1
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Yang Z, Arabinda M, Wang F, Chen LM, Gore JC. Layer-specific BOLD effects in gradient and spin-echo acquisitions in somatosensory cortex. Magn Reson Med 2024. [PMID: 39370926 DOI: 10.1002/mrm.30326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 09/10/2024] [Accepted: 09/14/2024] [Indexed: 10/08/2024]
Abstract
PURPOSE Previous studies have shown varied BOLD signals with gradient echo (GE) across cortical depth. To interpret these variations, and understand the effects of vascular geometry and size, the magnitudes and layer distributions of GE and spin-echo (SE) BOLD functional MRI signals were compared in the somatosensory cortex of squirrel monkeys during tactile stimulation and in a resting state at high spatial resolution and high field. METHODS A block-design stimulation was used to identify tactile-evoked activation signals in somatosensory Areas 3b and 1. Layer-specific connectivities were calculated using resting-state data. Signal power spectra were compared by depth and pulse sequence. The measured ratios of transverse relaxation rate changes were compared with Anderson and Weiss's model. RESULTS SE signals showed a 26% lower percentage signal change during tactile stimulation compared with GE, along with a slower time course. SE signals remained consistent but weaker in lower layers, whereas GE signals decreased with cortical depth. This pattern extended to resting-state power spectra. Resting-state functional connectivity indicated larger connectivity between the top layers of Area 3b and Area 1 for GE, with minimal changes for SE. Comparisons with theory suggest vessel diameters ranging from 19.4 to 9 microns are responsible for BOLD effects across cortical layers at 9.4 T. CONCLUSION These results provide further evidence that at high field, SE BOLD signals are relatively free of contributions from sources other than microvascular changes in response to neural activity, whereas GE signals, even in the superficial layers, are not dominated by very large vessels.
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Affiliation(s)
- Zhangyan Yang
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Mishra Arabinda
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Feng Wang
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Li Min Chen
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - John C Gore
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA
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2
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Phillips WA, Bachmann T, Spratling MW, Muckli L, Petro LS, Zolnik T. Cellular psychology: relating cognition to context-sensitive pyramidal cells. Trends Cogn Sci 2024:S1364-6613(24)00224-9. [PMID: 39353837 DOI: 10.1016/j.tics.2024.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 09/05/2024] [Accepted: 09/06/2024] [Indexed: 10/04/2024]
Abstract
'Cellular psychology' is a new field of inquiry that studies dendritic mechanisms for adapting mental events to the current context, thus increasing their coherence, flexibility, effectiveness, and comprehensibility. Apical dendrites of neocortical pyramidal cells have a crucial role in cognition - those dendrites receive input from diverse sources, including feedback, and can amplify the cell's feedforward transmission if relevant in that context. Specialized subsets of inhibitory interneurons regulate this cooperative context-sensitive processing by increasing or decreasing amplification. Apical input has different effects on cellular output depending on whether we are awake, deeply asleep, or dreaming. Furthermore, wakeful thought and imagery may depend on apical input. High-resolution neuroimaging in humans supports and complements evidence on these cellular mechanisms from other mammals.
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Affiliation(s)
- William A Phillips
- Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, FK9 4LA, UK.
| | - Talis Bachmann
- Institute of Psychology, University of Tartu, Tartu, Estonia.
| | - Michael W Spratling
- Department of Behavioral and Cognitive Sciences, University of Luxembourg, L-4366 Esch-Belval, Luxembourg
| | - Lars Muckli
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QB, UK; Imaging Centre of Excellence, College of Medical, Veterinary and Life Sciences, University of Glasgow and Queen Elizabeth University Hospital, Glasgow, UK
| | - Lucy S Petro
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QB, UK; Imaging Centre of Excellence, College of Medical, Veterinary and Life Sciences, University of Glasgow and Queen Elizabeth University Hospital, Glasgow, UK
| | - Timothy Zolnik
- Department of Biochemistry, Charité Universitätsmedizin Berlin, Berlin 10117, Germany; Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany
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3
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Degutis JK, Chaimow D, Haenelt D, Assem M, Duncan J, Haynes JD, Weiskopf N, Lorenz R. Dynamic layer-specific processing in the prefrontal cortex during working memory. Commun Biol 2024; 7:1140. [PMID: 39277694 PMCID: PMC11401931 DOI: 10.1038/s42003-024-06780-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 08/26/2024] [Indexed: 09/17/2024] Open
Abstract
The dorsolateral prefrontal cortex (dlPFC) is reliably engaged in working memory (WM) and comprises different cytoarchitectonic layers, yet their functional role in human WM is unclear. Here, participants completed a delayed-match-to-sample task while undergoing functional magnetic resonance imaging (fMRI) at ultra-high resolution. We examine layer-specific activity to manipulations in WM load and motor response. Superficial layers exhibit a preferential response to WM load during the delay and retrieval periods of a WM task, indicating a lamina-specific activation of the frontoparietal network. Multivariate patterns encoding WM load in the superficial layer dynamically change across the three periods of the task. Last, superficial and deep layers are non-differentially involved in the motor response, challenging earlier findings of a preferential deep layer activation. Taken together, our results provide new insights into the functional laminar circuitry of the dlPFC during WM and support a dynamic account of dlPFC coding.
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Affiliation(s)
- Jonas Karolis Degutis
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.
- Bernstein Center for Computational Neuroscience Berlin and Berlin Center for Advanced Neuroimaging, Charité Universitätsmedizin Berlin, corporate member of the Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
- Max Planck School of Cognition, Leipzig, Germany.
| | - Denis Chaimow
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Daniel Haenelt
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Moataz Assem
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire, UK
| | - John Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, Cambridgeshire, UK
| | - John-Dylan Haynes
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin and Berlin Center for Advanced Neuroimaging, Charité Universitätsmedizin Berlin, corporate member of the Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Max Planck School of Cognition, Leipzig, Germany
- Research Training Group "Extrospection" and Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Research Cluster of Excellence "Science of Intelligence", Technische Universität Berlin, Berlin, Germany
- Collaborative Research Center "Volition and Cognitive Control", Technische Universität Dresden, Dresden, Germany
| | - Nikolaus Weiskopf
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
- 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 Sciences, Leipzig University, Leipzig, Germany
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
| | - Romy Lorenz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
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4
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Carricarte T, Iamshchinina P, Trampel R, Chaimow D, Weiskopf N, Cichy RM. Laminar dissociation of feedforward and feedback in high-level ventral visual cortex during imagery and perception. iScience 2024; 27:110229. [PMID: 39006482 PMCID: PMC11246059 DOI: 10.1016/j.isci.2024.110229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 01/26/2024] [Accepted: 06/06/2024] [Indexed: 07/16/2024] Open
Abstract
Visual imagery and perception share neural machinery but rely on different information flow. While perception is driven by the integration of sensory feedforward and internally generated feedback information, imagery relies on feedback only. This suggests that although imagery and perception may activate overlapping brain regions, they do so in informationally distinctive ways. Using lamina-resolved MRI at 7 T, we measured the neural activity during imagery and perception of faces and scenes in high-level ventral visual cortex at the mesoscale of laminar organization that distinguishes feedforward from feedback signals. We found distinctive laminar profiles for imagery and perception of scenes and faces in the parahippocampal place area and the fusiform face area, respectively. Our findings provide insight into the neural basis of the phenomenology of visual imagery versus perception and shed new light into the mesoscale organization of feedforward and feedback information flow in high-level ventral visual cortex.
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Affiliation(s)
- Tony Carricarte
- Department of Education and Psychology, Freie Universität Berlin, 14195 Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Polina Iamshchinina
- Princeton Neuroscience Institute, Princeton University, New Jersey 08544, USA
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Denis Chaimow
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Universität Leipzig, 04103 Leipzig, Germany
| | - Radoslaw M. Cichy
- Department of Education and Psychology, Freie Universität Berlin, 14195 Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
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5
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Center EG, Federmeier KD, Beck DM. The Brain's Sensitivity to Real-world Statistical Regularity Does Not Require Full Attention. J Cogn Neurosci 2024; 36:1715-1740. [PMID: 38739561 DOI: 10.1162/jocn_a_02181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Predictive coding accounts of perception state that the brain generates perceptual predictions in the service of processing incoming sensory data. These predictions are hypothesized to be afforded by the brain's ability to internalize useful patterns, that is, statistical regularities, from the environment. We have previously argued that the N300 ERP component serves as an index of the brain's use of representations of (real-world) statistical regularities. However, we do not yet know whether overt attention is necessary in order for this process to engage. We addressed this question by presenting stimuli of either high or low real-world statistical regularity in terms of their representativeness (good/bad exemplars of natural scene categories) to participants who either fully attended the stimuli or were distracted by another task (attended/distracted conditions). Replicating past work, N300 responses were larger to bad than to good scene exemplars, and furthermore, we demonstrate minimal impacts of distraction on N300 effects. Thus, it seems that overtly focused attention is not required to maintain the brain's sensitivity to real-world statistical regularity. Furthermore, in an exploratory analysis, we showed that providing additional, artificial regularities, formed by altering the proportions of good and bad exemplars within blocks, further enhanced the N300 effect in both attended and distracted conditions, shedding light on the relationship between statistical regularities learned in the real world and those learned within the context of an experiment.
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Affiliation(s)
- Evan G Center
- University of Oulu
- University of Illinois at Urbana-Champaign
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6
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Báez-Yáñez MG, Siero JCW, Curcic V, van Osch MJP, Petridou N. On the influence of the vascular architecture on Gradient Echo and Spin Echo BOLD fMRI signals across cortical depth: a simulation approach based on realistic 3D vascular networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.30.596593. [PMID: 38853905 PMCID: PMC11160811 DOI: 10.1101/2024.05.30.596593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
GE-BOLD contrast stands out as the predominant technique in functional MRI experiments for its high sensitivity and straightforward implementation. GE-BOLD exhibits rather similar sensitivity to vessels independent of their size at submillimeter resolution studies like those examining cortical columns and laminae. However, the presence of nonspecific macrovascular contributions poses a challenge to accurately isolate neuronal activity. SE-BOLD increases specificity towards small vessels, thereby enhancing its specificity to neuronal activity, due to the effective suppression of extravascular contributions caused by macrovessels with its refocusing pulse. However, even SE-BOLD measurements may not completely remove these macrovascular contributions. By simulating hemodynamic signals across cortical depth, we gain insights into vascular contributions to the laminar BOLD signal. In this study, we employed four realistic 3D vascular models to simulate oxygen saturation states in various vascular compartments, aiming to characterize both intravascular and extravascular contributions to GE and SE signals, and corresponding BOLD signal changes, across cortical depth at 7T. Simulations suggest that SE-BOLD cannot completely reduce the macrovascular contribution near the pial surface. Simulations also show that both the specificity and signal amplitude of BOLD signals at 7T depend on the spatial arrangement of large vessels throughout cortical depth and on the pial surface.
