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Sugawara SK, Nishimura Y. The Mesocortical System Encodes the Strength of Subsequent Force Generation. Neurosci Insights 2024; 19:26331055241256948. [PMID: 38827248 PMCID: PMC11141215 DOI: 10.1177/26331055241256948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Accepted: 05/08/2024] [Indexed: 06/04/2024] Open
Abstract
Our minds impact motor outputs. Such mind-motor interactions are critical for understanding motor control mechanisms and optimizing motor performance. In particular, incentive motivation strongly enhances motor performance. Dopaminergic neurons located in the ventral midbrain (VM) are believed to be the center of incentive motivation. Direct projections from the VM to the primary motor cortex constitute a mesocortical pathway. However, the functional role of this pathway in humans remains unclear. Recently, we demonstrated the functional role of the mesocortical pathway in human motor control in the context of incentive motivation by using functional magnetic resonance imaging (fMRI). Incentive motivation remarkably improved not only reaction times but also the peak grip force in subsequent grip responses. Although the reaction time has been used as a proxy for incentive motivation mediated by dopaminergic midbrain activity, the premovement activity of the mesocortical pathway is involved in controlling the force strength rather than the initiation of subsequent force generation. In this commentary, we review our recent findings and discuss remaining questions regarding the functional role of the mesocortical pathway in mind-motor interactions.
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Affiliation(s)
- Sho K Sugawara
- Neural Prosthetics Project, Tokyo Metropolitan Institute of Medical Science, Setagaya, Tokyo, Japan
| | - Yukio Nishimura
- Neural Prosthetics Project, Tokyo Metropolitan Institute of Medical Science, Setagaya, Tokyo, Japan
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2
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Tahmazian I, Watts A, Chen O, Ferrara HJ, McCrimmon A, Hu B, Chomiak T. A wearable device-enabled therapeutic approach to improve joint attention in autism spectrum disorder: a prospective pilot study. J Neural Transm (Vienna) 2023; 130:1601-1607. [PMID: 37648903 DOI: 10.1007/s00702-023-02683-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 08/06/2023] [Indexed: 09/01/2023]
Abstract
It has been previously proposed that interventions aimed at integrating and co-activating music processing and motor control systems could have therapeutic potential for priming social skill development in children with autism spectrum disorder (ASD). In this study, we assessed this hypothesis through a wearable sensor platform called Ambulosono ("Ambulo"-walk; "sono"-sound) in which pleasurable children's musical stimuli are contingently linked to effortful motor action (locomotor step size), thus creating a motivational state proposed to be conducive to joint attention (JA) operation. Five participants were recruited from a community-based partner and were assessed by scoring responses following therapist-directed bids for JA. Multiple assessment sessions through a repeated time-series design were conducted to determine baseline and post-intervention scores. The intervention session consisted of approximately 15 min of Ambulosono exposure. Baseline and post-intervention data were aggregated and analyzed using a linear mixed-effect model. The wearable sensor and wireless headphones of the Ambulosono system were tolerated by the participants, and there were no adverse effects associated with the use of the device. We found an increase in the average responses to bids for JA during the Ambulosono intervention phase compared to baseline across participants. This increase did not appear to result from enhanced general arousal. Our pilot data support feasibility and further testing of Ambulosono as a therapeutic aid for integration into community-based ASD programs to augment shared child-therapist social interactions.
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Affiliation(s)
- Isabelle Tahmazian
- Division of Translational Neuroscience, Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada
| | - Alexander Watts
- Division of Translational Neuroscience, Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada
| | - Oswald Chen
- Division of Translational Neuroscience, Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada
| | - Hannah J Ferrara
- Division of Translational Neuroscience, Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada
| | - Adam McCrimmon
- Werklund School of Education, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N 1N4, Canada
| | - Bin Hu
- Division of Translational Neuroscience, Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada.
- Alberta Children's Hospital Research Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N 1N4, Canada.
| | - Taylor Chomiak
- Division of Translational Neuroscience, Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada.
- Alberta Children's Hospital Research Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N 1N4, Canada.
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3
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Gholston AS, Thurmann KE, Chiew KS. Contributions of transient and sustained reward to memory formation. PSYCHOLOGICAL RESEARCH 2023; 87:2477-2498. [PMID: 37079090 PMCID: PMC10116487 DOI: 10.1007/s00426-023-01829-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 04/10/2023] [Indexed: 04/21/2023]
Abstract
Reward benefits to memory formation have been robustly linked to dopaminergic activity. Despite the established characterization of dopaminergic mechanisms as operating at multiple timescales, potentially supporting distinct functional outcomes, the temporal dynamics by which reward might modulate memory encoding are just beginning to be investigated. In the present study, we leveraged a mixed block/event experimental design to disentangle transient and sustained reward influences on task engagement and subsequent recognition memory in an adapted monetary-incentive-encoding (MIE) paradigm. Across three behavioral experiments, transient and sustained reward modulation of item and context memory was probed, at both 24-h and ~ 15-min retention intervals, to investigate the importance of overnight consolidation. In general, we observed that transient reward was associated with enhanced item memory encoding, while sustained reward modulated response speed but did not appear to benefit subsequent recognition accuracy. Notably, reward effects on item memory performance and response speed were somewhat inconsistent across the three experiments, with suggestions that RT speeding might also be related to time on task, and we did not observe reward modulation of context memory performance or amplification of reward benefits to memory by overnight consolidation. Taken together, the observed pattern of behavior is consistent with potentially distinct roles for transient and sustained reward in memory encoding and cognitive performance and suggests that further investigation of the temporal dynamics of dopaminergic contributions to memory formation will advance the understanding of motivated memory.
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Affiliation(s)
- Avery S Gholston
- Department of Psychology, University of Denver, 2155 South Race Street, Denver, CO, 80208, USA
| | - Kyle E Thurmann
- Department of Psychology, University of Denver, 2155 South Race Street, Denver, CO, 80208, USA
| | - Kimberly S Chiew
- Department of Psychology, University of Denver, 2155 South Race Street, Denver, CO, 80208, USA.
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4
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Pereira AR, Alemi M, Cerqueira-Nunes M, Monteiro C, Galhardo V, Cardoso-Cruz H. Dynamics of Lateral Habenula-Ventral Tegmental Area Microcircuit on Pain-Related Cognitive Dysfunctions. Neurol Int 2023; 15:1303-1319. [PMID: 37987455 PMCID: PMC10660716 DOI: 10.3390/neurolint15040082] [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: 09/19/2023] [Revised: 10/20/2023] [Accepted: 10/25/2023] [Indexed: 11/22/2023] Open
Abstract
Chronic pain is a health problem that affects the ability to work and perform other activities, and it generally worsens over time. Understanding the complex pain interaction with brain circuits could help predict which patients are at risk of developing central dysfunctions. Increasing evidence from preclinical and clinical studies suggests that aberrant activity of the lateral habenula (LHb) is associated with depressive symptoms characterized by excessive negative focus, leading to high-level cognitive dysfunctions. The primary output region of the LHb is the ventral tegmental area (VTA), through a bidirectional connection. Recently, there has been growing interest in the complex interactions between the LHb and VTA, particularly regarding their crucial roles in behavior regulation and their potential involvement in the pathological impact of chronic pain on cognitive functions. In this review, we briefly discuss the structural and functional roles of the LHb-VTA microcircuit and their impact on cognition and mood disorders in order to support future studies addressing brain plasticity during chronic pain conditions.
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Affiliation(s)
- Ana Raquel Pereira
- Instituto de Investigação e Inovação em Saúde—Pain Neurobiology Group, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal; (A.R.P.); (M.A.); (M.C.-N.); (C.M.); (V.G.)
- Instituto de Biologia Molecular e Celular, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal
- Departamento de Biomedicina—Unidade de Biologia Experimental, Faculdade de Medicina, Universidade do Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Mobina Alemi
- Instituto de Investigação e Inovação em Saúde—Pain Neurobiology Group, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal; (A.R.P.); (M.A.); (M.C.-N.); (C.M.); (V.G.)
- Instituto de Biologia Molecular e Celular, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal
- Departamento de Biomedicina—Unidade de Biologia Experimental, Faculdade de Medicina, Universidade do Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Mariana Cerqueira-Nunes
- Instituto de Investigação e Inovação em Saúde—Pain Neurobiology Group, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal; (A.R.P.); (M.A.); (M.C.-N.); (C.M.); (V.G.)
- Instituto de Biologia Molecular e Celular, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal
- Departamento de Biomedicina—Unidade de Biologia Experimental, Faculdade de Medicina, Universidade do Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
- Programa Doutoral em Neurociências, Faculdade de Medicina, Universidade do Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Clara Monteiro
- Instituto de Investigação e Inovação em Saúde—Pain Neurobiology Group, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal; (A.R.P.); (M.A.); (M.C.-N.); (C.M.); (V.G.)
- Instituto de Biologia Molecular e Celular, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal
- Departamento de Biomedicina—Unidade de Biologia Experimental, Faculdade de Medicina, Universidade do Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Vasco Galhardo
- Instituto de Investigação e Inovação em Saúde—Pain Neurobiology Group, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal; (A.R.P.); (M.A.); (M.C.-N.); (C.M.); (V.G.)
- Instituto de Biologia Molecular e Celular, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal
- Departamento de Biomedicina—Unidade de Biologia Experimental, Faculdade de Medicina, Universidade do Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Helder Cardoso-Cruz
- Instituto de Investigação e Inovação em Saúde—Pain Neurobiology Group, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal; (A.R.P.); (M.A.); (M.C.-N.); (C.M.); (V.G.)
- Instituto de Biologia Molecular e Celular, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal
- Departamento de Biomedicina—Unidade de Biologia Experimental, Faculdade de Medicina, Universidade do Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
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Liu X, Tyler LK, Cam-Can, Davis SW, Rowe JB, Tsvetanov KA. Cognition's dependence on functional network integrity with age is conditional on structural network integrity. Neurobiol Aging 2023; 129:195-208. [PMID: 37392579 DOI: 10.1016/j.neurobiolaging.2023.06.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 05/29/2023] [Accepted: 06/02/2023] [Indexed: 07/03/2023]
Abstract
Maintaining good cognitive function is crucial for well-being across the lifespan. We proposed that the degree of cognitive maintenance is determined by the functional interactions within and between large-scale brain networks. Such connectivity can be represented by the white matter architecture of structural brain networks that shape intrinsic neuronal activity into integrated and distributed functional networks. We explored how the function-structure connectivity convergence, and the divergence of functional connectivity from structural connectivity, contribute to the maintenance of cognitive function across the adult lifespan. Multivariate analyses were used to investigate the relationship between function-structure connectivity convergence and divergence with multivariate cognitive profiles, respectively. Cognitive function was increasingly dependent on function-structure connectivity convergence as age increased. The dependency of cognitive function on connectivity was particularly strong for high-order cortical networks and subcortical networks. The results suggest that brain functional network integrity sustains cognitive functions in old age, as a function of the integrity of the brain's structural connectivity.
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Affiliation(s)
- Xulin Liu
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Lorraine K Tyler
- The Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK
| | - Cam-Can
- Cambridge Centre for Ageing and Neuroscience (Cam-CAN), MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Simon W Davis
- Department of Neurology, Duke University, School of Medicine, Durham, NC, USA
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Kamen A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; The Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK
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6
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Singer N, Poker G, Dunsky-Moran N, Nemni S, Reznik Balter S, Doron M, Baker T, Dagher A, Zatorre RJ, Hendler T. Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation. Neuroimage 2023; 276:120183. [PMID: 37225112 PMCID: PMC10300238 DOI: 10.1016/j.neuroimage.2023.120183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 04/06/2023] [Accepted: 05/22/2023] [Indexed: 05/26/2023] Open
Abstract
Reward processing is essential for our mental-health and well-being. In the current study, we developed and validated a scalable, fMRI-informed EEG model for monitoring reward processing related to activation in the ventral-striatum (VS), a significant node in the brain's reward system. To develop this EEG-based model of VS-related activation, we collected simultaneous EEG/fMRI data from 17 healthy individuals while listening to individually-tailored pleasurable music - a highly rewarding stimulus known to engage the VS. Using these cross-modal data, we constructed a generic regression model for predicting the concurrently acquired Blood-Oxygen-Level-Dependent (BOLD) signal from the VS using spectro-temporal features from the EEG signal (termed hereby VS-related-Electrical Finger Print; VS-EFP). The performance of the extracted model was examined using a series of tests that were applied on the original dataset and, importantly, an external validation dataset collected from a different group of 14 healthy individuals who underwent the same EEG/FMRI procedure. Our results showed that the VS-EFP model, as measured by simultaneous EEG, predicted BOLD activation in the VS and additional functionally relevant regions to a greater extent than an EFP model derived from a different anatomical region. The developed VS-EFP was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating its functional relevance. These findings provide compelling evidence for the feasibility of using EEG alone to model neural activation related to the VS, paving the way for future use of this scalable neural probing approach in neural monitoring and self-guided neuromodulation.
