Population Receptive Field Modeling Research Articles

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.

Neural Encoding for Human Visual Cortex With Deep Neural Networks Learning “What” and “Where”

Neural encoding, a crucial aspect to understand the human brain information processing system, aims to establish a quantitative relationship between the stimuli and the evoked brain activities. In the field of visual neuroscience, with the ability to explain how neurons in the primary visual cortex work, population receptive field (pRF) models have enjoyed high popularity and made reliable progress in recent years. However, existing models rely on either the inflexible prior assumptions about pRF or the clumsy parameter estimation methods, severely limiting the expressiveness and interpretability. In this article, we propose a novel neural encoding framework by learning “what” and “where” with deep neural networks. It involves two separate aspects: 1) the spatial characteristic (“where”) and 2) feature selection (“what”) of neuron populations in the visual cortex. Specifically, our approach first encodes visual stimuli into hierarchically intermediate features through a pretrained deep neural network (DNN), then converts DNN features into refined features with the channel attention and spatial receptive field (RF) to learn “where”, and finally regresses refined features simultaneously onto voxel activities to learn “what”. The sparsity regularization and smoothness regularization are adopted in our modeling approach so that the crucial RF can be estimated automatically without prior assumptions about shapes. Furthermore, an attempt is made to extend the voxel-wise modeling approach to multi-voxel joint encoding models, and we show that it is conducive to rescuing voxels with poor signal-to-noise characteristics. Extensive empirical results demonstrate that the method developed herein provides an effective strategy to establish neural encoding for the human visual cortex, with the weaker prior constraints but the higher encoding performance.

Resolving the Spatial Profile of Figure Enhancement in Human V1 through Population Receptive Field Modeling.

The detection and segmentation of meaningful figures from their background is one of the primary functions of vision. While work in nonhuman primates has implicated early visual mechanisms in this figure-ground modulation, neuroimaging in humans has instead largely ascribed the processing of figures and objects to higher stages of the visual hierarchy. Here, we used high-field fMRI at 7 Tesla to measure BOLD responses to task-irrelevant orientation-defined figures in human early visual cortex (N = 6, four females). We used a novel population receptive field mapping-based approach to resolve the spatial profiles of two constituent mechanisms of figure-ground modulation: a local boundary response, and a further enhancement spanning the full extent of the figure region that is driven by global differences in features. Reconstructing the distinct spatial profiles of these effects reveals that figure enhancement modulates responses in human early visual cortex in a manner consistent with a mechanism of automatic, contextually driven feedback from higher visual areas.SIGNIFICANCE STATEMENT A core function of the visual system is to parse complex 2D input into meaningful figures. We do so constantly and seamlessly, both by processing information about visible edges and by analyzing large-scale differences between figure and background. While influential neurophysiology work has characterized an intriguing mechanism that enhances V1 responses to perceptual figures, we have a poor understanding of how the early visual system contributes to figure-ground processing in humans. Here, we use advanced computational analysis methods and high-field human fMRI data to resolve the distinct spatial profiles of local edge and global figure enhancement in the early visual system (V1 and LGN); the latter is distinct and consistent with a mechanism of automatic, stimulus-driven feedback from higher-level visual areas.

Mapping sequences can bias population receptive field estimates

Population receptive field (pRF) modelling is a common technique for estimating the stimulus-selectivity of populations of neurons using neuroimaging. Here, we aimed to address if pRF properties estimated with this method depend on the spatio-temporal structure and the predictability of the mapping stimulus. We mapped the polar angle preference and tuning width of voxels in visual cortex (V1–V4) of healthy, adult volunteers. We compared sequences sweeping orderly through the visual field or jumping from location to location employing stimuli of different width (45° vs 6°) and cycles of variable duration (8s vs 60s). While we did not observe any systematic influence of stimulus predictability, the temporal structure of the sequences significantly affected tuning width estimates. Ordered designs with large wedges and short cycles produced systematically smaller estimates than random sequences. Interestingly, when we used small wedges and long cycles, we obtained larger tuning width estimates for ordered than random sequences. We suggest that ordered and random mapping protocols show different susceptibility to other design choices such as stimulus type and duration of the mapping cycle and can produce significantly different pRF results.