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Affiliation(s)
- Mario Gilberto Báez-Yáñez
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jeroen C W Siero
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
| | - Vanja Curcic
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Matthias J P van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Natalia Petridou
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
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7
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Wang X, Krieger-Redwood K, Lyu B, Lowndes R, Wu G, Souter NE, Wang X, Kong R, Shafiei G, Bernhardt BC, Cui Z, Smallwood J, Du Y, Jefferies E. The Brain's Topographical Organization Shapes Dynamic Interaction Patterns That Support Flexible Behavior Based on Rules and Long-Term Knowledge. J Neurosci 2024; 44:e2223232024. [PMID: 38527807 PMCID: PMC11140685 DOI: 10.1523/jneurosci.2223-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 03/14/2024] [Accepted: 03/17/2024] [Indexed: 03/27/2024] Open
Abstract
Adaptive behavior relies both on specific rules that vary across situations and stable long-term knowledge gained from experience. The frontoparietal control network (FPCN) is implicated in the brain's ability to balance these different influences on action. Here, we investigate how the topographical organization of the cortex supports behavioral flexibility within the FPCN. Functional properties of this network might reflect its juxtaposition between the dorsal attention network (DAN) and the default mode network (DMN), two large-scale systems implicated in top-down attention and memory-guided cognition, respectively. Our study tests whether subnetworks of FPCN are topographically proximal to the DAN and the DMN, respectively, and how these topographical differences relate to functional differences: the proximity of each subnetwork is anticipated to play a pivotal role in generating distinct cognitive modes relevant to working memory and long-term memory. We show that FPCN subsystems share multiple anatomical and functional similarities with their neighboring systems (DAN and DMN) and that this topographical architecture supports distinct interaction patterns that give rise to different patterns of functional behavior. The FPCN acts as a unified system when long-term knowledge supports behavior but becomes segregated into discrete subsystems with different patterns of interaction when long-term memory is less relevant. In this way, our study suggests that the topographical organization of the FPCN and the connections it forms with distant regions of cortex are important influences on how this system supports flexible behavior.
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Affiliation(s)
- Xiuyi Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Katya Krieger-Redwood
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Baihan Lyu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Rebecca Lowndes
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Guowei Wu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nicholas E Souter
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Xiaokang Wang
- Department of Biomedical Engineering, University of California, Davis, California 95616
| | - Ru Kong
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Jonathan Smallwood
- Department of Psychology, Queens University, Kingston, Ontario K7L 3N6, Canada
| | - Yi Du
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
- Chinese Institute for Brain Research, Beijing 102206, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai 200031, China
| | - Elizabeth Jefferies
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
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8
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Naccache L, Munoz-Musat E. A global neuronal workspace model of functional neurological disorders. DIALOGUES IN CLINICAL NEUROSCIENCE 2024; 26:1-23. [PMID: 38767966 PMCID: PMC11107854 DOI: 10.1080/19585969.2024.2340131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 04/03/2024] [Indexed: 05/22/2024]
Abstract
We introduce here a general model of Functional Neurological Disorders based on the following hypothesis: a Functional Neurological Disorder could correspond to a consciously initiated voluntary top-down process causing involuntary lasting consequences that are consciously experienced and subjectively interpreted by the patient as involuntary. We develop this central hypothesis according to Global Neuronal Workspace theory of consciousness, that is particularly suited to describe interactions between conscious and non-conscious cognitive processes. We then present a list of predictions defining a research program aimed at empirically testing their validity. Finally, this general model leads us to reinterpret the long-debated links between hypnotic suggestion and functional neurological disorders. Driven by both scientific and therapeutic goals, this theoretical paper aims at bringing closer the psychiatric and neurological worlds of functional neurological disorders with the latest developments of cognitive neuroscience of consciousness.
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Affiliation(s)
- Lionel Naccache
- Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, Paris, France- Sorbonne Université, UPMC Univ Paris 06, Faculté de Médecine Pitié-Salpêtrière, Sorbonne Université, Paris, France
- Department of Neurology, AP-HP, Hôpital Groupe hospitalier Pitié-Salpêtrière, DMU Neurosciences, Paris, France
- Department of Clinical Neurophysiology, AP-HP, Hôpital Groupe hospitalier Pitié-Salpêtrière, DMU Neurosciences, Paris, France
| | - Esteban Munoz-Musat
- Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, Paris, France- Sorbonne Université, UPMC Univ Paris 06, Faculté de Médecine Pitié-Salpêtrière, Sorbonne Université, Paris, France
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9
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Thomas ER, Haarsma J, Nicholson J, Yon D, Kok P, Press C. Predictions and errors are distinctly represented across V1 layers. Curr Biol 2024; 34:2265-2271.e4. [PMID: 38697110 DOI: 10.1016/j.cub.2024.04.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 04/09/2024] [Accepted: 04/13/2024] [Indexed: 05/04/2024]
Abstract
Popular accounts of mind and brain propose that the brain continuously forms predictions about future sensory inputs and combines predictions with inputs to determine what we perceive.1,2,3,4,5,6 Under "predictive processing" schemes, such integration is supported by the hierarchical organization of the cortex, whereby feedback connections communicate predictions from higher-level deep layers to agranular (superficial and deep) lower-level layers.7,8,9,10 Predictions are compared with input to compute the "prediction error," which is transmitted up the hierarchy from superficial layers of lower cortical regions to the middle layers of higher areas, to update higher-level predictions until errors are reconciled.11,12,13,14,15 In the primary visual cortex (V1), predictions have thereby been proposed to influence representations in deep layers while error signals may be computed in superficial layers. Despite the framework's popularity, there is little evidence for these functional distinctions because, to our knowledge, unexpected sensory events have not previously been presented in human laminar paradigms to contrast against expected events. To this end, this 7T fMRI study contrasted V1 responses to expected (75% likely) and unexpected (25%) Gabor orientations. Multivariate decoding analyses revealed an interaction between expectation and layer, such that expected events could be decoded with comparable accuracy across layers, while unexpected events could only be decoded in superficial laminae. Although these results are in line with these accounts that have been popular for decades, such distinctions have not previously been demonstrated in humans. We discuss how both prediction and error processes may operate together to shape our unitary perceptual experiences.
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Affiliation(s)
- Emily R Thomas
- Neuroscience Institute, New York University Medical Center, 435 East 30(th) Street, New York 10016, USA; Department of Psychological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.
| | - Joost Haarsma
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3AR, UK
| | - Jessica Nicholson
- Department of Psychological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK
| | - Daniel Yon
- Department of Psychological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK
| | - Peter Kok
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3AR, UK
| | - Clare Press
- Department of Psychological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK; Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3AR, UK; Department of Experimental Psychology, University College London, 26 Bedford Way, London WC1H 0AP, UK.
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10
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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] [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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11
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Ishida T, Nittono H. Visual omitted stimulus potentials are not retinotopic. Neurosci Lett 2024; 830:137777. [PMID: 38621505 DOI: 10.1016/j.neulet.2024.137777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 04/03/2024] [Accepted: 04/12/2024] [Indexed: 04/17/2024]
Abstract
Omitted stimulus potentials (OSPs) are elicited in response to the omission of expected stimuli and are thought to reflect prediction errors. If prediction errors are signaled in the sensory cortex, OSPs are expected to be generated in the sensory cortex. The present study investigated the involvement of the early visual cortex in the generation of OSPs by testing whether omitted visual stimuli elicit brain responses in a spatially specific manner. Checkerboard pattern stimuli were presented alternately in the upper and lower visual fields, and the stimuli were omitted in 10 % of the trials. Event-related potentials were recorded from 33 participants. While a retinotopic C1 component was evoked by real visual stimuli, omitted stimuli did not produce any response reflecting retinotopy but did elicit a visual mismatch negativity, which was larger for omitted stimuli expected in the lower visual field than for those in the upper visual field. These results suggest that omitted visual stimuli are processed in a different pathway than actual stimuli.
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Affiliation(s)
- Tomomi Ishida
- Graduate School of Human Sciences, Osaka University, Osaka, Japan.
| | - Hiroshi Nittono
- Graduate School of Human Sciences, Osaka University, Osaka, Japan.
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12
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Milne GA, Lisi M, McLean A, Zheng R, Groen II, Dekker TM. Perceptual reorganization from prior knowledge emerges late in childhood. iScience 2024; 27:108787. [PMID: 38303715 PMCID: PMC10831247 DOI: 10.1016/j.isci.2024.108787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 09/05/2023] [Accepted: 01/02/2024] [Indexed: 02/03/2024] Open
Abstract
Human vision relies heavily on prior knowledge. Here, we show for the first time that prior-knowledge-induced reshaping of visual inputs emerges gradually in late childhood. To isolate the effects of prior knowledge on perception, we presented 4- to 12-year-olds and adults with two-tone images - hard-to-recognize degraded photos. In adults, seeing the original photo triggers perceptual reorganization, causing mandatory recognition of the two-tone version. This involves top-down signaling from higher-order brain areas to early visual cortex. We show that children younger than 7-9 years do not experience this knowledge-guided shift, despite viewing the original photo immediately before each two-tone. To assess computations underlying this development, we compared human performance to three neural networks with varying architectures. The best-performing model behaved much like 4- to 5-year-olds, displaying feature-based rather than holistic processing strategies. The reconciliation of prior knowledge with sensory input undergoes a striking age-related shift, which may underpin the development of many perceptual abilities.
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Affiliation(s)
- Georgia A. Milne
- Institute of Ophthalmology, University College London, EC1V 9EL London, UK
- Division of Psychology and Language Sciences, University College London, WC1H 0AP London, UK
| | - Matteo Lisi
- Department of Psychology, Royal Holloway, University of London, TW20 0EX London, UK
| | - Aisha McLean
- Institute of Ophthalmology, University College London, EC1V 9EL London, UK
| | - Rosie Zheng
- Informatics Institute, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Iris I.A. Groen
- Informatics Institute, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Tessa M. Dekker
- Institute of Ophthalmology, University College London, EC1V 9EL London, UK
- Division of Psychology and Language Sciences, University College London, WC1H 0AP London, UK
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13
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Lankinen K, Ahveninen J, Jas M, Raij T, Ahlfors SP. Neuronal modeling of magnetoencephalography responses in auditory cortex to auditory and visual stimuli. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.16.545371. [PMID: 37398025 PMCID: PMC10312796 DOI: 10.1101/2023.06.16.545371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Previous studies have demonstrated that auditory cortex activity can be influenced by crosssensory visual inputs. Intracortical recordings in non-human primates (NHP) have suggested a bottom-up feedforward (FF) type laminar profile for auditory evoked but top-down feedback (FB) type for cross-sensory visual evoked activity in the auditory cortex. To test whether this principle applies also to humans, we analyzed magnetoencephalography (MEG) responses from eight human subjects (six females) evoked by simple auditory or visual stimuli. In the estimated MEG source waveforms for auditory cortex region of interest, auditory evoked responses showed peaks at 37 and 90 ms and cross-sensory visual responses at 125 ms. The inputs to the auditory cortex were then modeled through FF and FB type connections targeting different cortical layers using the Human Neocortical Neurosolver (HNN), which consists of a neocortical circuit model linking the cellular- and circuit-level mechanisms to MEG. The HNN models suggested that the measured auditory response could be explained by an FF input followed by an FB input, and the crosssensory visual response by an FB input. Thus, the combined MEG and HNN results support the hypothesis that cross-sensory visual input in the auditory cortex is of FB type. The results also illustrate how the dynamic patterns of the estimated MEG/EEG source activity can provide information about the characteristics of the input into a cortical area in terms of the hierarchical organization among areas.