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Affiliation(s)
- Neomi Singer
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel; Sagol school of Neuroscience, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel
| | - Gilad Poker
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel
| | - Netta Dunsky-Moran
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel; Sagol school of Neuroscience, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel
| | - Shlomi Nemni
- Sagol school of Neuroscience, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel; School of Psychological Sciences, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel
| | - Shira Reznik Balter
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel
| | - Maayan Doron
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; Sackler School of Medicine, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel
| | - Travis Baker
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada
| | - Robert J Zatorre
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; International Laboratory for Brain, Music, and Sound Research (BRAMS), Canada
| | - Talma Hendler
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel; Sagol school of Neuroscience, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel; School of Psychological Sciences, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel; Sackler School of Medicine, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel.
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Haugg A, Frei N, Menghini M, Stutz F, Steinegger S, Röthlisberger M, Brem S. Self-regulation of visual word form area activation with real-time fMRI neurofeedback. Sci Rep 2023; 13:9195. [PMID: 37280217 DOI: 10.1038/s41598-023-35932-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 05/25/2023] [Indexed: 06/08/2023] Open
Abstract
The Visual Word Form Area (VWFA) is a key region of the brain's reading network and its activation has been shown to be strongly associated with reading skills. Here, for the first time, we investigated whether voluntary regulation of VWFA activation is feasible using real-time fMRI neurofeedback. 40 adults with typical reading skills were instructed to either upregulate (UP group, N = 20) or downregulate (DOWN group, N = 20) their own VWFA activation during six neurofeedback training runs. The VWFA target region was individually defined based on a functional localizer task. Before and after training, also regulation runs without feedback ("no-feedback runs") were performed. When comparing the two groups, we found stronger activation across the reading network for the UP than the DOWN group. Further, activation in the VWFA was significantly stronger in the UP group than the DOWN group. Crucially, we observed a significant interaction of group and time (pre, post) for the no-feedback runs: The two groups did not differ significantly in their VWFA activation before neurofeedback training, but the UP group showed significantly stronger activation than the DOWN group after neurofeedback training. Our results indicate that upregulation of VWFA activation is feasible and that, once learned, successful upregulation can even be performed in the absence of feedback. These results are a crucial first step toward the development of a potential therapeutic support to improve reading skills in individuals with reading impairments.
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Affiliation(s)
- Amelie Haugg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Nada Frei
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Milena Menghini
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Felizia Stutz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Sara Steinegger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Martina Röthlisberger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
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8
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Kahnt T. Computationally Informed Interventions for Targeting Compulsive Behaviors. Biol Psychiatry 2023; 93:729-738. [PMID: 36464521 PMCID: PMC9989040 DOI: 10.1016/j.biopsych.2022.08.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/04/2022] [Accepted: 08/30/2022] [Indexed: 11/02/2022]
Abstract
Compulsive behaviors are central to addiction and obsessive-compulsive disorder and can be understood as a failure of adaptive decision making. Particularly, they can be conceptualized as an imbalance in behavioral control, such that behavior is guided predominantly by learned rather than inferred outcome expectations. Inference is a computational process required for adaptive behavior, and recent work across species has identified the neural circuitry that supports inference-based decision making. This includes the orbitofrontal cortex, which has long been implicated in disorders of compulsive behavior. Inspired by evidence that modulating orbitofrontal cortex activity can alter inference-based behaviors, here we discuss noninvasive approaches to target these circuits in humans. Specifically, we discuss the potential of network-targeted transcranial magnetic stimulation and real-time neurofeedback to modulate the neural underpinnings of inference. Both interventions leverage recent advances in our understanding of the neurocomputational mechanisms of inference-based behavior and may be used to complement current treatment approaches for behavioral disorders.
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Affiliation(s)
- Thorsten Kahnt
- National Institute on Drug Abuse Intramural Research Program, Baltimore, Maryland.
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9
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Testing the efficacy of real-time fMRI neurofeedback for training people who smoke daily to upregulate neural responses to nondrug rewards. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2023; 23:440-456. [PMID: 36788202 DOI: 10.3758/s13415-023-01070-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Accepted: 01/24/2023] [Indexed: 02/16/2023]
Abstract
Although the use of nondrug rewards (e.g., money) to facilitate smoking cessation is widespread, recent research has found that such rewards may be least effective when people who smoke cigarettes are tempted to do so. Specifically, among people who smoke, the neural response to nondrug rewards appears blunted when access to cigarettes is anticipated, and this blunting is linked to a decrease in willingness to refrain from smoking to earn a monetary incentive. Accordingly, methods to enhance the value of nondrug rewards may be theoretically and clinically important. The current proof-of-concept study tested if real-time fMRI neurofeedback training augments the ability to upregulate responses in reward-related brain areas relative to a no-feedback control condition in people who smoke. Adults (n = 44, age range = 20-44) who reported smoking >5 cigarettes per day completed the study. Those in the intervention group (n = 22, 5 females) were trained to upregulate brain responses using feedback of ongoing striatal activity (i.e., a dynamic "thermometer" that reflected ongoing changes of fMRI signal intensity in the striatum) in a single neurofeedback session with three training runs. The control group (n = 22, 5 females) underwent a nearly identical procedure but received no neurofeedback. Those who received neurofeedback training demonstrated significantly greater increases in striatal BOLD activation while attempting to think about something rewarding compared to controls, but this effect was present only during the first training run. Future neurofeedback research with those who smoke should explore how to make neurofeedback training more effective for the self-regulation of reward-related brain activities.
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Pereira DJ, Sayal A, Pereira J, Morais S, Macedo A, Direito B, Castelo-Branco M. Neurofeedback-dependent influence of the ventral striatum using a working memory paradigm targeting the dorsolateral prefrontal cortex. Front Behav Neurosci 2023; 17:1014223. [PMID: 36844653 PMCID: PMC9947361 DOI: 10.3389/fnbeh.2023.1014223] [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: 08/08/2022] [Accepted: 01/18/2023] [Indexed: 02/11/2023] Open
Abstract
Executive functions and motivation have been established as key aspects for neurofeedback success. However, task-specific influence of cognitive strategies is scarcely explored. In this study, we test the ability to modulate the dorsolateral prefrontal cortex, a strong candidate for clinical application of neurofeedback in several disorders with dysexecutive syndrome, and investigate how feedback contributes to better performance in a single session. Participants of both neurofeedback (n = 17) and sham-control (n = 10) groups were able to modulate DLPFC in most runs (with or without feedback) while performing a working memory imagery task. However, activity in the target area was higher and more sustained in the active group when receiving feedback. Furthermore, we found increased activity in the nucleus accumbens in the active group, compared with a predominantly negative response along the block in participants receiving sham feedback. Moreover, they acknowledged the non-contingency between imagery and feedback, reflecting the impact on motivation. This study reinforces DLPFC as a robust target for neurofeedback clinical implementations and enhances the critical influence of the ventral striatum, both poised to achieve success in the self-regulation of brain activity.
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Affiliation(s)
- Daniela Jardim Pereira
- Neurorradiology Functional Area, Imaging Department, Coimbra Hospital and University Center, Coimbra, Portugal,Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Alexandre Sayal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,Siemens Healthineers Portugal, Lisboa, Portugal
| | - João Pereira
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Sofia Morais
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,Psychiatry Department, Coimbra Hospital and University Center, Coimbra, Portugal
| | - António Macedo
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Psychiatry Department, Coimbra Hospital and University Center, Coimbra, Portugal
| | - Bruno Direito
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,IATV—Instituto do Ambiente, Tecnologia e Vida (IATV), Coimbra, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,*Correspondence: Miguel Castelo-Branco
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11
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Neural and functional validation of fMRI-informed EEG model of right inferior frontal gyrus activity. Neuroimage 2023; 266:119822. [PMID: 36535325 DOI: 10.1016/j.neuroimage.2022.119822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 11/17/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022] Open
Abstract
The right inferior frontal gyrus (rIFG) is a region involved in the neural underpinning of cognitive control across several domains such as inhibitory control and attentional allocation process. Therefore, it constitutes a desirable neural target for brain-guided interventions such as neurofeedback (NF). To date, rIFG-NF has shown beneficial ability to rehabilitate or enhance cognitive functions using functional Magnetic Resonance Imaging (fMRI-NF). However, the utilization of fMRI-NF for clinical purposes is severely limited, due to its poor scalability. The present study aimed to overcome the limited applicability of fMRI-NF by developing and validating an EEG model of fMRI-defined rIFG activity (hereby termed "Electrical FingerPrint of rIFG"; rIFG-EFP). To validate the computational model, we employed two experiments in healthy individuals. The first study (n = 14) aimed to test the target engagement of the model by employing rIFG-EFP-NF training while simultaneously acquiring fMRI. The second study (n = 41) aimed to test the functional outcome of two sessions of rIFG-EFP-NF using a risk preference task (known to depict cognitive control processes), employed before and after the training. Results from the first study demonstrated neural target engagement as expected, showing associated rIFG-BOLD signal changing during simultaneous rIFG-EFP-NF training. Target anatomical specificity was verified by showing a more precise prediction of the rIFG-BOLD by the rIFG-EFP model compared to other EFP models. Results of the second study suggested that successful learning to up-regulate the rIFG-EFP signal through NF can reduce one's tendency for risk taking, indicating improved cognitive control after two sessions of rIFG-EFP-NF. Overall, our results confirm the validity of a scalable NF method for targeting rIFG activity by using an EEG probe.
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12
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Collin SHP, van den Broek PLC, van Mourik T, Desain P, Doeller CF. Inducing a mental context for associative memory formation with real-time fMRI neurofeedback. Sci Rep 2022; 12:21226. [PMID: 36481793 PMCID: PMC9731952 DOI: 10.1038/s41598-022-25799-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 12/05/2022] [Indexed: 12/13/2022] Open
Abstract
Memory, one of the hallmarks of human cognition, can be modified when humans voluntarily modulate neural population activity using neurofeedback. However, it is currently unknown whether neurofeedback can influence the integration of memories, and whether memory is facilitated or impaired after such neural perturbation. In this study, participants memorized objects while we provided them with abstract neurofeedback based on their brain activity patterns in the ventral visual stream. This neurofeedback created an implicit face or house context in the brain while memorizing the objects. The results revealed that participants created associations between each memorized object and its implicit context solely due to the neurofeedback manipulation. Our findings shed light onto how memory formation can be influenced by synthetic memory tags with neurofeedback and advance our understanding of mnemonic processing.
