus. Lower response to reward anticipation in medial prefrontal and anterior cingulate cortex predicted higher stress reactivity at age 13. CONCLUSIONS Our findings provide support for bidirectional associations between stress and reward processing, in that stress may impact reward anticipation, but also in that reduced reward anticipation may increase susceptibility to stress.
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Affiliation(s)
- Pablo Vidal-Ribas
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
| | - Brenda Benson
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Aria D Vitale
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Hanna Keren
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Anita Harrewijn
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Nathan A Fox
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland
| | - Daniel S Pine
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Argyris Stringaris
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
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10
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Wolke SA, Mehta MA, O'Daly O, Zelaya F, Zahreddine N, Keren H, O'Callaghan G, Young AH, Leibenluft E, Pine DS, Stringaris A. Modulation of anterior cingulate cortex reward and penalty signalling in medication-naive young-adult subjects with depressive symptoms following acute dose lurasidone. Psychol Med 2019; 49:1365-1377. [PMID: 30606271 PMCID: PMC6518385 DOI: 10.1017/s0033291718003306] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Revised: 10/08/2018] [Accepted: 10/12/2018] [Indexed: 12/16/2022]
Abstract
BACKGROUND Aberrations in reward and penalty processing are implicated in depression and putatively reflect altered dopamine signalling. This study exploits the advantages of a placebo-controlled design to examine how a novel D2 antagonist with adjunctive antidepressant properties modifies activity in the brain's reward network in depression. METHODS We recruited 43 medication-naïve subjects across the range of depression severity (Beck's Depression Inventory-II score range: 0-43), including healthy volunteers, as well as people meeting full-criteria for major depressive disorder. In a double-blind placebo-controlled cross-over design, all subjects received either placebo or lurasidone (20 mg) across two visits separated by 1 week. Functional magnetic resonance imaging with the Monetary Incentive Delay (MID) task assessed reward functions via neural responses during anticipation and receipt of gains and losses. Arterial spin labelling measured cerebral blood flow (CBF) at rest. RESULTS Lurasidone altered fronto-striatal activity during anticipation and outcome phases of the MID task. A significant three-way Medication-by-Depression severity-by-Outcome interaction emerged in the anterior cingulate cortex (ACC) after correction for multiple comparisons. Follow-up analyses revealed significantly higher ACC activation to losses in high- v. low depression participants in the placebo condition, with a normalisation by lurasidone. This effect could not be accounted for by shifts in resting CBF. CONCLUSIONS Lurasidone acutely normalises reward processing signals in individuals with depressive symptoms. Lurasidone's antidepressant effects may arise from reducing responses to penalty outcomes in individuals with depressive symptoms.
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Affiliation(s)
- Selina A. Wolke
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, USA
| | - Mitul A. Mehta
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Nada Zahreddine
- Department of Psychiatry, Saint-Joseph University, Beirut, Lebanon
| | - Hanna Keren
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, USA
| | - Georgia O'Callaghan
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, USA
| | - Allan H. Young
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Ellen Leibenluft
- Section on Mood Dysregulation and Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, USA
| | - Daniel S. Pine
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, MD, USA
| | - Argyris Stringaris
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, USA
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11
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Keren H, Partzsch J, Marom S, Mayr CG. A Biohybrid Setup for Coupling Biological and Neuromorphic Neural Networks. Front Neurosci 2019; 13:432. [PMID: 31133779 PMCID: PMC6517490 DOI: 10.3389/fnins.2019.00432] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 04/15/2019] [Indexed: 12/30/2022] Open
Abstract
Developing technologies for coupling neural activity and artificial neural components, is key for advancing neural interfaces and neuroprosthetics. We present a biohybrid experimental setting, where the activity of a biological neural network is coupled to a biomimetic hardware network. The implementation of the hardware network (denoted NeuroSoC) exhibits complex dynamics with a multiplicity of time-scales, emulating 2880 neurons and 12.7 M synapses, designed on a VLSI chip. This network is coupled to a neural network in vitro, where the activities of both the biological and the hardware networks can be recorded, processed, and integrated bidirectionally in real-time. This experimental setup enables an adjustable and well-monitored coupling, while providing access to key functional features of neural networks. We demonstrate the feasibility to functionally couple the two networks and to implement control circuits to modify the biohybrid activity. Overall, we provide an experimental model for neuromorphic-neural interfaces, hopefully to advance the capability to interface with neural activity, and with its irregularities in pathology.
