Visual Field Maps Research Articles

Population receptive field models capture the event-related magnetoencephalography response with millisecond resolution

Abstract Much of the visual system is organized into visual field maps. In humans, this organization can be studied non-invasively by estimating the receptive fields of populations of neurons (population receptive fields; pRFs) with functional magnetic resonance imaging (fMRI). However, fMRI cannot capture the temporal dynamics of visual processing that operate on a millisecond scale. Magnetoencephalography (MEG) does provide this temporal resolution but generally lacks the required spatial resolution. Here, we introduce a forward modeling approach that combines fMRI and MEG, enabling us to estimate pRFs with millisecond resolution. Using fMRI, we estimated the participant’s pRFs using conventional pRF-modeling. We then combined the pRF models with a forward model that transforms the cortical responses to the MEG sensors. This enabled us to predict event-related field responses measured with MEG while the participants viewed brief (100 ms) contrast-defined bar and circle shapes. We computed the goodness of fit between the predicted and measured MEG responses across time using cross-validated variance explained. We found that the fMRI-estimated pRFs explained up to 91% of the variance in individual MEG sensor’s responses. The variance explained varied over time and peaked between 75 ms to 250 ms after stimulus onset. Perturbing the pRF positions decreased the explained variance, suggesting that the pRFs were driving the MEG responses. In conclusion, pRF models can predict event-related MEG responses, enabling routine investigation of the spatiotemporal dynamics of human pRFs with millisecond resolution.

Visual field map size predicts spatial working memory performance

Visual field map size predicts spatial working memory performance

Retinotopy drives the variation in scene responses across visual field map divisions of the occipital place area.

The occipital place area (OPA) is a scene-selective region on the lateral surface of human occipitotemporal cortex that spatially overlaps multiple visual field maps, as well as portions of cortex that are not currently defined as retinotopic. Here we combined population receptive field modeling and responses to scenes in a representational similarity analysis (RSA) framework to test the prediction that the OPA's visual field map divisions contribute uniquely to the overall pattern of scene selectivity within the OPA. Consistent with this prediction, the patterns of response to a set of complex scenes were heterogeneous between maps. To explain this heterogeneity, we tested the explanatory power of seven candidate models using RSA. These models spanned different scene dimensions (Content, Expanse, Distance), low- and high-level visual features, and navigational affordances. None of the tested models could account for the variation in scene response observed between the OPA's visual field maps. However, the heterogeneity in scene response was correlated with the differences in retinotopic profiles across maps. These data highlight the need to carefully examine the relationship between regions defined as category-selective and the underlying retinotopy, and they suggest that, in the case of the OPA, it may not be appropriate to conceptualize it as a single scene-selective region.

Visual Function and Driving Performance Under Different Lighting Conditions in Older Drivers: Preliminary Results From an Observational Study.