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Affiliation(s)
- Silvy H. P. Collin
- grid.12295.3d0000 0001 0943 3265Tilburg School of Humanities and Digital Sciences, Tilburg University, Tilburg, The Netherlands
| | - Philip L. C. van den Broek
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Tim van Mourik
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Peter Desain
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Christian F. Doeller
- grid.419524.f0000 0001 0041 5028Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany ,grid.5947.f0000 0001 1516 2393Kavli Institute for Systems Neuroscience, Centre for Neural Computation, The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer’s Disease, Norwegian University of Science and Technology, Trondheim, Norway ,grid.9647.c0000 0004 7669 9786Institute of Psychology-Wilhelm Wundt, Leipzig University, Leipzig, Germany
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13
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Wang Z, Wong CM, Nan W, Tang Q, Rosa AC, Xu P, Wan F. Learning Curve of a Short-Time Neurofeedback Training: Reflection of Brain Network Dynamics Based on Phase-Locking Value. IEEE Trans Cogn Dev Syst 2022. [DOI: 10.1109/tcds.2021.3125948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Ze Wang
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, Centre for Cognitive and Brain Sciences, and the Centre for Artificial Intelligence and Robotics, Institute of Collaborative Innovation, University of Macau, Macau, China
| | - Chi Man Wong
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, Centre for Cognitive and Brain Sciences, and the Centre for Artificial Intelligence and Robotics, Institute of Collaborative Innovation, University of Macau, Macau, China
| | - Wenya Nan
- Department of Psychology, Shanghai Normal University, Shanghai, China
| | - Qi Tang
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, Centre for Cognitive and Brain Sciences, and the Centre for Artificial Intelligence and Robotics, Institute of Collaborative Innovation, University of Macau, Macau, China
| | - Agostinho C. Rosa
- Department of Bioengineering, LaSEEBSystem and Robotics Institute, Instituto Superior Tecnico, University of Lisbon, Lisbon, Portugal
| | - Peng Xu
- Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, and the School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng Wan
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, Centre for Cognitive and Brain Sciences, and the Centre for Artificial Intelligence and Robotics, Institute of Collaborative Innovation, University of Macau, Macau, China
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14
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Hellrung L, Kirschner M, Sulzer J, Sladky R, Scharnowski F, Herdener M, Tobler PN. Analysis of individual differences in neurofeedback training illuminates successful self-regulation of the dopaminergic midbrain. Commun Biol 2022; 5:845. [PMID: 35986202 PMCID: PMC9391365 DOI: 10.1038/s42003-022-03756-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/21/2022] [Indexed: 11/27/2022] Open
Abstract
The dopaminergic midbrain is associated with reinforcement learning, motivation and decision-making - functions often disturbed in neuropsychiatric disorders. Previous research has shown that dopaminergic midbrain activity can be endogenously modulated via neurofeedback. However, the robustness of endogenous modulation, a requirement for clinical translation, is unclear. Here, we examine whether the activation of particular brain regions associates with successful regulation transfer when feedback is no longer available. Moreover, to elucidate mechanisms underlying effective self-regulation, we study the relation of successful transfer with learning (temporal difference coding) outside the midbrain during neurofeedback training and with individual reward sensitivity in a monetary incentive delay (MID) task. Fifty-nine participants underwent neurofeedback training either in standard (Study 1 N = 15, Study 2 N = 28) or control feedback group (Study 1, N = 16). We find that successful self-regulation is associated with prefrontal reward sensitivity in the MID task (N = 25), with a decreasing relation between prefrontal activity and midbrain learning signals during neurofeedback training and with increased activity within cognitive control areas during transfer. The association between midbrain self-regulation and prefrontal temporal difference and reward sensitivity suggests that reinforcement learning contributes to successful self-regulation. Our findings provide insights in the control of midbrain activity and may facilitate individually tailoring neurofeedback training.
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Affiliation(s)
- Lydia Hellrung
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland.
| | - Matthias Kirschner
- Department of Psychiatric, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Zurich, Switzerland
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | - James Sulzer
- Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Ronald Sladky
- Department of Psychiatric, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Zurich, Switzerland
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Frank Scharnowski
- Department of Psychiatric, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Zurich, Switzerland
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Marcus Herdener
- Center for Addictive Disorders, Psychiatric University Hospital, University of Zurich, Zurich, Switzerland
| | - Philippe N Tobler
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
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15
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Wallace G, Polcyn S, Brooks PP, Mennen AC, Zhao K, Scotti PS, Michelmann S, Li K, Turk-Browne NB, Cohen JD, Norman KA. RT-Cloud: A cloud-based software framework to simplify and standardize real-time fMRI. Neuroimage 2022; 257:119295. [PMID: 35580808 PMCID: PMC9494277 DOI: 10.1016/j.neuroimage.2022.119295] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 05/09/2022] [Indexed: 11/21/2022] Open
Abstract
Real-time fMRI (RT-fMRI) neurofeedback has been shown to be effective in treating neuropsychiatric disorders and holds tremendous promise for future breakthroughs, both with regard to basic science and clinical applications. However, the prevalence of its use has been hampered by computing hardware requirements, the complexity of setting up and running an experiment, and a lack of standards that would foster collaboration. To address these issues, we have developed RT-Cloud (https://github.com/brainiak/rt-cloud), a flexible, cloud-based, open-source Python software package for the execution of RT-fMRI experiments. RT-Cloud uses standardized data formats and adaptable processing streams to support and expand open science in RT-fMRI research and applications. Cloud computing is a key enabling technology for advancing RT-fMRI because it eliminates the need for on-premise technical expertise and high-performance computing; this allows installation, configuration, and maintenance to be automated and done remotely. Furthermore, the scalability of cloud computing makes it easier to deploy computationally-demanding multivariate analyses in real time. In this paper, we describe how RT-Cloud has been integrated with open standards, including the Brain Imaging Data Structure (BIDS) standard and the OpenNeuro database, how it has been applied thus far, and our plans for further development and deployment of RT-Cloud in the coming years.
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Affiliation(s)
- Grant Wallace
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
| | - Stephen Polcyn
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
| | - Paula P Brooks
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
| | - Anne C Mennen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
| | - Ke Zhao
- Cognitive Science Program, University of Pennsylvania, Philadelphia, PA, United States
| | - Paul S Scotti
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
| | - Sebastian Michelmann
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
| | - Kai Li
- Department of Computer Science, Princeton University, Princeton, NJ, United States
| | | | - Jonathan D Cohen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States; Department of Psychology, Princeton University, Princeton, NJ, United States
| | - Kenneth A Norman
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States; Department of Psychology, Princeton University, Princeton, NJ, United States.
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16
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Siddiqi SH, Kording KP, Parvizi J, Fox MD. Causal mapping of human brain function. Nat Rev Neurosci 2022; 23:361-375. [PMID: 35444305 PMCID: PMC9387758 DOI: 10.1038/s41583-022-00583-8] [Citation(s) in RCA: 108] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2022] [Indexed: 12/11/2022]
Abstract
Mapping human brain function is a long-standing goal of neuroscience that promises to inform the development of new treatments for brain disorders. Early maps of human brain function were based on locations of brain damage or brain stimulation that caused a functional change. Over time, this approach was largely replaced by technologies such as functional neuroimaging, which identify brain regions in which activity is correlated with behaviours or symptoms. Despite their advantages, these technologies reveal correlations, not causation. This creates challenges for interpreting the data generated from these tools and using them to develop treatments for brain disorders. A return to causal mapping of human brain function based on brain lesions and brain stimulation is underway. New approaches can combine these causal sources of information with modern neuroimaging and electrophysiology techniques to gain new insights into the functions of specific brain areas. In this Review, we provide a definition of causality for translational research, propose a continuum along which to assess the relative strength of causal information from human brain mapping studies and discuss recent advances in causal brain mapping and their relevance for developing treatments.
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Affiliation(s)
- Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Konrad P Kording
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Josef Parvizi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
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17
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Lubianiker N, Paret C, Dayan P, Hendler T. Neurofeedback through the lens of reinforcement learning. Trends Neurosci 2022; 45:579-593. [PMID: 35550813 DOI: 10.1016/j.tins.2022.03.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/11/2022] [Accepted: 03/24/2022] [Indexed: 11/29/2022]
Abstract
Despite decades of experimental and clinical practice, the neuropsychological mechanisms underlying neurofeedback (NF) training remain obscure. NF is a unique form of reinforcement learning (RL) task, during which participants are provided with rewarding feedback regarding desired changes in neural patterns. However, key RL considerations - including choices during practice, prediction errors, credit-assignment problems, or the exploration-exploitation tradeoff - have infrequently been considered in the context of NF. We offer an RL-based framework for NF, describing different internal states, actions, and rewards in common NF protocols, thus fashioning new proposals for characterizing, predicting, and hastening the course of learning. In this way we hope to advance current understanding of neural regulation via NF, and ultimately to promote its effectiveness, personalization, and clinical utility.
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Affiliation(s)
- Nitzan Lubianiker
- School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
| | - Christian Paret
- School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Peter Dayan
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany; University of Tübingen, Tübingen, Germany
| | - Talma Hendler
- School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Sagol school of Neuroscience, Tel Aviv University, Tel Aviv, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
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18
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Guardia T, Geerligs L, Tsvetanov KA, Ye R, Campbell KL. The role of the arousal system in age-related differences in cortical functional network architecture. Hum Brain Mapp 2022; 43:985-997. [PMID: 34713955 PMCID: PMC8764482 DOI: 10.1002/hbm.25701] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 10/04/2021] [Accepted: 10/17/2021] [Indexed: 01/10/2023] Open
Abstract
A common finding in the aging literature is that of the brain's decreased within- and increased between-network functional connectivity. However, it remains unclear what is causing this shift in network organization with age. Given the essential role of the ascending arousal system (ARAS) in cortical activation and previous findings of disrupted ARAS functioning with age, it is possible that age differences in ARAS functioning contribute to disrupted cortical connectivity. We test this possibility here using resting state fMRI data from over 500 individuals across the lifespan from the Cambridge Center for Aging and Neuroscience (Cam-CAN) population-based cohort. Our results show that ARAS-cortical connectivity declines with age and, consistent with our expectations, significantly mediates some age-related differences in connectivity within and between association networks (specifically, within the default mode and between the default mode and salience networks). Additionally, connectivity between the ARAS and association networks predicted cognitive performance across several tasks over and above the effects of age and connectivity within the cortical networks themselves. These findings suggest that age differences in cortical connectivity may be driven, at least in part, by altered arousal signals from the brainstem and that ARAS-cortical connectivity relates to cognitive performance with age.
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Affiliation(s)
- Tiago Guardia
- Department of PsychologyBrock UniversitySt. CatharinesOntarioCanada
| | - Linda Geerligs
- Donders Institute for Brain, Cognition, and BehaviourRadboud UniversityNijmegenThe Netherlands
| | | | - Rong Ye
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
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19
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Taschereau-Dumouchel V, Cushing C, Lau H. Real-Time Functional MRI in the Treatment of Mental Health Disorders. Annu Rev Clin Psychol 2022; 18:125-154. [DOI: 10.1146/annurev-clinpsy-072220-014550] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Multiple mental disorders have been associated with dysregulation of precise brain processes. However, few therapeutic approaches can correct such specific patterns of brain activity. Since the late 1960s and early 1970s, many researchers have hoped that this feat could be achieved by closed-loop brain imaging approaches, such as neurofeedback, that aim to modulate brain activity directly. However, neurofeedback never gained mainstream acceptance in mental health, in part due to methodological considerations. In this review, we argue that, when contemporary methodological guidelines are followed, neurofeedback is one of the few intervention methods in psychology that can be assessed in double-blind placebo-controlled trials. Furthermore, using new advances in machine learning and statistics, it is now possible to target very precise patterns of brain activity for therapeutic purposes. We review the recent literature in functional magnetic resonance imaging neurofeedback and discuss current and future applications to mental health. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Vincent Taschereau-Dumouchel
- Department of Psychiatry and Addictology, Université de Montréal, Montréal, Québec, Canada
- Centre de Recherche de l'Institut Universitaire en Santé Mentale de Montréal, Montréal, Québec, Canada
| | - Cody Cushing
- Department of Psychology, University of California, Los Angeles, California, USA
| | - Hakwan Lau
- RIKEN Center for Brain Science, Wakoshi, Saitama, Japan
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20
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Haugg A, Renz FM, Nicholson AA, Lor C, Götzendorfer SJ, Sladky R, Skouras S, McDonald A, Craddock C, Hellrung L, Kirschner M, Herdener M, Koush Y, Papoutsi M, Keynan J, Hendler T, Cohen Kadosh K, Zich C, Kohl SH, Hallschmid M, MacInnes J, Adcock RA, Dickerson KC, Chen NK, Young K, Bodurka J, Marxen M, Yao S, Becker B, Auer T, Schweizer R, Pamplona G, Lanius RA, Emmert K, Haller S, Van De Ville D, Kim DY, Lee JH, Marins T, Megumi F, Sorger B, Kamp T, Liew SL, Veit R, Spetter M, Weiskopf N, Scharnowski F, Steyrl D. Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis. Neuroimage 2021; 237:118207. [PMID: 34048901 DOI: 10.1016/j.neuroimage.2021.118207] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 05/14/2021] [Accepted: 05/24/2021] [Indexed: 12/12/2022] Open
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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Affiliation(s)
- Amelie Haugg
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Switzerland; Faculty of Psychology, University of Vienna, Austria.
