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Storm JF, Klink PC, Aru J, Senn W, Goebel R, Pigorini A, Avanzini P, Vanduffel W, Roelfsema PR, Massimini M, Larkum ME, Pennartz CMA. An integrative, multiscale view on neural theories of consciousness. Neuron 2024; 112:1531-1552. [PMID: 38447578 DOI: 10.1016/j.neuron.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 12/20/2023] [Accepted: 02/05/2024] [Indexed: 03/08/2024]
Abstract
How is conscious experience related to material brain processes? A variety of theories aiming to answer this age-old question have emerged from the recent surge in consciousness research, and some are now hotly debated. Although most researchers have so far focused on the development and validation of their preferred theory in relative isolation, this article, written by a group of scientists representing different theories, takes an alternative approach. Noting that various theories often try to explain different aspects or mechanistic levels of consciousness, we argue that the theories do not necessarily contradict each other. Instead, several of them may converge on fundamental neuronal mechanisms and be partly compatible and complementary, so that multiple theories can simultaneously contribute to our understanding. Here, we consider unifying, integration-oriented approaches that have so far been largely neglected, seeking to combine valuable elements from various theories.
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Affiliation(s)
- Johan F Storm
- The Brain Signaling Group, Division of Physiology, IMB, Faculty of Medicine, University of Oslo, Domus Medica, Sognsvannsveien 9, Blindern, 0317 Oslo, Norway.
| | - P Christiaan Klink
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Experimental Psychology, Helmholtz Institute, Utrecht University, 3584 CS Utrecht, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Paris 75012, France
| | - Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Walter Senn
- Department of Physiology, University of Bern, Bern, Switzerland
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
| | - Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan 20122, Italy
| | - Pietro Avanzini
- Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, 43125 Parma, Italy
| | - Wim Vanduffel
- Department of Neurosciences, Laboratory of Neuro and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
| | - Pieter R Roelfsema
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Paris 75012, France; Department of Integrative Neurophysiology, VU University, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands; Department of Neurosurgery, Academisch Medisch Centrum, Postbus 22660, 1100 DD Amsterdam, the Netherlands
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan 20157, Italy; Istituto di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan 20122, Italy; Azrieli Program in Brain, Mind and Consciousness, Canadian Institute for Advanced Research (CIFAR), Toronto, ON M5G 1M1, Canada
| | - Matthew E Larkum
- Institute of Biology, Humboldt University Berlin, Berlin, Germany; Neurocure Center for Excellence, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Sciencepark 904, Amsterdam 1098 XH, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
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2
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Senden M, van Albada SJ, Pezzulo G, Falotico E, Hashim I, Kroner A, Kurth AC, Lanillos P, Narayanan V, Pennartz C, Petrovici MA, Steffen L, Weidler T, Goebel R. Modular-integrative modeling: a new framework for building brain models that blend biological realism and functional performance. Natl Sci Rev 2024; 11:nwad318. [PMID: 38577673 PMCID: PMC10989280 DOI: 10.1093/nsr/nwad318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 12/04/2023] [Accepted: 12/18/2023] [Indexed: 04/06/2024] Open
Abstract
This Perspective presents the Modular-Integrative Modeling approach, a novel framework in neuroscience for developing brain models that blend biological realism with functional performance to provide a holistic view on brain function in interaction with the body and environment.
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Affiliation(s)
- Mario Senden
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Sacha J van Albada
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institut Brain Structure-Function Relationships (INM-10), Jülich Research Center, Germany
- Institute of Zoology, University of Cologne, Germany
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Italy
| | - Egidio Falotico
- The BioRobotics Institute, Scuola Superiore Sant’Anna, Italy
| | - Ibrahim Hashim
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Alexander Kroner
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Anno C Kurth
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institut Brain Structure-Function Relationships (INM-10), Jülich Research Center, Germany
- RWTH Aachen University, Germany
| | - Pablo Lanillos
- Donders Institute for Brain, Cognition and Behavior, Radboud University, The Netherlands
| | - Vaishnavi Narayanan
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Cyriel Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, The Netherlands
| | | | - Lea Steffen
- FZI Research Center of Information Technology, Germany
| | - Tonio Weidler
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, The Netherlands
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da Costa D, Kornemann L, Goebel R, Senden M. Convolutional neural networks develop major organizational principles of early visual cortex when enhanced with retinal sampling. Sci Rep 2024; 14:8980. [PMID: 38637554 PMCID: PMC11026486 DOI: 10.1038/s41598-024-59376-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 04/09/2024] [Indexed: 04/20/2024] Open
Abstract
Primate visual cortex exhibits key organizational principles: cortical magnification, eccentricity-dependent receptive field size and spatial frequency tuning as well as radial bias. We provide compelling evidence that these principles arise from the interplay of the non-uniform distribution of retinal ganglion cells, and a quasi-uniform convergence rate from the retina to the cortex. We show that convolutional neural networks outfitted with a retinal sampling layer, which resamples images according to retinal ganglion cell density, develop these organizational principles. Surprisingly, our results indicate that radial bias is spatial-frequency dependent and only manifests for high spatial frequencies. For low spatial frequencies, the bias shifts towards orthogonal orientations. These findings introduce a novel hypothesis about the origin of radial bias. Quasi-uniform convergence limits the range of spatial frequencies (in retinal space) that can be resolved, while retinal sampling determines the spatial frequency content throughout the retina.
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Affiliation(s)
- Danny da Costa
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands.
- Maastricht Brain Imaging Centre, Maastricht University, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands.
| | - Lukas Kornemann
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands
- University of Bonn, Regina-Pacis-Weg 3, 53113, Bonn, Germany
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre, Maastricht University, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands
| | - Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands.
- Maastricht Brain Imaging Centre, Maastricht University, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands.
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Dresbach S, Huber R, Gulban OF, Pizzuti A, Trampel R, Ivanov D, Weiskopf N, Goebel R. Characterisation of laminar and vascular spatiotemporal dynamics of CBV and BOLD signals using VASO and ME-GRE at 7T in humans. bioRxiv 2024:2024.01.25.576050. [PMID: 38410457 PMCID: PMC10896347 DOI: 10.1101/2024.01.25.576050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Interpretation of cortical laminar functional magnetic resonance imaging (fMRI) activity requires detailed knowledge of the spatiotemporal haemodynamic response across vascular compartments due to the well-known vascular biases (e.g. the draining veins). Further complications arise from the spatiotemporal hemodynamic response that differs depending on the duration of stimulation. This information is crucial for future studies using depth-dependent cerebral blood volume (CBV) measurements, which promise higher specificity for the cortical microvasculature than the blood oxygenation level dependent (BOLD) contrast. To date, direct information about CBV dynamics with respect to stimulus duration, cortical depth and vasculature is missing in humans. Therefore, we characterized the cortical depth-dependent CBV-haemodynamic responses across a wide set of stimulus durations with 0.9 mm isotropic spatial and 0.785 seconds effective temporal resolution in humans using slice-selective slab-inversion vascular space occupancy (SS-SI VASO). Additionally, we investigated signal contributions from macrovascular compartments using fine-scale vascular information from multi-echo gradient-echo (ME-GRE) data at 0.35 mm isotropic resolution. In total, this resulted in >7.5h of scanning per participant (n=5). We have three major findings: (I) While we could demonstrate that 1 second stimulation is viable using VASO, more than 12 seconds stimulation provides better CBV responses in terms of specificity to microvasculature, but durations beyond 24 seconds of stimulation may be wasteful for certain applications. (II) We observe that CBV responses show dilation patterns across the cortex. (III) While we found increasingly strong BOLD signal responses in vessel-dominated voxels with longer stimulation durations, we found increasingly strong CBV signal responses in vessel-dominated voxels only until 4 second stimulation durations. After 4 seconds, only the signal from non-vessel dominated voxels kept increasing. This might explain why CBV responses are more specific to the underlying neuronal activity for long stimulus durations.
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Affiliation(s)
- Sebastian Dresbach
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Renzo Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- National Institutes of Health, Bethesda, MD, USA
| | - Omer Faruk Gulban
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Brain innovation, Maastricht, the Netherlands
| | - Alessandra Pizzuti
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Brain innovation, Maastricht, the Netherlands
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Dimo Ivanov
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth System Sciences, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3AR, UK
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Brain innovation, Maastricht, the Netherlands
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Weidler T, Goebel R, Senden M. AngoraPy: A Python toolkit for modeling anthropomorphic goal-driven sensorimotor systems. Front Neuroinform 2023; 17:1223687. [PMID: 38204578 PMCID: PMC10777840 DOI: 10.3389/fninf.2023.1223687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 11/27/2023] [Indexed: 01/12/2024] Open
Abstract
Goal-driven deep learning increasingly supplements classical modeling approaches in computational neuroscience. The strength of deep neural networks as models of the brain lies in their ability to autonomously learn the connectivity required to solve complex and ecologically valid tasks, obviating the need for hand-engineered or hypothesis-driven connectivity patterns. Consequently, goal-driven models can generate hypotheses about the neurocomputations underlying cortical processing that are grounded in macro- and mesoscopic anatomical properties of the network's biological counterpart. Whereas, goal-driven modeling is already becoming prevalent in the neuroscience of perception, its application to the sensorimotor domain is currently hampered by the complexity of the methods required to train models comprising the closed sensation-action loop. This paper describes AngoraPy, a Python library that mitigates this obstacle by providing researchers with the tools necessary to train complex recurrent convolutional neural networks that model the human sensorimotor system. To make the technical details of this toolkit more approachable, an illustrative example that trains a recurrent toy model on in-hand object manipulation accompanies the theoretical remarks. An extensive benchmark on various classical, 3D robotic, and anthropomorphic control tasks demonstrates AngoraPy's general applicability to a wide range of tasks. Together with its ability to adaptively handle custom architectures, the flexibility of this toolkit demonstrates its power for goal-driven sensorimotor modeling.
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Affiliation(s)
- Tonio Weidler
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
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Heitmann C, Zhan M, Linke M, Hölig C, Kekunnaya R, van Hoof R, Goebel R, Röder B. Early visual experience refines the retinotopic organization within and across visual cortical regions. Curr Biol 2023; 33:4950-4959.e4. [PMID: 37918397 DOI: 10.1016/j.cub.2023.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 09/29/2023] [Accepted: 10/06/2023] [Indexed: 11/04/2023]
Abstract
Early visual areas are retinotopically organized in human and non-human primates. Population receptive field (pRF) size increases with eccentricity and from lower- to higher-level visual areas. Furthermore, the cortical magnification factor (CMF), a measure of how much cortical space is devoted to each degree of visual angle, is typically larger for foveal as opposed to peripheral regions of the visual field. Whether this fine-scale organization within and across visual areas depends on early visual experience has yet been unknown. Here, we employed 7T functional magnetic resonance imaging pRF mapping to assess the retinotopic organization of early visual regions (i.e., V1, V2, and V3) in eight sight recovery individuals with a history of congenital blindness until a maximum of 4 years of age. Compared with sighted controls, foveal pRF sizes in these individuals were larger, and pRF sizes did not show the typical increase with eccentricity and down the visual cortical processing stream (V1-V2-V3). Cortical magnification was overall diminished and decreased less from foveal to parafoveal visual field locations. Furthermore, cortical magnification correlated with visual acuity in sight recovery individuals. The results of this study suggest that early visual experience is essential for refining a presumably innate prototypical retinotopic organization in humans within and across visual areas, which seems to be crucial for acquiring full visual capabilities.
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Affiliation(s)
- Carolin Heitmann
- Biological Psychology and Neuropsychology Lab, Faculty of Psychology and Movement Sciences, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany.
| | - Minye Zhan
- U992 (Cognitive neuroimaging unit), NeuroSpin, INSERM-CEA, 91191 Gif sur Yvette, France
| | - Madita Linke
- Biological Psychology and Neuropsychology Lab, Faculty of Psychology and Movement Sciences, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany
| | - Cordula Hölig
- Biological Psychology and Neuropsychology Lab, Faculty of Psychology and Movement Sciences, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany
| | - Ramesh Kekunnaya
- U992 (Cognitive neuroimaging unit), NeuroSpin, INSERM-CEA, 91191 Gif sur Yvette, France
| | - Rick van Hoof
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, the Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, the Netherlands; Department of Development and Research, Brain Innovation B.V., Oxfordlaan 55, 6229 EV Maastricht, the Netherlands
| | - Brigitte Röder
- Biological Psychology and Neuropsychology Lab, Faculty of Psychology and Movement Sciences, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany; Child Sight Institute, Jasti V. Ramanamma Children's Eye Care Center, LV Prasad Eye Institute, Hyderabad, Telangana 500034, India.