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Affiliation(s)
- Kaisu Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129
- Department of Radiology, Harvard Medical School, Boston, MA 02115
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129
- Department of Radiology, Harvard Medical School, Boston, MA 02115
| | - Mainak Jas
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129
- Department of Radiology, Harvard Medical School, Boston, MA 02115
| | - Tommi Raij
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129
- Department of Radiology, Harvard Medical School, Boston, MA 02115
| | - Seppo P. Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129
- Department of Radiology, Harvard Medical School, Boston, MA 02115
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14
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Bergmann J, Petro LS, Abbatecola C, Li MS, Morgan AT, Muckli L. Cortical depth profiles in primary visual cortex for illusory and imaginary experiences. Nat Commun 2024; 15:1002. [PMID: 38307834 PMCID: PMC10837448 DOI: 10.1038/s41467-024-45065-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 01/12/2024] [Indexed: 02/04/2024] Open
Abstract
Visual illusions and mental imagery are non-physical sensory experiences that involve cortical feedback processing in the primary visual cortex. Using laminar functional magnetic resonance imaging (fMRI) in two studies, we investigate if information about these internal experiences is visible in the activation patterns of different layers of primary visual cortex (V1). We find that imagery content is decodable mainly from deep layers of V1, whereas seemingly 'real' illusory content is decodable mainly from superficial layers. Furthermore, illusory content shares information with perceptual content, whilst imagery content does not generalise to illusory or perceptual information. Together, our results suggest that illusions and imagery, which differ immensely in their subjective experiences, also involve partially distinct early visual microcircuits. However, overlapping microcircuit recruitment might emerge based on the nuanced nature of subjective conscious experience.
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Affiliation(s)
- Johanna Bergmann
- Imaging Centre of Excellence (ICE), Queen Elizabeth University Hospital, University of Glasgow, Glasgow, UK.
- Centre for Cognitive Neuroimaging (CCNi), School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
- Department of Psychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Lucy S Petro
- Imaging Centre of Excellence (ICE), Queen Elizabeth University Hospital, University of Glasgow, Glasgow, UK
- Centre for Cognitive Neuroimaging (CCNi), School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Clement Abbatecola
- Imaging Centre of Excellence (ICE), Queen Elizabeth University Hospital, University of Glasgow, Glasgow, UK
- Centre for Cognitive Neuroimaging (CCNi), School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Min S Li
- Centre for Cognitive Neuroimaging (CCNi), School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
- Centre for Computational Neuroscience and Cognitive Robotics, School of Psychology, University of Birmingham, Birmingham, UK
| | - A Tyler Morgan
- Imaging Centre of Excellence (ICE), Queen Elizabeth University Hospital, University of Glasgow, Glasgow, UK
- Centre for Cognitive Neuroimaging (CCNi), School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
- Functional MRI Core Facility, National Institute of Mental Health, NIH, Bethesda, MD, 20817, USA
| | - Lars Muckli
- Imaging Centre of Excellence (ICE), Queen Elizabeth University Hospital, University of Glasgow, Glasgow, UK.
- Centre for Cognitive Neuroimaging (CCNi), School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
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15
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Hodson R, Mehta M, Smith R. The empirical status of predictive coding and active inference. Neurosci Biobehav Rev 2024; 157:105473. [PMID: 38030100 DOI: 10.1016/j.neubiorev.2023.105473] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/27/2023] [Accepted: 11/16/2023] [Indexed: 12/01/2023]
Abstract
Research on predictive processing models has focused largely on two specific algorithmic theories: Predictive Coding for perception and Active Inference for decision-making. While these interconnected theories possess broad explanatory potential, they have only recently begun to receive direct empirical evaluation. Here, we review recent studies of Predictive Coding and Active Inference with a focus on evaluating the degree to which they are empirically supported. For Predictive Coding, we find that existing empirical evidence offers modest support. However, some positive results can also be explained by alternative feedforward (e.g., feature detection-based) models. For Active Inference, most empirical studies have focused on fitting these models to behavior as a means of identifying and explaining individual or group differences. While Active Inference models tend to explain behavioral data reasonably well, there has not been a focus on testing empirical validity of active inference theory per se, which would require formal comparison to other models (e.g., non-Bayesian or model-free reinforcement learning models). This review suggests that, while promising, a number of specific research directions are still necessary to evaluate the empirical adequacy and explanatory power of these algorithms.
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Affiliation(s)
| | | | - Ryan Smith
- Laureate Institute for Brain Research, USA.
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16
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Faes LK, Lage-Castellanos A, Valente G, Yu Z, Cloos MA, Vizioli L, Moeller S, Yacoub E, De Martino F. Evaluating the effect of denoising submillimeter auditory fMRI data with NORDIC. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.24.577070. [PMID: 38328173 PMCID: PMC10849717 DOI: 10.1101/2024.01.24.577070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Functional magnetic resonance imaging (fMRI) has emerged as an essential tool for exploring human brain function. Submillimeter fMRI, in particular, has emerged as a tool to study mesoscopic computations. The inherently low signal-to-noise ratio (SNR) at submillimeter resolutions warrants the use of denoising approaches tailored at reducing thermal noise - the dominant contributing noise component in high resolution fMRI. NORDIC PCA is one of such approaches, and has been benchmarked against other approaches in several applications. Here, we investigate the effects that two versions of NORDIC denoising have on auditory submillimeter data. As investigating auditory functional responses poses unique challenges, we anticipated that the benefit of this technique would be especially pronounced. Our results show that NORDIC denoising improves the detection sensitivity and the reliability of estimates in submillimeter auditory fMRI data. These effects can be explained by the reduction of the noise-induced signal variability. However, we also observed a reduction in the average response amplitude (percent signal), which may suggest that a small amount of signal was also removed. We conclude that, while evaluating the effects of the signal reduction induced by NORDIC may be necessary for each application, using NORDIC in high resolution auditory fMRI studies may be advantageous because of the large reduction in variability of the estimated responses.
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Affiliation(s)
- Lonike K. Faes
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, The Netherlands
| | - Agustin Lage-Castellanos
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, The Netherlands
- Department of Neuroinformatics, Cuban Neuroscience Center, Havana City 11600, Cuba
| | - Giancarlo Valente
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, The Netherlands
| | - Zidan Yu
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, USA
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- MRI Research Center, University of Hawaii, United States
| | - Martijn A. Cloos
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, USA
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, St Lucia 4066, Australia
| | - Luca Vizioli
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Steen Moeller
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Federico De Martino
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, The Netherlands
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
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17
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Peelen MV, Berlot E, de Lange FP. Predictive processing of scenes and objects. NATURE REVIEWS PSYCHOLOGY 2024; 3:13-26. [PMID: 38989004 PMCID: PMC7616164 DOI: 10.1038/s44159-023-00254-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/25/2023] [Indexed: 07/12/2024]
Abstract
Real-world visual input consists of rich scenes that are meaningfully composed of multiple objects which interact in complex, but predictable, ways. Despite this complexity, we recognize scenes, and objects within these scenes, from a brief glance at an image. In this review, we synthesize recent behavioral and neural findings that elucidate the mechanisms underlying this impressive ability. First, we review evidence that visual object and scene processing is partly implemented in parallel, allowing for a rapid initial gist of both objects and scenes concurrently. Next, we discuss recent evidence for bidirectional interactions between object and scene processing, with scene information modulating the visual processing of objects, and object information modulating the visual processing of scenes. Finally, we review evidence that objects also combine with each other to form object constellations, modulating the processing of individual objects within the object pathway. Altogether, these findings can be understood by conceptualizing object and scene perception as the outcome of a joint probabilistic inference, in which "best guesses" about objects act as priors for scene perception and vice versa, in order to concurrently optimize visual inference of objects and scenes.
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Affiliation(s)
- Marius V Peelen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Eva Berlot
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Floris P de Lange
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
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18
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Nakashima Y, Kanazawa S, Yamaguchi MK. Metacontrast masking is ineffective in the first 6 months of life. Cognition 2024; 242:105666. [PMID: 37984131 DOI: 10.1016/j.cognition.2023.105666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 11/09/2023] [Accepted: 11/11/2023] [Indexed: 11/22/2023]
Abstract
Metacontrast masking is one of the most widely studied types of visual masking, in which a visual stimulus is rendered invisible by a subsequent mask that does not spatially overlap with the target. Metacontrast has been used for many decades as a tool to study visual processing and conscious perception in adults. However, there are so far no infant studies on metacontrast and it remains unknown even whether it occurs in infants. The present study examined metacontrast masking in 3- to 8-month-old infants (N = 168) using a habituation paradigm. We found that metacontrast is ineffective for infants under 7 months and that younger infants can perceive a masked stimulus that older infants cannot. Our results suggest that metacontrast is distinct from other simple types of masking that occur in early infancy, and would be consistent with the idea that metacontrast results from the disruption of recurrent processing.
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Affiliation(s)
- Yusuke Nakashima
- Research and Development Initiative, Chuo University, 742-1 Higashinakano, Hachioji-shi, Tokyo 192-0393, Japan.
| | - So Kanazawa
- Department of Psychology, Japan Women's University, 2-8-1 Mejirodai, Bunkyo-ku, Tokyo 112-8681, Japan
| | - Masami K Yamaguchi
- Department of Psychology, Chuo University, 742-1 Higashinakano, Hachioji-shi, Tokyo 192-0393, Japan
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19
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Kotlarz P, Lankinen K, Hakonen M, Turpin T, Polimeni JR, Ahveninen J. Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.23.573208. [PMID: 38187540 PMCID: PMC10769454 DOI: 10.1101/2023.12.23.573208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. A neuroscience example is the hierarchy of connections between different cortical depths or "lamina". This hierarchy is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We then compared networks where the inter-regional connections were limited to a single cortical depth only ("layer-by-layer matrices") to those considering all possible connections between regions and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes such as network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial aspects of the cortex dominated information transfer and deeper aspects clustering. These differences were largest in frontotemporal and limbic brain regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information. Multilayer connectomics could provide a methodological framework for studies on how information flows across this hierarchy.
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Affiliation(s)
- Parker Kotlarz
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Kaisu Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Maria Hakonen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | | | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
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20
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Feinberg DA, Beckett AJS, Vu AT, Stockmann J, Huber L, Ma S, Ahn S, Setsompop K, Cao X, Park S, Liu C, Wald LL, Polimeni JR, Mareyam A, Gruber B, Stirnberg R, Liao C, Yacoub E, Davids M, Bell P, Rummert E, Koehler M, Potthast A, Gonzalez-Insua I, Stocker S, Gunamony S, Dietz P. Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla. Nat Methods 2023; 20:2048-2057. [PMID: 38012321 PMCID: PMC10703687 DOI: 10.1038/s41592-023-02068-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 10/09/2023] [Indexed: 11/29/2023]
Abstract
To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.