| | - Fabian M Renz
- Faculty of Psychology, University of Vienna, Austria
| | | | - Cindy Lor
- Faculty of Psychology, University of Vienna, Austria
| | | | - Ronald Sladky
- Faculty of Psychology, University of Vienna, Austria
| | - Stavros Skouras
- Department of Biological and Medical Psychology, University of Bergen, Norway
| | - Amalia McDonald
- Department of Psychology, University of Virginia, United States
| | - Cameron Craddock
- Department of Diagnostic Medicine, The University of Texas at Austin Dell Medical School, United States
| | - Lydia Hellrung
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Switzerland
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Switzerland; McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Canada
| | - Marcus Herdener
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Switzerland
| | - Yury Koush
- Department of Radiology and Biomedical Imaging, Yale University, United States
| | - Marina Papoutsi
- UCL Huntington's Disease Centre, Institute of Neurology, University College London, United Kingdom; IXICO plc, United Kingdom
| | - Jackob Keynan
- Functional Brain Center, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Center, Tel-Aviv University, Israel
| | - Talma Hendler
- Functional Brain Center, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Center, Tel-Aviv University, Israel
| | | | - Catharina Zich
- Nuffiled Department of Clinical Neurosciences, University of Oxford, United Kingdom
| | - Simon H Kohl
- JARA-Institute Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Germany
| | - Manfred Hallschmid
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Germany; German Center for Diabetes Research (DZD), Germany
| | - Jeff MacInnes
- Institute for Learning and Brain Sciences, University of Washington, United States
| | - R Alison Adcock
- Duke Institute for Brain Sciences, Duke University, United States; Department of Psychiatry and Behavioral Sciences, Duke University, United States
| | - Kathryn C Dickerson
- Department of Psychiatry and Behavioral Sciences, Duke University, United States
| | - Nan-Kuei Chen
- Department of Biomedical Engineering, University of Arizona, United States
| | - Kymberly Young
- Department of Psychiatry, School of Medicine, University of Pittsburgh, United States
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, United States; Stephenson School of Biomedical Engineering, University of Oklahoma, United States
| | - Michael Marxen
- Department of Psychiatry, Technische Universität Dresden, Germany
| | - Shuxia Yao
- Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, China
| | - Benjamin Becker
- Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, China
| | - Tibor Auer
- School of Psychology, University of Surrey, United Kingdom
| | | | - Gustavo Pamplona
- Department of Ophthalmology, University of Lausanne and Fondation Asile des Aveugles, Switzerland
| | - Ruth A Lanius
- Department of Psychiatry, University of Western Ontario, Canada
| | - Kirsten Emmert
- Department of Neurology, University Medical Center Schleswig-Holstein, Kiel University, Germany
| | - Sven Haller
- Department of Surgical Sciences, Radiology, Uppsala University, Sweden
| | - Dimitri Van De Ville
- Center for Neuroprosthetics, Ecole polytechnique féderale de Lausanne, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - Dong-Youl Kim
- Department of Brain and Cognitive Engineering, Korea University, Korea
| | - Jong-Hwan Lee
- Department of Brain and Cognitive Engineering, Korea University, Korea
| | - Theo Marins
- D'Or Institute for Research and Education, Brazil
| | | | - Bettina Sorger
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
| | - Tabea Kamp
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
| | | | - Ralf Veit
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Germany; German Center for Diabetes Research (DZD), Germany; High-Field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Germany
| | - Maartje Spetter
- School of Psychology, University of Birmingham, United Kingdom
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain Sciences, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Germany
| | - Frank Scharnowski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Switzerland; Faculty of Psychology, University of Vienna, Austria
| | - David Steyrl
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Switzerland; Faculty of Psychology, University of Vienna, Austria
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21
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Huang Y, Yu S, Wilson G, Park J, Cheng M, Kong X, Lu T, Kong J. Altered Extended Locus Coeruleus and Ventral Tegmental Area Networks in Boys with Autism Spectrum Disorders: A Resting-State Functional Connectivity Study. Neuropsychiatr Dis Treat 2021; 17:1207-1216. [PMID: 33911868 PMCID: PMC8075355 DOI: 10.2147/ndt.s301106] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 03/31/2021] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION Previous studies have suggested that cerebral projections of the norepinephrine (NE) and dopamine (DA) systems have important etiology and treatment implications for autism spectrum disorder (ASD). METHODS We used functional magnetic resonance imaging to evaluate spontaneous resting state functional connectivity in boys aged 7-15 years with ASD (n=86) and age-, intelligence quotient-matched typically developing boys (TD, n=118). Specifically, we investigated functional connectivity of the locus coeruleus (LC) and ventral tegmental area (VTA), the main source projection of neurotransmitters NE and DA, respectively. RESULTS 1) Both the LC and VTA showed reduced connectivity with the postcentral gyrus (PoCG) in boys with ASD, reflecting the potential roles of NE and DA in modulating the function of the somatosensory cortex in boys with ASD. 2) The VTA had increased connectivity with bilateral thalamus in ASD; this alteration was correlated with repetitive and restrictive features. 3) Altered functional connectivity of both the LC and VTA with brain regions such as the angular gyrus (AG), middle temporal gyrus visual area (MT/V5), and occipital face area (OFA) in ASD group. DISCUSSION Our findings implicate the role of LC-NE and VTA-DA systems from the perspective of functional neuroimaging and may shed light on pharmacological studies targeting NE and DA for the treatment of autism in the future.
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Affiliation(s)
- Yiting Huang
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, People's Republic of China.,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Siyi Yu
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Georgia Wilson
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Joel Park
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ming Cheng
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Xuejun Kong
- Martino Imaging Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tao Lu
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, People's Republic of China
| | - Jian Kong
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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22
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MacInnes JJ, Adcock RA, Stocco A, Prat CS, Rao RPN, Dickerson KC. Pyneal: Open Source Real-Time fMRI Software. Front Neurosci 2020; 14:900. [PMID: 33041750 PMCID: PMC7522368 DOI: 10.3389/fnins.2020.00900] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 08/03/2020] [Indexed: 11/13/2022] Open
Abstract
Increasingly, neuroimaging researchers are exploring the use of real-time functional magnetic resonance imaging (rt-fMRI) as a way to access a participant's ongoing brain function throughout a scan. This approach presents novel and exciting experimental applications ranging from monitoring data quality in real time, to delivering neurofeedback from a region of interest, to dynamically controlling experimental flow, or interfacing with remote devices. Yet, for those interested in adopting this method, the existing software options are few and limited in application. This presents a barrier for new users, as well as hinders existing users from refining techniques and methods. Here we introduce a free, open-source rt-fMRI package, the Pyneal toolkit, designed to address this limitation. The Pyneal toolkit is python-based software that offers a flexible and user friendly framework for rt-fMRI, is compatible with all three major scanner manufacturers (GE, Siemens, Phillips), and, critically, allows fully customized analysis pipelines. In this article, we provide a detailed overview of the architecture, describe how to set up and run the Pyneal toolkit during an experimental session, offer tutorials with scan data that demonstrate how data flows through the Pyneal toolkit with example analyses, and highlight the advantages that the Pyneal toolkit offers to the neuroimaging community.
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Affiliation(s)
- Jeff J MacInnes
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
| | - R Alison Adcock
- Department of Psychiatry and Behavioral Sciences, Center for Cognitive Neuroscience, Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
| | - Andrea Stocco
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States.,Department of Psychology, University of Washington, Seattle, WA, United States
| | - Chantel S Prat
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States.,Department of Psychology, University of Washington, Seattle, WA, United States
| | - Rajesh P N Rao
- Department of Computer Science and Engineering, Center for Neurotechnology, University of Washington, Seattle, WA, United States
| | - Kathryn C Dickerson
- Department of Psychiatry and Behavioral Sciences, Center for Cognitive Neuroscience, Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
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23
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Haugg A, Sladky R, Skouras S, McDonald A, Craddock C, Kirschner M, Herdener M, Koush Y, Papoutsi M, Keynan JN, Hendler T, Cohen Kadosh K, Zich C, MacInnes J, Adcock RA, Dickerson K, Chen N, Young K, Bodurka J, Yao S, Becker B, Auer T, Schweizer R, Pamplona G, Emmert K, Haller S, Van De Ville D, Blefari M, Kim D, Lee J, Marins T, Fukuda M, Sorger B, Kamp T, Liew S, Veit R, Spetter M, Weiskopf N, Scharnowski F. Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity? Hum Brain Mapp 2020; 41:3839-3854. [PMID: 32729652 PMCID: PMC7469782 DOI: 10.1002/hbm.25089] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/18/2020] [Accepted: 05/26/2020] [Indexed: 12/31/2022] Open
Abstract
Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.
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Affiliation(s)
- Amelie Haugg
- Psychiatric University Hospital ZurichUniversity of ZurichZürichSwitzerland
- Faculty of PsychologyUniversity of ViennaViennaAustria
| | - Ronald Sladky
- Faculty of PsychologyUniversity of ViennaViennaAustria
| | - Stavros Skouras
- Department of Biological and Medical PsychologyUniversity of BergenBergenNorway
| | - Amalia McDonald
- Department of PsychologyUniversity of VirginiaCharlottesvilleVirginia
| | - Cameron Craddock
- Department of Diagnostic MedicineThe University of Texas at Austin Dell Medical SchoolAustinTexas
| | - Matthias Kirschner
- Psychiatric University Hospital ZurichUniversity of ZurichZürichSwitzerland
- McConnell Brain Imaging CentreMontréal Neurological Institute, McGill UniversityMontrealCanada
| | - Marcus Herdener
- Psychiatric University Hospital ZurichUniversity of ZurichZürichSwitzerland
| | - Yury Koush
- Magnetic Resonance Research Center, Department of Radiology & Biomedical ImagingYale UniversityNew HavenConnecticut
| | - Marina Papoutsi
- UCL Huntington's Disease CentreInstitute of Neurology, University College LondonLondonEngland
| | - Jackob N. Keynan
- Functional Brain CenterWohl Institute for Advanced Imaging, Tel‐Aviv Sourasky Medical Center, Tel‐Aviv UniversityTel AvivIsrael
| | - Talma Hendler
- Functional Brain CenterWohl Institute for Advanced Imaging, Tel‐Aviv Sourasky Medical Center, Tel‐Aviv UniversityTel AvivIsrael
| | | | - Catharina Zich
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordEngland
| | - Jeff MacInnes
- Institute for Learning and Brain SciencesUniversity of WashingtonSeattleWashington
| | - R. Alison Adcock
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth Carolina
| | - Kathryn Dickerson
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth Carolina
| | - Nan‐Kuei Chen
- Department of Biomedical EngineeringUniversity of ArizonaTucsonArizona
| | - Kymberly Young
- Department of Psychiatry, School of MedicineUniversity of PittsburghPittsburghPennsylvania
| | | | - Shuxia Yao
- Clinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Benjamin Becker
- Clinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Tibor Auer
- School of PsychologyUniversity of SurreyGuildfordEngland
| | - Renate Schweizer
- Functional Imaging LaboratoryGerman Primate CenterGöttingenGermany
| | - Gustavo Pamplona
- Hôpital and Ophtalmique Jules GoninUniversity of LausanneLausanneSwitzerland
| | - Kirsten Emmert
- Department of NeurologyUniversity Medical Center Schleswig‐Holstein, Kiel UniversityKielGermany
| | - Sven Haller
- Radiology‐Department of Surgical SciencesUppsala UniversityUppsalaSweden
| | - Dimitri Van De Ville
- Center for NeuroprostheticsEcole Polytechnique Féderale de LausanneLausanneSwitzerland
- Department of Radiology and Medical Informatics, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Maria‐Laura Blefari
- Center for NeuroprostheticsEcole Polytechnique Féderale de LausanneLausanneSwitzerland
| | - Dong‐Youl Kim
- Department of Brain and Cognitive EngineeringKorea UniversitySeoulKorea
| | - Jong‐Hwan Lee
- Department of Brain and Cognitive EngineeringKorea UniversitySeoulKorea
| | - Theo Marins
- D'Or Institute for Research and Education (IDOR)Rio de JaneiroBrazil
| | - Megumi Fukuda
- School of Fundamental Science and EngineeringWaseda UniversityTokyoJapan
| | - Bettina Sorger
- Department Cognitive Neuroscience, Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Tabea Kamp
- Department Cognitive Neuroscience, Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Sook‐Lei Liew
- Division of Occupational Science and Occupational TherapyUniversity of Southern CaliforniaLos AngelesCalifornia
| | - Ralf Veit
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center MunichUniversity of TübingenTübingenGermany
| | - Maartje Spetter
- School of PsychologyUniversity of BirminghamBirminghamEngland
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Frank Scharnowski
- Psychiatric University Hospital ZurichUniversity of ZurichZürichSwitzerland
- Faculty of PsychologyUniversity of ViennaViennaAustria
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24
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Bègue I, Kaiser S, Kirschner M. Pathophysiology of negative symptom dimensions of schizophrenia – Current developments and implications for treatment. Neurosci Biobehav Rev 2020; 116:74-88. [DOI: 10.1016/j.neubiorev.2020.06.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 04/13/2020] [Accepted: 06/02/2020] [Indexed: 02/06/2023]
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25
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Martz ME, Hart T, Heitzeg MM, Peltier SJ. Neuromodulation of brain activation associated with addiction: A review of real-time fMRI neurofeedback studies. Neuroimage Clin 2020; 27:102350. [PMID: 32736324 PMCID: PMC7394772 DOI: 10.1016/j.nicl.2020.102350] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/07/2020] [Accepted: 07/13/2020] [Indexed: 02/07/2023]
Abstract
Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) has emerged in recent years as an imaging modality used to examine volitional control over targeted brain activity. rtfMRI-nf has also been applied clinically as a way to train individuals to self-regulate areas of the brain, or circuitry, involved in various disorders. One such application of rtfMRI-nf has been in the domain of addictive behaviors, including substance use. Given the pervasiveness of substance use and the challenges of existing treatments to sustain abstinence, rtfMRI-nf has been identified as a promising treatment tool. rtfMRI-nf has also been used in basic science research in order to test the ability to modulate brain function involved in addiction. This review focuses first on providing an overview of recent rtfMRI-nf studies in substance-using populations, specifically nicotine, alcohol, and cocaine users, aimed at reducing craving-related brain activation. Next, rtfMRI-nf studies targeting reward responsivity and emotion regulation in healthy samples are reviewed in order to examine the extent to which areas of the brain involved in addiction can be self-regulated using neurofeedback. We propose that future rtfMRI-nf studies could be strengthened by improvements to study design, sample selection, and more robust strategies in the development and assessment of rtfMRI-nf as a clinical treatment. Recommendations for ways to accomplish these improvements are provided. rtfMRI-nf holds much promise as an imaging modality that can directly target key brain regions involved in addiction, however additional studies are needed in order to establish rtfMRI-nf as an effective, and practical, treatment for addiction.