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Bressler RA, Raible S, Lührs M, Tier R, Goebel R, Linden DE. No threat: Emotion regulation neurofeedback for police special forces recruits. Neuropsychologia 2023; 190:108699. [PMID: 37816480 DOI: 10.1016/j.neuropsychologia.2023.108699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 08/15/2023] [Accepted: 10/06/2023] [Indexed: 10/12/2023]
Abstract
Police officers of the Special Forces are confronted with highly demanding situations in terms of stress, high tension and threats to their lives. Their tasks are specifically high-risk operations, such as arrests of armed suspects and anti-terror interventions. Improving the emotion regulation skills of police officers might be a vital investment, supporting them to stay calm and focused. A promising approach is training emotion regulation by using real-time (rt-) fMRI neurofeedback. Specifically, downregulating activity in key areas of the fronto-limbic emotion regulation network in the presence of threatening stimuli. Thirteen recruits of the Dutch police special forces underwent six weekly rt-fMRI sessions, receiving neurofeedback from individualized regions of their emotion regulation network. Their task was to reduce the image size of threatening images, wherein the image size represented their brain activity. A reduction in image size represented successful downregulation. Participants were free to use their preferred regulation strategy. A control group of fifteen recruits received no neurofeedback. Both groups completed behavioural tests (image rating on evoked valence and arousal, questionnaire) before and after the neurofeedback training. We hypothesized that the neurofeedback group would improve in downregulation and would score better than the control group on the behavioural tests after the neurofeedback training. Neurofeedback training resulted in a significant decrease in image size (t(12) = 2.82, p = .015) and a trend towards decreased activation in the target regions (t(10) = 1.82, p = .099) from the first to the last session. Notably, subjects achieved downregulation below the pre-stimulus baseline in the last two sessions. No relevant differences between groups were found in the behavioural tasks. Through the training of rt-fMRI neurofeedback, participants learned to downregulate the activity in individualized areas of the emotion regulation network, by using their own preferred strategies. The lack of behavioural between-group differences may be explained by floor effects. Tasks that are close to real-life situations may be needed to uncover behavioural correlates of this emotion regulation training.
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Affiliation(s)
- Ruben Andreas Bressler
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands.
| | - Sophie Raible
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands
| | - Michael Lührs
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands; Brain Innovation, Maastricht, The Netherlands, Oxfordlaan 55, 6229 EV, Maastricht, the Netherlands
| | - Ralph Tier
- Landelijke Eenheid, Dienst Speciale Interventies, Hoofdstraat 54, 3972 LB, Postbus 100, 3970 AC, Driebergen, the Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands; Brain Innovation, Maastricht, The Netherlands, Oxfordlaan 55, 6229 EV, Maastricht, the Netherlands
| | - David E Linden
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands
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Dresbach S, Huber LR, Gulban OF, Goebel R. Layer-fMRI VASO with short stimuli and event-related designs at 7 T. Neuroimage 2023; 279:120293. [PMID: 37562717 DOI: 10.1016/j.neuroimage.2023.120293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/06/2023] [Accepted: 07/22/2023] [Indexed: 08/12/2023] Open
Abstract
Layers and columns are the dominant processing units in the human (neo)cortex at the mesoscopic scale. While the blood oxygenation dependent (BOLD) signal has a high detection sensitivity, it is biased towards unwanted signals from large draining veins at the cortical surface. The additional fMRI contrast of vascular space occupancy (VASO) has the potential to augment the neuroscientific interpretability of layer-fMRI results by means of capturing complementary information of locally specific changes in cerebral blood volume (CBV). Specifically, VASO is not subject to unwanted sensitivity amplifications of large draining veins. Because of constrained sampling efficiency, it has been mainly applied in combination with efficient block task designs and long trial durations. However, to study cognitive processes in neuroscientific contexts, or probe vascular reactivity, short stimulation periods are often necessary. Here, we developed a VASO acquisition procedure with a short acquisition period and sub-millimeter resolution. During visual event-related stimulation, we show reliable responses in visual cortices within a reasonable number of trials (∼20). Furthermore, the short TR and high spatial specificity of our VASO implementation enabled us to show differences in laminar reactivity and onset times. Finally, we explore the generalizability to a different stimulus modality (somatosensation). With this, we showed that CBV-sensitive VASO provides the means to capture layer-specific haemodynamic responses with high spatio-temporal resolution and is able to be used with event-related paradigms.
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Affiliation(s)
- Sebastian Dresbach
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Laurentius Renzo Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; National Institute of Health, Bethesda, DC, USA
| | - Omer Faruk Gulban
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; Brain Innovation, Maastricht, Netherlands
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; Brain Innovation, Maastricht, Netherlands
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Jia K, Goebel R, Kourtzi Z. Ultra-High Field Imaging of Human Visual Cognition. Annu Rev Vis Sci 2023; 9:479-500. [PMID: 37137282 DOI: 10.1146/annurev-vision-111022-123830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e., submillimeter resolution) tool that allows us to probe laminar and columnar circuits, distinguish bottom-up versus top-down pathways, and map small subcortical areas. We review recent work demonstrating that UHF fMRI provides a robust methodology for imaging the brain across cortical depths and columns that provides insights into the brain's organization and functions at unprecedented spatial resolution, advancing our understanding of the fine-scale computations and interareal communication that support visual cognition.
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Affiliation(s)
- Ke Jia
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom;
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom;
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10
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Van de Wauw C, Riecke L, Goebel R, Kaas A, Sorger B. Talking with hands and feet: Selective somatosensory attention and fMRI enable robust and convenient brain-based communication. Neuroimage 2023; 276:120172. [PMID: 37230207 DOI: 10.1016/j.neuroimage.2023.120172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 03/07/2023] [Accepted: 05/15/2023] [Indexed: 05/27/2023] Open
Abstract
In brain-based communication, voluntarily modulated brain signals (instead of motor output) are utilized to interact with the outside world. The possibility to circumvent the motor system constitutes an important alternative option for severely paralyzed. Most communication brain-computer interface (BCI) paradigms require intact visual capabilities and impose a high cognitive load, but for some patients, these requirements are not given. In these situations, a better-suited, less cognitively demanding information-encoding approach may exploit auditorily-cued selective somatosensory attention to vibrotactile stimulation. Here, we propose, validate and optimize a novel communication-BCI paradigm using differential fMRI activation patterns evoked by selective somatosensory attention to tactile stimulation of the right hand or left foot. Using cytoarchitectonic probability maps and multi-voxel pattern analysis (MVPA), we show that the locus of selective somatosensory attention can be decoded from fMRI-signal patterns in (especially primary) somatosensory cortex with high accuracy and reliability, with the highest classification accuracy (85.93%) achieved when using Brodmann area 2 (SI-BA2) at a probability level of 0.2. Based on this outcome, we developed and validated a novel somatosensory attention-based yes/no communication procedure and demonstrated its high effectiveness even when using only a limited amount of (MVPA) training data. For the BCI user, the paradigm is straightforward, eye-independent, and requires only limited cognitive functioning. In addition, it is BCI-operator friendly given its objective and expertise-independent procedure. For these reasons, our novel communication paradigm has high potential for clinical applications.
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Affiliation(s)
- Cynthia Van de Wauw
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands.
| | - Lars Riecke
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands; Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Amanda Kaas
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Bettina Sorger
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
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11
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Pizzuti A, Huber L(R, Gulban OF, Benitez-Andonegui A, Peters J, Goebel R. Imaging the columnar functional organization of human area MT+ to axis-of-motion stimuli using VASO at 7 Tesla. Cereb Cortex 2023; 33:8693-8711. [PMID: 37254796 PMCID: PMC10321107 DOI: 10.1093/cercor/bhad151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 04/15/2023] [Accepted: 04/16/2023] [Indexed: 06/01/2023] Open
Abstract
Cortical columns of direction-selective neurons in the motion sensitive area (MT) have been successfully established as a microscopic feature of the neocortex in animals. The same property has been investigated at mesoscale (<1 mm) in the homologous brain area (hMT+, V5) in living humans by using ultra-high field functional magnetic resonance imaging (fMRI). Despite the reproducibility of the selective response to axis-of-motion stimuli, clear quantitative evidence for the columnar organization of hMT+ is still lacking. Using cerebral blood volume (CBV)-sensitive fMRI at 7 Tesla with submillimeter resolution and high spatial specificity to microvasculature, we investigate the columnar functional organization of hMT+ in 5 participants perceiving axis-of-motion stimuli for both blood oxygenation level dependent (BOLD) and vascular space occupancy (VASO) contrast mechanisms provided by the used slice-selective slab-inversion (SS-SI)-VASO sequence. With the development of a new searchlight algorithm for column detection, we provide the first quantitative columnarity map that characterizes the entire 3D hMT+ volume. Using voxel-wise measures of sensitivity and specificity, we demonstrate the advantage of using CBV-sensitive fMRI to detect mesoscopic cortical features by revealing higher specificity of axis-of-motion cortical columns for VASO as compared to BOLD contrast. These voxel-wise metrics also provide further insights on how to mitigate the highly debated draining veins effect. We conclude that using CBV-VASO fMRI together with voxel-wise measurements of sensitivity, specificity and columnarity offers a promising avenue to quantify the mesoscopic organization of hMT+ with respect to axis-of-motion stimuli. Furthermore, our approach and methodological developments are generalizable and applicable to other human brain areas where similar mesoscopic research questions are addressed.
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Affiliation(s)
- Alessandra Pizzuti
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
- Brain Innovation, Maastricht, The Netherlands
| | - Laurentius (Renzo) Huber
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
| | - Omer Faruk Gulban
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
- Brain Innovation, Maastricht, The Netherlands
| | | | - Judith Peters
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
- Brain Innovation, Maastricht, The Netherlands
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12
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Ivanov D, De Martino F, Formisano E, Fritz FJ, Goebel R, Huber L, Kashyap S, Kemper VG, Kurban D, Roebroeck A, Sengupta S, Sorger B, Tse DHY, Uludağ K, Wiggins CJ, Poser BA. Magnetic resonance imaging at 9.4 T: the Maastricht journey. MAGMA 2023; 36:159-173. [PMID: 37081247 PMCID: PMC10140139 DOI: 10.1007/s10334-023-01080-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/18/2023] [Accepted: 03/20/2023] [Indexed: 04/22/2023]
Abstract
The 9.4 T scanner in Maastricht is a whole-body magnet with head gradients and parallel RF transmit capability. At the time of the design, it was conceptualized to be one of the best fMRI scanners in the world, but it has also been used for anatomical and diffusion imaging. 9.4 T offers increases in sensitivity and contrast, but the technical ultra-high field (UHF) challenges, such as field inhomogeneities and constraints set by RF power deposition, are exacerbated compared to 7 T. This article reviews some of the 9.4 T work done in Maastricht. Functional imaging experiments included blood oxygenation level-dependent (BOLD) and blood-volume weighted (VASO) fMRI using different readouts. BOLD benefits from shorter T2* at 9.4 T while VASO from longer T1. We show examples of both ex vivo and in vivo anatomical imaging. For many applications, pTx and optimized coils are essential to harness the full potential of 9.4 T. Our experience shows that, while considerable effort was required compared to our 7 T scanner, we could obtain high-quality anatomical and functional data, which illustrates the potential of MR acquisitions at even higher field strengths. The practical challenges of working with a relatively unique system are also discussed.
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Affiliation(s)
- Dimo Ivanov
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands.
| | - Federico De Martino
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Elia Formisano
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Francisco J Fritz
- Institute of Systems Neuroscience, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Laurentius Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Sriranga Kashyap
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada
| | - Valentin G Kemper
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Denizhan Kurban
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Alard Roebroeck
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | | | - Bettina Sorger
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Desmond H Y Tse
- Scannexus BV, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands
| | - Kâmil Uludağ
- Krembil Brain Institute, Koerner Scientist in MR Imaging, University Health Network Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Christopher J Wiggins
- Imaging Core Facility (INM-ICF), Institut für Neurowissenschaften und Medizin, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany
| | - Benedikt A Poser
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
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13
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Bates S, Dumoulin SO, Folkers PJM, Formisano E, Goebel R, Haghnejad A, Helmich RC, Klomp D, van der Kolk AG, Li Y, Nederveen A, Norris DG, Petridou N, Roell S, Scheenen TWJ, Schoonheim MM, Voogt I, Webb A. A vision of 14 T MR for fundamental and clinical science. MAGMA 2023; 36:211-225. [PMID: 37036574 PMCID: PMC10088620 DOI: 10.1007/s10334-023-01081-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 04/11/2023]
Abstract
OBJECTIVE We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set. RESEARCH FIELDS The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes. CONCLUSIONS The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.
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Affiliation(s)
- Steve Bates
- Tesla Engineering Ltd., Water Lane, Storrington, West Sussex, RH20 3EA, UK
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Experimental and Applied Psychology, Vrije University Amsterdam, Amsterdam, The Netherlands
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands
| | | | - Elia Formisano
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | | | - Rick C Helmich
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
- Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Dennis Klomp
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anja G van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yi Li
- Independent Researcher, Magdeburg, Germany
| | - Aart Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands.
- Erwin L. Hahn Institute for Magnetic Resonance Imaging UNESCO World Cultural Heritage Zollverein, Kokereiallee 7, Building C84, 45141, Essen, Germany.
