pRF Modeling Research Articles

Octane Response of Gasoline Fuels to Different Anti-knock Oxygenates Addition

Abstract A series of renewable and clean oxygenated compounds possessing high octane numbers, including alcohols, ethers, esters and furans, were used as octane boosters for gasoline fuels, and the octane responses of the gasoline fuels to these oxygenates addition were evaluated. Gasoline model fuels of different typical hydrocarbon compounds, including iso-octane, n-heptane, toluene, diisobutylene, and cyclohexane, were designed to have the identical octane rating. The research octane number (RON) and motor octane number (MON) of the gasoline model fuels with anti-knock oxygenates addition were experimentally measured on a standard cooperative fuel research (CFR) engine. The results highlight the varied impact of anti-knock oxygenates on the octane enhancement of gasoline fuels, with 2-methylfuran exhibiting the most pronounced RON boost effect and ethanol demonstrating the strongest MON enhancement effects, and isopropyl ether and dimethyl carbonate shows the weakest RON and MON boost effects, respectively. The anti-knock enhancement effects of the oxygenated additives are dependent on gasoline fuel compositions. With the anti-knock oxygenates addition, PRF model fuel shows more significant octane enhancements, and the octane boosting effects are reduced for the gasoline model fuels containing toluene or diisobutylene, indicating an antagonistic interaction between the oxygenates and toluene/diisobutylene. By comparing the octane enhancement effects of the tested anti-knock additives, it is evident that 2-methylfuran and ethanol are the more superior anti-knock candidates for gasoline fuels.

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.

The Role of Population Receptive Field Sizes in Higher-Order Visual Dysfunction.

Population receptive field (pRF) modeling is an fMRI technique used to retinotopically map visual cortex, with pRF size characterizing the degree of spatial integration. In clinical populations, most pRF mapping research has focused on damage to visual system inputs. Herein, we highlight recent work using pRF modeling to study high-level visual dysfunctions. Larger pRF sizes, indicating coarser spatial processing, were observed in homonymous visual field deficits, aging, and autism spectrum disorder. Smaller pRF sizes, indicating finer processing, were observed in Alzheimer's disease and schizophrenia. In posterior cortical atrophy, a unique pattern was found in which pRF size changes depended on eccentricity. Changes to pRF properties were observed in clinical populations, even in high-order impairments, explaining visual behavior. These pRF changes likely stem from altered interactions between brain regions. Furthermore, some studies suggested that pRF sizes change as part of cortical reorganization, and they can point towards future prognosis.

Characterizing Spatiotemporal Population Receptive Fields in Human Visual Cortex with fMRI.

The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time-varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants (both females and males). We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (1) from early to later areas within a visual stream, spatial and temporal windows of pRFs progressively increase in size and show greater compressive nonlinearities, (2) later visual areas show diverging spatial and temporal windows across streams, and (3) within early visual areas (V1-V3), both spatial and temporal windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses using fMRI.

Two-Dimensional Population Receptive Field Mapping of Human Primary Somatosensory Cortex.

Functional magnetic resonance imaging can provide detailed maps of how sensory space is mapped in the human brain. Here, we use a novel 16 stimulator setup (a 4 × 4 grid) to measure two-dimensional sensory maps of between and within-digit (D2-D4) space using high spatial-resolution (1.25mm isotropic) imaging at 7 Tesla together with population receptive field (pRF) mapping in 10 participants. Using a 2D Gaussian pRF model, we capture maps of the coverage of digits D2-D5 across Brodmann areas and estimate pRF size and shape. In addition, we compare results to previous studies that used fewer stimulators by constraining pRF models to a 1D Gaussian Between Digit or 1D Gaussian Within Digit model. We show that pRFs across somatosensory areas tend to have a strong preference to cover the within-digit axis. We show an increase in pRF size moving from D2-D5. We quantify pRF shapes in Brodmann area (BA) 3b, 3a, 1, 2 and show differences in pRF size in Brodmann areas 3a-2, with larger estimates for BA2. Generally, the 2D Gaussian pRF model better represents pRF coverage maps generated by our data, which itself is produced from a 2D stimulation grid.