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Affiliation(s)
- David A Feinberg
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
- Advanced MRI Technologies, Sebastopol, CA, USA.
| | - Alexander J S Beckett
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Advanced MRI Technologies, Sebastopol, CA, USA
| | - An T Vu
- Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
- San Francisco Veteran Affairs Health Care System, San Francisco, CA, USA
| | - Jason Stockmann
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Laurentius Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | | | | | - Kawin Setsompop
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Suhyung Park
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Department of Computer Engineering, Chonnam National University, Gwangju, Republic of Korea
- Department of ICT Convergence System Engineering, Chonnam National University, Gwangju, Republic of Korea
| | - Chunlei Liu
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Lawrence L Wald
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Jonathan R Polimeni
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Azma Mareyam
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Bernhard Gruber
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
- BARNLabs, Muenzkirchen, Austria
| | | | - Congyu Liao
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Mathias Davids
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Paul Bell
- Siemens Medical Solutions, Malvern, PA, USA
| | | | | | | | | | | | - Shajan Gunamony
- Imaging Centre of Excellence, University of Glasgow, Glasgow, UK
- MR CoilTech Limited, Glasgow, UK
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21
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Haarsma J, Deveci N, Corbin N, Callaghan MF, Kok P. Expectation Cues and False Percepts Generate Stimulus-Specific Activity in Distinct Layers of the Early Visual Cortex. J Neurosci 2023; 43:7946-7957. [PMID: 37739797 PMCID: PMC10669763 DOI: 10.1523/jneurosci.0998-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/10/2023] [Accepted: 09/13/2023] [Indexed: 09/24/2023] Open
Abstract
Perception has been proposed to result from the integration of feedforward sensory signals with internally generated feedback signals. Feedback signals are believed to play an important role in driving false percepts, that is, seeing things that are not actually there. Feedforward and feedback influences on perception can be studied using layer-specific fMRI, which we used here to interrogate neural activity underlying high-confidence false percepts while healthy human participants (N = 25, male and female) performed a perceptual orientation discrimination task. Auditory cues implicitly signaled the most likely upcoming orientation (referred to here as expectations). These expectations induced orientation-specific templates in the deep and superficial layers of V2, without affecting perception. In contrast, the orientation of falsely perceived stimuli with high confidence was reflected in the middle input layers of V2, suggesting a feedforward signal contributing to false percepts. The prevalence of high-confidence false percepts was related to everyday hallucination severity in a separate online sample (N = 100), suggesting a possible link with abnormal perceptual experiences. These results reveal a potential feedforward mechanism underlying false percepts, reflected by spontaneous stimulus-like activity in the input layers of the visual cortex, independent of top-down signals reflecting cued orientations.SIGNIFICANCE STATEMENT False percepts have been suggested to arise through excessive feedback signals. However, feedforward contributions to false percepts have remained largely understudied. Laminar fMRI has been shown to be useful in distinguishing feedforward from feedback activity as it allows the imaging of different cortical layers. In the present study we demonstrate that although cued orientations are encoded in the feedback layers of the visual cortex, the content of the false percepts are encoded in the feedforward layers and did not rely on these cued orientations. This shows that false percepts can in principle emerge from random feedforward signals in the visual cortex, with possible implications for disorders hallmarked by hallucinations like schizophrenia and Parkinson's disease.
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Affiliation(s)
- Joost Haarsma
- Wellcome Centre for Human Neuroimaging, University College London Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom
| | - Narin Deveci
- Wellcome Centre for Human Neuroimaging, University College London Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom
| | - Nadege Corbin
- Wellcome Centre for Human Neuroimaging, University College London Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom
- Centre de Résonance Magnétique des Systèmes Biologiques, Unité Mixte de Recherche 5536, Centre National de la Recherche Scientifique, Université de Bordeaux, 33076 Bordeaux, France
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, University College London Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom
| | - Peter Kok
- Wellcome Centre for Human Neuroimaging, University College London Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom
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22
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Cheng FL, Horikawa T, Majima K, Tanaka M, Abdelhack M, Aoki SC, Hirano J, Kamitani Y. Reconstructing visual illusory experiences from human brain activity. SCIENCE ADVANCES 2023; 9:eadj3906. [PMID: 37967184 PMCID: PMC10651116 DOI: 10.1126/sciadv.adj3906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/13/2023] [Indexed: 11/17/2023]
Abstract
Visual illusions provide valuable insights into the brain's interpretation of the world given sensory inputs. However, the precise manner in which brain activity translates into illusory experiences remains largely unknown. Here, we leverage a brain decoding technique combined with deep neural network (DNN) representations to reconstruct illusory percepts as images from brain activity. The reconstruction model was trained on natural images to establish a link between brain activity and perceptual features and then tested on two types of illusions: illusory lines and neon color spreading. Reconstructions revealed lines and colors consistent with illusory experiences, which varied across the source visual cortical areas. This framework offers a way to materialize subjective experiences, shedding light on the brain's internal representations of the world.
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Affiliation(s)
- Fan L. Cheng
- Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
- ATR Computational Neuroscience Laboratories, Soraku, Kyoto 619-0288, Japan
| | - Tomoyasu Horikawa
- ATR Computational Neuroscience Laboratories, Soraku, Kyoto 619-0288, Japan
| | - Kei Majima
- Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Misato Tanaka
- Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Mohamed Abdelhack
- Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Shuntaro C. Aoki
- Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Jin Hirano
- Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Yukiyasu Kamitani
- Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
- ATR Computational Neuroscience Laboratories, Soraku, Kyoto 619-0288, Japan
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23
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Heij J, Raimondo L, Siero JCW, Dumoulin SO, van der Zwaag W, Knapen T. A selection and targeting framework of cortical locations for line-scanning fMRI. Hum Brain Mapp 2023; 44:5471-5484. [PMID: 37608563 PMCID: PMC10543358 DOI: 10.1002/hbm.26459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/15/2023] [Accepted: 08/02/2023] [Indexed: 08/24/2023] Open
Abstract
Depth-resolved functional magnetic resonance imaging (fMRI) is an emerging field growing in popularity given the potential of separating signals from different computational processes in cerebral cortex. Conventional acquisition schemes suffer from low spatial and temporal resolutions. Line-scanning methods allow depth-resolved fMRI by sacrificing spatial coverage to sample blood oxygenated level-dependent (BOLD) responses at ultra-high temporal and spatial resolution. For neuroscience applications, it is critical to be able to place the line accurately to (1) sample the right neural population and (2) target that neural population with tailored stimuli or tasks. To this end, we devised a multi-session framework where a target cortical location is selected based on anatomical and functional properties. The line is then positioned according to this information in a separate second session, and we tailor the experiment to focus on the target location. Anatomically, the precision of the line placement was confirmed by projecting a nominal representation of the acquired line back onto the surface. Functional estimates of neural selectivities in the line, as quantified by a visual population-receptive field model, resembled the target selectivities well for most subjects. This functional precision was quantified in detail by estimating the distance between the visual field location of the targeted vertex and the location in visual cortex (V1) that most closely resembled the line-scanning estimates; this distance was on average ~5.5 mm. Given the dimensions of the line, differences in acquisition, session, and stimulus design, this validates that line-scanning can be used to probe local neural sensitivities across sessions. In summary, we present an accurate framework for line-scanning MRI; we believe such a framework is required to harness the full potential of line-scanning and maximize its utility. Furthermore, this approach bridges canonical fMRI experiments with electrophysiological experiments, which in turn allows novel avenues for studying human physiology non-invasively.
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Affiliation(s)
- Jurjen Heij
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Experimental and Applied PsychologyVU UniversityAmsterdamNetherlands
| | - Luisa Raimondo
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Experimental and Applied PsychologyVU UniversityAmsterdamNetherlands
| | - Jeroen C. W. Siero
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of RadiologyUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Serge O. Dumoulin
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Experimental and Applied PsychologyVU UniversityAmsterdamNetherlands
- Department of Experimental PsychologyUtrecht UniversityUtrechtNetherlands
| | - Wietske van der Zwaag
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Tomas Knapen
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Experimental and Applied PsychologyVU UniversityAmsterdamNetherlands
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24
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Malekian V, Graedel NN, Hickling A, Aghaeifar A, Dymerska B, Corbin N, Josephs O, Maguire EA, Callaghan MF. Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T. Neuroimage 2023; 279:120294. [PMID: 37517572 PMCID: PMC10951962 DOI: 10.1016/j.neuroimage.2023.120294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 07/08/2023] [Accepted: 07/22/2023] [Indexed: 08/01/2023] Open
Abstract
Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI.
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Affiliation(s)
- Vahid Malekian
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK.
| | - Nadine N Graedel
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Alice Hickling
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Ali Aghaeifar
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK; MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | - Barbara Dymerska
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Nadège Corbin
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK; Centre de Résonance Magnétique des Systèmes Biologiques, CNRS-University Bordeaux, Bordeaux, France
| | - Oliver Josephs
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Eleanor A Maguire
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
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25
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Martin A, Lane TJ, Hsu TY. DLPFC-PPC-cTBS effects on metacognitive awareness. Cortex 2023; 167:41-50. [PMID: 37523964 DOI: 10.1016/j.cortex.2023.05.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 02/12/2023] [Accepted: 05/16/2023] [Indexed: 08/02/2023]
Abstract
BACKGROUND Neuroimaging and lesion studies suggested that the dorsolateral prefrontal and posterior parietal cortices mediate visual metacognitive awareness. The causal evidence provided by non-invasive brain stimulation, however, is inconsistent. OBJECTIVE/HYPOTHESIS Here we revisit a major figure discrimination experiment adding a new Kanizsa figure task trying to resolve whether bilateral continuous theta-burst transcranial magnetic stimulation (cTBS) over these regions affects perceptual metacognition. Specifically, we tested whether subjective visibility ratings and/or metacognitive efficiency are lower when cTBS is applied to these two regions in comparison to an active control region. METHODS A within-subjects design including three sessions spaced by one-week intervals was implemented. In each session, every participant was administered bilateral cTBS to either prefrontal, control or parietal cortices. Two concurrent tasks were performed, a real and an illusory figure task, stabilising objective performance with use of an adaptive staircase procedure. RESULTS When performing the replicated task, cTBS was found insufficient to disrupt neither visibility ratings nor metacognitive efficiency. However, with use of Kanizsa style illusory figures, cTBS over the dorsolateral prefrontal, but not over the posterior parietal cortex, was observed to significantly diminish metacognitive efficiency. CONCLUSION(S) Real and illusory figure tasks demonstrated different cTBS effects. A possible explanation is the involvement of the prefrontal cortex in the creation of expectations, which is necessary for efficient metacognition. Failure to replicate previous findings for the real figure task, however, cannot be said to support, conclusively, the notion that these brain regions have a causal role in metacognitive awareness. This inconsistent finding may result from certain limitations of our study, thereby suggesting the need for yet further investigation.