- Department of Clinical Neurophysiology (CNPH), Faculty Science and Technology, University of Twente, Enschede, The Netherlands.
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Stefan Roell
- Neoscan Solutions GmbH, Joseph-von-Fraunhofer-Str. 6, 39106, Magdeburg, Germany
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Ingmar Voogt
- Wavetronica, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Andrew Webb
- Department of Radiology, C.J. Gorter MRI Centre, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands
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14
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Pizzuti A, Gulban O, Huber L, Peters J, Goebel R. FV 6 Neural correlates of human motion perception at mesoscale: An fMRI study at 7 Tesla. Clin Neurophysiol 2023. [DOI: 10.1016/j.clinph.2023.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
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15
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Qubad M, Barnes-Scheufler CV, Schaum M, Raspor E, Rösler L, Peters B, Schiweck C, Goebel R, Reif A, Bittner RA. Improved correspondence of fMRI visual field localizer data after cortex-based macroanatomical alignment. Sci Rep 2022; 12:14310. [PMID: 35995943 PMCID: PMC9395433 DOI: 10.1038/s41598-022-17909-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 08/02/2022] [Indexed: 11/30/2022] Open
Abstract
Studying the visual system with fMRI often requires using localizer paradigms to define regions of interest (ROIs). However, the considerable interindividual variability of the cerebral cortex represents a crucial confound for group-level analyses. Cortex-based alignment (CBA) techniques reliably reduce interindividual macroanatomical variability. Yet, their utility has not been assessed for visual field localizer paradigms, which map specific parts of the visual field within retinotopically organized visual areas. We evaluated CBA for an attention-enhanced visual field localizer, mapping homologous parts of each visual quadrant in 50 participants. We compared CBA with volume-based alignment and a surface-based analysis, which did not include macroanatomical alignment. CBA led to the strongest increase in the probability of activation overlap (up to 86%). At the group level, CBA led to the most consistent increase in ROI size while preserving vertical ROI symmetry. Overall, our results indicate that in addition to the increased signal-to-noise ratio of a surface-based analysis, macroanatomical alignment considerably improves statistical power. These findings confirm and extend the utility of CBA for the study of the visual system in the context of group analyses. CBA should be particularly relevant when studying neuropsychiatric disorders with abnormally increased interindividual macroanatomical variability.
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Affiliation(s)
- Mishal Qubad
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy and Brain Imaging Center, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Catherine V Barnes-Scheufler
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy and Brain Imaging Center, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Michael Schaum
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Eva Raspor
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy and Brain Imaging Center, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Lara Rösler
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy and Brain Imaging Center, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany.,Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Benjamin Peters
- Institute of Medical Psychology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany.,Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Carmen Schiweck
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy and Brain Imaging Center, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Rainer Goebel
- Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.,Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy and Brain Imaging Center, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Robert A Bittner
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy and Brain Imaging Center, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany. .,Ernst Strüngmann Institute for Neuroscience (ESI) in Cooperation With Max Planck Society, Frankfurt am Main, Germany.
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16
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Sanders ZB, Fleming MK, Smejka T, Marzolla MC, Zich C, Rieger SW, Lührs M, Goebel R, Sampaio-Baptista C, Johansen-Berg H. Self-modulation of motor cortex activity after stroke: a randomized controlled trial. Brain 2022; 145:3391-3404. [PMID: 35960166 PMCID: PMC9586541 DOI: 10.1093/brain/awac239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 06/01/2022] [Accepted: 06/20/2022] [Indexed: 11/14/2022] Open
Abstract
Real-time functional MRI neurofeedback allows individuals to self-modulate their ongoing brain activity. This may be a useful tool in clinical disorders that are associated with altered brain activity patterns. Motor impairment after stroke has previously been associated with decreased laterality of motor cortex activity. Here we examined whether chronic stroke survivors were able to use real-time fMRI neurofeedback to increase laterality of motor cortex activity and assessed effects on motor performance and on brain structure and function. We carried out a randomized, double-blind, sham-controlled trial (ClinicalTrials.gov: NCT03775915) in which 24 chronic stroke survivors with mild to moderate upper limb impairment experienced three training days of either Real (n = 12) or Sham (n = 12) neurofeedback. Assessments of brain structure, brain function and measures of upper-limb function were carried out before and 1 week after neurofeedback training. Additionally, measures of upper-limb function were repeated 1 month after neurofeedback training. Primary outcome measures were (i) changes in lateralization of motor cortex activity during movements of the stroke-affected hand throughout neurofeedback training days; and (ii) changes in motor performance of the affected limb on the Jebsen Taylor Test (JTT). Stroke survivors were able to use Real neurofeedback to increase laterality of motor cortex activity within (P = 0.019), but not across, training days. There was no group effect on the primary behavioural outcome measure, which was average JTT performance across all subtasks (P = 0.116). Secondary analysis found improvements in the performance of the gross motor subtasks of the JTT in the Real neurofeedback group compared to Sham (P = 0.010). However, there were no improvements on the Action Research Arm Test or the Upper Extremity Fugl–Meyer score (both P > 0.5). Additionally, decreased white-matter asymmetry of the corticospinal tracts was detected 1 week after neurofeedback training (P = 0.008), indicating that the tracts become more similar with Real neurofeedback. Changes in the affected corticospinal tract were positively correlated with participants neurofeedback performance (P = 0.002). Therefore, here we demonstrate that chronic stroke survivors are able to use functional MRI neurofeedback to self-modulate motor cortex activity in comparison to a Sham control, and that training is associated with improvements in gross hand motor performance and with white matter structural changes.
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Affiliation(s)
- Zeena Britt Sanders
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Melanie K Fleming
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Tom Smejka
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Marilien C Marzolla
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Catharina Zich
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Sebastian W Rieger
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Michael Lührs
- Department of Cognitive Neuroscience, Maastricht University, 6229 EV Maastricht, The Netherlands.,Research Department, Brain Innovation B.V., 6229 EV Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, 6229 EV Maastricht, The Netherlands.,Research Department, Brain Innovation B.V., 6229 EV Maastricht, The Netherlands
| | - Cassandra Sampaio-Baptista
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK.,Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G61 1QH, UK
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
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17
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Ciarlo A, Russo AG, Ponticorvo S, Di Salle F, Lührs M, Goebel R, Esposito F. Semantic fMRI neurofeedback: A Multi-Subject Study at 3 Tesla. J Neural Eng 2022; 19. [PMID: 35561669 DOI: 10.1088/1741-2552/ac6f81] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 05/13/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Real-time fMRI neurofeedback is a non-invasive procedure allowing the self-regulation of brain functions via enhanced self-control of fMRI based neural activation. In semantic real-time fMRI neurofeedback, an estimated relation between multivariate fMRI activation patterns and abstract mental states is exploited for a multi-dimensional feedback stimulus via real-time representational similarity analysis (rt-RSA). Here, we assessed the performances of this framework in a multi-subject multi-session study on a 3T MRI clinical scanner. APPROACH Eighteen healthy volunteers underwent two semantic real-time fMRI neurofeedback sessions on two different days. In each session, participants were first requested to engage in specific mental states while local fMRI patterns of brain activity were recorded during stimulated mental imagery of concrete objects (pattern generation). The obtained neural representations were to be replicated and modulated by the participants in subsequent runs of the same session under the guidance of a rt-RSA generated visual feedback (pattern modulation). Performance indicators were derived from the rt-RSA output to assess individual abilities in replicating (and maintaining over time) a target pattern. Simulations were carried out to assess the impact of the geometric distortions implied by the low-dimensional representation of patterns' dissimilarities in the visual feedback. MAIN RESULTS Sixteen subjects successfully completed both semantic real-time fMRI neurofeedback sessions. Considering some performance indicators, a significant improvement between the first and the second runs, and within run increasing modulation performances were observed, whereas no improvements were found between sessions. Simulations confirmed that in a small percentage of cases visual feedback could be affected by metric distortions due to dimensionality reduction implicit to the rt-RSA approach. SIGNIFICANCE Our results proved the feasibility of the semantic real-time fMRI neurofeedback at 3T, showing that subjects can successfully modulate and maintain a target mental state, guided by rt-RSA derived feedback. Further development is needed to encourage future clinical applications.
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Affiliation(s)
- Assunta Ciarlo
- University of Salerno - Baronissi Campus, Via S. Allende, Baronissi, Campania, 84081, ITALY
| | | | - Sara Ponticorvo
- University of Salerno - Baronissi Campus, Via S. Allende, Baronissi, Campania, 84081, ITALY
| | - Francesco Di Salle
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno - Baronissi Campus, Via S. Allende, Baronissi, Campania, 84081, ITALY
| | - Michael Lührs
- Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, Maastricht, Limburg, 6200 MD, NETHERLANDS
| | - Rainer Goebel
- Faculty of Psychology, University of Maastricht, P.O. Box 616, 6200 MD Maastricht, The Netherlands, Maastricht, 6200 MD, NETHERLANDS
| | - Fabrizio Esposito
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli School of Medicine and Surgery, Piazza L. Miraglia, Napoli, 80138, ITALY
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18
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Tursic A, Eck J, Lührs M, Linden D, Goebel R. Response to Commentary of Dr. Robert T. Thibault and Dr. Hugo Pedder entitled: “Excess significance and power miscalculations in neurofeedback research”. NeuroImage: Clinical 2022; 35:103088. [PMID: 35780661 PMCID: PMC9254157 DOI: 10.1016/j.nicl.2022.103088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 06/16/2022] [Indexed: 11/28/2022] Open
Affiliation(s)
- Anita Tursic
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
| | - Judith Eck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
| | - Michael Lührs
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
| | - David Linden
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
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19
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Nagels-Coune L, Riecke L, Benitez-Andonegui A, Klinkhammer S, Goebel R, De Weerd P, Lührs M, Sorger B. See, Hear, or Feel - to Speak: A Versatile Multiple-Choice Functional Near-Infrared Spectroscopy-Brain-Computer Interface Feasible With Visual, Auditory, or Tactile Instructions. Front Hum Neurosci 2021; 15:784522. [PMID: 34899223 PMCID: PMC8656940 DOI: 10.3389/fnhum.2021.784522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/05/2021] [Indexed: 11/13/2022] Open
Abstract
Severely motor-disabled patients, such as those suffering from the so-called "locked-in" syndrome, cannot communicate naturally. They may benefit from brain-computer interfaces (BCIs) exploiting brain signals for communication and therewith circumventing the muscular system. One BCI technique that has gained attention recently is functional near-infrared spectroscopy (fNIRS). Typically, fNIRS-based BCIs allow for brain-based communication via voluntarily modulation of brain activity through mental task performance guided by visual or auditory instructions. While the development of fNIRS-BCIs has made great progress, the reliability of fNIRS-BCIs across time and environments has rarely been assessed. In the present fNIRS-BCI study, we tested six healthy participants across three consecutive days using a straightforward four-choice fNIRS-BCI communication paradigm that allows answer encoding based on instructions using various sensory modalities. To encode an answer, participants performed a motor imagery task (mental drawing) in one out of four time periods. Answer encoding was guided by either the visual, auditory, or tactile sensory modality. Two participants were tested outside the laboratory in a cafeteria. Answers were decoded from the time course of the most-informative fNIRS channel-by-chromophore combination. Across the three testing days, we obtained mean single- and multi-trial (joint analysis of four consecutive trials) accuracies of 62.5 and 85.19%, respectively. Obtained multi-trial accuracies were 86.11% for visual, 80.56% for auditory, and 88.89% for tactile sensory encoding. The two participants that used the fNIRS-BCI in a cafeteria obtained the best single- (72.22 and 77.78%) and multi-trial accuracies (100 and 94.44%). Communication was reliable over the three recording sessions with multi-trial accuracies of 86.11% on day 1, 86.11% on day 2, and 83.33% on day 3. To gauge the trade-off between number of optodes and decoding accuracy, averaging across two and three promising fNIRS channels was compared to the one-channel approach. Multi-trial accuracy increased from 85.19% (one-channel approach) to 91.67% (two-/three-channel approach). In sum, the presented fNIRS-BCI yielded robust decoding results using three alternative sensory encoding modalities. Further, fNIRS-BCI communication was stable over the course of three consecutive days, even in a natural (social) environment. Therewith, the developed fNIRS-BCI demonstrated high flexibility, reliability and robustness, crucial requirements for future clinical applicability.