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Affiliation(s)
- Meghan E Martz
- Addiction Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA.
| | - Tabatha Hart
- Addiction Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA
| | - Mary M Heitzeg
- Addiction Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA
| | - Scott J Peltier
- Functional MRI Laboratory, USA; Department of Biomedical Engineering, Bonisteel Interdisciplinary Research Building, 2360 Bonisteel Blvd, Ann Arbor, MI 48109, USA
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26
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Skouras S, Torner J, Andersson P, Koush Y, Falcon C, Minguillon C, Fauria K, Alpiste F, Blenow K, Zetterberg H, Gispert JD, Molinuevo JL. Earliest amyloid and tau deposition modulate the influence of limbic networks during closed-loop hippocampal downregulation. Brain 2020; 143:976-992. [PMID: 32091109 PMCID: PMC7089658 DOI: 10.1093/brain/awaa011] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 11/22/2019] [Accepted: 12/04/2019] [Indexed: 12/23/2022] Open
Abstract
Research into hippocampal self-regulation abilities may help determine the clinical significance of hippocampal hyperactivity throughout the pathophysiological continuum of Alzheimer's disease. In this study, we aimed to identify the effects of amyloid-β peptide 42 (amyloid-β42) and phosphorylated tau on the patterns of functional connectomics involved in hippocampal downregulation. We identified 48 cognitively unimpaired participants (22 with elevated CSF amyloid-β peptide 42 levels, 15 with elevated CSF phosphorylated tau levels, mean age of 62.705 ± 4.628 years), from the population-based 'Alzheimer's and Families' study, with baseline MRI, CSF biomarkers, APOE genotyping and neuropsychological evaluation. We developed a closed-loop, real-time functional MRI neurofeedback task with virtual reality and tailored it for training downregulation of hippocampal subfield cornu ammonis 1 (CA1). Neurofeedback performance score, cognitive reserve score, hippocampal volume, number of apolipoprotein ε4 alleles and sex were controlled for as confounds in all cross-sectional analyses. First, using voxel-wise multiple regression analysis and controlling for CSF biomarkers, we identified the effect of healthy ageing on eigenvector centrality, a measure of each voxel's overall influence based on iterative whole-brain connectomics, during hippocampal CA1 downregulation. Then, controlling for age, we identified the effects of abnormal CSF amyloid-β42 and phosphorylated tau levels on eigenvector centrality during hippocampal CA1 downregulation. Across subjects, our main findings during hippocampal downregulation were: (i) in the absence of abnormal biomarkers, age correlated with eigenvector centrality negatively in the insula and midcingulate cortex, and positively in the inferior temporal gyrus; (ii) abnormal CSF amyloid-β42 (<1098) correlated negatively with eigenvector centrality in the anterior cingulate cortex and primary motor cortex; and (iii) abnormal CSF phosphorylated tau levels (>19.2) correlated with eigenvector centrality positively in the ventral striatum, anterior cingulate and somatosensory cortex, and negatively in the precuneus and orbitofrontal cortex. During resting state functional MRI, similar eigenvector centrality patterns in the cingulate had previously been associated to CSF biomarkers in mild cognitive impairment and dementia patients. Using the developed closed-loop paradigm, we observed such patterns, which are characteristic of advanced disease stages, during a much earlier presymptomatic phase. In the absence of CSF biomarkers, our non-invasive, interactive, adaptive and gamified neuroimaging procedure may provide important information for clinical prognosis and monitoring of therapeutic efficacy. We have released the developed paradigm and analysis pipeline as open-source software to facilitate replication studies.
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Affiliation(s)
- Stavros Skouras
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Jordi Torner
- BarcelonaTech, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
| | | | - Yury Koush
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Francesc Alpiste
- BarcelonaTech, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
| | - Kaj Blenow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, University College London, London, UK
| | - Juan D Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - José L Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
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27
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Ros T, Enriquez-Geppert S, Zotev V, Young KD, Wood G, Whitfield-Gabrieli S, Wan F, Vuilleumier P, Vialatte F, Van De Ville D, Todder D, Surmeli T, Sulzer JS, Strehl U, Sterman MB, Steiner NJ, Sorger B, Soekadar SR, Sitaram R, Sherlin LH, Schönenberg M, Scharnowski F, Schabus M, Rubia K, Rosa A, Reiner M, Pineda JA, Paret C, Ossadtchi A, Nicholson AA, Nan W, Minguez J, Micoulaud-Franchi JA, Mehler DMA, Lührs M, Lubar J, Lotte F, Linden DEJ, Lewis-Peacock JA, Lebedev MA, Lanius RA, Kübler A, Kranczioch C, Koush Y, Konicar L, Kohl SH, Kober SE, Klados MA, Jeunet C, Janssen TWP, Huster RJ, Hoedlmoser K, Hirshberg LM, Heunis S, Hendler T, Hampson M, Guggisberg AG, Guggenberger R, Gruzelier JH, Göbel RW, Gninenko N, Gharabaghi A, Frewen P, Fovet T, Fernández T, Escolano C, Ehlis AC, Drechsler R, Christopher deCharms R, Debener S, De Ridder D, Davelaar EJ, Congedo M, Cavazza M, Breteler MHM, Brandeis D, Bodurka J, Birbaumer N, Bazanova OM, Barth B, Bamidis PD, Auer T, Arns M, Thibault RT. Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist). Brain 2020; 143:1674-1685. [PMID: 32176800 PMCID: PMC7296848 DOI: 10.1093/brain/awaa009] [Citation(s) in RCA: 151] [Impact Index Per Article: 37.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 10/10/2019] [Accepted: 10/28/2020] [Indexed: 02/02/2023] Open
Abstract
Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.
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Affiliation(s)
- Tomas Ros
- Departments of Neuroscience and Psychiatry, University of Geneva; Campus Biotech, Geneva, Switzerland
| | - Stefanie Enriquez-Geppert
- Department of Clinical Neuropsychology, University of Groningen, Groningen, The Netherlands
- Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, Groningen, The Netherlands
| | - Vadim Zotev
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Kymberly D Young
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Guilherme Wood
- Institute of Psychology, University of Graz, Graz, Austria
| | - Susan Whitfield-Gabrieli
- Massachusetts Institute of Technology, Cambridge, MA, USA
- Northeastern University, Boston, MA, USA
| | - Feng Wan
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China
| | | | | | - Dimitri Van De Ville
- Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL); Campus Biotech, Geneva, Switzerland
| | - Doron Todder
- Faculty of Health, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Beer-Sheva Mental Health Center, Israel Ministry of Health, Beer-Sheva, Israel
| | - Tanju Surmeli
- Living Health Center for Research and Education, Istanbul, Turkey
| | - James S Sulzer
- Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Ute Strehl
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Maurice Barry Sterman
- Neurobiology and Biobehavioral Psychiatry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Naomi J Steiner
- Boston University School of Medicine, Department of Pediatrics, Boston, MA, USA
| | - Bettina Sorger
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Surjo R Soekadar
- Clinical Neurotechnology Laboratory, Neuroscience Research Center (NWFZ), Department of Psychiatry and Psychotherapy (CCM), Charité - University Medicine Berlin, Berlin, Germany
| | - Ranganatha Sitaram
- Institute of Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Macul, Santiago, Chile
| | | | | | - Frank Scharnowski
- Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
| | - Manuel Schabus
- University of Salzburg, Centre for Cognitive Neuroscience and Department of Psychology, Salzburg, Austria
| | - Katya Rubia
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | | | - Miriam Reiner
- Technion, Israel Institute of Technology, Haifa, Israel
| | - Jaime A Pineda
- Cognitive Science Department, University of California, San Diego, CA, USA
| | - Christian Paret
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Germany
| | - Alexei Ossadtchi
- National Research University Higher School of Economics, Moscow, Russia
| | - Andrew A Nicholson
- Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
| | - Wenya Nan
- Department of Psychology, Shanghai Normal University, Shanghai, China
| | | | | | - David M A Mehler
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Michael Lührs
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Joel Lubar
- Department of Psychology, University of Tennessee, Knoxville, USA
| | - Fabien Lotte
- Inria Bordeaux Sud-Ouest/LaBRI University of Bordeaux - CNRS-Bordeaux INP, Bordeaux, France
| | - David E J Linden
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | | | - Mikhail A Lebedev
- Center for Bioelectric Interfaces of the Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
- Department of Information and Internet Technologies of Digital Health Institute; I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Duke Center for Neuroengineering, Duke University, Durham, NC, USA
| | - Ruth A Lanius
- Department of Psychiatry, Western University, London, Ontario, Canada
| | - Andrea Kübler
- Department of Psychology I, Psychological Intervention, Behavior Analysis and Regulation of Behavior, University of Würzburg
| | - Cornelia Kranczioch
- Neuropsychology Lab, Department of Psychology, University of Oldenburg, Oldenberg, Germany
| | - Yury Koush
- Magnetic Resonance Research Center (MRRC), Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Lilian Konicar
- Medical University of Vienna, Department of Child and Adolescent Psychiatry, Vienna, Austria
| | - Simon H Kohl
- JARA-Institute Molecular neuroscience and neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany
| | | | - Manousos A Klados
- Department of Psychology, The University of Sheffield International Faculty, City College, Thessaloniki, Greece
| | - Camille Jeunet
- CLLE Lab, CNRS, Université Toulouse Jean Jaurès, Toulouse, France
| | - T W P Janssen
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Rene J Huster
- Multimodal imaging and Cognitive Control Lab, Department of Psychology, University of Olso, Norway
| | - Kerstin Hoedlmoser
- University of Salzburg, Centre for Cognitive Neuroscience and Department of Psychology, Salzburg, Austria
| | | | - Stephan Heunis
- Electrical Engineering Department, Eindhoven University of Technology, The Netherlands
| | - Talma Hendler
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Sourasky Medical Center, Tel Aviv, Israel
| | - Michelle Hampson
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Adrian G Guggisberg
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital Geneva, Geneva, Switzerland
| | - Robert Guggenberger
- Division of Functional and Restorative Neurosurgery, University of Tübingen, Tübingen, Germany
| | - John H Gruzelier
- Department of Psychology, Goldsmiths, University of London, London, UK
| | - Rainer W Göbel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Nicolas Gninenko
- Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL); Campus Biotech, Geneva, Switzerland
| | - Alireza Gharabaghi
- Division of Functional and Restorative Neurosurgery, University of Tübingen, Tübingen, Germany
| | - Paul Frewen
- Department of Psychiatry, Western University, London, Ontario, Canada
| | - Thomas Fovet
- Univ. Lille, INSERM U1172, CHU LILLE, Centre Lille Neuroscience & Cognition, Pôle de Psychiatrie, F-59000, Lille, France
| | - Thalía Fernández
- UNAM Institute of Neurobiology, National Autonomous University of Mexico, Juriquilla, Mexico
| | | | - Ann-Christine Ehlis
- Psychophysiology and Optical Imaging, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Renate Drechsler
- Department of Child and Adolescent, Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
| | | | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, University of Oldenburg, Oldenberg, Germany
| | - Dirk De Ridder
- Department of Surgery, Section of Neurosurgery, University of Otago, Dunedin, New Zealand
| | - Eddy J Davelaar
- Department of Psychological Sciences Birkbeck, University of London, Bloomsbury, London, UK
| | - Marco Congedo
- GIPSA-lab, CNRS, University Grenoble Alpes, Grenoble-INP, Grenoble, France
| | - Marc Cavazza
- School of Computing and Mathematical Sciences, University of Greenwich, London, UK
| | - Marinus H M Breteler
- Radboud University Nijmegen, Department of Clinical Psychology, Nijmegen, The Netherlands
| | - Daniel Brandeis
- Department of Child and Adolescent, Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Niels Birbaumer
- Institute for Medical Psychology and Behavioural Neurobiology, University of Tübingen, Tübingen, Germany
| | - Olga M Bazanova
- State Research Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Beatrix Barth
- Psychophysiology and Optical Imaging, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | | | - Tibor Auer
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Martijn Arns
- Brainclinics Foundation, Research Institute Brainclinics, Nijmegen, The Netherlands
| | - Robert T Thibault
- School of Psychological Science, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
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28
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Caria A. Mesocorticolimbic Interactions Mediate fMRI-Guided Regulation of Self-Generated Affective States. Brain Sci 2020; 10:brainsci10040223. [PMID: 32276411 PMCID: PMC7226604 DOI: 10.3390/brainsci10040223] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/03/2020] [Accepted: 04/04/2020] [Indexed: 11/16/2022] Open
Abstract
Increasing evidence shows that the generation and regulation of affective responses is associated with activity of large brain networks that also include phylogenetically older regions in the brainstem. Mesencephalic regions not only control autonomic responses but also participate in the modulation of autonomic, emotional, and motivational responses. The specific contribution of the midbrain to emotion regulation in humans remains elusive. Neuroimaging studies grounding on appraisal models of emotion emphasize a major role of prefrontal cortex in modulating emotion-related cortical and subcortical regions but usually neglect the contribution of the midbrain and other brainstem regions. Here, the role of mesolimbic and mesocortical networks in core affect generation and regulation was explored during emotion regulation guided by real-time fMRI feedback of the anterior insula activity. The fMRI and functional connectivity analysis revealed that the upper midbrain significantly contributes to emotion regulation in humans. Moreover, differential functional interactions between the dopaminergic mesocorticolimbic system and frontoparietal networks mediate up and down emotion regulatory processes. Finally, these findings further indicate the potential of real-time fMRI feedback approach in guiding core affect regulation.
