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Kupers ER, Benson NC, Winawer J. A visual encoding model links magnetoencephalography signals to neural synchrony in human cortex. Neuroimage 2021; 245:118655. [PMID: 34687857 PMCID: PMC8788390 DOI: 10.1016/j.neuroimage.2021.118655] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 10/11/2021] [Indexed: 01/23/2023] Open
Abstract
Synchronization of neuronal responses over large distances is hypothesized to be important for many cortical functions. However, no straightforward methods exist to estimate synchrony non-invasively in the living human brain. MEG and EEG measure the whole brain, but the sensors pool over large, overlapping cortical regions, obscuring the underlying neural synchrony. Here, we developed a model from stimulus to cortex to MEG sensors to disentangle neural synchrony from spatial pooling of the instrument. We find that synchrony across cortex has a surprisingly large and systematic effect on predicted MEG spatial topography. We then conducted visual MEG experiments and separated responses into stimulus-locked and broadband components. The stimulus-locked topography was similar to model predictions assuming synchronous neural sources, whereas the broadband topography was similar to model predictions assuming asynchronous sources. We infer that visual stimulation elicits two distinct types of neural responses, one highly synchronous and one largely asynchronous across cortex.
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Affiliation(s)
- Eline R Kupers
- Department of Psychology, New York University, New York, NY 10003, United States; Center for Neural Science, New York University, New York, NY 10003, United States; Department of Psychology, Stanford University, Stanford, CA 94305, United States.
| | - Noah C Benson
- Department of Psychology, New York University, New York, NY 10003, United States; Center for Neural Science, New York University, New York, NY 10003, United States; eSciences Institute, University of Washington, Seattle, WA 98195, United States
| | - Jonathan Winawer
- Department of Psychology, New York University, New York, NY 10003, United States; Center for Neural Science, New York University, New York, NY 10003, United States
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Kupers ER, Edadan A, Benson NC, Zuiderbaan W, de Jong MC, Dumoulin SO, Winawer J. A population receptive field model of the magnetoencephalography response. Neuroimage 2021; 244:118554. [PMID: 34509622 PMCID: PMC8631249 DOI: 10.1016/j.neuroimage.2021.118554] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 07/16/2021] [Accepted: 09/02/2021] [Indexed: 12/23/2022] Open
Abstract
Computational models which predict the neurophysiological response from experimental stimuli have played an important role in human neuroimaging. One type of computational model, the population receptive field (pRF), has been used to describe cortical responses at the millimeter scale using functional magnetic resonance imaging (fMRI) and electrocorticography (ECoG). However, pRF models are not widely used for non-invasive electromagnetic field measurements (EEG/MEG), because individual sensors pool responses originating from several centimeter of cortex, containing neural populations with widely varying spatial tuning. Here, we introduce a forward-modeling approach in which pRFs estimated from fMRI data are used to predict MEG sensor responses. Subjects viewed contrast-reversing bar stimuli sweeping across the visual field in separate fMRI and MEG sessions. Individual subject's pRFs were modeled on the cortical surface at the millimeter scale using the fMRI data. We then predicted cortical time series and projected these predictions to MEG sensors using a biophysical MEG forward model, accounting for the pooling across cortex. We compared the predicted MEG responses to observed visually evoked steady-state responses measured in the MEG session. We found that pRF parameters estimated by fMRI could explain a substantial fraction of the variance in steady-state MEG sensor responses (up to 60% in individual sensors). Control analyses in which we artificially perturbed either pRF size or pRF position reduced MEG prediction accuracy, indicating that MEG data are sensitive to pRF properties derived from fMRI. Our model provides a quantitative approach to link fMRI and MEG measurements, thereby enabling advances in our understanding of spatiotemporal dynamics in human visual field maps.