Age-related vision changes significantly contribute to fatal crashes at night among older drivers. However, the effects of lighting conditions on age-related vision changes and associated driving performance remain unclear. This pilot study examined the associations between visual function and driving performance assessed by a high-fidelity driving simulator among drivers 60 and older across 3 lighting conditions: daytime (photopic), nighttime (mesopic), and nighttime with glare. Active drivers aged 60 years or older participated in visual function assessments and simulated driving on a high-fidelity driving simulator. Visual acuity (VA), contrast sensitivity function (CSF), and visual field map (VFM) were measured using quantitative VA, quantitative CSF, and quantitative VFM procedures under photopic and mesopic conditions. VA and CSF were also obtained in the presence of glare in the mesopic condition. Two summary metrics, the area under the log CSF (AULCSF) and volume under the surface of VFM (VUSVFM), quantified CSF and VFM. Driving performance measures (average speed, SD of speed [SDspeed], SD of lane position (SDLP), and reaction time) were assessed under daytime, nighttime, and nighttime with glare conditions. Pearson correlations determined the associations between visual function and driving performance across the 3 lighting conditions. Of the 20 drivers included, the average age was 70.3 years; 55% were male. Poor photopic VA was significantly correlated with greater SDspeed (r=0.26; P<.001) and greater SDLP (r=0.31; P<.001). Poor photopic AULCSF was correlated with greater SDLP (r=-0.22; P=.01). Poor mesopic VUSFVM was significantly correlated with slower average speed (r=-0.24; P=.007), larger SDspeed (r=-0.19; P=.04), greater SDLP (r=-0.22; P=.007), and longer reaction times (r=-0.22; P=.04) while driving at night. For functional vision in the mesopic condition with glare, poor VA was significantly correlated with longer reaction times (r=0.21; P=.046) while driving at night with glare; poor AULCSF was significantly correlated with slower speed (r=-0.32; P<.001), greater SDLP (r=-0.26; P=.001) and longer reaction times (r=-0.2; P=.04) while driving at night with glare. No other significant correlations were observed between visual function and driving performance under the same lighting conditions. Visual functions differentially affect driving performance in different lighting conditions among older drivers, with more substantial impacts on driving during nighttime, especially in glare. Additional research with larger sample sizes is needed to confirm these results.

Visual working memories are abstractions of percepts.

During perception, decoding the orientation of gratings depends on complex interactions between the orientation of the grating, aperture edges, and topographic structure of the visual map. Here, we aimed to test how aperture biases described during perception affect working memory (WM) decoding. For memoranda, we used gratings multiplied by radial and angular modulators to generate orthogonal aperture biases for identical orientations. Therefore, if WM representations are simply maintained sensory representations, they would have similar aperture biases. If they are abstractions of sensory features, they would be unbiased and the modulator would have no effect on orientation decoding. Neural patterns of delay period activity while maintaining the orientation of gratings with one modulator (e.g. radial) were interchangeable with patterns while maintaining gratings with the other modulator (e.g. angular) in visual and parietal cortex, suggesting that WM representations are insensitive to aperture biases during perception. Then, we visualized memory abstractions of stimuli using models of visual field map properties. Regardless of aperture biases, WM representations of both modulated gratings were recoded into a single oriented line. These results provide strong evidence that visual WM representations are abstractions of percepts, immune to perceptual aperture biases, and compel revisions of WM theory.

Visual working memories are abstractions of percepts

During perception, decoding the orientation of gratings depends on complex interactions between the orientation of the grating, aperture edges, and topographic structure of the visual map. Here, we aimed to test how aperture biases described during perception affect working memory (WM) decoding. For memoranda, we used gratings multiplied by radial and angular modulators to generate orthogonal aperture biases for identical orientations. Therefore, if WM representations are simply maintained sensory representations, they would have similar aperture biases. If they are abstractions of sensory features, they would be unbiased and the modulator would have no effect on orientation decoding. Neural patterns of delay period activity while maintaining the orientation of gratings with one modulator (e.g. radial) were interchangeable with patterns while maintaining gratings with the other modulator (e.g. angular) in visual and parietal cortex, suggesting that WM representations are insensitive to aperture biases during perception. Then, we visualized memory abstractions of stimuli using models of visual field map properties. Regardless of aperture biases, WM representations of both modulated gratings were recoded into a single oriented line. These results provide strong evidence that visual WM representations are abstractions of percepts, immune to perceptual aperture biases, and compel revisions of WM theory.

RLPeri: Accelerating Visual Perimetry Test with Reinforcement Learning and Convolutional Feature Extraction