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Affiliation(s)
- Hanna Keren
- Department of Physiology, Biophysics and Systems Biology, Ruth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.,Network Biology Research Laboratory, Faculty of Electrical Engineering, Technion - Israel Institute of Technology, Haifa, Israel.,Institute of Circuits and Systems, Faculty of Electrical and Computer Engineering, School of Engineering Sciences, Dresden University of Technology, Dresden, Germany
| | - Johannes Partzsch
- Institute of Circuits and Systems, Faculty of Electrical and Computer Engineering, School of Engineering Sciences, Dresden University of Technology, Dresden, Germany
| | - Shimon Marom
- Department of Physiology, Biophysics and Systems Biology, Ruth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.,Network Biology Research Laboratory, Faculty of Electrical Engineering, Technion - Israel Institute of Technology, Haifa, Israel
| | - Christian G Mayr
- Institute of Circuits and Systems, Faculty of Electrical and Computer Engineering, School of Engineering Sciences, Dresden University of Technology, Dresden, Germany
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Keren H, O’Callaghan G, Vidal-Ribas P, Buzzell GA, Brotman MA, Leibenluft E, Pan PM, Meffert L, Kaiser A, Wolke S, Pine DS, Stringaris A. Reward Processing in Depression: A Conceptual and Meta-Analytic Review Across fMRI and EEG Studies. Am J Psychiatry 2018; 175:1111-1120. [PMID: 29921146 PMCID: PMC6345602 DOI: 10.1176/appi.ajp.2018.17101124] [Citation(s) in RCA: 268] [Impact Index Per Article: 44.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
OBJECTIVE A role for aberrant reward processing in the pathogenesis of depression has long been proposed. However, no review has yet examined its role in depression by integrating conceptual and quantitative findings across functional MRI (fMRI) and EEG methodologies. The authors quantified these effects, with an emphasis on development. METHOD A total of 38 fMRI and 12 EEG studies were entered into fMRI and EEG meta-analyses. fMRI studies primarily examined reward anticipation and reward feedback. These were analyzed using the activation likelihood estimation method. EEG studies involved mainly the feedback-related negativity (FRN) event-related potential, and these studies were analyzed using random-effects meta-analysis of the association between FRN and depression. RESULTS Analysis of fMRI studies revealed significantly reduced striatal activation in depressed compared with healthy individuals during reward feedback. When region-of-interest analyses were included, reduced activation was also observed in reward anticipation, an effect that was stronger in individuals under age 18. FRN was also significantly reduced in depression, with pronounced effects in individuals under age 18. In longitudinal studies, reduced striatal activation in fMRI and blunted FRN in EEG were found to precede the onset of depression in adolescents. CONCLUSIONS Taken together, the findings show consistent neural aberrations during reward processing in depression, namely, reduced striatal signal during feedback and blunted FRN. These aberrations may underlie the pathogenesis of depression and have important implications for development of new treatments.