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Affiliation(s)
- Eline R Kupers
- Department of Psychology, New York University, New York, NY 10003, United States; Center for Neural Science, New York University, New York, NY 10003, United States; Department of Psychology, Stanford University, Stanford, CA 94305, United States.
| | - Akhil Edadan
- Spinoza Center for Neuroimaging, Amsterdam 1105 BK, the Netherlands; Department of Experimental Psychology, Utrecht University, Utrecht 3584 CS, the Netherlands
| | - Noah C Benson
- Department of Psychology, New York University, New York, NY 10003, United States; Center for Neural Science, New York University, New York, NY 10003, United States; Sciences Institute, University of Washington, Seattle, WA 98195, United States
| | | | - Maartje C de Jong
- Spinoza Center for Neuroimaging, Amsterdam 1105 BK, the Netherlands; Department of Psychology, University of Amsterdam, Amsterdam 1001 NK, the Netherlands; Amsterdam Brain and Cognition (ABC), University of Amsterdam, Amsterdam 1001 NK, the Netherlands
| | - Serge O Dumoulin
- Spinoza Center for Neuroimaging, Amsterdam 1105 BK, the Netherlands; Department of Experimental Psychology, Utrecht University, Utrecht 3584 CS, the Netherlands; Department of Experimental and Applied Psychology, VU University, Amsterdam 1081 BT, the Netherlands
| | - Jonathan Winawer
- Department of Psychology, New York University, New York, NY 10003, United States; Center for Neural Science, New York University, New York, NY 10003, United States
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Excitatory Contribution to Binocular Interactions in Human Visual Cortex Is Reduced in Strabismic Amblyopia. J Neurosci 2021; 41:8632-8643. [PMID: 34433631 PMCID: PMC8513700 DOI: 10.1523/jneurosci.0268-21.2021] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 01/14/2023] Open
Abstract
Binocular summation in strabismic amblyopia is typically reported as being absent or greatly reduced in behavioral studies and is thought to be because of a preferential loss of excitatory interactions between the eyes. Here, we studied how excitatory and suppressive interactions contribute to binocular contrast interactions along the visual cortical hierarchy of humans with strabismic and anisometropic amblyopia in both sexes, using source-imaged steady-state visual evoked potentials (SSVEP) over a wide range of relative contrast between the two eyes. Dichoptic parallel grating stimuli modulated at unique temporal frequencies in each eye allowed us to quantify spectral response components associated with monocular inputs (self-terms) and the response components because of interaction of the inputs of the two eyes [intermodulation (IM) terms]. Although anisometropic amblyopes revealed a similar pattern of responses to normal-vision observers, strabismic amblyopes exhibited substantially reduced IM responses across cortical regions of interest (V1, V3a, hV4, hMT+ and lateral occipital cortex), indicating reduced interocular interactions in visual cortex. A contrast gain control model that simultaneously fits self- and IM-term responses within each cortical area revealed different patterns of binocular interactions between individuals with normal and disrupted binocularity. Our model fits show that in strabismic amblyopia, the excitatory contribution to binocular interactions is significantly reduced in both V1 and extra-striate cortex, whereas suppressive contributions remain intact. Our results provide robust electrophysiological evidence supporting the view that disruption of binocular interactions in strabismus or amblyopia is because of preferential loss of excitatory interactions between the eyes.SIGNIFICANCE STATEMENT We studied how excitatory and suppressive interactions contribute to binocular contrast interactions along the visual cortical hierarchy of humans with normal and amblyopic vision, using source-imaged SSVEP and frequency-domain analysis of dichoptic stimuli over a wide range of relative contrast between the two eyes. A dichoptic contrast gain control model was used to characterize these interactions in amblyopia and provided a quantitative comparison to normal vision. Our model fits revealed different patterns of binocular interactions between normal and amblyopic vision. Strabismic amblyopia significantly reduced excitatory contributions to binocular interactions, whereas suppressive contributions remained intact. Our results provide robust evidence supporting the view that the preferential loss of excitatory interactions disrupts binocular interactions in strabismic amblyopia.
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Lim M, Ales JM, Cottereau BR, Hastie T, Norcia AM. Sparse EEG/MEG source estimation via a group lasso. PLoS One 2017; 12:e0176835. [PMID: 28604790 PMCID: PMC5467834 DOI: 10.1371/journal.pone.0176835] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Accepted: 04/18/2017] [Indexed: 01/23/2023] Open
Abstract
Non-invasive recordings of human brain activity through electroencephalography (EEG) or magnetoencelphalography (MEG) are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches.