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.

Development of a Piezoelectric Actuated Tactile Stimulation Device for Population Receptive Field Mapping in Human Somatosensory Cortex With fMRI.

Multichannel tactile stimulation devices is need to investigate human finger population receptive field (pRF) characteristics in the primary somatosensory cortex during functional magnetic resonance imaging (fMRI). To accurately characterize right-hand somatosensory representation based on the Bayesian pRF model. Prospective. A water phantom and six healthy participants (four males, mean 23.8 years old). T1-weighted magnetization-prepared rapid gradient-echo, T2*-weighted echo planar imaging at 3T. The piezoelectric actuated tactile stimulation device consisted of execution unit and control unit. The output performance of the device was measured by a laser displacement sensor. The effect of the device on images' signal-to-noise ratio (SNR) was measured by phantom experiments. The activation representation arrangement order, relative volumes, and receptive field size of the right hand were assessed during the along-digits and cross-digits paradigms. The normality of the data was tested by the Shapiro-Wilk method. A paired-sample t test was performed to test pRF characteristics for all digit pairings. The significance level was set to P=0.05 (false discovery rate [FDR] correct). Percussive stimulation provided by the piezoelectric actuated tactile stimulator had a stable displacement (2.64 mm) over a wide range of vibration frequencies (0-30 Hz). The output delay of the device was 1millisecond. The device did not affect the image's SNR (without the device: SNR=138.24 ± 7.87, temporal SNR [TSNR]=440.03 ± 52.08. With the device: SNR=138.06 ± 8.44, TSNR=438.52 ± 56.38. PSNR =0.88, PTSNR =0.46). Representations of right-hand fingers showed the same arrangement order in both experiments (D1-D5 arranged along the central sulcus). However, the relative volumes of D3 showed significant differences in S1 (P=0.003). Among four subareas, the relative volumes of D3 were significantly different in area 1 (P=0.047). This developed stimulator, through experimental verification, could play a role in pRF mapping exploration. 2 TECHNICAL EFFICACY STAGE: 1.

Divisive normalization unifies disparate response signatures throughout the human visual hierarchy

Neural processing is hypothesized to apply the same mathematical operations in a variety of contexts, implementing so-called canonical neural computations. Divisive normalization (DN) is considered a prime candidate for a canonical computation. Here, we propose a population receptive field (pRF) model based on DN and evaluate it using ultra-high-field functional MRI (fMRI). The DN model parsimoniously captures seemingly disparate response signatures with a single computation, superseding existing pRF models in both performance and biological plausibility. We observe systematic variations in specific DN model parameters across the visual hierarchy and show how they relate to differences in response modulation and visuospatial information integration. The DN model delivers a unifying framework for visuospatial responses throughout the human visual hierarchy and provides insights into its underlying information-encoding computations. These findings extend the role of DN as a canonical computation to neuronal populations throughout the human visual hierarchy.

Population receptive fields in nonhuman primates from whole-brain fMRI and large-scale neurophysiology in visual cortex.

Population receptive field (pRF) modeling is a popular fMRI method to map the retinotopic organization of the human brain. While fMRI-based pRF maps are qualitatively similar to invasively recorded single-cell receptive fields in animals, it remains unclear what neuronal signal they represent. We addressed this question in awake nonhuman primates comparing whole-brain fMRI and large-scale neurophysiological recordings in areas V1 and V4 of the visual cortex. We examined the fits of several pRF models based on the fMRI blood-oxygen-level-dependent (BOLD) signal, multi-unit spiking activity (MUA), and local field potential (LFP) power in different frequency bands. We found that pRFs derived from BOLD-fMRI were most similar to MUA-pRFs in V1 and V4, while pRFs based on LFP gamma power also gave a good approximation. fMRI-based pRFs thus reliably reflect neuronal receptive field properties in the primate brain. In addition to our results in V1 and V4, the whole-brain fMRI measurements revealed retinotopic tuning in many other cortical and subcortical areas with a consistent increase in pRF size with increasing eccentricity, as well as a retinotopically specific deactivation of default mode network nodes similar to previous observations in humans.