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Affiliation(s)
- Hanna Keren
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Georgia O’Callaghan
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Pablo Vidal-Ribas
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - George A. Buzzell
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Melissa A. Brotman
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Ellen Leibenluft
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Pedro M. Pan
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Liana Meffert
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Ariela Kaiser
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Selina Wolke
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Daniel S. Pine
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
| | - Argyris Stringaris
- From the Mood, Brain, and Development Unit, the Section on Mood Dysregulation and Neuroscience, and the Section on Development and Affective Neuroscience, Emotion and Development Branch, NIMH, Bethesda, Md.; the Department of Human Development and Quantitative Methodology, University of Maryland, College Park; the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; and the Department of Child and Adolescent Psychiatry,
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Keren H, Chen G, Benson B, Ernst M, Leibenluft E, Fox NA, Pine DS, Stringaris A. Is the encoding of Reward Prediction Error reliable during development? Neuroimage 2018; 178:266-276. [PMID: 29777827 PMCID: PMC7518449 DOI: 10.1016/j.neuroimage.2018.05.039] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 04/22/2018] [Accepted: 05/15/2018] [Indexed: 11/23/2022] Open
Abstract
Reward Prediction Errors (RPEs), defined as the difference between the expected and received outcomes, are integral to reinforcement learning models and play an important role in development and psychopathology. In humans, RPE encoding can be estimated using fMRI recordings, however, a basic measurement property of RPE signals, their test-retest reliability across different time scales, remains an open question. In this paper, we examine the 3-month and 3-year reliability of RPE encoding in youth (mean age at baseline = 10.6 ± 0.3 years), a period of developmental transitions in reward processing. We show that RPE encoding is differentially distributed between the positive values being encoded predominantly in the striatum and negative RPEs primarily encoded in the insula. The encoding of negative RPE values is highly reliable in the right insula, across both the long and the short time intervals. Insula reliability for RPE encoding is the most robust finding, while other regions, such as the striatum, are less consistent. Striatal reliability appeared significant as well once covarying for factors, which were possibly confounding the signal to noise ratio. By contrast, task activation during feedback in the striatum is highly reliable across both time intervals. These results demonstrate the valence-dependent differential encoding of RPE signals between the insula and striatum, and the consistency of RPE signals or lack thereof, during childhood and into adolescence. Characterizing the regions where the RPE signal in BOLD fMRI is a reliable marker is key for estimating reward-processing alterations in longitudinal designs, such as developmental or treatment studies.
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Affiliation(s)
- Hanna Keren
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000, Rockville Pike, Bethesda, MD, USA.
| | - Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, 9000, Rockville Pike, Bethesda, MD, USA
| | - Brenda Benson
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000, Rockville Pike, Bethesda, MD, USA
| | - Monique Ernst