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Affiliation(s)
- Michael Lim
- Department of Statistics, Stanford University, Stanford, CA, United States of America
| | - Justin M. Ales
- School of Psychology & Neuroscience, University of St Andrews, Scotland, United Kingdom
| | - Benoit R. Cottereau
- Universite de Toulouse, Centre de Recherche Cerveau et Cognition, Toulouse, France
- Centre National de la Recherche Scientific, Toulouse Cedex, France
| | - Trevor Hastie
- Department of Statistics, Stanford University, Stanford, CA, United States of America
| | - Anthony M. Norcia
- Department of Psychology, Stanford University, Stanford, CA, United States of America
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Fornaciai M, Brannon EM, Woldorff MG, Park J. Numerosity processing in early visual cortex. Neuroimage 2017; 157:429-438. [PMID: 28583882 DOI: 10.1016/j.neuroimage.2017.05.069] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Revised: 05/26/2017] [Accepted: 05/31/2017] [Indexed: 10/19/2022] Open
Abstract
While parietal cortex is thought to be critical for representing numerical magnitudes, we recently reported an event-related potential (ERP) study demonstrating selective neural sensitivity to numerosity over midline occipital sites very early in the time course, suggesting the involvement of early visual cortex in numerosity processing. However, which specific brain area underlies such early activation is not known. Here, we tested whether numerosity-sensitive neural signatures arise specifically from the initial stages of visual cortex, aiming to localize the generator of these signals by taking advantage of the distinctive folding pattern of early occipital cortices around the calcarine sulcus, which predicts an inversion of polarity of ERPs arising from these areas when stimuli are presented in the upper versus lower visual field. Dot arrays, including 8-32dots constructed systematically across various numerical and non-numerical visual attributes, were presented randomly in either the upper or lower visual hemifields. Our results show that neural responses at about 90ms post-stimulus were robustly sensitive to numerosity. Moreover, the peculiar pattern of polarity inversion of numerosity-sensitive activity at this stage suggested its generation primarily in V2 and V3. In contrast, numerosity-sensitive ERP activity at occipito-parietal channels later in the time course (210-230ms) did not show polarity inversion, indicating a subsequent processing stage in the dorsal stream. Overall, these results demonstrate that numerosity processing begins in one of the earliest stages of the cortical visual stream.
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Affiliation(s)
- Michele Fornaciai
- Department of Psychological and Brain Sciences, University of Massachusetts Amherst, USA.
| | | | | | - Joonkoo Park
- Department of Psychological and Brain Sciences, University of Massachusetts Amherst, USA; Commonwealth Honors College, University of Massachusetts Amherst, USA.
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Effects of Stimulus Size and Contrast on the Initial Primary Visual Cortical Response in Humans. Brain Topogr 2017; 30:450-460. [PMID: 28474167 DOI: 10.1007/s10548-016-0530-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Accepted: 10/11/2016] [Indexed: 10/19/2022]
Abstract
Decades of intracranial electrophysiological investigation into the primary visual cortex (V1) have produced many fundamental insights into the computations carried out in low-level visual circuits of the brain. Some of the most important work has been simply concerned with the precise measurement of neural response variations as a function of elementary stimulus attributes such as contrast and size. Surprisingly, such simple but fundamental characterization of V1 responses has not been carried out in human electrophysiology. Here we report such a detailed characterization for the initial "C1" component of the scalp-recorded visual evoked potential (VEP). The C1 is known to be dominantly generated by initial afferent activation in V1, but is difficult to record reliably due to interindividual anatomical variability. We used pattern-pulse multifocal VEP mapping to identify a stimulus position that activates the left lower calcarine bank in each individual, and afterwards measured robust negative C1s over posterior midline scalp to gratings presented sequentially at that location. We found clear and systematic increases in C1 peak amplitude and decreases in peak latency with increasing size as well as with increasing contrast. With a sample of 15 subjects and ~180 trials per condition, reliable C1 amplitudes of -0.46 µV were evoked at as low a contrast as 3.13% and as large as -4.82 µV at 100% contrast, using stimuli of 3.33° diameter. A practical implication is that by placing sufficiently-sized stimuli to target favorable calcarine cortical loci, robust V1 responses can be measured at contrasts close to perceptual thresholds, which could greatly facilitate principled studies of early visual perception and attention.