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Affiliation(s)
- Laurien Nagels-Coune
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht, Netherlands
- Zorggroep Sint-Kamillus, Bierbeek, Belgium
| | - Lars Riecke
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht, Netherlands
| | - Amaia Benitez-Andonegui
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht, Netherlands
- MEG Core Facility, National Institutes of Mental Health, Bethesda, MD, United States
| | - Simona Klinkhammer
- Department of Psychiatry and Neuropsychology, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht, Netherlands
- Brain Innovation B.V., Maastricht, Netherlands
| | - Peter De Weerd
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht, Netherlands
- Maastricht Centre for Systems Biology, Maastricht University, Maastricht, Netherlands
| | | | - Bettina Sorger
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht, Netherlands
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20
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Bhat S, Lührs M, Goebel R, Senden M. Extremely fast pRF mapping for real-time applications. Neuroimage 2021; 245:118671. [PMID: 34710584 DOI: 10.1016/j.neuroimage.2021.118671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 09/28/2021] [Accepted: 10/20/2021] [Indexed: 11/28/2022] Open
Abstract
Population receptive field (pRF) mapping is a popular tool in computational neuroimaging that allows for the investigation of receptive field properties, their topography and interrelations in health and disease. Furthermore, the possibility to invert population receptive fields provides a decoding model for constructing stimuli from observed cortical activation patterns. This has been suggested to pave the road towards pRF-based brain-computer interface (BCI) communication systems, which would be able to directly decode internally visualized letters from topographically organized brain activity. A major stumbling block for such an application is, however, that the pRF mapping procedure is computationally heavy and time consuming. To address this, we propose a novel and fast pRF mapping procedure that is suitable for real-time applications. The method is built upon hashed-Gaussian encoding of the stimulus, which tremendously reduces computational resources. After the stimulus is encoded, mapping can be performed using either ridge regression for fast offline analyses or gradient descent for real-time applications. We validate our model-agnostic approach in silico, as well as on empirical fMRI data obtained from 3T and 7T MRI scanners. Our approach is capable of estimating receptive fields and their parameters for millions of voxels in mere seconds. This method thus facilitates real-time applications of population receptive field mapping.
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Affiliation(s)
- Salil Bhat
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Michael Lührs
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Research and Development, Brain Innovation B.V., Maastricht, the Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Research and Development, Brain Innovation B.V., Maastricht, the Netherlands; Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, the Netherlands
| | - Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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21
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Krause F, Kogias N, Krentz M, Lührs M, Goebel R, Hermans EJ. Self-regulation of stress-related large-scale brain network balance using real-time fMRI neurofeedback. Neuroimage 2021; 243:118527. [PMID: 34469815 DOI: 10.1016/j.neuroimage.2021.118527] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 08/23/2021] [Accepted: 08/25/2021] [Indexed: 10/20/2022] Open
Abstract
It has recently been shown that acute stress affects the allocation of neural resources between large-scale brain networks, and the balance between the executive control network and the salience network in particular. Maladaptation of this dynamic resource reallocation process is thought to play a major role in stress-related psychopathology, suggesting that stress resilience may be determined by the retained ability to adaptively reallocate neural resources between these two networks. Actively training this ability could hence be a potentially promising way to increase resilience in individuals at risk for developing stress-related symptomatology. Using real-time functional Magnetic Resonance Imaging, the current study investigated whether individuals can learn to self-regulate stress-related large-scale network balance. Participants were engaged in a bidirectional and implicit real-time fMRI neurofeedback paradigm in which they were intermittently provided with a visual representation of the difference signal between the average activation of the salience and executive control networks, and tasked with attempting to self-regulate this signal. Our results show that, given feedback about their performance over three training sessions, participants were able to (1) learn strategies to differentially control the balance between SN and ECN activation on demand, as well as (2) successfully transfer this newly learned skill to a situation where they (a) did not receive any feedback anymore, and (b) were exposed to an acute stressor in form of the prospect of a mild electric stimulation. The current study hence constitutes an important first successful demonstration of neurofeedback training based on stress-related large-scale network balance - a novel approach that has the potential to train control over the central response to stressors in real-life and could build the foundation for future clinical interventions that aim at increasing resilience.
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Affiliation(s)
- Florian Krause
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Nikos Kogias
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Martin Krentz
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Michael Lührs
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Research and Development, Brain Innovation B.V., Maastricht, the Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Research and Development, Brain Innovation B.V., Maastricht, the Netherlands
| | - Erno J Hermans
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
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22
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Huber LR, Poser BA, Bandettini PA, Arora K, Wagstyl K, Cho S, Goense J, Nothnagel N, Morgan AT, van den Hurk J, Müller AK, Reynolds RC, Glen DR, Goebel R, Gulban OF. LayNii: A software suite for layer-fMRI. Neuroimage 2021; 237:118091. [PMID: 33991698 PMCID: PMC7615890 DOI: 10.1016/j.neuroimage.2021.118091] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 02/19/2021] [Accepted: 04/16/2021] [Indexed: 01/06/2023] Open
Abstract
High-resolution fMRI in the sub-millimeter regime allows researchers to resolve brain activity across cortical layers and columns non-invasively. While these high-resolution data make it possible to address novel questions of directional information flow within and across brain circuits, the corresponding data analyses are challenged by MRI artifacts, including image blurring, image distortions, low SNR, and restricted coverage. These challenges often result in insufficient spatial accuracy of conventional analysis pipelines. Here we introduce a new software suite that is specifically designed for layer-specific functional MRI: LayNii. This toolbox is a collection of command-line executable programs written in C/C++ and is distributed opensource and as pre-compiled binaries for Linux, Windows, and macOS. LayNii is designed for layer-fMRI data that suffer from SNR and coverage constraints and thus cannot be straightforwardly analyzed in alternative software packages. Some of the most popular programs of LayNii contain 'layerification' and columnarization in the native voxel space of functional data as well as many other layer-fMRI specific analysis tasks: layer-specific smoothing, model-based vein mitigation of GE-BOLD data, quality assessment of artifact dominated sub-millimeter fMRI, as well as analyses of VASO data.
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Affiliation(s)
| | - Benedikt A Poser
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | | | - Kabir Arora
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Shinho Cho
- CMRR, University of Minneapolis, MN, USA
| | | | | | | | | | | | | | | | - Rainer Goebel
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands; Brain Innovation, Maastricht, the Netherlands
| | - Omer Faruk Gulban
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands; Brain Innovation, Maastricht, the Netherlands
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23
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Marimpis AD, Dimitriadis SI, Goebel R. Dyconnmap: Dynamic connectome mapping-A neuroimaging python module. Hum Brain Mapp 2021; 42:4909-4939. [PMID: 34250674 PMCID: PMC8449119 DOI: 10.1002/hbm.25589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 06/10/2021] [Accepted: 06/25/2021] [Indexed: 11/16/2022] Open
Abstract
Despite recent progress in the analysis of neuroimaging data sets, our comprehension of the main mechanisms and principles which govern human brain cognition and function remains incomplete. Network neuroscience makes substantial efforts to manipulate these challenges and provide real answers. For the last decade, researchers have been modelling brain structure and function via a graph or network that comprises brain regions that are either anatomically connected via tracts or functionally via a more extensive repertoire of functional associations. Network neuroscience is a relatively new multidisciplinary scientific avenue of the study of complex systems by pursuing novel ways to analyze, map, store and model the essential elements and their interactions in complex neurobiological systems, particularly the human brain, the most complex system in nature. Due to a rapid expansion of neuroimaging data sets' size and complexity, it is essential to propose and adopt new empirical tools to track dynamic patterns between neurons and brain areas and create comprehensive maps. In recent years, there is a rapid growth of scientific interest in moving functional neuroimaging analysis beyond simplified group or time‐averaged approaches and sophisticated algorithms that can capture the time‐varying properties of functional connectivity. We describe algorithms and network metrics that can capture the dynamic evolution of functional connectivity under this perspective. We adopt the word ‘chronnectome’ (integration of the Greek word ‘Chronos’, which means time, and connectome) to describe this specific branch of network neuroscience that explores how mutually informed brain activity correlates across time and brain space in a functional way. We also describe how good temporal mining of temporally evolved dynamic functional networks could give rise to the detection of specific brain states over which our brain evolved. This characteristic supports our complex human mind. The temporal evolution of these brain states and well‐known network metrics could give rise to new analytic trends. Functional brain networks could also increase the multi‐faced nature of the dynamic networks revealing complementary information. Finally, we describe a python module (https://github.com/makism/dyconnmap) which accompanies this article and contains a collection of dynamic complex network analytics and measures and demonstrates its great promise for the study of a healthy subject's repeated fMRI scans.
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Affiliation(s)
- Avraam D Marimpis
- Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Neuroinformatics Group, Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.,Brain Innovation B.V, Maastricht, The Netherlands
| | - Stavros I Dimitriadis
- Neuroinformatics Group, Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.,Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, United Kingdom.,Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.,School of Psychology, Cardiff University, Cardiff, United Kingdom.,Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom.,MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Rainer Goebel
- Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Brain Innovation B.V, Maastricht, The Netherlands
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24
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Abstract
Ultra-high field (UHF) neuroimaging affords the sub-millimeter resolution that allows researchers to interrogate brain computations at a finer scale than that afforded by standard fMRI techniques. Here, we present a step-by-step protocol for using UHF imaging (Siemens Terra 7T scanner) to measure activity in the human brain. We outline how to preprocess the data using a pipeline that combines tools from SPM, FreeSurfer, ITK-SNAP, and BrainVoyager and correct for vasculature-related confounders to improve the spatial accuracy of the fMRI signal. For complete details on the use and execution of this protocol, please refer to Jia et al. (2020) and Zamboni et al. (2020).
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Affiliation(s)
- Ke Jia
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Elisa Zamboni
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Catarina Rua
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Valentin Kemper
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6200 MD, the Netherlands
| | - Adrian Ka Tsun Ng
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
- Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Christopher T. Rodgers
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Guy Williams
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6200 MD, the Netherlands
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
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25
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Huber LR, Poser BA, Kaas AL, Fear EJ, Dresbach S, Berwick J, Goebel R, Turner R, Kennerley AJ. Validating layer-specific VASO across species. Neuroimage 2021; 237:118195. [PMID: 34038769 DOI: 10.1016/j.neuroimage.2021.118195] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 05/17/2021] [Accepted: 05/19/2021] [Indexed: 01/27/2023] Open
Abstract
Cerebral blood volume (CBV) has been shown to be a robust and important physiological parameter for quantitative interpretation of functional (f)MRI, capable of delivering highly localized mapping of neural activity. Indeed, with recent advances in ultra-high-field (≥7T) MRI hardware and associated sequence libraries, it has become possible to capture non-invasive CBV weighted fMRI signals across cortical layers. One of the most widely used approaches to achieve this (in humans) is through vascular-space-occupancy (VASO) fMRI. Unfortunately, the exact contrast mechanisms of layer-dependent VASO fMRI have not been validated for human fMRI and thus interpretation of such data is confounded. Here we validate the signal source of layer-dependent SS-SI VASO fMRI using multi-modal imaging in a rat model in response to neuronal activation (somatosensory cortex) and respiratory challenge (hypercapnia). In particular VASO derived CBV measures are directly compared to concurrent measures of total haemoglobin changes from high resolution intrinsic optical imaging spectroscopy (OIS). Quantified cortical layer profiling is demonstrated to be in agreement between VASO and contrast enhanced fMRI (using monocrystalline iron oxide nanoparticles, MION). Responses show high spatial localisation to layers of cortical processing independent of confounding large draining veins which can hamper BOLD fMRI studies, (depending on slice positioning). Thus, a cross species comparison is enabled using VASO as a common measure. We find increased VASO based CBV reactivity (3.1 ± 1.2 fold increase) in humans compared to rats. Together, our findings confirm that the VASO contrast is indeed a reliable estimate of layer-specific CBV changes. This validation study increases the neuronal interpretability of human layer-dependent VASO fMRI as an appropriate method in neuroscience application studies, in which the presence of large draining intracortical and pial veins limits neuroscientific inference with BOLD fMRI.
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Affiliation(s)
- Laurentius Renzo Huber
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands.
| | - Benedikt A Poser
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Amanda L Kaas
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Elizabeth J Fear
- Hull-York-Medical-School (HYMS), University of York, York, United Kingdom
| | - Sebastian Dresbach
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Jason Berwick
- Department of Psychology, University of Sheffield, Sheffield, United Kingdom
| | - Rainer Goebel
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Robert Turner
- Neurophysics Department Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
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26
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van Zutphen L, Siep N, Jacob GA, Domes G, Sprenger A, Willenborg B, Goebel R, Tüscher O, Arntz A. Impulse control under emotion processing: an fMRI investigation in borderline personality disorder compared to non-patients and cluster-C personality disorder patients. Brain Imaging Behav 2021; 14:2107-2121. [PMID: 31321661 PMCID: PMC7647993 DOI: 10.1007/s11682-019-00161-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Impulsivity is a characteristic syndromal and neurobehavioral feature of borderline personality disorder (BPD). Research suggests an important interaction between high negative emotions and low behavioral inhibition in BPD. However, knowledge about the generalizability across stimulus categories and diagnosis specificity is limited. We investigated neural correlates of hypothesized impaired response inhibition of BPD patients to negative, positive and erotic stimuli, by comparing them to non-patients and cluster-C personality disorder patients. During fMRI scanning, 53 BPD patients, 34 non-patients and 20 cluster-C personality disorder patients completed an affective go/no-go task, including social pictures. BPD patients showed more omission errors than non-patients, independent of the stimulus category. Furthermore, BPD patients showed higher activity in the inferior parietal lobule and frontal eye fields when inhibiting negative versus neutral stimuli. Activity of the inferior parietal lobule correlated positively with the BPD checklist subscale impulsivity. When inhibiting emotional stimuli, BPD patients showed an altered brain activity in the inferior parietal lobe and frontal eye fields, whereas previously shown dysfunctional prefrontal activity was not replicated. BPD patients showed a general responsivity across stimulus categories in the frontal eye fields, whereas effects in the inferior parietal lobe were specific for negative stimuli. Results of diagnosis specificity support a dimensional rather than a categorical differentiation between BPD and cluster-C patients during inhibition of social emotional stimuli. Supported by behavioral results, BPD patients showed no deficiencies in emotionally modulated response inhibition per se but the present findings rather hint at attentional difficulties for emotional information.