Bayesian population receptive field modeling in human somatosensory cortex

Somatosensation is fundamental to our ability to sense our body and interact with the world. Our body is continuously sampling the environment using a variety of receptors tuned to different features, and this information is routed up to primary somatosensory cortex. Strikingly, the spatial organization of the peripheral receptors in the body are well maintained, with the resulting representation of the body in the brain being referred to as the somatosensory homunculus. Recent years have seen considerable advancements in the field of high-resolution fMRI, which have enabled an increasingly detailed examination of the organization and properties of this homunculus. Here we combined advanced imaging techniques at ultra-high field (7T) with a recently developed Bayesian population receptive field (pRF) modeling framework to examine pRF properties in primary somatosensory cortex. In each subject, vibrotactile stimulation of the fingertips (i.e., the peripheral mechanoreceptors) modulated the fMRI response along the post-central gyrus and these signals were used to estimate pRFs. We found the pRF center location estimates to be in accord with previous work as well as evidence of other properties in line with the underlying neurobiology. Specifically, as expected from the known properties of cortical magnification, we find a larger representation of the index finger compared to the other stimulated digits (middle, index, little). We also show evidence that the little finger is marked by the largest pRF sizes, and that pRF size increases from anterior to posterior regions of S1. The ability to estimate somatosensory pRFs in humans provides an unprecedented opportunity to examine the neural mechanisms underlying somatosensation and is critical for studying how the brain, body, and environment interact to inform perception and action.

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

Saliency and the population receptive field model to identify images from brain activity

Saliency and the population receptive field model to identify images from brain activity

Distinguishing Hemodynamics from Function in the Human LGN Using a Temporal Response Model

We developed a temporal population receptive field model to differentiate the neural and hemodynamic response functions (HRF) in the human lateral geniculate nucleus (LGN). The HRF in the human LGN is dominated by the richly vascularized hilum, a structure that serves as a point of entry for blood vessels entering the LGN and supplying the substrates of central vision. The location of the hilum along the ventral surface of the LGN and the resulting gradient in the amplitude of the HRF across the extent of the LGN have made it difficult to segment the human LGN into its more interesting magnocellular and parvocellular regions that represent two distinct visual processing streams. Here, we show that an intrinsic clustering of the LGN responses to a variety of visual inputs reveals the hilum, and further, that this clustering is dominated by the amplitude of the HRF. We introduced a temporal population receptive field model that includes separate sustained and transient temporal impulse response functions that vary on a much short timescale than the HRF. When we account for the HRF amplitude, we demonstrate that this temporal response model is able to functionally segregate the residual responses according to their temporal properties.

Larger Auditory Cortical Area and Broader Frequency Tuning Underlie Absolute Pitch

Absolute pitch (AP), the ability of some musicians to precisely identify and name musical tones in isolation, is associated with a number of gross morphological changes in the brain, but the fundamental neural mechanisms underlying this ability have not been clear. We presented a series of logarithmic frequency sweeps to age- and sex-matched groups of musicians with or without AP and controls without musical training. We used fMRI and population receptive field (pRF) modeling to measure the responses in the auditory cortex in 61 human subjects. The tuning response of each fMRI voxel was characterized as Gaussian, with independent center frequency and bandwidth parameters. We identified three distinct tonotopic maps, corresponding to primary (A1), rostral (R), and rostral-temporal (RT) regions of auditory cortex. We initially hypothesized that AP abilities might manifest in sharper tuning in the auditory cortex. However, we observed that AP subjects had larger cortical area, with the increased area primarily devoted to broader frequency tuning. We observed anatomically that A1, R and RT were significantly larger in AP musicians than in non-AP musicians or control subjects, which did not differ significantly from each other. The increased cortical area in AP in areas A1 and R were primarily low frequency and broadly tuned, whereas the distribution of responses in area RT did not differ significantly. We conclude that AP abilities are associated with increased early auditory cortical area devoted to broad-frequency tuning and likely exploit increased ensemble encoding.SIGNIFICANCE STATEMENT Absolute pitch (AP), the ability of some musicians to precisely identify and name musical tones in isolation, is associated with a number of gross morphological changes in the brain, but the fundamental neural mechanisms have not been clear. Our study shows that AP musicians have significantly larger volume in early auditory cortex than non-AP musicians and non-musician controls and that this increased volume is primarily devoted to broad-frequency tuning. We conclude that AP musicians are likely able to exploit increased ensemble representations to encode and identify frequency.