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Affiliation(s)
- Antonio Martin
- Graduate Institute of Mind, Brain and Consciousness (GIMBC), Taipei Medical University, Taipei, Taiwan
| | - Timothy J Lane
- Graduate Institute of Mind, Brain and Consciousness (GIMBC), Taipei Medical University, Taipei, Taiwan; Brain and Consciousness Research Center (BCRC), TMU-Shuang Ho Hospital, New Taipei City, Taiwan
| | - Tzu-Yu Hsu
- Graduate Institute of Mind, Brain and Consciousness (GIMBC), Taipei Medical University, Taipei, Taiwan; Brain and Consciousness Research Center (BCRC), TMU-Shuang Ho Hospital, New Taipei City, Taiwan.
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26
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Stange L, Ossandón JP, Röder B. Crossmodal visual predictions elicit spatially specific early visual cortex activity but later than real visual stimuli. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220339. [PMID: 37545314 PMCID: PMC10404923 DOI: 10.1098/rstb.2022.0339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 06/30/2023] [Indexed: 08/08/2023] Open
Abstract
Previous studies have indicated that crossmodal visual predictions are instrumental in controlling early visual cortex activity. The exact time course and spatial precision of such crossmodal top-down influences on the visual cortex have been unknown. In the present study, participants were exposed to audiovisual combinations comprising one of two sounds and a Gabor patch either in the top left or in the bottom right visual field. Event-related potentials (ERPs) were recorded to these frequent crossmodal combinations (standards) as well as to trials in which the visual stimulus was omitted (omissions) or the visual and auditory stimuli were recombined (deviants). Standards and deviants elicited an ERP between 50 and 100 ms of opposite polarity known as the C1 effect commonly associated with retinotopic processing in early visual cortex. By contrast, a C1 effect was not observed in omission trials. Spatially specific omission and mismatch effects (deviants minus standards) started only later with a latency of 230 ms and 170 ms, respectively. These results suggest that crossmodal visual predictions control visual cortex activity in a spatially specific manner. However, visual predictions do not modulate visual cortex activity with the same timing as visual stimulation activates these areas but rather seem to involve distinct neural mechanisms. This article is part of the theme issue 'Decision and control processes in multisensory perception'.
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Affiliation(s)
- Liesa Stange
- Biological Psychology and Neuropsychology, Hamburg University, Von-Melle-Park 11, Hamburg 20148, Germany
| | - José P. Ossandón
- Biological Psychology and Neuropsychology, Hamburg University, Von-Melle-Park 11, Hamburg 20148, Germany
| | - Brigitte Röder
- Biological Psychology and Neuropsychology, Hamburg University, Von-Melle-Park 11, Hamburg 20148, Germany
- LV Prasad Eye Institute, Hyderabad 500 034, India
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27
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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] [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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28
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Riley SN, Davies J. Vividness as the similarity between generated imagery and an internal model. Brain Cogn 2023; 169:105988. [PMID: 37150045 DOI: 10.1016/j.bandc.2023.105988] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 05/09/2023]
Abstract
Vividness in visual mental imagery has been relatively under-explored compared to imagery's representational format and neural mechanisms. In this paper, we take a deeper look at vividness and suggest that in re-framing it, we can potentially reconcile disparate findings regarding visual cortex activation during imagery. Unlike traditional views of vividness that define the concept in terms of perception, we frame vividness in terms of imagery's relation to an internal model; the closer the generated imagery is to this model, the more vivid it is. This view is considered alongside existing neuroscientific, psychological, and philosophical research, as well as directions for future research.
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Affiliation(s)
- Sean N Riley
- Department of Cognitive Science, Carleton University, Canada
| | - Jim Davies
- Department of Cognitive Science, Carleton University, Canada.
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29
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Chu Q, Ma O, Hang Y, Tian X. Dual-stream cortical pathways mediate sensory prediction. Cereb Cortex 2023:7169133. [PMID: 37197767 DOI: 10.1093/cercor/bhad168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 04/24/2023] [Accepted: 04/26/2023] [Indexed: 05/19/2023] Open
Abstract
Predictions are constantly generated from diverse sources to optimize cognitive functions in the ever-changing environment. However, the neural origin and generation process of top-down induced prediction remain elusive. We hypothesized that motor-based and memory-based predictions are mediated by distinct descending networks from motor and memory systems to the sensory cortices. Using functional magnetic resonance imaging (fMRI) and a dual imagery paradigm, we found that motor and memory upstream systems activated the auditory cortex in a content-specific manner. Moreover, the inferior and posterior parts of the parietal lobe differentially relayed predictive signals in motor-to-sensory and memory-to-sensory networks. Dynamic causal modeling of directed connectivity revealed selective enabling and modulation of connections that mediate top-down sensory prediction and ground the distinctive neurocognitive basis of predictive processing.
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Affiliation(s)
- Qian Chu
- Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning, Division of Arts and Sciences, New York University Shanghai, Shanghai 200126, China
- NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai 200062, China
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, ON M5S 2E4, Canada
| | - Ou Ma
- NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai 200062, China
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Yuqi Hang
- NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai 200062, China
- Department of Administration, Leadership, and Technology, Steinhardt School of Culture, Education, and Human Development, New York University, New York, NY 10003, United States
| | - Xing Tian
- Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning, Division of Arts and Sciences, New York University Shanghai, Shanghai 200126, China
- NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai 200062, China
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
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30
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Olman CA. What multiplexing means for the interpretation of functional MRI data. Front Hum Neurosci 2023; 17:1134811. [PMID: 37091812 PMCID: PMC10117671 DOI: 10.3389/fnhum.2023.1134811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 03/20/2023] [Indexed: 04/08/2023] Open
Abstract
Despite technology advances that have enabled routine acquisition of functional MRI data with sub-millimeter resolution, the inferences that cognitive neuroscientists must make to link fMRI data to behavior are complicated. Thus, a single dataset subjected to different analyses can be interpreted in different ways. This article presents two optical analogies that can be useful for framing fMRI analyses in a way that allows for multiple interpretations of fMRI data to be valid simultaneously without undermining each other. The first is reflection: when an object is reflected in a mirrored surface, it appears as if the reflected object is sharing space with the mirrored object, but of course it is not. This analogy can be a good guide for interpreting the fMRI signal, since even at sub-millimeter resolutions the signal is determined by a mixture of local and long-range neural computations. The second is refraction. If we view an object through a multi-faceted prism or gemstone, our view will change-sometimes dramatically-depending on our viewing angle. In the same way, interpretation of fMRI data (inference of underlying neuronal activity) can and should be different depending on the analysis approach. Rather than representing a weakness of the methodology, or the superiority of one approach over the other (for example, simple regression analysis versus multi-voxel pattern analysis), this is an expected consequence of how information is multiplexed in the neural networks of the brain: multiple streams of information are simultaneously present in each location. The fact that any one analysis typically shows only one view of the data also puts some parentheses around fMRI practitioners' constant search for ground truth against which to compare their data. By holding our interpretations lightly and understanding that many interpretations of the data can all be true at the same time, we do a better job of preparing ourselves to appreciate, and eventually understand, the complexity of the brain and the behavior it produces.
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Affiliation(s)
- Cheryl A. Olman
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
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31
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Knudsen L, Bailey CJ, Blicher JU, Yang Y, Zhang P, Lund TE. Improved sensitivity and microvascular weighting of 3T laminar fMRI with GE-BOLD using NORDIC and phase regression. Neuroimage 2023; 271:120011. [PMID: 36914107 DOI: 10.1016/j.neuroimage.2023.120011] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 03/03/2023] [Accepted: 03/09/2023] [Indexed: 03/15/2023] Open
Abstract
INTRODUCTION Functional MRI with spatial resolution in the submillimeter domain enables measurements of activation across cortical layers in humans. This is valuable as different types of cortical computations, e.g., feedforward versus feedback related activity, take place in different cortical layers. Laminar fMRI studies have almost exclusively employed 7T scanners to overcome the reduced signal stability associated with small voxels. However, such systems are relatively rare and only a subset of those are clinically approved. In the present study, we examined if the feasibility of laminar fMRI at 3T could be improved by use of NORDIC denoising and phase regression. METHODS 5 healthy subjects were scanned on a Siemens MAGNETOM Prisma 3T scanner. To assess across-session reliability, each subject was scanned in 3-8 sessions on 3-4 consecutive days. A 3D gradient echo EPI (GE-EPI) sequence was used for BOLD acquisitions (voxel size 0.82 mm isotopic, TR = 2.2 s) using a block design finger tapping paradigm. NORDIC denoising was applied to the magnitude and phase time series to overcome limitations in temporal signal-to-noise ratio (tSNR) and the denoised phase time series were subsequently used to correct for large vein contamination through phase regression. RESULTS AND CONCLUSION NORDIC denoising resulted in tSNR values comparable to or higher than commonly observed at 7T. Layer-dependent activation profiles could thus be extracted robustly, within and across sessions, from regions of interest located in the hand knob of the primary motor cortex (M1). Phase regression led to substantially reduced superficial bias in obtained layer profiles, although residual macrovascular contribution remained. We believe the present results support an improved feasibility of laminar fMRI at 3T.
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Affiliation(s)
- Lasse Knudsen
- Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Universitetsbyen 3, Aarhus C 8000, Denmark; Sino-Danish Center for Education and Research (SDC), University of Chinese Academy of Sciences, 380 Huaibeizhuang, Huairou District, Beijing 101400, PR China.
| | - Christopher J Bailey
- Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Universitetsbyen 3, Aarhus C 8000, Denmark; Sino-Danish Center for Education and Research (SDC), University of Chinese Academy of Sciences, 380 Huaibeizhuang, Huairou District, Beijing 101400, PR China
| | - Jakob U Blicher
- Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Universitetsbyen 3, Aarhus C 8000, Denmark; Department of Neurology, Aalborg University Hospital, Aalborg, Denmark
| | - Yan Yang
- Sino-Danish Center for Education and Research (SDC), University of Chinese Academy of Sciences, 380 Huaibeizhuang, Huairou District, Beijing 101400, PR China; Institute of Biophysics, Chinese Academy of Sciences, Beijing, PR China
| | - Peng Zhang
- Sino-Danish Center for Education and Research (SDC), University of Chinese Academy of Sciences, 380 Huaibeizhuang, Huairou District, Beijing 101400, PR China; Institute of Biophysics, Chinese Academy of Sciences, Beijing, PR China
| | - Torben E Lund
- Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Universitetsbyen 3, Aarhus C 8000, Denmark
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32
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Scheeringa R, Bonnefond M, van Mourik T, Jensen O, Norris DG, Koopmans PJ. Relating neural oscillations to laminar fMRI connectivity in visual cortex. Cereb Cortex 2023; 33:1537-1549. [PMID: 35512361 PMCID: PMC9977363 DOI: 10.1093/cercor/bhac154] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 03/30/2022] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Laminar functional magnetic resonance imaging (fMRI) holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded electroencephalography (EEG) and high-resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions in visual cortex. Our results indicate that our task-induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent, alpha band oscillations relate to laminar-specific fMRI connectivity. The differential effects for alpha and beta bands indicate that they relate to different feedback-related neural processes that are differentially expressed in intra-region laminar fMRI-based connectivity.