Visual perimetry is an important eye examination that helps detect vision problems caused by ocular or neurological conditions. During the test, a patient's gaze is fixed at a specific location while light stimuli of varying intensities are presented in central and peripheral vision. Based on the patient's responses to the stimuli, the visual field mapping and sensitivity are determined. However, maintaining high levels of concentration throughout the test can be challenging for patients, leading to increased examination times and decreased accuracy. In this work, we present RLPeri, a reinforcement learning-based approach to optimize visual perimetry testing. By determining the optimal sequence of locations and initial stimulus values, we aim to reduce the examination time without compromising accuracy. Additionally, we incorporate reward shaping techniques to further improve the testing performance. To monitor the patient's responses over time during testing, we represent the test's state as a pair of 3D matrices. We apply two different convolutional kernels to extract spatial features across locations as well as features across different stimulus values for each location. Through experiments, we demonstrate that our approach results in a 10-20% reduction in examination time while maintaining the accuracy as compared to state-of-the-art methods. With the presented approach, we aim to make visual perimetry testing more efficient and patient-friendly, while still providing accurate results.

Variability of visual field maps in human early extrastriate cortex challenges the canonical model of organization of V2 and V3.

Visual field maps in human early extrastriate areas (V2 and V3) are traditionally thought to form mirror-image representations which surround the primary visual cortex (V1). According to this scheme, V2 and V3 form nearly symmetrical halves with respect to the calcarine sulcus, with the dorsal halves representing lower contralateral quadrants, and the ventral halves representing upper contralateral quadrants. This arrangement is considered to be consistent across individuals, and thus predictable with reasonable accuracy using templates. However, data that deviate from this expected pattern have been observed, but mainly treated as artifactual. Here, we systematically investigate individual variability in the visual field maps of human early visual cortex using the 7T Human Connectome Project (HCP) retinotopy dataset. Our results demonstrate substantial and principled inter-individual variability. Visual field representation in the dorsal portions of V2 and V3 was more variable than in their ventral counterparts, including substantial departures from the expected mirror-symmetrical patterns. In addition, left hemisphere retinotopic maps were more variable than those in the right hemisphere. Surprisingly, only one-third of individuals had maps that conformed to the expected pattern in the left hemisphere. Visual field sign analysis further revealed that in many individuals the area conventionally identified as dorsal V3 shows a discontinuity in the mirror-image representation of the retina, associated with a Y-shaped lower vertical representation. Our findings challenge the current view that inter-individual variability in early extrastriate cortex is negligible, and that the dorsal portions of V2 and V3 are roughly mirror images of their ventral counterparts.

Retinotopic connectivity maps of human visual cortex with unconstrained eye movements.

Human visual cortex contains topographic visual field maps whose organization can be revealed with retinotopic mapping. Unfortunately, constraints posed by standard mapping hinder its use in patients, atypical subject groups, and individuals at either end of the lifespan. This severely limits the conclusions we can draw about visual processing in such individuals. Here, we present a novel data-driven method to estimate connective fields, resulting in fine-grained maps of the functional connectivity between brain areas. We find that inhibitory connectivity fields accompany, and often surround facilitatory fields. The visual field extent of these inhibitory subfields falls off with cortical magnification. We further show that our method is robust to large eye movements and myopic defocus. Importantly, freed from the controlled stimulus conditions in standard mapping experiments, using entertaining stimuli and unconstrained eye movements our approach can generate retinotopic maps, including the periphery visual field hitherto only possible to map with special stimulus displays. Generally, our results show that the connective field method can gain knowledge about retinotopic architecture of visual cortex in patients and participants where this is at best difficult and confounded, if not impossible, with current methods.

Effects of Stimulus Luminance, Stimulus Color and Intra-Stimulus Color Contrast on Visual Field Mapping in Neurologically Impaired Adults Using Flicker Pupil Perimetry.