How Ocular Dominance and Binocularity Are Reflected by the Population Receptive Field Properties

The neural substrate of binocularity and sighting ocular dominance in humans is not clear. By utilizing the population receptive field (pRF) modeling technique, we explored whether these phenomena are associated with amplitude and pRF size differences. The visual field maps of 13 subjects were scanned (3-T Skyra) while viewing drifting bar stimuli. Both eyes (binocular condition), the dominant eye and the nondominant eye (two monocular conditions) were stimulated in separate sessions. For each condition, pRF size and amplitude were assessed. Binocular summation ratios were calculated by dividing binocular by mean monocular values (amplitude and pRF size). No differences in pRF size were seen between the viewing conditions within each region, that is, either between binocular and monocular or between dominant and nondominant viewing conditions. Binocular amplitudes were higher than the monocular amplitudes, but similar among the dominant and nondominant eyes. Binocular summation ratios derived from amplitudes were significantly higher than one (∼1.2), while those ratios derived from pRF size were not. These effects were found in all studied areas along the visual hierarchy, starting in V1. Neither the amplitude nor the pRF size show intereye difference and therefore cannot explain the different roles of the dominant and the nondominant eyes. Binocular, as compared to monocular vision, resulted in higher amplitudes, while receptive fields' sizes were similar, suggesting increased binocular response intensity as the basis for the binocular summation phenomenon. Our results could be applicable in imaging studies of monocular disease and studies that deal with nondisparity binocularity effects.

Human V2A: A map of the peripheral visual hemifield with functional connections to scene-selective cortex.

Humans can recognize a scene in the blink of an eye. This gist-based visual scene perception is thought to be underpinned by specialized visual processing emphasizing the visual periphery at a cortical locus relatively low in the visual processing hierarchy. Using wide-field retinotopic mapping and population receptive field (pRF) modeling, we identified a new visual hemifield map anterior of area V2d and inferior to area V6, which we propose to call area V2A. Based on its location relative to other visual areas, V2A may correspond to area 23V described in nonhuman primates. The pRF analysis revealed unique receptive field properties for V2A: a large (FWHM ∼23°) and constant receptive field size across the central ∼70° of the visual field. Resting-state fMRI connectivity analysis further suggests that V2A is ideally suited to quickly feed the scene-processing network with information that is not biased towards the center of the visual field. Our findings not only indicate a likely cortical locus for the initial stages of gist-based visual scene perception, but also suggest a reappraisal of the organization of human dorsomedial occipital cortex with a strip of separate hemifield representations anterior to the early visual areas (V1, V2d, and V3d).

Detailed somatotopy in primary motor and somatosensory cortex revealed by Gaussian population receptive fields

The relevance of human primary motor cortex (M1) for motor actions has long been established. However, it is still unknown how motor actions are represented, and whether M1 contains an ordered somatotopy at the mesoscopic level. In the current study we show that a detailed within-limb somatotopy can be obtained in M1 during finger movements using Gaussian population Receptive Field (pRF) models. Similar organizations were also obtained for primary somatosensory cortex (S1), showing that individual finger representations are interconnected throughout sensorimotor cortex. The current study additionally estimates receptive field sizes of neuronal populations, showing differences between finger digit representations, between M1 and S1, and additionally between finger digit flexion and extension. Using the Gaussian pRF approach, the detailed somatotopic organization of M1 can be obtained including underlying characteristics, allowing for the in-depth investigation of cortical motor representation and sensorimotor integration.