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Affiliation(s)
- René Scheeringa
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO-Weltkulturerbe Zollverein, University of Duisburg-Essen, Kokereiallee 7, 45141 Essen, Germany.,High-Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany.,Lyon Neuroscience Research Center; CRNL, INSERM U1028, CNRS UMR5292, University of Lyon 1, Université de Lyon, Bâtiment 462 - Neurocampus, 95 Bd Pinel, 69500 Bron, France.,Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Trigon 204, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands
| | - Mathilde Bonnefond
- Lyon Neuroscience Research Center; CRNL, INSERM U1028, CNRS UMR5292, University of Lyon 1, Université de Lyon, Bâtiment 462 - Neurocampus, 95 Bd Pinel, 69500 Bron, France
| | - Tim van Mourik
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Trigon 204, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands
| | - Ole Jensen
- School of Psychology, Centre for Human Brain Health, University of Birmingham, Hills Building, Birmingham B15 2TT, United Kingdom
| | - David G Norris
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO-Weltkulturerbe Zollverein, University of Duisburg-Essen, Kokereiallee 7, 45141 Essen, Germany.,Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Trigon 204, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands
| | - Peter J Koopmans
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO-Weltkulturerbe Zollverein, University of Duisburg-Essen, Kokereiallee 7, 45141 Essen, Germany.,High-Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany.,Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Trigon 204, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.,Department of Radiation Oncology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
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33
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Faes LK, De Martino F, Huber L(R. Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities. PLoS One 2023; 18:e0280855. [PMID: 36758009 PMCID: PMC9910709 DOI: 10.1371/journal.pone.0280855] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 01/09/2023] [Indexed: 02/10/2023] Open
Abstract
The development of ultra high field fMRI signal readout strategies and contrasts has led to the possibility of imaging the human brain in vivo and non-invasively at increasingly higher spatial resolutions of cortical layers and columns. One emergent layer-fMRI acquisition method with increasing popularity is the cerebral blood volume sensitive sequence named vascular space occupancy (VASO). This approach has been shown to be mostly sensitive to locally-specific changes of laminar microvasculature, without unwanted biases of trans-laminar draining veins. Until now, however, VASO has not been applied in the technically challenging cortical area of the auditory cortex. Here, we describe the main challenges we encountered when developing a VASO protocol for auditory neuroscientific applications and the solutions we have adopted. With the resulting protocol, we present preliminary results of laminar responses to sounds and as a proof of concept for future investigations, we map the topographic representation of frequency preference (tonotopy) in the auditory cortex.
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Affiliation(s)
- Lonike K. Faes
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- * E-mail:
| | - Federico De Martino
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Laurentius (Renzo) Huber
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
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34
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Ye Z, Ding J, Tu Y, Zhang Q, Chen S, Yu H, Sun Q, Hua T. Suppression of top-down influence decreases both behavioral and V1 neuronal response sensitivity to stimulus orientations in cats. Front Behav Neurosci 2023; 17:1061980. [PMID: 36844652 PMCID: PMC9944033 DOI: 10.3389/fnbeh.2023.1061980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 01/24/2023] [Indexed: 02/11/2023] Open
Abstract
How top-down influence affects behavioral detection of visual signals and neuronal response sensitivity in the primary visual cortex (V1) remains poorly understood. This study examined both behavioral performance in stimulus orientation identification and neuronal response sensitivity to stimulus orientations in the V1 of cat before and after top-down influence of area 7 (A7) was modulated by non-invasive transcranial direct current stimulation (tDCS). Our results showed that cathode (c) but not sham (s) tDCS in A7 significantly increased the behavioral threshold in identifying stimulus orientation difference, which effect recovered after the tDCS effect vanished. Consistently, c-tDCS but not s-tDCS in A7 significantly decreased the response selectivity bias of V1 neurons for stimulus orientations, which effect could recover after withdrawal of the tDCS effect. Further analysis showed that c-tDCS induced reduction of V1 neurons in response selectivity was not resulted from alterations of neuronal preferred orientation, nor of spontaneous activity. Instead, c-tDCS in A7 significantly lowered the visually-evoked response, especially the maximum response of V1 neurons, which caused a decrease in response selectivity and signal-to-noise ratio. By contrast, s-tDCS exerted no significant effect on the responses of V1 neurons. These results indicate that top-down influence of A7 may enhance behavioral identification of stimulus orientations by increasing neuronal visually-evoked response and response selectivity in the V1.
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Affiliation(s)
- Zheng Ye
- College of Life sciences, Anhui Normal University, Wuhu, Anhui, China
| | - Jian Ding
- College of Life sciences, Anhui Normal University, Wuhu, Anhui, China,School of Basic Medical, Wannan Medical College, Wuhu, Anhui, China
| | - Yanni Tu
- College of Life sciences, Anhui Normal University, Wuhu, Anhui, China
| | - Qiuyu Zhang
- College of Life sciences, Anhui Normal University, Wuhu, Anhui, China
| | - Shunshun Chen
- College of Life sciences, Anhui Normal University, Wuhu, Anhui, China
| | - Hao Yu
- College of Life sciences, Anhui Normal University, Wuhu, Anhui, China
| | - Qingyan Sun
- College of Life sciences, Anhui Normal University, Wuhu, Anhui, China
| | - Tianmiao Hua
- College of Life sciences, Anhui Normal University, Wuhu, Anhui, China,*Correspondence: Tianmiao Hua,
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35
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Lankinen K, Ahlfors SP, Mamashli F, Blazejewska AI, Raij T, Turpin T, Polimeni JR, Ahveninen J. Cortical depth profiles of auditory and visual 7 T functional MRI responses in human superior temporal areas. Hum Brain Mapp 2023; 44:362-372. [PMID: 35980015 PMCID: PMC9842898 DOI: 10.1002/hbm.26046] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 07/06/2022] [Accepted: 07/16/2022] [Indexed: 02/02/2023] Open
Abstract
Invasive neurophysiological studies in nonhuman primates have shown different laminar activation profiles to auditory vs. visual stimuli in auditory cortices and adjacent polymodal areas. Means to examine the underlying feedforward vs. feedback type influences noninvasively have been limited in humans. Here, using 1-mm isotropic resolution 3D echo-planar imaging at 7 T, we studied the intracortical depth profiles of functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) signals to brief auditory (noise bursts) and visual (checkerboard) stimuli. BOLD percent-signal-changes were estimated at 11 equally spaced intracortical depths, within regions-of-interest encompassing auditory (Heschl's gyrus, Heschl's sulcus, planum temporale, and posterior superior temporal gyrus) and polymodal (middle and posterior superior temporal sulcus) areas. Effects of differing BOLD signal strengths for auditory and visual stimuli were controlled via normalization and statistical modeling. The BOLD depth profile shapes, modeled with quadratic regression, were significantly different for auditory vs. visual stimuli in auditory cortices, but not in polymodal areas. The different depth profiles could reflect sensory-specific feedforward versus cross-sensory feedback influences, previously shown in laminar recordings in nonhuman primates. The results suggest that intracortical BOLD profiles can help distinguish between feedforward and feedback type influences in the human brain. Further experimental studies are still needed to clarify how underlying signal strength influences BOLD depth profiles under different stimulus conditions.
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Affiliation(s)
- Kaisu Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Seppo P. Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Fahimeh Mamashli
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Anna I. Blazejewska
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Tommi Raij
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Tori Turpin
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Division of Health Sciences and TechnologyMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
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36
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Himmelberg MM, Gardner JL, Winawer J. What has vision science taught us about functional MRI? Neuroimage 2022; 261:119536. [PMID: 35931310 PMCID: PMC9756767 DOI: 10.1016/j.neuroimage.2022.119536] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/21/2022] [Accepted: 08/02/2022] [Indexed: 10/31/2022] Open
Abstract
In the domain of human neuroimaging, much attention has been paid to the question of whether and how the development of functional magnetic resonance imaging (fMRI) has advanced our scientific knowledge of the human brain. However, the opposite question is also important; how has our knowledge of the brain advanced our understanding of fMRI? Here, we discuss how and why scientific knowledge about the human and animal visual system has been used to answer fundamental questions about fMRI as a brain measurement tool and how these answers have contributed to scientific discoveries beyond vision science.
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Affiliation(s)
- Marc M Himmelberg
- Department of Psychology, New York University, NY, USA; Center for Neural Science, New York University, NY, USA.
| | | | - Jonathan Winawer
- Department of Psychology, New York University, NY, USA; Center for Neural Science, New York University, NY, USA
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37
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Liu TT, Fu JZ, Chai Y, Japee S, Chen G, Ungerleider LG, Merriam EP. Layer-specific, retinotopically-diffuse modulation in human visual cortex in response to viewing emotionally expressive faces. Nat Commun 2022; 13:6302. [PMID: 36273204 PMCID: PMC9588045 DOI: 10.1038/s41467-022-33580-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 09/22/2022] [Indexed: 12/25/2022] Open
Abstract
Viewing faces that are perceived as emotionally expressive evokes enhanced neural responses in multiple brain regions, a phenomenon thought to depend critically on the amygdala. This emotion-related modulation is evident even in primary visual cortex (V1), providing a potential neural substrate by which emotionally salient stimuli can affect perception. How does emotional valence information, computed in the amygdala, reach V1? Here we use high-resolution functional MRI to investigate the layer profile and retinotopic distribution of neural activity specific to emotional facial expressions. Across three experiments, human participants viewed centrally presented face stimuli varying in emotional expression and performed a gender judgment task. We found that facial valence sensitivity was evident only in superficial cortical layers and was not restricted to the retinotopic location of the stimuli, consistent with diffuse feedback-like projections from the amygdala. Together, our results provide a feedback mechanism by which the amygdala directly modulates activity at the earliest stage of visual processing.
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Affiliation(s)
- Tina T Liu
- Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892, MD, USA.
| | - Jason Z Fu
- Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892, MD, USA
| | - Yuhui Chai
- Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892, MD, USA
| | - Shruti Japee
- Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892, MD, USA
| | - Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, NIH, Bethesda, 20892, MD, USA
| | - Leslie G Ungerleider
- Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892, MD, USA
| | - Elisha P Merriam
- Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892, MD, USA
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38
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Huang L, Chen Y, Shen S, Ye H, Ou S, Zhang X. Awareness-independent gradual spread of object-based attention. CURRENT PSYCHOLOGY 2022. [DOI: 10.1007/s12144-022-03875-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
AbstractAlthough attention can be directed at certain objects, how object-based attention spreads within an object and whether this spread interacts with awareness remain unclear. Using a modified spatial cuing paradigm with backward masking, we addressed these issues with either visible or invisible displays presenting the real (Experiment 1) and illusory (Experiment 2) U-shaped objects (UOs), whose ends and middles, the possible locations of the cue and target, have iso-eccentric distances from the fixation. These equidistant ends and middles of UOs offered us a unique opportunity to examine whether attention gradually spreads within a given object, i.e., within an UO, attention spreads from its cued-end to uncued-end via the uncued-middle. Despite the visibility (visible or invisible) of UOs, both experiments supported this gradual spread manner by showing a faster response of human participants (male and female) to the target in the uncued-middle than that in the uncued-end. Our results thus indicate a gradual spread of object-based attention and further reveal that this gradual spread is independent of both the “visual objectness” (whether the object is defined as the real or illusory boundaries) and conscious access to objects.