The multivariable prognostic models for severe complications after heart valve surgery

BackgroundTo provide multivariable prognostic models for severe complications prediction after heart valve surgery, including low cardiac output syndrome (LCOS), acute kidney injury requiring hemodialysis (AKI-rH) and multiple organ dysfunction syndrome (MODS).MethodsWe developed multivariate logistic regression models to predict severe complications after heart valve surgery using 930 patients collected retrospectively from the first affiliated hospital of Sun Yat-Sen University from January 2014 to December 2015. The validation was conducted using a retrospective dataset of 713 patients from the same hospital from January 2016 to March 2017. We considered two kinds of prognostic models: the PRF models which were built by using the preoperative risk factors only, and the PIRF models which were built by using both of the preoperative and intraoperative risk factors. The least absolute shrinkage selector operator was used for developing the models. We assessed and compared the discriminative abilities for both of the PRF and PIRF models via the receiver operating characteristic (ROC) curve.ResultsCompared with the PRF models, the PIRF modes selected additional intraoperative factors, such as auxiliary cardiopulmonary bypass time and combined tricuspid valve replacement. Area under the ROC curves (AUCs) of PRF models for predicting LCOS, AKI-rH and MODS are 0.565 (0.466, 0.664), 0.688 (0.62, 0.757) and 0.657 (0.563, 0.751), respectively. As a comparison, the AUCs of the PIRF models for predicting LOCS, AKI-rH and MODS are 0.821 (0.747, 0.896), 0.78 (0.717, 0.843) and 0.774 (0.7, 0.847), respectively.ConclusionsAdding the intraoperative factors can increase the predictive power of the prognostic models for severe complications prediction after heart valve surgery.

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.

Visual Field Reconstruction in Hemianopia Using fMRI Based Mapping Techniques.

PurposeA stroke that includes the primary visual cortex unilaterally leads to a loss of visual field (VF) representation in the hemifield contralateral to the damage. While behavioral procedures for measuring the VF, such as perimetry, may indicate that a patient cannot see in a particular area, detailed psychophysical testing often detects the ability to perform detection or discrimination of visual stimuli (“blindsight”). The aim of this study was to determine whether functional magnetic resonance imaging (fMRI) could be used to determine whether perimetrically blind regions of the VF were still represented in VF maps reconstructed on the basis of visually evoked neural activity.MethodsThirteen patients with hemianopia and nine control participants were scanned using 3T MRI while presented with visual stimulation. Two runs of a dynamic “wedge and ring” mapping stimulus, totaling approximately 10 min, were performed while participants fixated centrally. Two different analysis approaches were taken: the conventional population receptive field (pRF) analysis and micro-probing (MP). The latter is a variant of the former that makes fewer assumptions when modeling the visually evoked neural activity. Both methods were used to reconstruct the VF by projecting modeled activity back onto the VF. Following a normalization step, these “coverage maps” can be compared to the VF sensitivity plots obtained using perimetry.ResultsWhile both fMRI-based approaches revealed regions of neural activity within the perimetrically “blind” sections of the VF, the MP approach uncovered more voxels in the lesioned hemisphere in which a modest degree of visual sensitivity was retained. Furthermore, MP-based analysis indicated that both early (V1/V2) and extrastriate visual areas contributed equally to the retained sensitivity in both patients and controls.ConclusionIn hemianopic patients, fMRI-based approaches for reconstructing the VF can pick up activity in perimetrically blind regions of the VF. Such regions of the VF may be particularly amenable for rehabilitation to regain visual function. Compared to conventional pRF modeling, MP reveals more voxels with retained visual sensitivity, suggesting it is a more sensitive approach for VF reconstruction.