We improve pupillary responses and diagnostic performance of flicker pupil perimetry through alterations in global and local color contrast and luminance contrast in adult patients suffering from visual field defects due to cerebral visual impairment (CVI). Two experiments were conducted on patients with CVI (Experiment 1: 19 subjects, age M and SD 57.9 ± 14.0; Experiment 2: 16 subjects, age M and SD 57.3 ± 14.7) suffering from absolute homonymous visual field (VF) defects. We altered global color contrast (stimuli consisted of white, yellow, cyan and yellow-equiluminant-to-cyan colored wedges) in Experiment 1, and we manipulated luminance and local color contrast with bright and dark yellow and multicolor wedges in a 2-by-2 design in Experiment 2. Stimuli consecutively flickered across 44 stimulus locations within the inner 60 degrees of the VF and were offset to a contrasting (opponency colored) dark background. Pupil perimetry results were compared to standard automated perimetry (SAP) to assess diagnostic accuracy. A bright stimulus with global color contrast using yellow (p=0.009) or white (p=0.006) evoked strongest pupillary responses as opposed to stimuli containing local color contrast and lower brightness. Diagnostic accuracy, however, was similar across global color contrast conditions in Experiment 1 (p=0.27) and decreased when local color contrast and less luminance contrast was introduced in Experiment 2 (p=0.02). The bright yellow condition resulted in highest performance (AUC M =0.85±0.10, Mdn=0.85). Pupillary responses and pupil perimetry's diagnostic accuracy both benefit from high luminance contrast and global but not local color contrast.

Capturing Luminous Flux Entering Human Eyes with a Camera, Part 2: A Field Verification Experiment

ABSTRACT A space occupant’s real-time exposure to light reaching his/her eyes has been a concern in lighting research and design practice. Following the parallel fundamental research in Part 1, Part 2 of this study explored a way to use a Canon 550D fitted with the Sigma 4.5 mm F2.8 circular fisheye lens to estimate the luminous flux arriving at the entrance pupil from the visible luminous environment. By taking two 180° HDR images at the same camera position but in different aiming directions and merging them into a single luminance map covering the observer’s entire binocular visual field (214° horizontally and 125° vertically), the monocular and binocular luminance map can be generated with the aid of the dynamic visual field model proposed in Part 1. In a field verification experiment, the luminous flux passing through the entrance pupil in the preset scenes and gaze angles was estimated. Individual luminous contribution from an object or a region of interest within the occupant’s dynamic binocular visual field or subfields was also calculated. This study expanded the capacity of HDR photography in lighting measurement to capture binocular luminous flux entering human eyes as input for optimizing human-light interaction in various luminous environments.

Deep Learning Estimation of 10-2 Visual Field Map Based on Circumpapillary Retinal Nerve Fiber Layer Thickness Measurements

To estimate central 10-degree visual field (VF) map from spectral-domain optical coherence tomography (SD-OCT) retinal nerve fiber layer thickness (RNFL) measurements in glaucoma with artificial intelligence. Artificial intelligence (convolutional neural networks) study. This study included 5352 SD-OCT scans and 10-2 VF pairs from 1365 eyes of 724 healthy patients, patients with suspected glaucoma, and patients with glaucoma. Convolutional neural networks (CNNs) were developed to estimate the 68 individual sensitivity thresholds of 10-2 VF map using all-sectors (CNNA) and temporal-sectors (CNNT) RNFL thickness information of the SD-OCT circle scan (768 thickness points). 10-2 indices including pointwise total deviation (TD) values, mean deviation (MD), and pattern standard deviation (PSD) were generated using the CNN-estimated sensitivity thresholds at individual test locations. Linear regression (LR) models with the same input were used for comparison. The CNNA model achieved an average pointwise mean absolute error of 4.04 dB (95% confidence interval [CI] 3.76-4.35) and correlation coefficient (r) of 0.59 (95% CI 0.52-0.64) over 10-2 map and the mean absolute error and r of 2.88 dB (95% CI 2.63-3.15) and 0.74 (95% CI 0.67-0.80) for MD, and 2.31 dB (95% CI 2.03-2.61) and 0.59 (95% CI 0.51-0.65) for PSD estimations, respectively, significantly outperforming the LRA model. The proposed CNNA model improved the estimation of 10-2 VF map based on circumpapillary SD-OCT RNFL thickness measurements. These artificial intelligence methods using SD-OCT structural data show promise to individualize the frequency of central VF assessment in patients with glaucoma and would enable the reallocation of resources from patients at lowest risk to those at highest risk of central VF damage.