Development differentially sculpts receptive fields across early and high-level human visual cortex

Receptive fields (RFs) processing information in restricted parts of the visual field are a key property of visual system neurons. However, how RFs develop in humans is unknown. Using fMRI and population receptive field (pRF) modeling in children and adults, we determine where and how pRFs develop across the ventral visual stream. Here we report that pRF properties in visual field maps, from the first visual area, V1, through the first ventro-occipital area, VO1, are adult-like by age 5. However, pRF properties in face-selective and character-selective regions develop into adulthood, increasing the foveal coverage bias for faces in the right hemisphere and words in the left hemisphere. Eye-tracking indicates that pRF changes are related to changing fixation patterns on words and faces across development. These findings suggest a link between face and word viewing behavior and the differential development of pRFs across visual cortex, potentially due to competition on foveal coverage.

Differential Sampling of Visual Space in Ventral and Dorsal Early Visual Cortex.

A fundamental feature of cortical visual processing is the separation of visual processing for the upper and lower visual fields. In early visual cortex (EVC), the upper visual field is processed ventrally, with the lower visual field processed dorsally. This distinction persists into several category-selective regions of occipitotemporal cortex, with ventral and lateral scene-, face-, and object-selective regions biased for the upper and lower visual fields, respectively. Here, using an elliptical population receptive field (pRF) model, we systematically tested the sampling of visual space within ventral and dorsal divisions of human EVC in both male and female participants. We found that (1) pRFs tend to be elliptical and oriented toward the fovea with distinct angular distributions for ventral and dorsal divisions of EVC, potentially reflecting a radial bias; and (2) pRFs in ventral areas were larger (∼1.5×) and more elliptical (∼1.2×) than those in dorsal areas. These differences potentially reflect a tendency for receptive fields in ventral temporal cortex to overlap the fovea with less emphasis on precise localization and isotropic representation of space compared with dorsal areas. Collectively, these findings suggest that ventral and dorsal divisions of EVC sample visual space differently, likely contributing to and/or stemming from the functional differentiation of visual processing observed in higher-level regions of the ventral and dorsal cortical visual pathways.SIGNIFICANCE STATEMENT The processing of visual information from the upper and lower visual fields is separated in visual cortex. Although ventral and dorsal divisions of early visual cortex (EVC) are commonly assumed to sample visual space equivalently, we demonstrate systematic differences using an elliptical population receptive field (pRF) model. Specifically, we demonstrate that (1) ventral and dorsal divisions of EVC exhibit diverging distributions of pRF angle, which are biased toward the fovea; and (2) ventral pRFs exhibit higher aspect ratios and cover larger areas than dorsal pRFs. These results suggest that ventral and dorsal divisions of EVC sample visual space differently and that such differential sampling likely contributes to different functional roles attributed to the ventral and dorsal pathways, such as object recognition and visually guided attention, respectively.

Compressive Temporal Summation in Human Visual Cortex.

Combining sensory inputs over space and time is fundamental to vision. Population receptive field models have been successful in characterizing spatial encoding throughout the human visual pathways. A parallel question, how visual areas in the human brain process information distributed over time, has received less attention. One challenge is that the most widely used neuroimaging method, fMRI, has coarse temporal resolution compared with the time-scale of neural dynamics. Here, via carefully controlled temporally modulated stimuli, we show that information about temporal processing can be readily derived from fMRI signal amplitudes in male and female subjects. We find that all visual areas exhibit subadditive summation, whereby responses to longer stimuli are less than the linear prediction from briefer stimuli. We also find fMRI evidence that the neural response to two stimuli is reduced for brief interstimulus intervals (indicating adaptation). These effects are more pronounced in visual areas anterior to V1-V3. Finally, we develop a general model that shows how these effects can be captured with two simple operations: temporal summation followed by a compressive nonlinearity. This model operates for arbitrary temporal stimulation patterns and provides a simple and interpretable set of computations that can be used to characterize neural response properties across the visual hierarchy. Importantly, compressive temporal summation directly parallels earlier findings of compressive spatial summation in visual cortex describing responses to stimuli distributed across space. This indicates that, for space and time, cortex uses a similar processing strategy to achieve higher-level and increasingly invariant representations of the visual world.SIGNIFICANCE STATEMENT Combining sensory inputs over time is fundamental to seeing. Two important temporal phenomena are summation, the accumulation of sensory inputs over time, and adaptation, a response reduction for repeated or sustained stimuli. We investigated these phenomena in the human visual system using fMRI. We built predictive models that operate on arbitrary temporal patterns of stimulation using two simple computations: temporal summation followed by a compressive nonlinearity. Our new temporal compressive summation model captures (1) subadditive temporal summation, and (2) adaptation. We show that the model accounts for systematic differences in these phenomena across visual areas. Finally, we show that for space and time, the visual system uses a similar strategy to achieve increasingly invariant representations of the visual world.