Aberrant visual population receptive fields in human albinism.

Retinotopic organization is a fundamental feature of visual cortex thought to play a vital role in encoding spatial information. One important aspect of normal retinotopy is the representation of the right and left hemifields in contralateral visual cortex. However, in human albinism, many temporal retinal afferents decussate aberrantly at the optic chiasm resulting in partially superimposed representations of opposite hemifields in each hemisphere of visual cortex. Previous functional magnetic resonance imaging (fMRI) studies in human albinism suggest that the right and left hemifield representations are superimposed in a mirror-symmetric manner. This should produce imaging voxels which respond to two separate locations mirrored across the vertical meridian. However, it is not yet clear how retino-cortical miswiring in albinism manifests at the level of single voxel population receptive fields (pRFs). Here, we used pRF modeling to fit both single and dual pRF models to the visual responses of voxels in visual areas V1 to V3 of five subjects with albinism. We found that subjects with albinism (but not controls) have sizable clusters of voxels with unequivocal dual pRFs consistently corresponding to, but not fully coextensive with, regions of hemifield overlap. These dual pRFs were typically positioned at locations roughly mirrored across the vertical meridian and were uniquely clustered within a portion of the visual field for each subject.

Foveal pRF properties in the visual cortex depend on the extent of stimulated visual field

Previous studies demonstrated that alterations in functional MRI derived receptive field (pRF) properties in cortical projection zones of retinal lesions can erroneously be mistaken for cortical large-scale reorganization in response to visual system pathologies. We tested, whether such confounds are also evident in the normal cortical projection zone of the fovea for simulated peripheral visual field defects. We applied fMRI-based visual field mapping of the central visual field at 3 T in eight controls to compare the pRF properties of the central visual field of a reference condition (stimulus radius: 14°) and two conditions with simulated peripheral visual field defect, i.e., with a peripheral gray mask, stimulating only the central 7° or 4° radius. We quantified, for the cortical representation of the actually stimulated visual field, the changes in the position and size of the pRFs associated with reduced peripheral stimulation using conventional and advanced pRF modeling. We found foveal pRF-positions (≤3°) to be significantly shifted towards the periphery (p<0.05, corrected). These pRF-shifts were largest for the 4° condition [visual area (mean eccentricity shift): V1 (0.9°), V2 (0.9°), V3 (1.0°)], but also evident for the 7° condition [V1 (0.5°), V2 (0.5°), V3 (0.9°)]. Further, an overall enlargement of pRF-sizes was observed. These findings indicate the dependence of foveal pRF parameters on the spatial extent of the stimulated visual field and are likely associated with methodological biases and/or physiological mechanisms. Consequently, our results imply that, previously reported similar findings in patients with actual peripheral scotomas need to be interpreted with caution and indicate the need for adequate control conditions in investigations of visual cortex reorganization.

Investigating the Reliability of Population Receptive Field Size Estimates Using fMRI.

In functional MRI (fMRI), population receptive field (pRF) models allow a quantitative description of the response as a function of the features of the stimuli that are relevant for each voxel. The most popular pRF model used in fMRI assumes a Gaussian shape in the features space (e.g., the visual field) reducing the description of the voxel’s pRF to the Gaussian mean (the pRF preferred feature) and standard deviation (the pRF size). The estimation of the pRF mean has been proven to be highly reliable. However, the estimate of the pRF size has been shown not to be consistent within and between subjects. While this issue has been noted experimentally, here we use an optimization theory perspective to describe how the inconsistency in estimating the pRF size is linked to an inherent property of the Gaussian pRF model. When fitting such models, the goodness of fit is less sensitive to variations in the pRF size than to variations in the pRF mean. We also show how the same issue can be considered from a bias-variance perspective. We compare different estimation procedures in terms of the reliability of their estimates using simulated and real fMRI data in the visual (using the Human Connectome Project database) and auditory domain. We show that, the reliability of the estimate of the pRF size can be improved considering a linear combination of those pRF models with similar goodness of fit or a permutation based approach. This increase in reliability of the pRF size estimate does not affect the reliability of the estimate of the pRF mean and the prediction accuracy.