Evaluating the efficacy of multi-echo ICA denoising on model-based fMRI

fMRI is an indispensable tool for neuroscience investigation, but this technique is limited by multiple sources of physiological and measurement noise. These noise sources are particularly problematic for analysis techniques that require high signal-to-noise ratio for stable model fitting, such as voxel-wise modeling. Multi-echo data acquisition in combination with echo-time dependent ICA denoising (ME-ICA) represents one promising strategy to mitigate physiological and hardware-related noise sources as well as motion-related artifacts. However, most studies employing ME-ICA to date are resting-state fMRI studies, and therefore we have a limited understanding of the impact of ME-ICA on complex task or model-based fMRI paradigms. Here, we addressed this knowledge gap by comparing data quality and model fitting performance of data acquired during a visual population receptive field (pRF) mapping (N = 13 participants) experiment after applying one of three preprocessing procedures: ME-ICA, optimally combined multi-echo data without ICA-denoising, and typical single echo processing. As expected, multi-echo fMRI improved temporal signal-to-noise compared to single echo fMRI, with ME-ICA amplifying the improvement compared to optimal combination alone. However, unexpectedly, this boost in temporal signal-to-noise did not directly translate to improved model fitting performance: compared to single echo acquisition, model fitting was only improved after ICA-denoising. Specifically, compared to single echo acquisition, ME-ICA resulted in improved variance explained by our pRF model throughout the visual system, including anterior regions of the temporal and parietal lobes where SNR is typically low, while optimal combination without ICA did not. ME-ICA also improved reliability of parameter estimates compared to single echo and optimally combined multi-echo data without ICA-denoising. Collectively, these results suggest that ME-ICA is effective for denoising task-based fMRI data for modeling analyzes and maintains the integrity of the original data. Therefore, ME-ICA may be beneficial for complex fMRI experiments, including voxel-wise modeling and naturalistic paradigms.

Dynamic changes in spatial representation within the posterior parietal cortex in response to visuomotor adaptation.

Recent studies used functional magnetic resonance imaging (fMRI)population receptive field (pRF) mapping to demonstrate that retinotopic organization extends from the primary visual cortex to ventral and dorsal visual pathways, by quantifying visual field maps, receptive field size, and laterality throughout multiple areas. Visuospatial representation in the posterior parietal cortex (PPC) is modulated by attentional deployment, raising the question of whether spatial representation in the PPC is dynamic and flexible, and whether this flexibility contributes to visuospatial learning. To answer this question, changes in spatial representation within the PPC and early visual cortex were recorded with pRF mapping before and after prism adaptation (PA)-a well-established visuomotor technique that modulates visuospatial attention according to the direction of the visual displacement. As predicted, results showed that adaptation to left-shifting prisms increases pRF size in left PPC, while leaving space representation in the early visual cortex unchanged. This is the first evidence that PA drives a dynamic reorganization of response profiles in the PPC. These findings show that spatial representations in the PPC not only reflect changes driven by attentional deployment but dynamically change in response to modulation of external factors such as manipulation of the visuospatial input during visuomotor adaptation.

Topographic map formation and the effects of NMDA receptor blockade in the developing visual system