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Affiliation(s)
- Linda van Zutphen
- Department of Clinical Psychological Science, Faculty of Psychology and Neuroscience, Maastricht University, PO Box 616, 6200, MD, Maastricht, the Netherlands.
| | - Nicolette Siep
- Department of Clinical Psychological Science, Faculty of Psychology and Neuroscience, Maastricht University, PO Box 616, 6200, MD, Maastricht, the Netherlands
| | - Gitta A Jacob
- Department of Clinical Psychology and Psychotherapy, University of Freiburg, Freiburg, Germany
| | - Gregor Domes
- Department of Psychology, Laboratory for Biological and Personality Psychology, University of Freiburg, Freiburg, Germany.,Freiburg Brain Imaging Center, University Medical Center Freiburg, Freiburg, Germany.,Department of Biological and Clinical Psychology, University of Trier, Trier, Germany
| | - Andreas Sprenger
- Departments of Neurology and Psychology, University of Lübeck, Lübeck, Germany
| | - Bastian Willenborg
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands.,Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, the Netherlands
| | - Oliver Tüscher
- Department of Clinical Psychology and Psychotherapy, University of Freiburg, Freiburg, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Mainz, Germany
| | - Arnoud Arntz
- Department of Clinical Psychological Science, Faculty of Psychology and Neuroscience, Maastricht University, PO Box 616, 6200, MD, Maastricht, the Netherlands.,Department of Clinical Psychology, University of Amsterdam, Amsterdam, the Netherlands
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27
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Benitez-Andonegui A, Lührs M, Nagels-Coune L, Ivanov D, Goebel R, Sorger B. Guiding functional near-infrared spectroscopy optode-layout design using individual (f)MRI data: effects on signal strength. Neurophotonics 2021; 8:025012. [PMID: 34155480 PMCID: PMC8211086 DOI: 10.1117/1.nph.8.2.025012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 05/11/2021] [Indexed: 05/20/2023]
Abstract
Significance: Designing optode layouts is an essential step for functional near-infrared spectroscopy (fNIRS) experiments as the quality of the measured signal and the sensitivity to cortical regions-of-interest depend on how optodes are arranged on the scalp. This becomes particularly relevant for fNIRS-based brain-computer interfaces (BCIs), where developing robust systems with few optodes is crucial for clinical applications. Aim: Available resources often dictate the approach researchers use for optode-layout design. We investigated whether guiding optode layout design using different amounts of subject-specific magnetic resonance imaging (MRI) data affects the fNIRS signal quality and sensitivity to brain activation when healthy participants perform mental-imagery tasks typically used in fNIRS-BCI experiments. Approach: We compared four approaches that incrementally incorporated subject-specific MRI information while participants performed mental-calculation, mental-rotation, and inner-speech tasks. The literature-based approach (LIT) used a literature review to guide the optode layout design. The probabilistic approach (PROB) employed individual anatomical data and probabilistic maps of functional MRI (fMRI)-activation from an independent dataset. The individual fMRI (iFMRI) approach used individual anatomical and fMRI data, and the fourth approach used individual anatomical, functional, and vascular information of the same subject (fVASC). Results: The four approaches resulted in different optode layouts and the more informed approaches outperformed the minimally informed approach (LIT) in terms of signal quality and sensitivity. Further, PROB, iFMRI, and fVASC approaches resulted in a similar outcome. Conclusions: We conclude that additional individual MRI data lead to a better outcome, but that not all the modalities tested here are required to achieve a robust setup. Finally, we give preliminary advice to efficiently using resources for developing robust optode layouts for BCI and neurofeedback applications.
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Affiliation(s)
- Amaia Benitez-Andonegui
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
- Maastricht University, Laboratory for Cognitive Robotics and Complex Self-Organizing Systems, Department of Data Science and Knowledge Engineering, Maastricht, The Netherlands
- Address all correspondence to Amaia Benitez-Andonegui,
| | - Michael Lührs
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
- Brain Innovation B.V., Research Department, Maastricht, The Netherlands
| | - Laurien Nagels-Coune
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
| | - Dimo Ivanov
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
| | - Rainer Goebel
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
- Brain Innovation B.V., Research Department, Maastricht, The Netherlands
| | - Bettina Sorger
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
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28
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Russo AG, Lührs M, Di Salle F, Esposito F, Goebel R. Towards semantic fMRI neurofeedback: navigating among mental states using real-time representational similarity analysis. J Neural Eng 2021; 18. [PMID: 33684900 DOI: 10.1088/1741-2552/abecc3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 03/08/2021] [Indexed: 11/12/2022]
Abstract
Objective. Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF) is a non-invasive MRI procedure allowing examined participants to learn to self-regulate brain activity by performing mental tasks. A novel two-step rt-fMRI-NF procedure is proposed whereby the feedback display is updated in real-time based on high-level representations of experimental stimuli (e.g. objects to imagine) via real-time representational similarity analysis of multi-voxel patterns of brain activity.Approach. In a localizer session, the stimuli become associated with anchored points on a two-dimensional representational space where distances approximate between-pattern (dis)similarities. In the NF session, participants modulate their brain response, displayed as a movable point, to engage in a specific neural representation. The developed method pipeline is verified in a proof-of-concept rt-fMRI-NF study at 7 T involving a single healthy participant imagining concrete objects. Based on this data and artificial data sets with similar (simulated) spatio-temporal structure and variable (injected) signal and noise, the dependence on noise is systematically assessed.Main results. The participant in the proof-of-concept study exhibited robust activation patterns in the localizer session and managed to control the neural representation of a stimulus towards the selected target in the NF session. The offline analyses validated the rt-fMRI-NF results, showing that the rapid convergence to the target representation is noise-dependent.Significance. Our proof-of-concept study introduces a new NF method allowing the participant to navigate among different mental states. Compared to traditional NF designs (e.g. using a thermometer display to set the level of the neural signal), the proposed approach provides content-specific feedback to the participant and extra degrees of freedom to the experimenter enabling real-time control of the neural activity towards a target brain state without suggesting a specific mental strategy to the subject.
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Affiliation(s)
- Andrea G Russo
- Department of Political and Communication Sciences, University of Salerno, Fisciano (Salerno), Italy.,Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi (Salerno), Italy
| | - Michael Lührs
- Department of Cognitive Neuroscience, University of Maastricht, Maastricht, The Netherlands.,Brain Innovation B.V., Maastricht, The Netherlands
| | - Francesco Di Salle
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi (Salerno), Italy
| | - Fabrizio Esposito
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Baronissi (Salerno), Italy.,Department of Cognitive Neuroscience, University of Maastricht, Maastricht, The Netherlands.,Department of Advanced Medical and Surgical Sciences,University of Campania 'Luigi Vanvitelli', Napoli,Italy
| | - Rainer Goebel
- Department of Cognitive Neuroscience, University of Maastricht, Maastricht, The Netherlands.,Brain Innovation B.V., Maastricht, The Netherlands
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Sousa T, Duarte JV, Costa GN, Kemper VG, Martins R, Goebel R, Castelo-Branco M. The dual nature of the BOLD signal: Responses in visual area hMT+ reflect both input properties and perceptual decision. Hum Brain Mapp 2021; 42:1920-1929. [PMID: 33576552 PMCID: PMC7978123 DOI: 10.1002/hbm.25339] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 11/29/2020] [Accepted: 12/26/2020] [Indexed: 11/24/2022] Open
Abstract
Neuroimaging studies have suggested that hMT+ encodes global motion interpretation, but this contradicts the notion that BOLD activity mainly reflects neuronal input. While measuring fMRI responses at 7 Tesla, we used an ambiguous moving stimulus, yielding the perception of two incoherently moving surfaces—component motion—or only one coherently moving surface—pattern motion, to induce perceptual fluctuations and identify perceptual organization size‐matched domains in hMT+. Then, moving gratings, exactly matching either the direction of component or pattern motion percepts of the ambiguous stimulus, were shown to the participants to investigate whether response properties reflect the input or decision. If hMT+ responses reflect the input, component motion domains (selective to incoherent percept) should show grating direction stimulus‐dependent changes, unlike pattern motion domains (selective to the coherent percept). This hypothesis is based on the known direction‐selective nature of inputs in component motion perceptual domains versus non‐selectivity in pattern motion perceptual domains. The response amplitude of pattern motion domains did not change with grating direction (consistently with their non‐selective input), in contrast to what happened for the component motion domains (consistently with their selective input). However, when we analyzed relative ratio measures they mirrored perceptual interpretation. These findings are consistent with the notion that patterns of BOLD responses reflect both sensory input and perceptual read‐out.
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Affiliation(s)
- Teresa Sousa
- 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.,Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, University of Maastricht, Maastricht, Netherlands
| | - João V Duarte
- 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
| | - Gabriel N Costa
- 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
| | - Valentin G Kemper
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, University of Maastricht, Maastricht, Netherlands
| | - Ricardo Martins
- 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
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, University of Maastricht, Maastricht, Netherlands.,Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, Netherlands
| | - Miguel Castelo-Branco
- 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.,Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, University of Maastricht, Maastricht, Netherlands.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
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Vezoli J, Magrou L, Goebel R, Wang XJ, Knoblauch K, Vinck M, Kennedy H. Cortical hierarchy, dual counterstream architecture and the importance of top-down generative networks. Neuroimage 2021; 225:117479. [PMID: 33099005 PMCID: PMC8244994 DOI: 10.1016/j.neuroimage.2020.117479] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 09/29/2020] [Accepted: 10/15/2020] [Indexed: 12/18/2022] Open
Abstract
Hierarchy is a major organizational principle of the cortex and underscores modern computational theories of cortical function. The local microcircuit amplifies long-distance inter-areal input, which show distance-dependent changes in their laminar profiles. Statistical modeling of these changes in laminar profiles demonstrates that inputs from multiple hierarchical levels to their target areas show remarkable consistency, allowing the construction of a cortical hierarchy based on a principle of hierarchical distance. The statistical modeling that is applied to structure can also be applied to laminar differences in the oscillatory coherence between areas thereby determining a functional hierarchy of the cortex. Close examination of the anatomy of inter-areal connectivity reveals a dual counterstream architecture with well-defined distance-dependent feedback and feedforward pathways in both the supra- and infragranular layers, suggesting a multiplicity of feedback pathways with well-defined functional properties. These findings are consistent with feedback connections providing a generative network involved in a wide range of cognitive functions. A dynamical model constrained by connectivity data sheds insight into the experimentally observed signatures of frequency-dependent Granger causality for feedforward versus feedback signaling. Concerted experiments capitalizing on recent technical advances and combining tract-tracing, high-resolution fMRI, optogenetics and mathematical modeling hold the promise of a much improved understanding of lamina-constrained mechanisms of neural computation and cognition. However, because inter-areal interactions involve cortical layers that have been the target of important evolutionary changes in the primate lineage, these investigations will need to include human and non-human primate comparisons.
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Affiliation(s)
- Julien Vezoli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Loïc Magrou
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, the Netherlands
| | - Xiao-Jing Wang
- Center for Neural Science, New York University (NYU), New York, NY 10003, USA
| | - Kenneth Knoblauch
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany.
| | - Henry Kennedy
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, CAS, Shanghai 200031, China.
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Rosenke M, van Hoof R, van den Hurk J, Grill-Spector K, Goebel R. A Probabilistic Functional Atlas of Human Occipito-Temporal Visual Cortex. Cereb Cortex 2021; 31:603-619. [PMID: 32968767 PMCID: PMC7727347 DOI: 10.1093/cercor/bhaa246] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 07/01/2020] [Accepted: 07/30/2020] [Indexed: 11/12/2022] Open
Abstract
Human visual cortex contains many retinotopic and category-specific regions. These brain regions have been the focus of a large body of functional magnetic resonance imaging research, significantly expanding our understanding of visual processing. As studying these regions requires accurate localization of their cortical location, researchers perform functional localizer scans to identify these regions in each individual. However, it is not always possible to conduct these localizer scans. Here, we developed and validated a functional region of interest (ROI) atlas of early visual and category-selective regions in human ventral and lateral occipito-temporal cortex. Results show that for the majority of functionally defined ROIs, cortex-based alignment results in lower between-subject variability compared to nonlinear volumetric alignment. Furthermore, we demonstrate that 1) the atlas accurately predicts the location of an independent dataset of ventral temporal cortex ROIs and other atlases of place selectivity, motion selectivity, and retinotopy. Next, 2) we show that the majority of voxel within our atlas is responding mostly to the labeled category in a left-out subject cross-validation, demonstrating the utility of this atlas. The functional atlas is publicly available (download.brainvoyager.com/data/visfAtlas.zip) and can help identify the location of these regions in healthy subjects as well as populations (e.g., blind people, infants) in which functional localizers cannot be run.