- Section on the Neurobiology of Fear and Anxiety, National Institute of Mental Health, National Institutes of Health, 9000, Rockville Pike, Bethesda, MD, USA
| | - Ellen Leibenluft
- Section on Mood Dysregulation and Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000, Rockville Pike, Bethesda, MD, USA
| | - Nathan A Fox
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, 9000, Rockville Pike, Bethesda, MD, USA
| | - Daniel S Pine
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000, Rockville Pike, Bethesda, MD, USA
| | - Argyris Stringaris
- Mood Brain and Development Unit, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, 9000, Rockville Pike, Bethesda, MD, USA
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Rubchinsky LL, Ahn S, Klijn W, Cumming B, Yates S, Karakasis V, Peyser A, Woodman M, Diaz-Pier S, Deraeve J, Vassena E, Alexander W, Beeman D, Kudela P, Boatman-Reich D, Anderson WS, Luque NR, Naveros F, Carrillo RR, Ros E, Arleo A, Huth J, Ichinose K, Park J, Kawai Y, Suzuki J, Mori H, Asada M, Oprisan SA, Dave AI, Babaie T, Robinson P, Tabas A, Andermann M, Rupp A, Balaguer-Ballester E, Lindén H, Christensen RK, Nakamura M, Barkat TR, Tosi Z, Beggs J, Lonardoni D, Boi F, Di Marco S, Maccione A, Berdondini L, Jędrzejewska-Szmek J, Dorman DB, Blackwell KT, Bauermeister C, Keren H, Braun J, Dornas JV, Mavritsaki E, Aldrovandi S, Bridger E, Lim S, Brunel N, Buchin A, Kerr CC, Chizhov A, Huberfeld G, Miles R, Gutkin B, Spencer MJ, Meffin H, Grayden DB, Burkitt AN, Davey CE, Tao L, Tiruvadi V, Ali R, Mayberg H, Butera R, Gunay C, Lamb D, Calabrese RL, Doloc-Mihu A, López-Madrona VJ, Matias FS, Pereda E, Mirasso CR, Canals S, Geminiani A, Pedrocchi A, D’Angelo E, Casellato C, Chauhan A, Soman K, Srinivasa Chakravarthy V, Muddapu VR, Chuang CC, Chen NY, Bayati M, Melchior J, Wiskott L, Azizi AH, Diba K, Cheng S, Smirnova EY, Yakimova EG, Chizhov AV, Chen NY, Shih CT, Florescu D, Coca D, Courtiol J, Jirsa VK, Covolan RJM, Teleńczuk B, Kempter R, Curio G, Destexhe A, Parker J, Klishko AN, Prilutsky BI, Cymbalyuk G, Franke F, Hierlemann A, da Silveira RA, Casali S, Masoli S, Rizza M, Rizza MF, Masoli S, Sun Y, Wong W, Farzan F, Blumberger DM, Daskalakis ZJ, Popovych S, Viswanathan S, Rosjat N, Grefkes C, Daun S, Gentiletti D, Suffczynski P, Gnatkovski V, De Curtis M, Lee H, Paik SB, Choi W, Jang J, Park Y, Song JH, Song M, Pallarés V, Gilson M, Kühn S, Insabato A, Deco G, Glomb K, Ponce-Alvarez A, Ritter P, Gilson M, Campo AT, Thiele A, Deeba F, Robinson PA, van Albada SJ, Rowley A, Hopkins M, Schmidt M, Stokes AB, Lester DR, Furber S, Diesmann M, Barri A, Wiechert MT, DiGregorio DA, Dimitrov AG, Vich C, Berg RW, Guillamon A, Ditlevsen S, Cazé RD, Girard B, Doncieux S, Doyon N, Boahen F, Desrosiers P, Laurence E, Doyon N, Dubé LJ, Eleonora R, Durstewitz D, Schmidt D, Mäki-Marttunen T, Krull F, Bettella F, Metzner C, Devor A, Djurovic S, Dale AM, Andreassen OA, Einevoll GT, Næss S, Ness TV, Halnes G, Halgren E, Halnes G, Mäki-Marttunen T, Pettersen KH, Andreassen OA, Sætra MJ, Hagen E, Schiffer A, Grzymisch A, Persike M, Ernst U, Harnack D, Ernst UA, Tomen N, Zucca S, Pasquale V, Pica G, Molano-Mazón M, Chiappalone M, Panzeri S, Fellin T, Oie KS, Boothe DL, Crone JC, Yu AB, Felton MA, Zulfiqar I, Moerel M, De Weerd P, Formisano E, Boothe DL, Crone JC, Felton MA, Oie K, Franaszczuk P, Diggelmann R, Fiscella M, Hierlemann A, Franke F, Guarino D, Antolík J, Davison AP, Frègnac Y, Etienne BX, Frohlich F, Lefebvre J, Marcos E, Mattia M, Genovesio A, Fedorov LA, Dijkstra TM, Sting L, Hock H, Giese MA, Buhry L, Langlet C, Giovannini F, Verbist C, Salvadé S, Giugliano M, Henderson JA, Wernecke H, Sándor B, Gros C, Voges N, Dabrovska P, Riehle A, Brochier T, Grün S, Gu Y, Gong P, Dumont G, Novikov NA, Gutkin BS, Tewatia P, Eriksson O, Kramer A, Santos J, Jauhiainen A, Kotaleski