Comparing population receptive fields in human and macaque visual cortex

The population receptive field (pRF) modelling approach has been applied widely in human fMRI to inform the organization of both early and late stages of the cortical visual hierarchy. Recently, a pRF implementation was developed that allows for oriented and elliptical pRFs and demonstrated that dorsal and ventral divisions of early visual cortex (EVC) differentially sample visual space. Thus, differences between the larger dorsal and ventral visual processing streams may be set early on in the visual hierarchy. However, despite its common use, we do not yet understand how pRFs relate to the receptive fields of single neurons. Therefore, cross-species validation by means of comparative fMRI would go a long way to bridging the gap between single-unit recordings in monkeys and fMRI in humans. Here, we compare pRFs from dorsal and ventral divisions of EVC in both humans (n=12) and macaques (Macaca mulatta; n=2). Participants (both humans and macaques) fixated centrally while a bar aperture traversed gradually across the visual field revealing brief scene fragments. Data from both study populations were analyzed in AFNI using both standard (circular) and elliptical pRF models. Cross-validation analyses revealed that, similar to the human, the elliptical pRF model captured more variance in the time-course of macaque data than a circular pRF implementation. Further, pRF eccentricity was positively correlated with both pRF aspect ratio and pRF area, with the strength of correlation increasing generally as a function of position in the visual hierarchy. Also consistent with our human data, the average pRF angles of dorsal and ventral divisions of EVC are oriented differentially. Finally, we found that on average pRF size estimates in macaques tended to be larger than in humans, despite the overall similarity. Overall, these results reveal a very similar pattern of pRF properties between macaque and human visual cortex

Development of population receptive fields in the lateral visual stream improves spatial coding amid stable structural-functional coupling

Human visual cortex encompasses more than a dozen visual field maps across three major processing streams. One of these streams is the lateral visual stream, which extends from V1 to lateral-occipital (LO) and temporal-occipital (TO) visual field maps and plays a prominent role in shape as well as motion perception. However, it is unknown if and how population receptive fields (pRFs) in the lateral visual stream develop from childhood to adulthood, and what impact this development may have on spatial coding. Here, we used functional magnetic resonance imaging and pRF modeling in school-age children and adults to investigate the development of the lateral visual stream. Our data reveal four main findings: 1) The topographic organization of eccentricity and polar angle maps of the lateral stream is stable after age five. 2) In both age groups there is a reliable relationship between eccentricity map transitions and cortical folding: the middle occipital gyrus predicts the transition between the peripheral representation of LO and TO maps. 3) pRFs in LO and TO maps undergo differential development from childhood to adulthood, resulting in increasing coverage of the central visual field in LO and of the peripheral visual field in TO. 4) Model-based decoding shows that the consequence of pRF and visual field coverage development is improved spatial decoding from LO and TO distributed responses in adults vs. children. Together, these results explicate both the development and topography of the lateral visual stream. Our data show that the general structural-functional organization is laid out early in development, but fine-scale properties, such as pRF distribution across the visual field and consequently, spatial precision, become fine-tuned across childhood development. These findings advance understanding of the development of the human visual system from childhood to adulthood and provide an essential foundation for understanding developmental deficits.

Optical Properties Influence Visual Cortical Functional Resolution After Cataract Surgery and Both Dissociate From Subjectively Perceived Quality of Vision.