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Affiliation(s)
- Mona Rosenke
- Department of Psychology, Stanford University, Stanford, CA 94305, USA
| | - Rick van Hoof
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, 6229 EV, The Netherlands
| | - Job van den Hurk
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, 6229 EV, The Netherlands
- Scannexus MRI Center, Maastricht, 6229 EV, The Netherlands
| | - Kalanit Grill-Spector
- Department of Psychology, Stanford University, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, 94305 CA, USA
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, 6229 EV, The Netherlands
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Subramanian L, Skottnik L, Cox WM, Lührs M, McNamara R, Hood K, Watson G, Whittaker JR, Williams AN, Sakhuja R, Ihssen N, Goebel R, Playle R, Linden DE. Neurofeedback Training versus Treatment-as-Usual for Alcohol Dependence: Results of an Early-Phase Randomized Controlled Trial and Neuroimaging Correlates. Eur Addict Res 2021; 27:381-394. [PMID: 33677449 PMCID: PMC8491491 DOI: 10.1159/000513448] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 10/20/2020] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Alcohol dependence is one of the most common substance use disorders, and novel treatment options are urgently needed. Neurofeedback training (NFT) based on real-time functional magnetic resonance imaging (rtf-MRI) has emerged as an attractive candidate for add-on treatments in psychiatry, but its use in alcohol dependence has not been formally investigated in a clinical trial. We investigated the use of rtfMRI-based NFT to prevent relapse in alcohol dependence. METHODS Fifty-two alcohol-dependent patients from the UK who had completed a detoxification program were randomly assigned to a treatment group (receiving rtfMRI NFT in addition to standard care) or the control group (receiving standard care only). At baseline, alcohol consumption was assessed as the primary outcome measure and a variety of psychological, behavioral, and neural parameters as secondary outcome measures to determine feasibility and secondary training effects. Participants in the treatment group underwent 6 NFT sessions over 4 months and were trained to downregulate their brain activation in the salience network in the presence of alcohol stimuli and to upregulate frontal activation in response to pictures related to positive goals. Four, 8, and 12 months after baseline assessment, both groups were followed up with a battery of clinical and psychometric tests. RESULTS Primary outcome measures showed very low relapse rates for both groups. Analysis of neural secondary outcome measures indicated that the majority of patients modulated the salience system in the desired directions, by decreasing activity in response to alcohol stimuli and increasing activation in response to positive goals. The intervention had a good safety and acceptability profile. CONCLUSION We demonstrated that rtfMRI-neurofeedback targeting hyperactivity of the salience network in response to alcohol cues is feasible in currently abstinent patients with alcohol dependence.
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Affiliation(s)
- Leena Subramanian
- MRC Centre for Neuropsychiatric Genetics and Genomics and Cardiff University Brain Research Imaging Centre, Schools of Medicine and Psychology, Cardiff University, Cardiff, United Kingdom
| | - Leon Skottnik
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands,*Leon Skottnik, School for Mental Health and Neuroscience, Maastricht University, Vijverdalseweg 1, NL–62226 Maastricht (The Netherlands),
| | - W. Miles Cox
- School of Psychology, Bangor University, Bangor, United Kingdom
| | - Michael Lührs
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands,Brain Innovation B.V., Maastricht, The Netherlands
| | - Rachel McNamara
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Kerry Hood
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Gareth Watson
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Joseph R. Whittaker
- School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Angharad N. Williams
- Adaptive Memory Research Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Raman Sakhuja
- Addiction Services, Cwm Taf Morgannwg University Health Board, Mountain Ash, United Kingdom
| | - Niklas Ihssen
- Department of Psychology, Durham University, Durham, United Kingdom
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands,Brain Innovation B.V., Maastricht, The Netherlands
| | - Rebecca Playle
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - David E.J. Linden
- MRC Centre for Neuropsychiatric Genetics and Genomics and Cardiff University Brain Research Imaging Centre, Schools of Medicine and Psychology, Cardiff University, Cardiff, United Kingdom,School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
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Biggs EE, Timmers I, Meulders A, Vlaeyen JW, Goebel R, Kaas AL. The neural correlates of pain-related fear: A meta-analysis comparing fear conditioning studies using painful and non-painful stimuli. Neurosci Biobehav Rev 2020; 119:52-65. [DOI: 10.1016/j.neubiorev.2020.09.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 08/18/2020] [Accepted: 09/07/2020] [Indexed: 01/24/2023]
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Tursic A, Eck J, Lührs M, Linden DEJ, Goebel R. A systematic review of fMRI neurofeedback reporting and effects in clinical populations. Neuroimage Clin 2020; 28:102496. [PMID: 33395987 PMCID: PMC7724376 DOI: 10.1016/j.nicl.2020.102496] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 10/29/2020] [Accepted: 11/02/2020] [Indexed: 12/22/2022]
Abstract
Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of fMRI neurofeedback studies in clinical populations was performed. Reporting was evaluated using a limited number of Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies (CRED-NF checklist) items, which was, together with a statistical power and sensitivity calculation, used to also evaluate the existing evidence of the neurofeedback benefits on clinical measures. The 62 found studies investigated regulation abilities and/or clinical benefits in a wide range of disorders, but with small sample sizes and were therefore unable to detect small effects. Most points from the CRED-NF checklist were adequately reported by the majority of the studies, but some improvements are suggested for the reporting of group comparisons and relations between regulation success and clinical benefits. To establish fMRI neurofeedback as a clinical tool, more emphasis should be placed in the future on using larger sample sizes determined through a priori power calculations and standardization of procedures and reporting.
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Affiliation(s)
- Anita Tursic
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands.
| | - Judith Eck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands.
| | - Michael Lührs
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands.
| | - David E J Linden
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, The Netherlands.
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA Amsterdam, the Netherlands.
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Zamboni E, Kemper VG, Goncalves NR, Jia K, Karlaftis VM, Bell SJ, Giorgio J, Rideaux R, Goebel R, Kourtzi Z. Fine-scale computations for adaptive processing in the human brain. eLife 2020; 9:e57637. [PMID: 33170124 PMCID: PMC7688307 DOI: 10.7554/elife.57637] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 11/09/2020] [Indexed: 12/02/2022] Open
Abstract
Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.
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Affiliation(s)
- Elisa Zamboni
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Valentin G Kemper
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Center, Maastricht UniversityMaastrichtNetherlands
| | | | - Ke Jia
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | | | - Samuel J Bell
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Joseph Giorgio
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Reuben Rideaux
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Center, Maastricht UniversityMaastrichtNetherlands
| | - Zoe Kourtzi
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
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Brem S, Maurer U, Kronbichler M, Schurz M, Richlan F, Blau V, Reithler J, van der Mark S, Schulz E, Bucher K, Moll K, Landerl K, Martin E, Goebel R, Schulte-Körne G, Blomert L, Wimmer H, Brandeis D. Visual word form processing deficits driven by severity of reading impairments in children with developmental dyslexia. Sci Rep 2020; 10:18728. [PMID: 33127943 PMCID: PMC7603304 DOI: 10.1038/s41598-020-75111-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 09/23/2020] [Indexed: 12/25/2022] Open
Abstract
The visual word form area (VWFA) in the left ventral occipito-temporal (vOT) cortex is key to fluent reading in children and adults. Diminished VWFA activation during print processing tasks is a common finding in subjects with severe reading problems. Here, we report fMRI data from a multicentre study with 140 children in primary school (7.9-12.2 years; 55 children with dyslexia, 73 typical readers, 12 intermediate readers). All performed a semantic task on visually presented words and a matched control task on symbol strings. With this large group of children, including the entire spectrum from severely impaired to highly fluent readers, we aimed to clarify the association of reading fluency and left vOT activation during visual word processing. The results of this study confirm reduced word-sensitive activation within the left vOT in children with dyslexia. Interestingly, the association of reading skills and left vOT activation was especially strong and spatially extended in children with dyslexia. Thus, deficits in basic visual word form processing increase with the severity of reading disability but seem only weakly associated with fluency within the typical reading range suggesting a linear dependence of reading scores with VFWA activation only in the poorest readers.
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Affiliation(s)
- S Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Neumuensterallee 9, 8032, Zurich, Switzerland.
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.
| | - U Maurer
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Neumuensterallee 9, 8032, Zurich, Switzerland
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
- Brain and Mind Institute, The Chinese University of Hong Kong, Hong Kong, China
| | - M Kronbichler
- Centre for Cognitive Neuroscience and Department of Psychology, University of Salzburg, Salzburg, Austria
- Neuroscience Institute, Christian Doppler Clinic, Paracelsus Medical University, Salzburg, Austria
| | - M Schurz
- Centre for Cognitive Neuroscience and Department of Psychology, University of Salzburg, Salzburg, Austria
| | - F Richlan
- Centre for Cognitive Neuroscience and Department of Psychology, University of Salzburg, Salzburg, Austria
| | - V Blau
- Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - J Reithler
- Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - S van der Mark
- MR-Center, University Children's Hospital, University of Zürich, Zurich, Switzerland
| | - E Schulz
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - K Bucher
- MR-Center, University Children's Hospital, University of Zürich, Zurich, Switzerland
| | - K Moll
- Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - K Landerl
- Department of Psychology, University of Salzburg, Salzburg, Austria
- Institute of Psychology, University of Graz, Graz, Austria
| | - E Martin
- MR-Center, University Children's Hospital, University of Zürich, Zurich, Switzerland
| | - R Goebel
- Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - G Schulte-Körne
- Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - L Blomert
- Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - H Wimmer
- Centre for Cognitive Neuroscience and Department of Psychology, University of Salzburg, Salzburg, Austria
| | - D Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Neumuensterallee 9, 8032, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Jia K, Zamboni E, Kemper V, Rua C, Goncalves NR, Ng AKT, Rodgers CT, Williams G, Goebel R, Kourtzi Z. Recurrent Processing Drives Perceptual Plasticity. Curr Biol 2020; 30:4177-4187.e4. [PMID: 32888488 PMCID: PMC7658806 DOI: 10.1016/j.cub.2020.08.016] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/30/2020] [Accepted: 08/05/2020] [Indexed: 11/06/2022]
Abstract
Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high-field (7T) functional imaging at sub-millimeter resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. We demonstrate that learning alters orientation-specific representations in superficial rather than middle or deeper V1 layers, consistent with recurrent plasticity mechanisms via horizontal connections. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro-circuits of experience-dependent plasticity. Discrimination training alters orientation representations in superficial V1 layers Orientation-specific V1 plasticity is independent of task context Discrimination training alters orientation representations in middle IPS layers Learning enhances feedforward connectivity from visual to parietal cortex
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Affiliation(s)
- Ke Jia
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Elisa Zamboni
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Valentin Kemper
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6229 ER, The Netherlands
| | - Catarina Rua
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Adrian Ka Tsun Ng
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Christopher T Rodgers
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Guy Williams
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6229 ER, The Netherlands
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK.
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38
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Gulban OF, Goebel R, Moerel M, Zachlod D, Mohlberg H, Amunts K, de Martino F. Improving a probabilistic cytoarchitectonic atlas of auditory cortex using a novel method for inter-individual alignment. eLife 2020; 9:56963. [PMID: 32755545 PMCID: PMC7406353 DOI: 10.7554/elife.56963] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 07/25/2020] [Indexed: 11/23/2022] Open
Abstract
The human superior temporal plane, the site of the auditory cortex, displays high inter-individual macro-anatomical variation. This questions the validity of curvature-based alignment (CBA) methods for in vivo imaging data. Here, we have addressed this issue by developing CBA+, which is a cortical surface registration method that uses prior macro-anatomical knowledge. We validate this method by using cytoarchitectonic areas on 10 individual brains (which we make publicly available). Compared to volumetric and standard surface registration, CBA+ results in a more accurate cytoarchitectonic auditory atlas. The improved correspondence of micro-anatomy following the improved alignment of macro-anatomy validates the superiority of CBA+ compared to CBA. In addition, we use CBA+ to align in vivo and postmortem data. This allows projection of functional and anatomical information collected in vivo onto the cytoarchitectonic areas, which has the potential to contribute to the ongoing debate on the parcellation of the human auditory cortex.