JH, Belić JJ, Kumar A, Kotaleski JH, Shimono M, Hatano N, Ahmad S, Cui Y, Hawkins J, Senk J, Korvasová K, Tetzlaff T, Helias M, Kühn T, Denker M, Mana P, Grün S, Dahmen D, Schuecker J, Goedeke S, Keup C, Goedeke S, Heuer K, Bakker R, Tiesinga P, Toro R, Qin W, Hadjinicolaou A, Grayden DB, Ibbotson MR, Kameneva T, Lytton WW, Mulugeta L, Drach A, Myers JG, Horner M, Vadigepalli R, Morrison T, Walton M, Steele M, Anthony Hunt C, Tam N, Amaducci R, Muñiz C, Reyes-Sánchez M, Rodríguez FB, Varona P, Cronin JT, Hennig MH, Iavarone E, Yi J, Shi Y, Zandt BJ, Van Geit W, Rössert C, Markram H, Hill S, O’Reilly C, Iavarone E, Shi Y, Perin R, Lu H, Zandt BJ, Bryson A, Rössert C, Hadrava M, Hlinka J, Hosaka R, Olenik M, Houghton C, Iannella N, Launey T, Kameneva T, Kotsakidis R, Meffin H, Soriano J, Kubo T, Inoue T, Kida H, Yamakawa T, Suzuki M, Ikeda K, Abbasi S, Hudson AE, Heck DH, Jaeger D, Lee J, Abbasi S, Janušonis S, Saggio ML, Spiegler A, Stacey WC, Bernard C, Lillo D, Bernard C, Petkoski S, Spiegler A, Drakesmith M, Jones DK, Zadeh AS, Kambhampati C, Karbowski J, Kaya ZG, Lakretz Y, Treves A, Li LW, Lizier J, Kerr CC, Masquelier T, Kheradpisheh SR, Kim H, Kim CS, Marakshina JA, Vartanov AV, Neklyudova AA, Kozlovskiy SA, Kiselnikov AA, Taniguchi K, Kitano K, Schmitt O, Lessmann F, Schwanke S, Eipert P, Meinhardt J, Beier J, Kadir K, Karnitzki A, Sellner L, Klünker AC, Kuch L, Ruß F, Jenssen J, Wree A, Sanz-Leon P, Knock SA, Chien SC, Maess B, Knösche TR, Cohen CC, Popovic MA, Klooster J, Kole MH, Roberts EA, Kopell NJ, Kepple D, Giaffar H, Rinberg D, Koulakov A, Forlim CG, Klock L, Bächle J, Stoll L, Giemsa P, Fuchs M, Schoofs N, Montag C, Gallinat J, Lee RX, Stephens GJ, Kuhn B, Tauffer L, Isope P, Inoue K, Ohmura Y, Yonekura S, Kuniyoshi Y, Jang HJ, Kwag J, de Kamps M, Lai YM, dos Santos F, Lam KP, Andras P, Imperatore J, Helms J, Tompa T, Lavin A, Inkpen FH, Ashby MC, Lepora NF, Shifman AR, Lewis JE, Zhang Z, Feng Y, Tetzlaff C, Kulvicius T, Li Y, Pena RFO, Bernardi D, Roque AC, Lindner B, Bernardi D, Vellmer S, Saudargiene A, Maninen T, Havela R, Linne ML, Powanwe A, Longtin A, Naveros F, Garrido JA, Graham JW, Dura-Bernal S, Angulo SL, Neymotin SA, Antic SD. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2. BMC Neurosci 2017. [PMCID: PMC5592442 DOI: 10.1186/s12868-017-0371-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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Affiliation(s)
- Ophir Orenstein
- Network Biology Research Laboratory, Electrical Engineering, Technion - Israel Institute of TechnologyHaifa, Israel; Department of Physiology, Biophysics and Systems Biology, Technion - Israel Institute of TechnologyHaifa, Israel
| | - Hanna Keren
- Network Biology Research Laboratory, Electrical Engineering, Technion - Israel Institute of TechnologyHaifa, Israel; Department of Physiology, Biophysics and Systems Biology, Technion - Israel Institute of TechnologyHaifa, Israel
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Abstract
In recent years much effort is invested in means to control neural population responses at the whole brain level, within the context of developing advanced medical applications. The tradeoffs and constraints involved, however, remain elusive due to obvious complications entailed by studying whole brain dynamics. Here, we present effective control of response features (probability and latency) of cortical networks in vitro over many hours, and offer this approach as an experimental toy for studying controllability of neural networks in the wider context. Exercising this approach we show that enforcement of stable high activity rates by means of closed loop control may enhance alteration of underlying global input-output relations and activity dependent dispersion of neuronal pair-wise correlations across the network.