Attention Priority Map of Face Images in Human Early Visual Cortex.

Attention priority maps are topographic representations that are used for attention selection and guidance of task-related behavior during visual processing. Previous studies have identified attention priority maps of simple artificial stimuli in multiple cortical and subcortical areas, but investigating neural correlates of priority maps of natural stimuli is complicated by the complexity of their spatial structure and the difficulty of behaviorally characterizing their priority map. To overcome these challenges, we reconstructed the topographic representations of upright/inverted face images from fMRI BOLD signals in human early visual areas primary visual cortex (V1) and the extrastriate cortex (V2 and V3) based on a voxelwise population receptive field model. We characterized the priority map behaviorally as the first saccadic eye movement pattern when subjects performed a face-matching task relative to the condition in which subjects performed a phase-scrambled face-matching task. We found that the differential first saccadic eye movement pattern between upright/inverted and scrambled faces could be predicted from the reconstructed topographic representations in V1-V3 in humans of either sex. The coupling between the reconstructed representation and the eye movement pattern increased from V1 to V2/3 for the upright faces, whereas no such effect was found for the inverted faces. Moreover, face inversion modulated the coupling in V2/3, but not in V1. Our findings provide new evidence for priority maps of natural stimuli in early visual areas and extend traditional attention priority map theories by revealing another critical factor that affects priority maps in extrastriate cortex in addition to physical salience and task goal relevance: image configuration.SIGNIFICANCE STATEMENT Prominent theories of attention posit that attention sampling of visual information is mediated by a series of interacting topographic representations of visual space known as attention priority maps. Until now, neural evidence of attention priority maps has been limited to studies involving simple artificial stimuli and much remains unknown about the neural correlates of priority maps of natural stimuli. Here, we show that attention priority maps of face stimuli could be found in primary visual cortex (V1) and the extrastriate cortex (V2 and V3). Moreover, representations in extrastriate visual areas are strongly modulated by image configuration. These findings extend our understanding of attention priority maps significantly by showing that they are modulated, not only by physical salience and task-goal relevance, but also by the configuration of stimuli images.

Bayesian population receptive field modelling

We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated in the context of 2D retinotopic mapping. The framework enables the experimenter to specify generative (encoding) models of fMRI timeseries, in which experimental stimuli enter a pRF model of neural activity, which in turns drives a nonlinear model of neurovascular coupling and Blood Oxygenation Level Dependent (BOLD) response. The neuronal and haemodynamic parameters are estimated together on a voxel-by-voxel or region-of-interest basis using a Bayesian estimation algorithm (variational Laplace). This offers several novel contributions to receptive field modelling. The variance/covariance of parameters are estimated, enabling receptive fields to be plotted while properly representing uncertainty about pRF size and location. Variability in the haemodynamic response across the brain is accounted for. Furthermore, the framework introduces formal hypothesis testing to pRF analysis, enabling competing models to be evaluated based on their log model evidence (approximated by the variational free energy), which represents the optimal tradeoff between accuracy and complexity. Using simulations and empirical data, we found that parameters typically used to represent pRF size and neuronal scaling are strongly correlated, which is taken into account by the Bayesian methods we describe when making inferences. We used the framework to compare the evidence for six variants of pRF model using 7 T functional MRI data and we found a circular Difference of Gaussians (DoG) model to be the best explanation for our data overall. We hope this framework will prove useful for mapping stimulus spaces with any number of dimensions onto the anatomy of the brain.

Visual field map clusters in human frontoparietal cortex.