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Affiliation(s)
- Omer Faruk Gulban
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Brain Innovation B.V, Maastricht, Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Brain Innovation B.V, Maastricht, Netherlands
| | - Michelle Moerel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Centre for Systems Biology, Faculty of Science and Engineering, Maastricht University, Maastricht, Netherlands
| | - Daniel Zachlod
- Institute for Neuroscience and Medicine (INM-1), and JARA Brain, Research Centre Jülich, Jülich, Germany.,C. and O. Vogt Institute for Brain Research, Heinrich Heine University, Düsseldorf, Germany
| | - Hartmut Mohlberg
- Institute for Neuroscience and Medicine (INM-1), and JARA Brain, Research Centre Jülich, Jülich, Germany.,C. and O. Vogt Institute for Brain Research, Heinrich Heine University, Düsseldorf, Germany
| | - Katrin Amunts
- Institute for Neuroscience and Medicine (INM-1), and JARA Brain, Research Centre Jülich, Jülich, Germany.,C. and O. Vogt Institute for Brain Research, Heinrich Heine University, Düsseldorf, Germany
| | - Federico de Martino
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, United States
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39
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Biggs EE, Meulders A, Kaas AL, Goebel R, Vlaeyen JWS. The acquisition and generalization of fear of touch. Scand J Pain 2020; 20:809-819. [PMID: 32712594 DOI: 10.1515/sjpain-2019-0177] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 06/01/2020] [Indexed: 12/17/2022]
Abstract
Objectives Contemporary fear-avoidance models of chronic pain posit that fear of pain, and overgeneralization of fear to non-threatening stimuli is a potential pathway to chronic pain. While increasing experimental evidence supports this hypothesis, a comprehensive investigation requires testing in multiple modalities due to the diversity of symptomatology among individuals with chronic pain. In the present study we used an established tactile fear conditioning paradigm as an experimental model of allodynia and spontaneous pain fluctuations, to investigate whether stimulus generalization occurs resulting in fear of touch spreading to new locations. Methods In our paradigm, innocuous touch is presented either paired (predictable context) or unpaired (unpredictable context) with a painful electrocutaneous stimulus (pain-US). In the predictable context, vibrotactile stimulation to the index or little finger was paired with the pain-US (CS+), whilst stimulation of the other finger was never paired with pain (CS-). In the unpredictable context, vibrotactile stimulation to the index and little fingers of the opposite hand (CS1 and CS2) was unpaired with pain, but pain-USs occurred unpredictable during the intertrial interval. During the subsequent generalization phase, we tested the spreading of conditioned responses (self-reported fear of touch and pain expectancy) to the (middle and ring) fingers between the CS+ and CS-, and between the CS1 and CS2. Results Differential fear acquisition was evident in the predictable context from increased self-reported pain expectancy and self-reported fear for the CS + compared to the CS-. However, expectancy and fear ratings to the novel generalization stimuli (GS+ and GS-) were comparable to the responses elicited by the CS-. Participants reported equal levels of pain expectancy and fear to the CS1 and CS2 in the unpredictable context. However, the acquired fear did not spread in this context either: participants reported less pain expectancy and fear to the GS1 and GS2 than to the CS1 and CS2. As in our previous study, we did not observe differential acquisition in the startle responses. Conclusions Whilst our findings for the acquisition of fear of touch replicate the results from our previous study (Biggs et al., 2017), there was no evidence of fear generalization. We discuss the limitations of the present study, with a primary focus on procedural issues that were further investigated with post-hoc analyses, concluding that the present results do not show support for the hypothesis that stimulus generalization underlies spreading of fear of touch to new locations, and discuss how this may be the consequence of a context change that prevented transfer of acquisition.
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Affiliation(s)
- Emma E Biggs
- Research Group Health Psychology, KU Leuven, Leuven, Belgium.,Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands.,Experimental Health Psychology, Maastricht University, Maastricht, The Netherlands
| | - Ann Meulders
- Research Group Health Psychology, KU Leuven, Leuven, Belgium.,Experimental Health Psychology, Maastricht University, Maastricht, The Netherlands
| | - Amanda L Kaas
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Johan W S Vlaeyen
- Research Group Health Psychology, KU Leuven, Leuven, Belgium.,Experimental Health Psychology, Maastricht University, Maastricht, The Netherlands
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40
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Senden M, Peters J, Röhrbein F, Deco G, Goebel R. Editorial: The Embodied Brain: Computational Mechanisms of Integrated Sensorimotor Interactions With a Dynamic Environment. Front Comput Neurosci 2020; 14:53. [PMID: 32625074 PMCID: PMC7314992 DOI: 10.3389/fncom.2020.00053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 05/15/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center (M-BIC), Maastricht University, Maastricht, Netherlands
| | - Judith Peters
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center (M-BIC), Maastricht University, Maastricht, Netherlands.,Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, Netherlands
| | - Florian Röhrbein
- Institut für Informatik VI, Technische Universität München, Munich, Germany
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.,Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Barcelona, Spain
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center (M-BIC), Maastricht University, Maastricht, Netherlands.,Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, Netherlands
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41
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Špiclin Ž, McClelland J, Kybic J, Goksel O, Pyles J, Eck J, Bastiani M, Roebroeck A, Ashburner J, Goebel R. An Image Registration-Based Method for EPI Distortion Correction Based on Opposite Phase Encoding (COPE). Biomedical Image Registration 2020; 12120. [PMCID: PMC7279930 DOI: 10.1007/978-3-030-50120-4_12] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Surprisingly, estimated voxel displacement maps (VDMs), based on image registration, seem to work just as well to correct geometrical distortion in functional MRI data (EPI) as VDMs based on actual information about the magnetic field. In this article, we compare our new image registration-based distortion correction method ‘COPE’ to an implementation of the pixelshift method. Our approach builds on existing image registration-based techniques using opposite phase encoding, extending these by local cost aggregation. Comparison of these methods with 3T and 7T spin-echo (SE) and gradient-echo (GE) data show that the image registration-based method is a good alternative to the fieldmap-based EPI distortion correction method.
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Affiliation(s)
- Žiga Špiclin
- Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
| | - Jamie McClelland
- Centre for Medical Image Computing, University College London, London, UK
| | - Jan Kybic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Orcun Goksel
- Computer Vision Lab, ETH Zurich, Zurich, Switzerland
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42
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Kroner A, Senden M, Driessens K, Goebel R. Contextual encoder-decoder network for visual saliency prediction. Neural Netw 2020; 129:261-270. [PMID: 32563023 DOI: 10.1016/j.neunet.2020.05.004] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Revised: 03/19/2020] [Accepted: 05/04/2020] [Indexed: 11/28/2022]
Abstract
Predicting salient regions in natural images requires the detection of objects that are present in a scene. To develop robust representations for this challenging task, high-level visual features at multiple spatial scales must be extracted and augmented with contextual information. However, existing models aimed at explaining human fixation maps do not incorporate such a mechanism explicitly. Here we propose an approach based on a convolutional neural network pre-trained on a large-scale image classification task. The architecture forms an encoder-decoder structure and includes a module with multiple convolutional layers at different dilation rates to capture multi-scale features in parallel. Moreover, we combine the resulting representations with global scene information for accurately predicting visual saliency. Our model achieves competitive and consistent results across multiple evaluation metrics on two public saliency benchmarks and we demonstrate the effectiveness of the suggested approach on five datasets and selected examples. Compared to state of the art approaches, the network is based on a lightweight image classification backbone and hence presents a suitable choice for applications with limited computational resources, such as (virtual) robotic systems, to estimate human fixations across complex natural scenes. Our TensorFlow implementation is openly available at https://github.com/alexanderkroner/saliency.
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Affiliation(s)
- Alexander Kroner
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands; Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
| | - Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands; Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
| | - Kurt Driessens
- Department of Data Science and Knowledge Engineering, Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands.
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands; Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands; Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands.
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43
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Nagels-Coune L, Benitez-Andonegui A, Reuter N, Lührs M, Goebel R, De Weerd P, Riecke L, Sorger B. Brain-Based Binary Communication Using Spatiotemporal Features of fNIRS Responses. Front Hum Neurosci 2020; 14:113. [PMID: 32351371 PMCID: PMC7174771 DOI: 10.3389/fnhum.2020.00113] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Accepted: 03/12/2020] [Indexed: 12/14/2022] Open
Abstract
“Locked-in” patients lose their ability to communicate naturally due to motor system dysfunction. Brain-computer interfacing offers a solution for their inability to communicate by enabling motor-independent communication. Straightforward and convenient in-session communication is essential in clinical environments. The present study introduces a functional near-infrared spectroscopy (fNIRS)-based binary communication paradigm that requires limited preparation time and merely nine optodes. Eighteen healthy participants performed two mental imagery tasks, mental drawing and spatial navigation, to answer yes/no questions during one of two auditorily cued time windows. Each of the six questions was answered five times, resulting in five trials per answer. This communication paradigm thus combines both spatial (two different mental imagery tasks, here mental drawing for “yes” and spatial navigation for “no”) and temporal (distinct time windows for encoding a “yes” and “no” answer) fNIRS signal features for information encoding. Participants’ answers were decoded in simulated real-time using general linear model analysis. Joint analysis of all five encoding trials resulted in an average accuracy of 66.67 and 58.33% using the oxygenated (HbO) and deoxygenated (HbR) hemoglobin signal respectively. For half of the participants, an accuracy of 83.33% or higher was reached using either the HbO signal or the HbR signal. For four participants, effective communication with 100% accuracy was achieved using either the HbO or HbR signal. An explorative analysis investigated the differentiability of the two mental tasks based solely on spatial fNIRS signal features. Using multivariate pattern analysis (MVPA) group single-trial accuracies of 58.33% (using 20 training trials per task) and 60.56% (using 40 training trials per task) could be obtained. Combining the five trials per run using a majority voting approach heightened these MVPA accuracies to 62.04 and 75%. Additionally, an fNIRS suitability questionnaire capturing participants’ physical features was administered to explore its predictive value for evaluating general data quality. Obtained questionnaire scores correlated significantly (r = -0.499) with the signal-to-noise of the raw light intensities. While more work is needed to further increase decoding accuracy, this study shows the potential of answer encoding using spatiotemporal fNIRS signal features or spatial fNIRS signal features only.
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Affiliation(s)
- Laurien Nagels-Coune
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center, Maastricht, Netherlands.,University Psychiatric Centre Sint-Kamillus, Bierbeek, Belgium
| | - Amaia Benitez-Andonegui
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center, Maastricht, Netherlands
| | - Niels Reuter
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany.,Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
| | | | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center, Maastricht, Netherlands.,Brain Innovation B.V., Maastricht, Netherlands
| | - Peter De Weerd
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center, Maastricht, Netherlands.,Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, Netherlands
| | - Lars Riecke
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center, Maastricht, Netherlands
| | - Bettina Sorger
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Center, Maastricht, Netherlands
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44
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Peters JC, Reithler J, Graaf TAD, Schuhmann T, Goebel R, Sack AT. Concurrent human TMS-EEG-fMRI enables monitoring of oscillatory brain state-dependent gating of cortico-subcortical network activity. Commun Biol 2020; 3:40. [PMID: 31969657 PMCID: PMC6976670 DOI: 10.1038/s42003-020-0764-0] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 01/07/2020] [Indexed: 11/08/2022] Open
Abstract
Despite growing interest, the causal mechanisms underlying human neural network dynamics remain elusive. Transcranial Magnetic Stimulation (TMS) allows to noninvasively probe neural excitability, while concurrent fMRI can log the induced activity propagation through connected network nodes. However, this approach ignores ongoing oscillatory fluctuations which strongly affect network excitability and concomitant behavior. Here, we show that concurrent TMS-EEG-fMRI enables precise and direct monitoring of causal dependencies between oscillatory states and signal propagation throughout cortico-subcortical networks. To demonstrate the utility of this multimodal triad, we assessed how pre-TMS EEG power fluctuations influenced motor network activations induced by subthreshold TMS to right dorsal premotor cortex. In participants with adequate motor network reactivity, strong pre-TMS alpha power reduced TMS-evoked hemodynamic activations throughout the bilateral cortico-subcortical motor system (including striatum and thalamus), suggesting shunted network connectivity. Concurrent TMS-EEG-fMRI opens an exciting noninvasive avenue of subject-tailored network research into dynamic cognitive circuits and their dysfunction.
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Affiliation(s)
- Judith C Peters
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.
- Maastricht Brain Imaging Center (M-BIC), Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.