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Affiliation(s)
- Andrea Caria
- Department of Psychology and Cognitive Sciences, University of Trento, Corso Bettini 33, 38068 Rovereto, Italy
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29
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Video games as rich environments to foster brain plasticity. HANDBOOK OF CLINICAL NEUROLOGY 2020; 168:117-136. [PMID: 32164847 DOI: 10.1016/b978-0-444-63934-9.00010-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
This chapter highlights the key role of two main factors, attentional control and reward processing, in unlocking brain plasticity. We first review the evidence for the role that each of these mechanisms plays in neuroplasticity, and then make the case that tools and technologies that combine these two are likely to result in maximal and broad, generalized benefits. In this context, we review the evidence concerning the impact of video game play on brain plasticity, with an eye toward plasticity-driving methods such as the seamless integration of neurofeedback into the video game platforms.
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30
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Fede SJ, Dean SF, Manuweera T, Momenan R. A Guide to Literature Informed Decisions in the Design of Real Time fMRI Neurofeedback Studies: A Systematic Review. Front Hum Neurosci 2020; 14:60. [PMID: 32161529 PMCID: PMC7052377 DOI: 10.3389/fnhum.2020.00060] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 02/07/2020] [Indexed: 11/26/2022] Open
Abstract
Background: Although biofeedback using electrophysiology has been explored extensively, the approach of using neurofeedback corresponding to hemodynamic response is a relatively young field. Real time functional magnetic resonance imaging-based neurofeedback (rt-fMRI-NF) uses sensory feedback to operantly reinforce patterns of neural response. It can be used, for example, to alter visual perception, increase brain connectivity, and reduce depression symptoms. Within recent years, interest in rt-fMRI-NF in both research and clinical contexts has expanded considerably. As such, building a consensus regarding best practices is of great value. Objective: This systematic review is designed to describe and evaluate the variations in methodology used in previous rt-fMRI-NF studies to provide recommendations for rt-fMRI-NF study designs that are mostly likely to elicit reproducible and consistent effects of neurofeedback. Methods: We conducted a database search for fMRI neurofeedback papers published prior to September 26th, 2019. Of 558 studies identified, 146 met criteria for inclusion. The following information was collected from each study: sample size and type, task used, neurofeedback calculation, regulation procedure, feedback, whether feedback was explicitly related to changing brain activity, feedback timing, control group for active neurofeedback, how many runs and sessions of neurofeedback, if a follow-up was conducted, and the results of neurofeedback training. Results: rt-fMRI-NF is typically upregulation practice based on hemodynamic response from a specific region of the brain presented using a continually updating thermometer display. Most rt-fMRI-NF studies are conducted in healthy samples and half evaluate its effect on immediate changes in behavior or affect. The most popular control group method is to provide sham signal from another region; however, many studies do not compare use a comparison group. Conclusions: We make several suggestions for designs of future rt-fMRI-NF studies. Researchers should use feedback calculation methods that consider neural response across regions (i.e., SVM or connectivity), which should be conveyed as intermittent, auditory feedback. Participants should be given explicit instructions and should be assessed on individual differences. Future rt-fMRI-NF studies should use clinical samples; effectiveness of rt-fMRI-NF should be evaluated on clinical/behavioral outcomes at follow-up time points in comparison to both a sham and no feedback control group.
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Affiliation(s)
| | | | | | - Reza Momenan
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
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31
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Griffies WS. Impaired Mind-Body Connections in Psychosomatic Patients: A Contemporary Neuropsychodynamic Model. Psychodyn Psychiatry 2019; 47:317-342. [PMID: 31448984 DOI: 10.1521/pdps.2019.47.3.317] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
In alexithymia-type psychosomatic patients who do not have the capacity to mentalize, arousal is experienced non-symbolically within the body. These people also often have significant histories of attachment trauma and other adverse childhood experiences. This article extends a previous neuropsychodynamic formulation that takes into account recent work on how attachment trauma is internalized in developing brain circuits. Specifically, it considers the possibility that early attachment trauma impairs thalamo-amygdala-striatal-thalamic circuits, resulting in disconnect of subcortical arousal to the prefrontal cortex where the arousal can be mentalized. These impaired subcortical circuits perpetuate stress deep within these patients' implicit procedural circuitry, making them very resistant to psychotherapy. Knowledge of this interaction deepens our understanding of these patients, who suffer greatly, and suggests guidelines for treatment approaches with which they are more likely to engage.
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Affiliation(s)
- W Scott Griffies
- Associate Professor, Duke Psychiatry and Behavioral Sciences, Medical Director, Psychosomatic Medicine Service, Duke Raleigh Hospital
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32
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Endogenous fluctuations in the dopaminergic midbrain drive behavioral choice variability. Proc Natl Acad Sci U S A 2019; 116:18732-18737. [PMID: 31451671 PMCID: PMC6744888 DOI: 10.1073/pnas.1900872116] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Humans are surprisingly inconsistent in their behavior, often making different choices under identical conditions. Previous research suggests that intrinsic fluctuations in brain activity can influence low-level processes, such as the amount of force applied in a motor response. Here, we show that intrinsic prestimulus brain activity in the dopaminergic midbrain influences how we choose between risky and safe options. Using computational modeling, we demonstrate that endogenous fluctuations alter phasic responses in a decision network and thereby modulate risk taking. Our findings demonstrate that higher-order cognition is influenced by fluctuations in internal brain states, providing a physiological basis for variability in complex human behavior. Human behavior is surprisingly variable, even when facing the same problem under identical circumstances. A prominent example is risky decision making. Economic theories struggle to explain why humans are so inconsistent. Resting-state studies suggest that ongoing endogenous fluctuations in brain activity can influence low-level perceptual and motor processes, but it remains unknown whether endogenous fluctuations also influence high-level cognitive processes including decision making. Here, using real-time functional magnetic resonance imaging, we tested whether risky decision making is influenced by endogenous fluctuations in blood oxygenation level-dependent (BOLD) activity in the dopaminergic midbrain, encompassing ventral tegmental area and substantia nigra. We show that low prestimulus brain activity leads to increased risky choice in humans. Using computational modeling, we show that increased risk taking is explained by enhanced phasic responses to offers in a decision network. Our findings demonstrate that endogenous brain activity provides a physiological basis for variability in complex human behavior.
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33
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Reiss D, Nielsen L, Godfrey K, McEwen B, Power C, Seeman T, Suomi S. Midlife reversibility of early-established biobehavioral risk factors: A research agenda. Dev Psychol 2019; 55:2203-2218. [PMID: 31368762 DOI: 10.1037/dev0000780] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Epidemiological evidence links exposure to early life adversities-such as childhood maltreatment-with impaired health and well-being in adulthood. Since these effects are usually unrecognized or untreated in childhood, preventive and remediating interventions in adults are needed. Our focus on adulthood prompted three major questions. First, does our increased understanding of mechanisms accounting for the long-term effects of early life adversities help delineate underlying dimensions that underscore key similarities and differences among these adversities? Second, can adults accurately report on adversities they experienced in childhood? Third, can we identify malleable risk processes in adulthood that might be targets for preventive intervention? Supported by the National Institute on Aging, the U.K. Economic and Social and the Biotechnology and Biological Sciences Research Councils, a network of researchers in human and animal development addressed these questions through meetings and literature review. A small number of dimensions may adequately distinguish among a range of co-occurring childhood adversities. Widely used adult ascertainments of childhood adversity are poorly related to prospective ascertainment. Strategies for preventive interventions should be aimed both at adults who were actually exposed to adversity as well as those who recall adversity, but the targeted risk processes may be different. Now is an opportune time to support research on adult interventions based on unfolding research on critical periods of sensitivity to adversity in fetal and child development, on improved understanding of risk mechanisms that may persist across the life span, and on new insights on enhancing neuroplasticity in adults. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Affiliation(s)
| | - Lisbeth Nielsen
- Division of Social and Behavioral Research, National Institute on Aging
| | - Keith Godfrey
- MRC Lifecourse Epidemiology Unit, University of Southampton
| | - Bruce McEwen
- Laboratory of Neuroendocrinology, The Rockefeller University
| | - Christine Power
- Great Ormond Street Institute of Child Health, University College London
| | - Teresa Seeman
- Division of Geriatrics, David Geffen School of Medicine, University of California, Los Angeles
| | - Stephen Suomi
- Laboratory of Comparative Ethology, Eunice Kennedy Shriver National Institute of Child Health and Human Development
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34
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Stanek JK, Dickerson KC, Chiew KS, Clement NJ, Adcock RA. Expected Reward Value and Reward Uncertainty Have Temporally Dissociable Effects on Memory Formation. J Cogn Neurosci 2019; 31:1443-1454. [PMID: 30990388 DOI: 10.1162/jocn_a_01411] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Anticipating rewards has been shown to enhance memory formation. Although substantial evidence implicates dopamine in this behavioral effect, the precise mechanisms remain ambiguous. Because dopamine nuclei have been associated with two distinct physiological signatures of reward prediction, we hypothesized two dissociable effects on memory formation. These two signatures are a phasic dopamine response immediately following a reward cue that encodes its expected value and a sustained, ramping response that has been demonstrated during high reward uncertainty [Fiorillo, C. D., Tobler, P. N., & Schultz, W. Discrete coding of reward probability and uncertainty by dopamine neurons. Science, 299, 1898-1902, 2003]. Here, we show in humans that the impact of reward anticipation on memory for an event depends on its timing relative to these physiological signatures. By manipulating reward probability (100%, 50%, or 0%) and the timing of the event to be encoded (just after the reward cue versus just before expected reward outcome), we demonstrated the predicted double dissociation: Early during reward anticipation, memory formation was improved by increased expected reward value, whereas late during reward anticipation, memory formation was enhanced by reward uncertainty. Notably, although the memory benefits of high expected reward in the early interval were consolidation dependent, the memory benefits of high uncertainty in the later interval were not. These findings support the view that expected reward benefits memory consolidation via phasic dopamine release. The novel finding of a distinct memory enhancement, temporally consistent with sustained anticipatory dopamine release, points toward new mechanisms of memory modulation by reward now ripe for further investigation.