The development of functional topography in the developing brain follows a progression from initially coarse to more precisely organized maps. To examine the emergence of topographically organized maps in the retinotectal system, we performed longitudinal visual receptive field mapping by calcium imaging in the optic tectum of GCaMP6-expressing transgenic Xenopus laevis tadpoles. At stage 42, just 1 d after retinal axons arrived in the optic tectum, a clear retinotopic azimuth map was evident. Animals were imaged over the following week at stages 45 and 48, over which time the tectal neuropil nearly doubled in length and exhibited more precise retinotopic organization. By microinjecting GCaMP6s messenger ribonucleic acid (mRNA) into one blastomere of two-cell stage embryos, we acquired bilateral mosaic tadpoles with GCaMP6s expression in postsynaptic tectal neurons on one side of the animal and in retinal ganglion cell axons crossing to the tectum on the opposite side. Longitudinal observation of retinotopic map emergence revealed the presence of orderly representations of azimuth and elevation as early as stage 42, although presynaptic inputs exhibited relatively less topographic organization than the postsynaptic component for the azimuth axis. Retinotopic gradients in the tectum became smoother between stages 42 and 45. Blocking N-methyl-D-aspartate (NMDA) receptor conductance by rearing tadpoles in MK-801 did not prevent the emergence of retinotopic maps, but it produced more discontinuous topographic gradients and altered receptive field characteristics. These results provide evidence that current through NMDA receptors is dispensable for coarse topographic ordering of retinotectal inputs but does contribute to the fine-scale organization of the retinotectal projection.

Linking Multi-Modal MRI to Clinical Measures of Visual Field Loss After Stroke.

Loss of vision across large parts of the visual field is a common and devastating complication of cerebral strokes. In the clinic, this loss is quantified by measuring the sensitivity threshold across the field of vision using static perimetry. These methods rely on the ability of the patient to report the presence of lights in particular locations. While perimetry provides important information about the intactness of the visual field, the approach has some shortcomings. For example, it cannot distinguish where in the visual pathway the key processing deficit is located. In contrast, brain imaging can provide important information about anatomy, connectivity, and function of the visual pathway following stroke. In particular, functional magnetic resonance imaging (fMRI) and analysis of population receptive fields (pRF) can reveal mismatches between clinical perimetry and maps of cortical areas that still respond to visual stimuli after stroke. Here, we demonstrate how information from different brain imaging modalities—visual field maps derived from fMRI, lesion definitions from anatomical scans, and white matter tracts from diffusion weighted MRI data—provides a more complete picture of vision loss. For any given location in the visual field, the combination of anatomical and functional information can help identify whether vision loss is due to absence of gray matter tissue or likely due to white matter disconnection from other cortical areas. We present a combined imaging acquisition and visual stimulus protocol, together with a description of the analysis methodology, and apply it to datasets from four stroke survivors with homonymous field loss (two with hemianopia, two with quadrantanopia). For researchers trying to understand recovery of vision after stroke and clinicians seeking to stratify patients into different treatment pathways, this approach combines multiple, convergent sources of data to characterize the extent of the stroke damage. We show that such an approach gives a more comprehensive measure of residual visual capacity—in two particular respects: which locations in the visual field should be targeted and what kind of visual attributes are most suited for rehabilitation.

1401. Infliximab for Immune Reconstitution Inflammatory Syndrome (IRIS) in Tuberculous Meningitis; A Treatment Paradox

BackgroundTumor necrosis factor (TNF)-α inhibitors are known for the reactivation of latent tuberculosis (TB). As a paradox, it has been reported to have a role in the treatment of immune reconstitution inflammatory syndrome (IRIS) from anti-TB therapy.MethodsWe report a case of paradoxical worsening of central nervous system TB after initiation of anti-TB medications, which was treated successfully with infliximab (TNF-α inhibitor).ResultsA 34-year-old man from Nepal with a history of untreated latent TB presented with complaints of occipital headache, slurred speech, and witnessed seizure. His physical exam was consistent with hyperreflexia. MRI of the brain revealed multiple small contrast-enhancing lesions in cerebral hemispheres. CT Chest showed bilateral centrilobular nodules suggestive of miliary TB. Cerebrospinal fluid (CSF) analysis showed pleocytosis, high protein, and low glucose. He was started on isoniazid, rifampin, ethambutol, and pyrazinamide along with high-dose dexamethasone for TB meningitis. Later, MTB DNA probe from bronchioalveolar lavage and CSF detected Mycobacterium Tuberculosis which was pan-susceptible. Repeat MRI of the brain 6 months into therapy revealed worsening of brain lesions. Moxifloxacin and linezolid were added to the regimen given clinical progression on first-line therapy. 6-months into this enhanced regimen he started experiencing blurring of vision. Visual field mapping showed left homonymous hemianopia. Repeat MRI of the brain confirmed extensive changes of basilar meningitis completely enveloping the optic chiasm. IRIS from TB was suspected. His prednisone dose was increased, and 3-doses of infliximab infusion were, 2-weeks apart were administered which showed clinical and radiological improvement.MRI Brain MRI Brain (axial T2/flair sequence) shows hyperintensities in multiple locations including the involvement of the left optic nerve and the left occipital region.ConclusionExacerbation of pre-existing clinical symptoms, formation of new lesions, or cavitation of prior pulmonary infiltrates is known as tuberculosis IRIS or paradoxical reaction. Despite the clinical and radiological exacerbation, mycobacterial cultures usually stay negative. Continuation of anti-TB medications and high-dose corticosteroids are the backbone of treatment but in refractory cases, immune modulation is needed with anti-TNF-α agents.Disclosures All Authors: No reported disclosures