To investigate the relation between optical properties, population receptive fields (pRFs), visual function, and subjectively perceived quality of vision after cataract surgery. The study includes 30 patients who had recently undergone bilateral sequential cataract surgery. We used functional magnetic resonance imaging and pRF modelling methods to assess pRF sizes across visual cortical regions (V1-V3). Subjects also performed a complete ophthalmologic and psychophysical examination and answered a quality of vision questionnaire. Subjects with worse optical properties had, as predicted, larger pRF sizes. In addition, analysis in the primary visual cortex revealed significantly larger mean pRF sizes for operated subjects with worse contrast sensitivity (P = 0.038). In contrast, patients who scored high in the subjective "bothersome" dimension induced by dysphotic symptoms had surprisingly lower pRF size fitting interception (P = 0.012) and pRF size fitting slopes (P = 0.020), suggesting a dissociation between objective quality of vision and subjective appraisal. Optical properties of the eye influence pRF size. In particular, visual aberrations have a negative impact on visual cortical processing. A novel dissociation between subjective reports of quality of vision and pRF sizes was further identified. This suggests that patients with better cortical resolution may have a negative subjective response possibly because of improved perception of dysphotic phenomena. pRF properties represent a valuable quantitative measure to objectively evaluate quality of vision but do not necessarily predict subjective complaints.

Simultaneous estimation of population receptive field and hemodynamic parameters from single point BOLD responses using Metropolis-Hastings sampling

We introduce a new approach to Bayesian pRF model estimation using Markov Chain Monte Carlo (MCMC) sampling for simultaneous estimation of pRF and hemodynamic parameters. To obtain high performance on commonly accessible hardware we present a novel heuristic consisting of interpolation between precomputed responses for predetermined stimuli and a large cross-section of receptive field parameters. We investigate the validity of the proposed approach with respect to MCMC convergence, tuning and biases. We compare different combinations of pRF - Compressive Spatial Summation (CSS), Dumoulin-Wandell (DW) and hemodynamic (5-parameter and 3-parameter Balloon-Windkessel) models within our framework with and without the usage of the new heuristic. We evaluate estimation consistency and log probability across models. We perform as well a comparison of one model with and without lookup table within the RStan framework using its No-U-Turn Sampler. We present accelerated computation of whole-ROI parameters for one subject. Finally, we discuss risks and limitations associated with the usage of the new heuristic as well as the means of resolving them. We found that the new algorithm is a valid sampling approach to joint pRF/hemodynamic parameter estimation and that it exhibits very high performance.

Radial asymmetries in population receptive field size and cortical magnification factor in early visual cortex

Human visual cortex does not represent the whole visual field with the same detail. Changes in receptive field size, population receptive field (pRF) size and cortical magnification factor (CMF) with eccentricity are well established, and associated with changes in visual acuity with eccentricity. Visual acuity also changes across polar angle. However, it remains unclear how RF size, pRF size and CMF change across polar angle. Here, we examine differences in pRF size and CMF across polar angle in V1, V2 and V3 using pRF modeling of human fMRI data. In these visual field maps, we find smaller pRFs and larger CMFs in horizontal (left and right) than vertical (upper and lower) visual field quadrants. Differences increase with eccentricity, approximately in proportion to average pRF size and CMF. Similarly, we find larger CMFs in the lower than upper quadrant, and again differences increase with eccentricity. However, pRF size differences between lower and upper quadrants change direction with eccentricity. Finally, we find slightly smaller pRFs in the left than right quadrants of V2 and V3, though this difference is very small, and we find no differences in V1 and no differences in CMF. Moreover, differences in pRF size and CMF vary gradually with polar angle and are not limited to the meridians or visual field map discontinuities. PRF size and CMF differences do not consistently follow patterns of cortical curvature, despite the link between cortical curvature and polar angle in V1. Thus, the early human visual cortex has a radially asymmetric representation of the visual field. These asymmetries may underlie consistent reports of asymmetries in perceptual abilities.