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39
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Demirayak P, Deshpande G, Visscher K. Laminar functional magnetic resonance imaging in vision research. Front Neurosci 2022; 16:910443. [PMID: 36267240 PMCID: PMC9577024 DOI: 10.3389/fnins.2022.910443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
Magnetic resonance imaging (MRI) scanners at ultra-high magnetic fields have become available to use in humans, thus enabling researchers to investigate the human brain in detail. By increasing the spatial resolution, ultra-high field MR allows both structural and functional characterization of cortical layers. Techniques that can differentiate cortical layers, such as histological studies and electrode-based measurements have made critical contributions to the understanding of brain function, but these techniques are invasive and thus mainly available in animal models. There are likely to be differences in the organization of circuits between humans and even our closest evolutionary neighbors. Thus research on the human brain is essential. Ultra-high field MRI can observe differences between cortical layers, but is non-invasive and can be used in humans. Extensive previous literature has shown that neuronal connections between brain areas that transmit feedback and feedforward information terminate in different layers of the cortex. Layer-specific functional MRI (fMRI) allows the identification of layer-specific hemodynamic responses, distinguishing feedback and feedforward pathways. This capability has been particularly important for understanding visual processing, as it has allowed researchers to test hypotheses concerning feedback and feedforward information in visual cortical areas. In this review, we provide a general overview of successful ultra-high field MRI applications in vision research as examples of future research.
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Affiliation(s)
- Pinar Demirayak
- Civitan International Research Center, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL, United States
- *Correspondence: Pinar Demirayak,
| | - Gopikrishna Deshpande
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Department of Psychological Sciences, Auburn University, Auburn, AL, United States
- Alabama Advanced Imaging Consortium, Birmingham, AL, United States
- Center for Neuroscience, Auburn University, Auburn, AL, United States
- School of Psychology, Capital Normal University, Beijing, China
- Key Laboratory of Learning and Cognition, Capital Normal University, Beijing, China
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
| | - Kristina Visscher
- Civitan International Research Center, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL, United States
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40
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Dual counterstream architecture may support separation between vision and predictions. Conscious Cogn 2022; 103:103375. [DOI: 10.1016/j.concog.2022.103375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 12/03/2021] [Accepted: 06/28/2022] [Indexed: 11/24/2022]
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41
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Graedel NN, Miller KL, Chiew M. Ultrahigh Resolution fMRI at 7T Using Radial-Cartesian TURBINE Sampling. Magn Reson Med 2022; 88:2058-2073. [PMID: 35785429 PMCID: PMC9546489 DOI: 10.1002/mrm.29359] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 04/21/2022] [Accepted: 05/23/2022] [Indexed: 12/05/2022]
Abstract
Purpose We investigate the use of TURBINE, a 3D radial‐Cartesian acquisition scheme in which EPI planes are rotated about the phase‐encoding axis to acquire a cylindrical k‐space for high‐fidelity ultrahigh isotropic resolution fMRI at 7 Tesla with minimal distortion and blurring. Methods An improved, completely self‐navigated version of the TURBINE sampling scheme was designed for fMRI at 7 Telsa. To demonstrate the image quality and spatial specificity of the acquisition, thin‐slab visual and motor BOLD fMRI at 0.67 mm isotropic resolution (16 mm slab, TRvol = 2.32 s), and 0.8 × 0.8 × 2.0 mm (whole‐brain, TRvol = 2.4 s) data were acquired. To prioritize the high spatial fidelity, we employed a temporally regularized reconstruction to improve sensitivity without any spatial bias. Results TURBINE images provide high structural fidelity with almost no distortion, dropout, or T2* blurring for the thin‐slab acquisitions compared to conventional 3D EPI owing to the radial sampling in‐plane and the short echo train used. This results in activation that can be localized to pre‐ and postcentral gyri in a motor task, for example, with excellent correspondence to brain structure measured by a T1‐MPRAGE. The benefits of TURBINE (low distortion, dropout, blurring) are reduced for the whole‐brain acquisition due to the longer EPI train. We demonstrate robust BOLD activation at 0.67 mm isotropic resolution (thin‐slab) and also anisotropic 0.8 × 0.8 × 2.0 mm (whole‐brain) acquisitions. Conclusion TURBINE is a promising acquisition approach for high‐resolution, minimally distorted fMRI at 7 Tesla and could be particularly useful for fMRI in areas of high B0 inhomogeneity. Click here for author‐reader discussions
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Affiliation(s)
- Nadine N Graedel
- Wellcome Centre for Integrative Neuroscience, FMRIB Centre, University of Oxford, Oxford, United Kingdom.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroscience, FMRIB Centre, University of Oxford, Oxford, United Kingdom
| | - Mark Chiew
- Wellcome Centre for Integrative Neuroscience, FMRIB Centre, University of Oxford, Oxford, United Kingdom
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42
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Sheldon AD, Kafadar E, Fisher V, Greenwald MS, Aitken F, Negreira AM, Woods SW, Powers AR. Perceptual pathways to hallucinogenesis. Schizophr Res 2022; 245:77-89. [PMID: 35216865 PMCID: PMC9232894 DOI: 10.1016/j.schres.2022.02.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/31/2022] [Accepted: 02/02/2022] [Indexed: 12/22/2022]
Abstract
Recent advances in computational psychiatry have provided unique insights into the neural and cognitive underpinnings of psychotic symptoms. In particular, a host of new data has demonstrated the utility of computational frameworks for understanding how hallucinations might arise from alterations in typical perceptual processing. Of particular promise are models based in Bayesian inference that link hallucinatory perceptual experiences to latent states that may drive them. In this piece, we move beyond these findings to ask: how and why do these latent states arise, and how might we take advantage of heterogeneity in that process to develop precision approaches to the treatment of hallucinations? We leverage specific models of Bayesian inference to discuss components that might lead to the development of hallucinations. Using the unifying power of our model, we attempt to place disparate findings in the study of psychotic symptoms within a common framework. Finally, we suggest directions for future elaboration of these models in the service of a more refined psychiatric nosology based on predictable, testable, and ultimately treatable information processing derangements.
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Affiliation(s)
- Andrew D Sheldon
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States of America
| | - Eren Kafadar
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States of America
| | - Victoria Fisher
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States of America
| | - Maximillian S Greenwald
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States of America
| | - Fraser Aitken
- School of Biomedical and Imaging Sciences, Kings College, London, UK
| | | | - Scott W Woods
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States of America
| | - Albert R Powers
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States of America.
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43
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Haarsma J, Kok P, Browning M. The promise of layer-specific neuroimaging for testing predictive coding theories of psychosis. Schizophr Res 2022; 245:68-76. [PMID: 33199171 PMCID: PMC9241988 DOI: 10.1016/j.schres.2020.10.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 10/03/2020] [Accepted: 10/28/2020] [Indexed: 12/24/2022]
Abstract
Predictive coding potentially provides an explanatory model for understanding the neurocognitive mechanisms of psychosis. It proposes that cognitive processes, such as perception and inference, are implemented by a hierarchical system, with the influence of each level being a function of the estimated precision of beliefs at that level. However, predictive coding models of psychosis are insufficiently constrained-any phenomenon can be explained in multiple ways by postulating different changes to precision at different levels of processing. One reason for the lack of constraint in these models is that the core processes are thought to be implemented by the function of specific cortical layers, and the technology to measure layer specific neural activity in humans has until recently been lacking. As a result, our ability to constrain the models with empirical data has been limited. In this review we provide a brief overview of predictive processing models of psychosis and then describe the potential for newly developed, layer specific neuroimaging techniques to test and thus constrain these models. We conclude by discussing the most promising avenues for this research as well as the technical and conceptual challenges which may limit its application.
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Affiliation(s)
- J. Haarsma
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom,Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Corresponding author at: Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.
| | - P. Kok
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - M. Browning
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Oxford Health NHS Trust, Oxford, United Kingdom
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44
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Yun SD, Pais-Roldán P, Palomero-Gallagher N, Shah NJ. Mapping of whole-cerebrum resting-state networks using ultra-high resolution acquisition protocols. Hum Brain Mapp 2022; 43:3386-3403. [PMID: 35384130 PMCID: PMC9248311 DOI: 10.1002/hbm.25855] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/17/2022] [Accepted: 03/25/2022] [Indexed: 12/28/2022] Open
Abstract
Resting‐state functional magnetic resonance imaging (fMRI) has been used in numerous studies to map networks in the brain that employ spatially disparate regions. However, attempts to map networks with high spatial resolution have been hampered by conflicting technical demands and associated problems. Results from recent fMRI studies have shown that spatial resolution remains around 0.7 × 0.7 × 0.7 mm3, with only partial brain coverage. Therefore, this work aims to present a novel fMRI technique that was developed based on echo‐planar‐imaging with keyhole (EPIK) combined with repetition‐time‐external (TR‐external) EPI phase correction. Each technique has been previously shown to be effective in enhancing the spatial resolution of fMRI, and in this work, the combination of the two techniques into TR‐external EPIK provided a nominal spatial resolution of 0.51 × 0.51 × 1.00 mm3 (0.26 mm3 voxel) with whole‐cerebrum coverage. Here, the feasibility of using half‐millimetre in‐plane TR‐external EPIK for resting‐state fMRI was validated using 13 healthy subjects and the corresponding reproducible mapping of resting‐state networks was demonstrated. Furthermore, TR‐external EPIK enabled the identification of various resting‐state networks distributed throughout the brain from a single fMRI session, with mapping fidelity onto the grey matter at 7T. The high‐resolution functional image further revealed mesoscale anatomical structures, such as small cerebral vessels and the internal granular layer of the cortex within the postcentral gyrus.
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Affiliation(s)
- Seong Dae Yun
- Institute of Neuroscience and Medicine-4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Patricia Pais-Roldán
- Institute of Neuroscience and Medicine-4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine-1, Structural and Functional Organisation of the Brain, Forschungszentrum Jülich, Jülich, Germany.,C. & O. Vogt Institute for Brain Research, Heinrich-Heine-University, Düsseldorf, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine-4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany.,Institute of Neuroscience and Medicine-11, Molecular Neuroscience and Neuroimaging, JARA, Forschungszentrum Jülich, Jülich, Germany.,JARA - BRAIN - Translational Medicine, Aachen, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany
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45
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Central-peripheral dichotomy: color-motion and luminance-motion binding show stronger top-down feedback in central vision. Atten Percept Psychophys 2022; 84:861-877. [PMID: 35304697 DOI: 10.3758/s13414-022-02465-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/22/2022] [Indexed: 11/08/2022]
Abstract
Recently a theory (Zhaoping, Vision Research, 136, 32-49, 2017) proposed that top-down feedback from higher to lower visual cortical areas, to aid visual recognition, is stronger in the central than in the peripheral visual fields. Since top-down feedback helps feature binding, a critical visual recognition process, this theory predicts that insufficient feedback in the periphery should make feature misbinding more likely. To test this prediction, this study assessed binding between color and motion features, or between luminance and motion features, at different visual field eccentricities. We first used color-motion stimuli containing equiluminant red and green dots moving in opposite directions, for example, red dots moved leftward while green dots moved rightward. Such stimuli were shown in both a central reference strip and a peripheral test strip; participants reported whether it was the first or second interval in a trial in which the dots of each color moved in the opposite directions between the two strips. The center of the test strip was at 4° or 15° away from the gaze fixation. Participants' performance was much worse when the test strip was more peripheral, suggesting that feature misbinding occurred more frequently there. This held even when the size and density of the dots were adjusted by eccentricity-dependent cortical magnification factors, and even when red/green dots were replaced by yellow/blue dots or black/white dots to suit the retinal input sampling peripherally. Our findings support that top-down feedback is more directed to central vision, which can resolve ambiguities in feature binding at more central visual locations.