The visual neurosciences have made enormous progress in recent decades, in part because of the ability to drive visual areas by their sensory inputs, allowing researchers to define visual areas reliably across individuals and across species. Similar strategies for parcellating higher-order cortex have proven elusive. Here, using a novel experimental task and nonlinear population receptive field modeling, we map and characterize the topographic organization of several regions in human frontoparietal cortex. We discover representations of both polar angle and eccentricity that are organized into clusters, similar to visual cortex, where multiple gradients of polar angle of the contralateral visual field share a confluent fovea. This is striking because neural activity in frontoparietal cortex is believed to reflect higher-order cognitive functions rather than external sensory processing. Perhaps the spatial topography in frontoparietal cortex parallels the retinotopic organization of sensory cortex to enable an efficient interface between perception and higher-order cognitive processes. Critically, these visual maps constitute well-defined anatomical units that future studies of frontoparietal cortex can reliably target.

Visual Field Map Clusters in High-Order Visual Processing: Organization of V3A/V3B and a New Cloverleaf Cluster in the Posterior Superior Temporal Sulcus.

The cortical hierarchy of the human visual system has been shown to be organized around retinal spatial coordinates throughout much of low- and mid-level visual processing. These regions contain visual field maps (VFMs) that each follows the organization of the retina, with neighboring aspects of the visual field processed in neighboring cortical locations. On a larger, macrostructural scale, groups of such sensory cortical field maps (CFMs) in both the visual and auditory systems are organized into roughly circular cloverleaf clusters. CFMs within clusters tend to share properties such as receptive field distribution, cortical magnification, and processing specialization. Here we use fMRI and population receptive field (pRF) modeling to investigate the extent of VFM and cluster organization with an examination of higher-level visual processing in temporal cortex and compare these measurements to mid-level visual processing in dorsal occipital cortex. In human temporal cortex, the posterior superior temporal sulcus (pSTS) has been implicated in various neuroimaging studies as subserving higher-order vision, including face processing, biological motion perception, and multimodal audiovisual integration. In human dorsal occipital cortex, the transverse occipital sulcus (TOS) contains the V3A/B cluster, which comprises two VFMs subserving mid-level motion perception and visuospatial attention. For the first time, we present the organization of VFMs in pSTS in a cloverleaf cluster. This pSTS cluster contains four VFMs bilaterally: pSTS-1:4. We characterize these pSTS VFMs as relatively small at ∼125 mm2 with relatively large pRF sizes of ∼2–8° of visual angle across the central 10° of the visual field. V3A and V3B are ∼230 mm2 in surface area, with pRF sizes here similarly ∼1–8° of visual angle across the same region. In addition, cortical magnification measurements show that a larger extent of the pSTS VFM surface areas are devoted to the peripheral visual field than those in the V3A/B cluster. Reliability measurements of VFMs in pSTS and V3A/B reveal that these cloverleaf clusters are remarkably consistent and functionally differentiable. Our findings add to the growing number of measurements of widespread sensory CFMs organized into cloverleaf clusters, indicating that CFMs and cloverleaf clusters may both be fundamental organizing principles in cortical sensory processing.

Can responses to basic non-numerical visual features explain neural numerosity responses?

Humans and many animals can distinguish between stimuli that differ in numerosity, the number of objects in a set. Human and macaque parietal lobes contain neurons that respond to changes in stimulus numerosity. However, basic non-numerical visual features can affect neural responses to and perception of numerosity, and visual features often co-vary with numerosity. Therefore, it is debated whether numerosity or co-varying low-level visual features underlie neural and behavioral responses to numerosity. To test the hypothesis that non-numerical visual features underlie neural numerosity responses in a human parietal numerosity map, we analyze responses to a group of numerosity stimulus configurations that have the same numerosity progression but vary considerably in their non-numerical visual features. Using ultra-high-field (7T) fMRI, we measure responses to these stimulus configurations in an area of posterior parietal cortex whose responses are believed to reflect numerosity-selective activity. We describe an fMRI analysis method to distinguish between alternative models of neural response functions, following a population receptive field (pRF) modeling approach. For each stimulus configuration, we first quantify the relationships between numerosity and several non-numerical visual features that have been proposed to underlie performance in numerosity discrimination tasks. We then determine how well responses to these non-numerical visual features predict the observed fMRI responses, and compare this to the predictions of responses to numerosity. We demonstrate that a numerosity response model predicts observed responses more accurately than models of responses to simple non-numerical visual features. As such, neural responses in cognitive processing need not reflect simpler properties of early sensory inputs.