A method for mapping retinal images in early visual cortical areas

The visual cortex has been a heavily studied region in neuroscience due to many factors, not the least of which is its well-defined retinotopic organization. This organization makes it possible to predict the general location of cortical regions that stimuli will activate during visual tasks. However, the precise and accurate mapping of these regions in human patients takes time, effort, and participant compliance that can be difficult in many patient populations. In humans, this retino-cortical mapping has typically been done using functional localizers which maximally activate the area of interest, and then the activation profile is thresholded and converted to a binary mask region of interest (ROI). An alternative method involves performing population receptive field (pRF) mapping of the whole visual field and choosing vertices whose pRF centers fall within the stimulus. This method ignores the spatial extent of the pRF which changes dramatically between central and peripheral vision. Both methods require a dedicated functional scan and depend on participants’ stable fixation. The aim of this project was to develop a user-friendly method that can transform a retinal object of interest (for example, an image, a retinal lesion, or a preferred locus for fixation) from retinal space to its expected representation on the cortical surface without a functional scan. We modeled the retinal representation of each cortical vertex as a 2D Gaussian with a location and spatial extent given by a previously published retinotopic atlas. To identify how affected any cortical vertex would be by a given retinal object, we took the product of the retinal object with the Gaussian pRF of that cortical vertex. Normalizing this value gives the expected response of a given vertex to the retinal object. This method was validated using BOLD data obtained using a localizer with discrete visual stimuli, and showed good agreement to predicted values. Cortical localization of a visual stimulus or retinal defect can be obtained using our publicly available software, without a functional scan. Our software may benefit research with disease populations who have trouble maintaining stable fixation.

Dichoptic visual field mapping of suppression in exotropia with homonymous hemianopia

The purpose of this study was to investigate which portions of the visual scene are perceived by each eye in an exotropic subject with acquired hemianopia. The pattern of suppression is predictable from knowledge of how suppression scotomas are organized in exotropic subjects with intact visual fields. Dichoptic perimetry was performed by having a subject wear red/blue goggles while fixating a cross that was either red or blue. Red, blue, or purple spots were presented briefly at peripheral locations. The subject's identification of the spot color revealed which eye was perceptually engaged at any given location in the visual fields. A 17-year-old female with a history of exotropia was evaluated after rupture of a right parietal arteriovenous malformation. Dichoptic perimetry showed a left homonymous hemianopia. All stimuli to the right of the right fovea's projection point were perceived via the right eye. Stimuli between the foveal projection points, which were separated horizontally by the 20° exotropia, were perceived by the left eye. Perception of the visual scene is shared by the eyes in hemianopia and exotropia. Suppression occurs only in the peripheral temporal retina of the eye contralateral to the brain lesion, regardless of which eye is engaged in fixation. Although exotropia expands the binocular field of vision in hemianopia, it is probably not an adaptive response, even when it develops after hemianopia.

A population receptive field model of the magnetoencephalography response

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.