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Leptourgos P, Bouttier V, Denève S, Jardri R. From hallucinations to synaesthesia: A circular inference account of unimodal and multimodal erroneous percepts in clinical and drug-induced psychosis. Neurosci Biobehav Rev 2022; 135:104593. [PMID: 35217108 DOI: 10.1016/j.neubiorev.2022.104593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 02/15/2022] [Accepted: 02/21/2022] [Indexed: 10/19/2022]
Abstract
Psychedelics distort perception and induce visual and multimodal hallucinations as well as synaesthesia. This is in contradiction with the high prevalence of distressing voices in schizophrenia. Here we introduce a unifying account of unimodal and multimodal erroneous percepts based on circular inference. We show that amplification of top-down predictions (descending loops) leads to an excessive reliance on priors and aberrant levels of integration of the sensory representations, resulting in crossmodal percepts and stronger illusions. By contrast, amplification of bottom-up information (ascending loops) results in overinterpretation of unreliable sensory inputs and high levels of segregation between sensory modalities, bringing about unimodal hallucinations and reduced vulnerability to illusions. We delineate a canonical microcircuit in which layer-specific inhibition controls the propagation of information across hierarchical levels: inhibitory interneurons in the deep layers exert control over priors, removing descending loops. Conversely, inhibition in the supragranular layers counterbalances the effects of the ascending loops. Overall, we put forward a multiscale and transnosographic account of erroneous percepts with important theoretical, conceptual and clinical implications.
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Affiliation(s)
- Pantelis Leptourgos
- Department of Psychiatry, Connecticut Mental Health Center, Yale University, New Haven, CT, USA; Laboratoire de Neurosciences Cognitives & Computationnelles (LNC²), ENS, INSERM U-960, PSL Research University, Paris, France.
| | - Vincent Bouttier
- Laboratoire de Neurosciences Cognitives & Computationnelles (LNC²), ENS, INSERM U-960, PSL Research University, Paris, France; Univ Lille, INSERM U-1172, Lille Neurosciences & Cognition Centre, Plasticity and Subjectivity Team, & CHU Lille, Fontan Hospital, CURE Platform, Lille, France
| | - Sophie Denève
- Laboratoire de Neurosciences Cognitives & Computationnelles (LNC²), ENS, INSERM U-960, PSL Research University, Paris, France
| | - Renaud Jardri
- Laboratoire de Neurosciences Cognitives & Computationnelles (LNC²), ENS, INSERM U-960, PSL Research University, Paris, France; Univ Lille, INSERM U-1172, Lille Neurosciences & Cognition Centre, Plasticity and Subjectivity Team, & CHU Lille, Fontan Hospital, CURE Platform, Lille, France.
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Deshpande G, Zhao X, Robinson J. Functional Parcellation of the Hippocampus based on its Layer-specific Connectivity with Default Mode and Dorsal Attention Networks. Neuroimage 2022; 254:119078. [PMID: 35276366 DOI: 10.1016/j.neuroimage.2022.119078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 01/29/2022] [Accepted: 03/07/2022] [Indexed: 12/25/2022] Open
Abstract
Recent neuroimaging evidence suggests that there might be an anterior-posterior functional differentiation of the hippocampus along the long-axis. The HERNET (hippocampal encoding/retrieval and network) model proposed an encoding/retrieval dichotomy with the anterior hippocampus more connected to the dorsal attention network (DAN) during memory encoding, and the posterior portions more connected to the default mode network (DMN) during retrieval. Evidence both for and against the HERNET model has been reported. In this study, we test the validity of the HERNET model non-invasively in humans by computing functional connectivity (FC) in layer-specific cortico-hippocampal microcircuits. This was achieved by acquiring sub-millimeter functional magnetic resonance imaging (fMRI) data during encoding/retrieval tasks at 7T. Specifically, FC between infra-granular output layers of DAN with hippocampus during encoding and FC between supra-granular input layers of DMN with hippocampus during retrieval were computed to test the predictions of the HERNET model. Our results support some predictions of the HERNET model including anterior-posterior gradient along the long axis of the hippocampus. While preferential relationships between the entire hippocampus and DAN/DMN during encoding/retrieval, respectively, were observed as predicted, anterior-posterior specificity in these network relationships could not be confirmed. The strength and clarity of evidence for/against the HERNET model were superior with layer-specific data compared to conventional volume data.
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Affiliation(s)
- Gopikrishna Deshpande
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL 36849, USA; Department of Psychological Sciences, Auburn University, Auburn, AL, USA; Alabama Advanced Imaging Consortium, Birmingham, AL, USA; Center for Neuroscience, Auburn University, Auburn, AL, USA; Key Laboratory for Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China; Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Centre for Brain Research, Indian Institute of Science, Bangalore, India.
| | - Xinyu Zhao
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL 36849, USA; Quora Inc., Mountain View, CA, USA
| | - Jennifer Robinson
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL 36849, USA; Department of Psychological Sciences, Auburn University, Auburn, AL, USA; Alabama Advanced Imaging Consortium, Birmingham, AL, USA; Center for Neuroscience, Auburn University, Auburn, AL, USA
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Dijkstra N, Kok P, Fleming SM. Perceptual reality monitoring: Neural mechanisms dissociating imagination from reality. Neurosci Biobehav Rev 2022; 135:104557. [PMID: 35122782 DOI: 10.1016/j.neubiorev.2022.104557] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 01/12/2022] [Accepted: 01/30/2022] [Indexed: 01/21/2023]
Abstract
There is increasing evidence that imagination relies on similar neural mechanisms as externally triggered perception. This overlap presents a challenge for perceptual reality monitoring: deciding what is real and what is imagined. Here, we explore how perceptual reality monitoring might be implemented in the brain. We first describe sensory and cognitive factors that could dissociate imagery and perception and conclude that no single factor unambiguously signals whether an experience is internally or externally generated. We suggest that reality monitoring is implemented by higher-level cortical circuits that evaluate first-order sensory and cognitive factors to determine the source of sensory signals. According to this interpretation, perceptual reality monitoring shares core computations with metacognition. This multi-level architecture might explain several types of source confusion as well as dissociations between simply knowing whether something is real and actually experiencing it as real. We discuss avenues for future research to further our understanding of perceptual reality monitoring, an endeavour that has important implications for our understanding of clinical symptoms as well as general cognitive function.
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Affiliation(s)
- Nadine Dijkstra
- Wellcome Centre for Human Neuroimaging, University College London, United Kingdom.
| | - Peter Kok
- Wellcome Centre for Human Neuroimaging, University College London, United Kingdom
| | - Stephen M Fleming
- Wellcome Centre for Human Neuroimaging, University College London, United Kingdom; Max Planck UCL Centre for Computational Psychiatry and Aging Research, University College London, United Kingdom; Department of Experimental Psychology, University College London, United Kingdom
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Deshpande G, Wang Y, Robinson J. Resting state fMRI connectivity is sensitive to laminar connectional architecture in the human brain. Brain Inform 2022; 9:2. [PMID: 35038072 PMCID: PMC8764001 DOI: 10.1186/s40708-021-00150-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/28/2021] [Indexed: 11/10/2022] Open
Abstract
Previous invasive studies indicate that human neocortical graymatter contains cytoarchitectonically distinct layers, with notable differences in their structural connectivity with the rest of the brain. Given recent improvements in the spatial resolution of anatomical and functional magnetic resonance imaging (fMRI), we hypothesize that resting state functional connectivity (FC) derived from fMRI is sensitive to layer-specific thalamo-cortical and cortico-cortical microcircuits. Using sub-millimeter resting state fMRI data obtained at 7 T, we found that: (1) FC between the entire thalamus and cortical layers I and VI was significantly stronger than between the thalamus and other layers. Furthermore, FC between somatosensory thalamus (ventral posterolateral nucleus, VPL) and layers IV, VI of the primary somatosensory cortex were stronger than with other layers; (2) Inter-hemispheric cortico-cortical FC between homologous regions in superficial layers (layers I-III) was stronger compared to deep layers (layers V-VI). These findings are in agreement with structural connections inferred from previous invasive studies that showed that: (i) M-type neurons in the entire thalamus project to layer-I; (ii) Pyramidal neurons in layer-VI target all thalamic nuclei, (iii) C-type neurons in the VPL project to layer-IV and receive inputs from layer-VI of the primary somatosensory cortex, and (iv) 80% of collosal projecting neurons between homologous cortical regions connect superficial layers. Our results demonstrate for the first time that resting state fMRI is sensitive to structural connections between cortical layers (previously inferred through invasive studies), specifically in thalamo-cortical and cortico-cortical networks.
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Affiliation(s)
- Gopikrishna Deshpande
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA. .,Department of Psychological Sciences, Auburn University, Auburn, AL, USA. .,Alabama Advanced Imaging Consortium, Birmingham, AL, USA. .,Center for Neuroscience, Auburn University, Auburn, AL, USA. .,Key Laboratory for Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China. .,Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India. .,Centre for Brain Research, Indian Institute of Science, Bangalore, India.
| | - Yun Wang
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA.,Department of Psychiatry, Columbia University, New York, NY, USA
| | - Jennifer Robinson
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA.,Department of Psychological Sciences, Auburn University, Auburn, AL, USA.,Alabama Advanced Imaging Consortium, Birmingham, AL, USA.,Center for Neuroscience, Auburn University, Auburn, AL, USA
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Hogendoorn H. Perception in real-time: predicting the present, reconstructing the past. Trends Cogn Sci 2022; 26:128-141. [PMID: 34973925 DOI: 10.1016/j.tics.2021.11.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 11/16/2021] [Accepted: 11/17/2021] [Indexed: 01/06/2023]
Abstract
We feel that we perceive events in the environment as they unfold in real-time. However, this intuitive view of perception is impossible to implement in the nervous system due to biological constraints such as neural transmission delays. I propose a new way of thinking about real-time perception: at any given moment, instead of representing a single timepoint, perceptual mechanisms represent an entire timeline. On this timeline, predictive mechanisms predict ahead to compensate for delays in incoming sensory input, and reconstruction mechanisms retroactively revise perception when those predictions do not come true. This proposal integrates and extends previous work to address a crucial gap in our understanding of a fundamental aspect of our everyday life: the experience of perceiving the present.
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Affiliation(s)
- Hinze Hogendoorn
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC 3010, Australia.
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