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35
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Lubianiker N, Goldway N, Fruchtman-Steinbok T, Paret C, Keynan JN, Singer N, Cohen A, Kadosh KC, Linden DEJ, Hendler T. Process-based framework for precise neuromodulation. Nat Hum Behav 2019; 3:436-445. [DOI: 10.1038/s41562-019-0573-y] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 03/05/2019] [Indexed: 12/20/2022]
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36
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Sorger B, Scharnowski F, Linden DEJ, Hampson M, Young KD. Control freaks: Towards optimal selection of control conditions for fMRI neurofeedback studies. Neuroimage 2019; 186:256-265. [PMID: 30423429 PMCID: PMC6338498 DOI: 10.1016/j.neuroimage.2018.11.004] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 10/31/2018] [Accepted: 11/05/2018] [Indexed: 12/31/2022] Open
Abstract
fMRI Neurofeedback research employs many different control conditions. Currently, there is no consensus as to which control condition is best, and the answer depends on what aspects of the neurofeedback-training design one is trying to control for. These aspects can range from determining whether participants can learn to control brain activity via neurofeedback to determining whether there are clinically significant effects of the neurofeedback intervention. Lack of consensus over criteria for control conditions has hampered the design and interpretation of studies employing neurofeedback protocols. This paper presents an overview of the most commonly employed control conditions currently used in neurofeedback studies and discusses their advantages and disadvantages. Control conditions covered include no control, treatment-as-usual, bidirectional-regulation control, feedback of an alternative brain signal, sham feedback, and mental-rehearsal control. We conclude that the selection of the control condition(s) should be determined by the specific research goal of the study and best procedures that effectively control for relevant confounding factors.
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Affiliation(s)
- Bettina Sorger
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Frank Scharnowski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland; Neuroscience Center Zürich, University of Zürich and Swiss Federal Institute of Technology, Zürich, Switzerland; Zürich Center for Integrative Human Physiology (ZIHP), University of Zürich, Zürich, Switzerland
| | - David E J Linden
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Michelle Hampson
- Department of Radiology and Biomedical Imaging, Psychiatry and the Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Kymberly D Young
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
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37
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Functional neuroanatomical review of the ventral tegmental area. Neuroimage 2019; 191:258-268. [PMID: 30710678 DOI: 10.1016/j.neuroimage.2019.01.062] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 01/22/2019] [Accepted: 01/23/2019] [Indexed: 12/19/2022] Open
Abstract
The ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) are assumed to play a key role in dopamine-related functions such as reward-related behaviour, motivation, addiction and motor functioning. Although dopamine-producing midbrain structures are bordering, they show significant differences in structure and function that argue for a distinction when studying the functions of the dopaminergic midbrain, especially by means of neuroimaging. First, unlike the SNc, the VTA is not a nucleus, which makes it difficult to delineate the structure due to lack of clear anatomical borders. Second, there is no consensus in the literature about the anatomical nomenclature to describe the VTA. Third, these factors in combination with limitations in magnetic resonance imaging (MRI) complicate VTA visualization. We suggest that developing an MRI-compatible probabilistic atlas of the VTA will help to overcome these issues. Such an atlas can be used to identify the individual VTA and serve as region-of-interest for functional MRI.
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38
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Dickerson KC. Upregulating brain activity using non-drug reward imagery and real-time fMRI neurofeedback-A new treatment approach for addiction? EBioMedicine 2018; 38:21-22. [PMID: 30448154 PMCID: PMC6306366 DOI: 10.1016/j.ebiom.2018.11.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Accepted: 11/13/2018] [Indexed: 12/15/2022] Open
Affiliation(s)
- Kathryn C Dickerson
- Department of Psychiatry and Behavioral Sciences, Center of Cognitive Neuroscience, Duke University, Box 90999, Durham, NC 27708, United States.
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39
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Fonzo GA. Diminished positive affect and traumatic stress: A biobehavioral review and commentary on trauma affective neuroscience. Neurobiol Stress 2018; 9:214-230. [PMID: 30450386 PMCID: PMC6234277 DOI: 10.1016/j.ynstr.2018.10.002] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 07/20/2018] [Accepted: 10/17/2018] [Indexed: 11/28/2022] Open
Abstract
Post-traumatic stress manifests in disturbed affect and emotion, including exaggerated severity and frequency of negative valence emotions, e.g., fear, anxiety, anger, shame, and guilt. However, another core feature of common post-trauma psychopathologies, i.e. post-traumatic stress disorder (PTSD) and major depression, is diminished positive affect, or reduced frequency and intensity of positive emotions and affective states such as happiness, joy, love, interest, and desire/capacity for interpersonal affiliation. There remains a stark imbalance in the degree to which the neuroscience of each affective domain has been probed and characterized in PTSD, with our knowledge of post-trauma diminished positive affect remaining comparatively underdeveloped. This remains a prominent barrier to realizing the clinical breakthroughs likely to be afforded by the increasing availability of neuroscience assessment and intervention tools. In this review and commentary, the author summarizes the modest extant neuroimaging literature that has probed diminished positive affect in PTSD using reward processing behavioral paradigms, first briefly reviewing and outlining the neurocircuitry implicated in reward and positive emotion and its interrelationship with negative emotion and negative valence circuitry. Specific research guidelines are then offered to best and most efficiently develop the knowledge base in this area in a way that is clinically translatable and will exert a positive impact on routine clinical care. The author concludes with the prediction that the development of an integrated, bivalent theoretical and predictive model of how trauma impacts affective neurocircuitry to promote post-trauma psychopathology will ultimately lead to breakthroughs in how trauma treatments are conceptualized mechanistically and developed pragmatically.
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Affiliation(s)
- Gregory A. Fonzo
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, 401 Quarry Road, MC 5722, Stanford, CA, 94305, USA.
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40
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Kirschner M, Sladky R, Haugg A, Stämpfli P, Jehli E, Hodel M, Engeli E, Hösli S, Baumgartner MR, Sulzer J, Huys QJM, Seifritz E, Quednow BB, Scharnowski F, Herdener M. Self-regulation of the dopaminergic reward circuit in cocaine users with mental imagery and neurofeedback. EBioMedicine 2018; 37:489-498. [PMID: 30377073 PMCID: PMC6286189 DOI: 10.1016/j.ebiom.2018.10.052] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 10/21/2018] [Accepted: 10/22/2018] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Enhanced drug-related reward sensitivity accompanied by impaired sensitivity to non-drug related rewards in the mesolimbic dopamine system are thought to underlie the broad motivational deficits and dysfunctional decision-making frequently observed in cocaine use disorder (CUD). Effective approaches to modify this imbalance and reinstate non-drug reward responsiveness are urgently needed. Here, we examined whether cocaine users (CU) can use mental imagery of non-drug rewards to self-regulate the ventral tegmental area and substantia nigra (VTA/SN). We expected that obsessive and compulsive thoughts about cocaine consumption would hamper the ability to self-regulate the VTA/SN activity and tested if real-time fMRI (rtfMRI) neurofeedback (NFB) can improve self-regulation of the VTA/SN. METHODS Twenty-two CU and 28 healthy controls (HC) were asked to voluntarily up-regulate VTA/SN activity with non-drug reward imagery alone, or combined with rtfMRI NFB. RESULTS On a group level, HC and CU were able to activate the dopaminergic midbrain and other reward regions with reward imagery. In CU, the individual ability to self-regulate the VTA/SN was reduced in those with more severe obsessive-compulsive drug use. NFB enhanced the effect of reward imagery but did not result in transfer effects at the end of the session. CONCLUSION CU can voluntary activate their reward system with non-drug reward imagery and improve this ability with rtfMRI NFB. Combining mental imagery and rtFMRI NFB has great potential for modifying the maladapted reward sensitivity and reinstating non-drug reward responsiveness. This motivates further work to examine the use of rtfMRI NFB in the treatment of CUD.
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Affiliation(s)
- Matthias Kirschner
- Center for Addictive Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland.
| | - Ronald Sladky
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland
| | - Amelie Haugg
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology, Switzerland
| | - Philipp Stämpfli
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland
| | - Elisabeth Jehli
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland
| | - Martina Hodel
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland
| | - Etna Engeli
- Center for Addictive Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland
| | - Sarah Hösli
- Center for Addictive Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland
| | - Markus R Baumgartner
- Center for Forensic Hair Analysis, Institute of Forensic Medicine, University of Zurich, Switzerland
| | - James Sulzer
- Department of Mechanical Engineering, University of Texas at Austin, TX, USA
| | - Quentin J M Huys
- Center for Addictive Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland; Translational Neuromodeling Unit, Institute of Biomedical Engineering, University of Zurich and ETH, Zurich, Switzerland
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland
| | - Boris B Quednow
- Experimental and Clinical Pharmacopsychology, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology, Switzerland; Zurich Center for Integrative Human Physiology, University of Zurich, Switzerland
| | - Frank Scharnowski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology, Switzerland; Zurich Center for Integrative Human Physiology, University of Zurich, Switzerland; Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Marcus Herdener
- Center for Addictive Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Switzerland
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41
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Abnormal reward prediction-error signalling in antipsychotic naive individuals with first-episode psychosis or clinical risk for psychosis. Neuropsychopharmacology 2018; 43:1691-1699. [PMID: 29748629 PMCID: PMC6006166 DOI: 10.1038/s41386-018-0056-2] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 03/12/2018] [Accepted: 03/13/2018] [Indexed: 12/20/2022]
Abstract
Ongoing research suggests preliminary, though not entirely consistent, evidence of neural abnormalities in signalling prediction errors in schizophrenia. Supporting theories suggest mechanistic links between the disruption of these processes and the generation of psychotic symptoms. However, it is unknown at what stage in the pathogenesis of psychosis these impairments in prediction-error signalling develop. One major confound in prior studies is the use of medicated patients with strongly varying disease durations. Our study aims to investigate the involvement of the meso-cortico-striatal circuitry during reward prediction-error signalling in earliest stages of psychosis. We studied patients with first-episode psychosis (FEP) and help-seeking individuals at-risk for psychosis due to sub-threshold prodromal psychotic symptoms. Patients with either FEP (n = 14), or at-risk for developing psychosis (n = 30), and healthy volunteers (n = 39) performed a reinforcement learning task during fMRI scanning. ANOVA revealed significant (p < 0.05 family-wise error corrected) prediction-error signalling differences between groups in the dopaminergic midbrain and right middle frontal gyrus (dorsolateral prefrontal cortex, DLPFC). FEP patients showed disrupted reward prediction-error signalling compared to controls in both regions. At-risk patients showed intermediate activation in the midbrain that significantly differed from controls and from FEP patients, but DLPFC activation that did not differ from controls. Our study confirms that FEP patients have abnormal meso-cortical signalling of reward-prediction errors, whereas reward-prediction-error dysfunction in the at-risk patients appears to show a more nuanced pattern of activation with a degree of midbrain impairment but preserved cortical function.