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Inverso SA, Goh XL, Henriksson L, Vanni S, James AC. From evoked potentials to cortical currents: Resolving V1 and V2 components using retinotopy constrained source estimation without fMRI. Hum Brain Mapp 2016; 37:1696-709. [PMID: 26870938 DOI: 10.1002/hbm.23128] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Revised: 01/12/2016] [Accepted: 01/19/2016] [Indexed: 11/09/2022] Open
Abstract
Despite evoked potentials' (EP) ubiquity in research and clinical medicine, insights are limited to gross brain dynamics as it remains challenging to map surface potentials to their sources in specific cortical regions. Multiple sources cancellation due to cortical folding and cross-talk obscures close sources, e.g. between visual areas V1 and V2. Recently retinotopic functional magnetic resonance imaging (fMRI) responses were used to constrain source locations to assist separating close sources and to determine cortical current generators. However, an fMRI is largely infeasible for routine EP investigation. We developed a novel method that replaces the fMRI derived retinotopic layout (RL) by an approach where the retinotopy and current estimates are generated from EEG or MEG signals and a standard clinical T1-weighted anatomical MRI. Using the EEG-RL, sources were localized to within 2 mm of the fMRI-RL constrained localized sources. The EEG-RL also produced V1 and V2 current waveforms that closely matched the fMRI-RL's (n = 2) r(1,198) = 0.99, P < 0.0001. Applying the method to subjects without fMRI (n = 4) demonstrates it generates waveforms that agree closely with the literature. Our advance allows investigators with their current EEG or MEG systems to create a library of brain models tuned to individual subjects' cortical folding in retinotopic maps, and should be applicable to auditory and somatosensory maps. The novel method developed expands EP's ability to study specific brain areas, revitalizing this well-worn technique. Hum Brain Mapp 37:1696-1709, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Samuel A Inverso
- Eccles Institute of Neuroscience, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia.,Australian Research Council Centre of Excellence in Vision Science and Research School of Biology, Australian National University, Canberra, ACT, Australia.,Wyss Institute, Harvard University, Boston, Massachusetts
| | - Xin-Lin Goh
- Eccles Institute of Neuroscience, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia.,Australian Research Council Centre of Excellence in Vision Science and Research School of Biology, Australian National University, Canberra, ACT, Australia
| | - Linda Henriksson
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.,AMI Centre, Aalto Neuroimaging, Aalto University, Finland
| | - Simo Vanni
- AMI Centre, Aalto Neuroimaging, Aalto University, Finland.,Clinical Neurosciences, Neurology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Andrew C James
- Eccles Institute of Neuroscience, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia.,Australian Research Council Centre of Excellence in Vision Science and Research School of Biology, Australian National University, Canberra, ACT, Australia
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Abstract
Behavioral responses to visual stimuli exhibit visual field asymmetries, but cortical folding and the close proximity of visual cortical areas make electrophysiological comparisons between different stimulus locations problematic. Retinotopy-constrained source estimation (RCSE) uses distributed dipole models simultaneously constrained by multiple stimulus locations to provide separation between individual visual areas that is not possible with conventional source estimation methods. Magnetoencephalography and RCSE were used to estimate time courses of activity in V1, V2, V3, and V3A. Responses to left and right hemifield stimuli were not significantly different. Peak latencies for peripheral stimuli were significantly shorter than those for perifoveal stimuli in V1, V2, and V3A, likely related to the greater proportion of magnocellular input to V1 in the periphery. Consistent with previous results, sensor magnitudes for lower field stimuli were about twice as large as for upper field, which is only partially explained by the proximity to sensors for lower field cortical sources in V1, V2, and V3. V3A exhibited both latency and amplitude differences for upper and lower field responses. There were no differences for V3, consistent with previous suggestions that dorsal and ventral V3 are two halves of a single visual area, rather than distinct areas V3 and VP.
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Affiliation(s)
- Donald J Hagler
- Department of Radiology, University of California-San Diego, La Jolla, CA, USA
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