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Affiliation(s)
- Hanna Keren
- Network Biology Research Laboratory, Faculty of Electrical Engineering, Technion - Israel Institute of Technology Haifa, Israel ; Department of Physiology, Faculty of Medicine, Technion - Israel Institute of Technology Haifa, Israel
| | - Shimon Marom
- Network Biology Research Laboratory, Faculty of Electrical Engineering, Technion - Israel Institute of Technology Haifa, Israel ; Department of Physiology, Faculty of Medicine, Technion - Israel Institute of Technology Haifa, Israel
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Huining L, Jingting C, Keren H. Metastasis gene expression analyses of choriocarcinoma and the effect of silencing metastasis-associated genes on metastatic ability of choriocarcinoma cells. EUR J GYNAECOL ONCOL 2011; 32:264-268. [PMID: 21797113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
OBJECTIVE Obtaining choriocarcinoma metastasis-associated genes and identifying the role and mechanism of VEGF-B in the progression of human choriocarcinoma. STUDY DESIGN (1) cDNA microarray technique was used to compare the transcriptional profiles between highly metastatic JEG-3 cells and lowly metastatic JAR cells; (2) An inhibitory effect of VEGF-B shRNA was demonstrated by RT-PCR; (3) The effect of VEGF-B shRNA on invasion of JEG-3 cells in vitro was detected by Matrigel invasion assay. RESULTS (1) In upregulated genes, 51 genes were correlated with the cell metastasis ability, and FN, MMP-2, uPA, CAV-1 and VEGF-B were the first five genes; (2) Afterwards transfected VEGF-B shRNA, VEGF-B mRNA expression decreased obviously; (3) VEGF-B shRNA transfection significantly downregulated invasion level of JEG-3 cells in vitro (p < 0.05). CONCLUSION VEGF-B plays an important role in the metastatic capability of human choriocarcinoma. Reducing the expression of VEGF-B can help weaken the invasion ability of human choriocarcinoma.
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Affiliation(s)
- L Huining
- Department of Obstetrics and Gynecology, Xiangya Hospital, Central South University, Changsha, Hunan, China
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Abstract
OBJECTIVE To determine whether in addition to repetitiveness, the motor rituals of patients with obsessive-compulsive disorder (OCD) involve reduced functionality due to numerous and measurable acts that are irrelevant and unnecessary for task completion. METHOD Comparing motor rituals of OCD patients with behavior of non-patient control individuals who were instructed to perform the same motor task. RESULTS Obsessive-compulsive disorder behavior comprises abundant acts that were not performed by the controls. These acts seem unnecessary or even irrelevant for the task that the patients were performing, and therefore are termed 'non-functional'. Non-functional acts comprise some 60% of OCD motor behavior. Moreover, OCD behavior consists of short chains of functional acts bounded by long chains of non-functional acts. CONCLUSION The abundance of irrelevant or unnecessary acts in OCD motor rituals represents reduced functionality in terms of task completion, typifying OCD rituals as pessimal behavior (antonym of optimal behavior).
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Affiliation(s)
- R Zor
- Department of Zoology, Tel-Aviv University, Ramat-Aviv, Israel
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Bekefi G, Avivi P, Dothan‐Deutsch F, Friedland L, Hirshfield JL, Keren H. Light emission from an argon discharge containing an admixture of carbon monoxide. J Chem Phys 1974. [DOI: 10.1063/1.1681603] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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