- Department of Vision, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), Meibergdreef 47, 1105 BA, Amsterdam, The Netherlands.
| | - Joel Reithler
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Vision, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), Meibergdreef 47, 1105 BA, Amsterdam, The Netherlands
| | - Tom A de Graaf
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
| | - Teresa Schuhmann
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Vision, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), Meibergdreef 47, 1105 BA, Amsterdam, The Netherlands
| | - Alexander T Sack
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Maastricht Brain Imaging Center (M-BIC), Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Brain+Nerve Centre, Maastricht University Medical Centre+(MUMC+), Maastricht, The Netherlands
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Abstract
Brain-computer interfaces (BCIs) based on functional magnetic resonance imaging (fMRI) provide an important complement to other noninvasive BCIs. While fMRI has several disadvantages (being nonportable, methodologically challenging, costly, and noisy), it is the only method providing high spatial resolution whole-brain coverage of brain activation. These properties allow relating mental activities to specific brain regions and networks providing a transparent scheme for BCI users to encode information and for real-time fMRI BCI systems to decode the intents of the user. Various mental activities have been used successfully in fMRI BCIs so far that can be classified into the four categories: (a) higher-order cognitive tasks (e.g., mental calculation), (b) covert language-related tasks (e.g., mental speech and mental singing), (c) imagery tasks (motor, visual, auditory, tactile, and emotion imagery), and (d) selective attention tasks (visual, auditory, and tactile attention). While the ultimate spatial and temporal resolution of fMRI BCIs is limited by the physiologic properties of the hemodynamic response, technical and analytical advances will likely lead to substantially improved fMRI BCIs in the future using, for example, decoding of imagined letter shapes at 7T as the basis for more "natural" communication BCIs.
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Affiliation(s)
- Bettina Sorger
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands; Maastricht Brain Imaging Center (M-BIC), Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands; Maastricht Brain Imaging Center (M-BIC), Maastricht, The Netherlands.
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46
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Beugels J, van den Hurk J, Peters JC, Heuts EM, Tuinder SMH, Goebel R, van der Hulst RRWJ. Somatotopic mapping of the human breast using 7 T functional MRI. Neuroimage 2020; 204:116201. [PMID: 31541697 DOI: 10.1016/j.neuroimage.2019.116201] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 08/06/2019] [Accepted: 09/16/2019] [Indexed: 11/26/2022] Open
Abstract
How are tactile sensations in the breast represented in the female and male brain? Using ultra high-field 7 T MRI in ten females and ten males, we demonstrate that the representation of tactile breast information shows a somatotopic organization, with cortical magnification of the nipple. Furthermore, we show that the core representation of the breast is organized according to the specific nerve architecture that underlies breast sensation, where the medial and lateral sides of one breast are asymmetrically represented in bilateral primary somatosensory cortex. Finally, gradual selectivity signatures allude to a somatotopic organization of the breast area with overlapping, but distinctive, cortical representations of breast segments. Our univariate and multivariate analyses consistently showed similar somatosensory breast representations in males and females. The findings can guide future research on neuroplastic reorganization of the breast area, across reproductive life stages, and after breast surgery.
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Affiliation(s)
- Jop Beugels
- Department of Plastic, Reconstructive and Hand Surgery, Maastricht University Medical Center, 6229 HX, Maastricht, Netherlands; GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, 6229 ER, Maastricht, Netherlands.
| | - Job van den Hurk
- Scannexus ultra high-field MRI center, 6229 EV, Maastricht, Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, Netherlands; Maastricht Brain Imaging Center (M-BIC), Maastricht University, 6229 EV, Maastricht, Netherlands
| | - Judith C Peters
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, Netherlands; Maastricht Brain Imaging Center (M-BIC), Maastricht University, 6229 EV, Maastricht, Netherlands; Department of Vision and Cognition, Netherlands Institute for Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), 1105 BA, Amsterdam, the Netherlands
| | - Esther M Heuts
- Department of Surgery, Maastricht University Medical Center, 622 HX, Maastricht, Netherlands
| | - Stefania M H Tuinder
- Department of Plastic, Reconstructive and Hand Surgery, Maastricht University Medical Center, 6229 HX, Maastricht, Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, Netherlands; Maastricht Brain Imaging Center (M-BIC), Maastricht University, 6229 EV, Maastricht, Netherlands; Department of Vision and Cognition, Netherlands Institute for Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), 1105 BA, Amsterdam, the Netherlands
| | - René R W J van der Hulst
- Department of Plastic, Reconstructive and Hand Surgery, Maastricht University Medical Center, 6229 HX, Maastricht, Netherlands; GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, 6229 ER, Maastricht, Netherlands
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47
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Hohenfeld C, Kuhn H, Müller C, Nellessen N, Ketteler S, Heinecke A, Goebel R, Shah NJ, Schulz JB, Reske M, Reetz K. Changes in brain activation related to visuo-spatial memory after real-time fMRI neurofeedback training in healthy elderly and Alzheimer's disease. Behav Brain Res 2019; 381:112435. [PMID: 31863845 DOI: 10.1016/j.bbr.2019.112435] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 12/11/2019] [Accepted: 12/13/2019] [Indexed: 12/12/2022]
Abstract
Cognitive decline is a symptom of healthy ageing and Alzheimer's disease. We examined the effect of real-time fMRI based neurofeedback training on visuo-spatial memory and its associated neuronal response. Twelve healthy subjects and nine patients of prodromal Alzheimer's disease were included. The examination spanned five days (T1-T5): T1 contained a neuropsychological pre-test, the encoding of an itinerary and a fMRI-based task related that itinerary. T2-T4 hosted the real-time fMRI neurofeedback training of the parahippocampal gyrus and on T5 a post-test session including encoding of another itinerary and a subsequent fMRI-based task were done. Scores from neuropsychological tests, brain activation and task performance during the fMRI-paradigm were compared between pre and post-test as well as between healthy controls and patients. Behavioural performance in the fMRI-task remained unchanged, while cognitive testing showed improvements in visuo-spatial memory performance. Both groups displayed task-relevant brain activation, which decreased in the right precentral gyrus and left occipital lobe from pre to post-test in controls, but increased in the right occipital lobe, middle frontal gyrus and left frontal lobe in the patient group. While results suggest that the training has affected brain activation differently between controls and patients, there are no pointers towards a behavioural manifestation of these changes. Future research is required on the effects that can be induced using real-time fMRI based neurofeedback training and the required training duration to elicit broad and lasting effects.
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Affiliation(s)
- Christian Hohenfeld
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA Brain Institute Molecular Neuroscience and Neuroimaging, Research Centre Jülich and RWTH Aachen University, Aachen, Germany
| | - Hanna Kuhn
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA Brain Institute Molecular Neuroscience and Neuroimaging, Research Centre Jülich and RWTH Aachen University, Aachen, Germany; University Hospital Bern, Emergency Department, Bern, Switzerland
| | - Christine Müller
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA Brain Institute Molecular Neuroscience and Neuroimaging, Research Centre Jülich and RWTH Aachen University, Aachen, Germany; Bethesda Clinic, Department of Neurorehabilitation, Tschugg, Switzerland
| | - Nils Nellessen
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA Brain Institute Molecular Neuroscience and Neuroimaging, Research Centre Jülich and RWTH Aachen University, Aachen, Germany; University of Cologne, Department of Neurology, Cologne, Germany
| | - Simon Ketteler
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA Brain Institute Molecular Neuroscience and Neuroimaging, Research Centre Jülich and RWTH Aachen University, Aachen, Germany
| | | | - Rainer Goebel
- Netherlands Institute for Neuroscience, Department of Neuroimaging and Neuromodeling, Amsterdam, The Netherlands; Maastricht University, Department of Cognitive Neuroscience, Maastricht, The Netherlands; Brain Innovation, Maastricht, The Netherlands
| | - N Jon Shah
- Research Centre Jülich, Institute for Neuroscience and Medicine (INM-4/6), Jülich, Germany; RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA Brain Institute Molecular Neuroscience and Neuroimaging, Research Centre Jülich and RWTH Aachen University, Aachen, Germany
| | - Jörg B Schulz
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA Brain Institute Molecular Neuroscience and Neuroimaging, Research Centre Jülich and RWTH Aachen University, Aachen, Germany
| | - Martina Reske
- Research Centre Jülich, Institute for Neuroscience and Medicine (INM-4/6), Jülich, Germany
| | - Kathrin Reetz
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA Brain Institute Molecular Neuroscience and Neuroimaging, Research Centre Jülich and RWTH Aachen University, Aachen, Germany.
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Kaas A, Goebel R, Valente G, Sorger B. Topographic Somatosensory Imagery for Real-Time fMRI Brain-Computer Interfacing. Front Hum Neurosci 2019; 13:427. [PMID: 31920588 PMCID: PMC6915074 DOI: 10.3389/fnhum.2019.00427] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 11/18/2019] [Indexed: 11/23/2022] Open
Abstract
Real-time functional magnetic resonance imaging (fMRI) is a promising non-invasive method for brain-computer interfaces (BCIs). BCIs translate brain activity into signals that allow communication with the outside world. Visual and motor imagery are often used as information-encoding strategies, but can be challenging if not grounded in recent experience in these modalities, e.g., in patients with locked-in-syndrome (LIS). In contrast, somatosensory imagery might constitute a more suitable information-encoding strategy as the somatosensory function is often very robust. Somatosensory imagery has been shown to activate the somatotopic cortex, but it has been unclear so far whether it can be reliably detected on a single-trial level and successfully classified according to specific somatosensory imagery content. Using ultra-high field 7-T fMRI, we show reliable and high-accuracy single-trial decoding of left-foot (LF) vs. right-hand (RH) somatosensory imagery. Correspondingly, higher decoding accuracies were associated with greater spatial separation of hand and foot decoding-weight patterns in the primary somatosensory cortex (S1). Exploiting these novel neuroscientific insights, we developed-and provide a proof of concept for-basic BCI communication by showing that binary (yes/no) answers encoded by somatosensory imagery can be decoded with high accuracy in simulated real-time (in 7 subjects) as well as in real-time (1 subject). This study demonstrates that body part-specific somatosensory imagery differentially activates somatosensory cortex in a topographically specific manner; evidence which was surprisingly still lacking in the literature. It also offers proof of concept for a novel somatosensory imagery-based fMRI-BCI control strategy, with particularly high potential for visually and motor-impaired patients. The strategy could also be transferred to lower MRI field strengths and to mobile functional near-infrared spectroscopy. Finally, given that communication BCIs provide the BCI user with a form of feedback based on their brain signals and can thus be considered as a specific form of neurofeedback, and that repeated use of a BCI has been shown to enhance underlying representations, we expect that the current BCI could also offer an interesting new approach for somatosensory rehabilitation training in the context of stroke and phantom limb pain.
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Affiliation(s)
- Amanda Kaas
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht University, Maastricht, Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht University, Maastricht, Netherlands
| | - Giancarlo Valente
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht University, Maastricht, Netherlands
| | - Bettina Sorger
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Center, Maastricht University, Maastricht, Netherlands
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Sarkheil P, Klasen M, Schneider F, Goebel R, Mathiak K. Amygdala response and functional connectivity during cognitive emotion regulation of aversive image sequences. Eur Arch Psychiatry Clin Neurosci 2019; 269:803-811. [PMID: 30008118 DOI: 10.1007/s00406-018-0920-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Accepted: 06/25/2018] [Indexed: 02/02/2023]
Abstract
Emotion regulation (ER) is crucial in terms of mental health and social functioning. Attention deployment (AD) and cognitive reappraisal (CR) are both efficient cognitive ER strategies, which are based on partially dissociated neural effects. Our understanding of the neural underpinnings of ER is based on laboratory paradigms that study changes of the brain activation related to isolated emotional stimuli. To track the neural response to ER in the changing and dynamic environment of daily life, we extended the common existing paradigms by applying a sequence of emotionally provocative stimuli involving three aversive images. Eighteen participants completed an ER paradigm, in which they had to either shift their attention away from the emotionally negative images by counting backwards (AD strategy) or reinterpret the meaning of stimuli (CR strategy) to attain a down-regulation of affective responses. An increased recruitment of left-sided lateral and medial PFC was shown upon regulation of negative emotions with CR as compared to AD. Remarkably, the amygdala activation showed an increasing pattern of activation during CR. The inverse relationship between PFC and amygdala was compromised during elongated blocks of reappraisal, reflecting a reduction in engagement of the top-down prefrontal regulatory circuitry upon repeated exposure to negative stimuli. These results highlight that temporal dynamic of amygdala response and its functional connectivity differentiates AD and CR strategies in regulating emotions. Findings of the current study underscore the importance of adopting temporally variant approaches for investigating the neural effects of ER. Identifying neural systems that subserve down-regulation of negative emotions is of importance in developing treatment strategies for various forms of psychopathology.
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Affiliation(s)
- Pegah Sarkheil
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicin, RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany. .,Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands. .,JARA - Translational Brain Medicine, Aachen, Germany.
| | - Martin Klasen
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicin, RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany.,JARA - Translational Brain Medicine, Aachen, Germany
| | - Frank Schneider
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicin, RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany.,JARA - Translational Brain Medicine, Aachen, Germany
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicin, RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany.,JARA - Translational Brain Medicine, Aachen, Germany
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Self MW, van Kerkoerle T, Goebel R, Roelfsema PR. Benchmarking laminar fMRI: Neuronal spiking and synaptic activity during top-down and bottom-up processing in the different layers of cortex. Neuroimage 2019. [DOI: 10.1016/j.neuroimage.2017.06.045] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
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