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Thibault RT, MacPherson A, Lifshitz M, Roth RR, Raz A. Neurofeedback with fMRI: A critical systematic review. Neuroimage 2018; 172:786-807. [DOI: 10.1016/j.neuroimage.2017.12.071] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2017] [Revised: 12/18/2017] [Accepted: 12/21/2017] [Indexed: 10/18/2022] Open
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Papoutsi M, Weiskopf N, Langbehn D, Reilmann R, Rees G, Tabrizi SJ. Stimulating neural plasticity with real-time fMRI neurofeedback in Huntington's disease: A proof of concept study. Hum Brain Mapp 2018; 39:1339-1353. [PMID: 29239063 PMCID: PMC5838530 DOI: 10.1002/hbm.23921] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 11/14/2017] [Accepted: 12/07/2017] [Indexed: 01/28/2023] Open
Abstract
Novel methods that stimulate neuroplasticity are increasingly being studied to treat neurological and psychiatric conditions. We sought to determine whether real-time fMRI neurofeedback training is feasible in Huntington's disease (HD), and assess any factors that contribute to its effectiveness. In this proof-of-concept study, we used this technique to train 10 patients with HD to volitionally regulate the activity of their supplementary motor area (SMA). We collected detailed behavioral and neuroimaging data before and after training to examine changes of brain function and structure, and cognitive and motor performance. We found that patients overall learned to increase activity of the target region during training with variable effects on cognitive and motor behavior. Improved cognitive and motor performance after training predicted increases in pre-SMA grey matter volume, fMRI activity in the left putamen, and increased SMA-left putamen functional connectivity. Although we did not directly target the putamen and corticostriatal connectivity during neurofeedback training, our results suggest that training the SMA can lead to regulation of associated networks with beneficial effects in behavior. We conclude that neurofeedback training can induce plasticity in patients with Huntington's disease despite the presence of neurodegeneration, and the effects of training a single region may engage other regions and circuits implicated in disease pathology.
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Affiliation(s)
- Marina Papoutsi
- UCL Huntington's Disease Centre, Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Wellcome Trust Centre for NeuroimagingInstitute of Neurology, University College LondonLondonUnited Kingdom
| | | | - Ralf Reilmann
- George Huntington Institute and Department of RadiologyUniversity of MuensterMünsterGermany
- Section for Neurodegeneration and Hertie Institute for Clinical Brain Research, University of TuebingenTübingenGermany
| | - Geraint Rees
- Wellcome Trust Centre for NeuroimagingInstitute of Neurology, University College LondonLondonUnited Kingdom
- Institute of Cognitive Neuroscience, University College LondonLondonUnited Kingdom
| | - Sarah J Tabrizi
- UCL Huntington's Disease Centre, Institute of Neurology, University College LondonLondonUnited Kingdom
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Maksimenko VA, Runnova AE, Zhuravlev MO, Makarov VV, Nedayvozov V, Grubov VV, Pchelintceva SV, Hramov AE, Pisarchik AN. Visual perception affected by motivation and alertness controlled by a noninvasive brain-computer interface. PLoS One 2017; 12:e0188700. [PMID: 29267295 PMCID: PMC5739396 DOI: 10.1371/journal.pone.0188700] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Accepted: 11/11/2017] [Indexed: 11/19/2022] Open
Abstract
The influence of motivation and alertness on brain activity associated with visual perception was studied experimentally using the Necker cube, which ambiguity was controlled by the contrast of its ribs. The wavelet analysis of recorded multichannel electroencephalograms (EEG) allowed us to distinguish two different scenarios while the brain processed the ambiguous stimulus. The first scenario is characterized by a particular destruction of alpha rhythm (8–12 Hz) with a simultaneous increase in beta-wave activity (20–30 Hz), whereas in the second scenario, the beta rhythm is not well pronounced while the alpha-wave energy remains unchanged. The experiments were carried out with a group of financially motivated subjects and another group of unpaid volunteers. It was found that the first scenario occurred mainly in the motivated group. This can be explained by the increased alertness of the motivated subjects. The prevalence of the first scenario was also observed in a group of subjects to whom images with higher ambiguity were presented. We believe that the revealed scenarios can occur not only during the perception of bistable images, but also in other perceptual tasks requiring decision making. The obtained results may have important applications for monitoring and controlling human alertness in situations which need substantial attention. On the base of the obtained results we built a brain-computer interface to estimate and control the degree of alertness in real time.
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Affiliation(s)
- Vladimir A. Maksimenko
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
| | - Anastasia E. Runnova
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
| | - Maksim O. Zhuravlev
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
| | - Vladimir V. Makarov
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
| | - Vladimir Nedayvozov
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
| | - Vadim V. Grubov
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
| | - Svetlana V. Pchelintceva
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
| | - Alexander E. Hramov
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
| | - Alexander N. Pisarchik
- Yuri Gagarin Technical State University of Saratov, Politehnicheskaya, 77, 410054 Saratov, Russia
- Center for Biomedical Technology, Technical University of Madrid, Campus Montegancedo, 28223 Pozuelo de Alarcon, Madrid, Spain
- * E-mail:
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Motivational wheel running reverses cueing behavioural inflexibility in rodents. J Neural Transm (Vienna) 2017; 124:1635-1640. [DOI: 10.1007/s00702-017-1790-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 09/06/2017] [Indexed: 12/11/2022]
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Bassett DS, Khambhati AN. A network engineering perspective on probing and perturbing cognition with neurofeedback. Ann N Y Acad Sci 2017; 1396:126-143. [PMID: 28445589 PMCID: PMC5446287 DOI: 10.1111/nyas.13338] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition.
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Affiliation(s)
- Danielle S. Bassett
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of Electrical and Systems EngineeringUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Ankit N. Khambhati
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvania
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Osacka J, Horvathova L, Majercikova Z, Kiss A. Eff ect of a single asenapine treatment on Fos expression in the brain catecholamine-synthesizing neurons: impact of a chronic mild stress preconditioning. Endocr Regul 2017; 51:73-83. [PMID: 28609288 DOI: 10.1515/enr-2017-0007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE Fos protein expression in catecholamine-synthesizing neurons of the substantia nigra (SN) pars compacta (SNC, A8), pars reticulata (SNR, A9), and pars lateralis (SNL), the ventral tegmental area (VTA, A10), the locus coeruleus (LC, A6) and subcoeruleus (sLC), the ventrolateral pons (PON-A5), the nucleus of the solitary tract (NTS-A2), the area postrema (AP), and the ventrolateral medulla (VLM-A1) was quantitatively evaluated aft er a single administration of asenapine (ASE) (designated for schizophrenia treatment) in male Wistar rats preconditioned with a chronic unpredictable variable mild stress (CMS) for 21 days. Th e aim of the present study was to reveal whether a single ASE treatment may 1) activate Fos expression in the brain areas selected; 2) activate tyrosine hydroxylase (TH)-synthesizing cells displaying Fos presence; and 3) be modulated by CMS preconditioning. METHODS Control (CON), ASE, CMS, and CMS+ASE groups were used. CMS included restraint, social isolation, crowding, swimming, and cold. Th e ASE and CMS+ASE groups received a single dose of ASE (0.3 mg/kg, s.c.) and CON and CMS saline (300 μl/rat, s.c.). The animals were sacrificed 90 min aft er the treatments. Fos protein and TH-labeled immunoreactive perikarya were analyzed on double labeled histological sections and enumerated on captured pictures using combined light and fluorescence microscope illumination. RESULTS Saline or CMS alone did not promote Fos expression in any of the structures investigated. ASE alone or in combination with CMS elicited Fos expression in two parts of the SN (SNC, SNR) and the VTA. Aside from some cells in the central gray tegmental nuclei adjacent to LC, where a small number of Fos profiles occurred, none or negligible Fos occurrence was detected in the other structures investigated including the LC and sLC, PON-A5, NTS-A2, AP, and VLM-A1. CMS preconditioning did not infl uence the level of Fos induction in the SN and VTA elicited by ASE administration. Similarly, the ratio between the amount of free Fos and Fos colocalized with TH was not aff ected by stress preconditioning in the SNC, SNR, and the VTA. CONCLUSIONS Th e present study provides an anatomical/functional knowledge about the nature of the acute ASE treatment on the catecholamine-synthesizing neurons activity in certain brain structures and their missing interplay with the CMS preconditioning.
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Cohen MS, Rissman J, Hovhannisyan M, Castel AD, Knowlton BJ. Free recall test experience potentiates strategy-driven effects of value on memory. J Exp Psychol Learn Mem Cogn 2017; 43:1581-1601. [PMID: 28394160 DOI: 10.1037/xlm0000395] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
People tend to show better memory for information that is deemed valuable or important. By one mechanism, individuals selectively engage deeper, semantic encoding strategies for high value items (Cohen, Rissman, Suthana, Castel, & Knowlton, 2014). By another mechanism, information paired with value or reward is automatically strengthened in memory via dopaminergic projections from midbrain to hippocampus (Shohamy & Adcock, 2010). We hypothesized that the latter mechanism would primarily enhance recollection-based memory, while the former mechanism would strengthen both recollection and familiarity. We also hypothesized that providing interspersed tests during study is a key to encouraging selective engagement of strategies. To test these hypotheses, we presented participants with sets of words, and each word was associated with a high or low point value. In some experiments, free recall tests were given after each list. In all experiments, a recognition test was administered 5 minutes after the final word list. Process dissociation was accomplished via remember/know judgments at recognition, a recall test probing both item memory and memory for a contextual detail (word plurality), and a task dissociation combining a recognition test for plurality (intended to probe recollection) with a speeded item recognition test (to probe familiarity). When recall tests were administered after study lists, high value strengthened both recollection and familiarity. When memory was not tested after each study list, but rather only at the end, value increased recollection but not familiarity. These dual process dissociations suggest that interspersed recall tests guide learners' use of metacognitive control to selectively apply effective encoding strategies. (PsycINFO Database Record
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Affiliation(s)
- Michael S Cohen
- Department of Psychology, University of California, Los Angeles
| | - Jesse Rissman
- Department of Psychology, University of California, Los Angeles
| | | | - Alan D Castel
- Department of Psychology, University of California, Los Angeles
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Chomiak T, Watts A, Meyer N, Pereira FV, Hu B. A training approach to improve stepping automaticity while dual-tasking in Parkinson's disease: A prospective pilot study. Medicine (Baltimore) 2017; 96:e5934. [PMID: 28151878 PMCID: PMC5293441 DOI: 10.1097/md.0000000000005934] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Deficits in motor movement automaticity in Parkinson's disease (PD), especially during multitasking, are early and consistent hallmarks of cognitive function decline, which increases fall risk and reduces quality of life. This study aimed to test the feasibility and potential efficacy of a wearable sensor-enabled technological platform designed for an in-home music-contingent stepping-in-place (SIP) training program to improve step automaticity during dual-tasking (DT). METHODS This was a 4-week prospective intervention pilot study. The intervention uses a sensor system and algorithm that runs off the iPod Touch which calculates step height (SH) in real-time. These measurements were then used to trigger auditory (treatment group, music; control group, radio podcast) playback in real-time through wireless headphones upon maintenance of repeated large amplitude stepping. With small steps or shuffling, auditory playback stops, thus allowing participants to use anticipatory motor control to regain positive feedback. Eleven participants were recruited from an ongoing trial (Trial Number: ISRCTN06023392). Fear of falling (FES-I), general cognitive functioning (MoCA), self-reported freezing of gait (FOG-Q), and DT step automaticity were evaluated. RESULTS While we found no significant effect of training on FES-I, MoCA, or FOG-Q, we did observe a significant group (music vs podcast) by training interaction in DT step automaticity (P<0.01). CONCLUSION Wearable device technology can be used to enable musically-contingent SIP training to increase motor automaticity for people living with PD. The training approach described here can be implemented at home to meet the growing demand for self-management of symptoms by patients.
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Sitaram R, Ros T, Stoeckel L, Haller S, Scharnowski F, Lewis-Peacock J, Weiskopf N, Blefari ML, Rana M, Oblak E, Birbaumer N, Sulzer J. Closed-loop brain training: the science of neurofeedback. Nat Rev Neurosci 2016; 18:86-100. [PMID: 28003656 DOI: 10.1038/nrn.2016.164] [Citation(s) in RCA: 540] [Impact Index Per Article: 67.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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