Edward Silson

A Retinotopic Basis for the Division of High-Level Scene Processing between Lateral and Ventral Human Occipitotemporal Cortex

In humans, there is a repeated category-selective organization across the lateral and ventral surfaces of the occipitotemporal cortex. This apparent redundancy is often explained as a feedforward hierarchy, with processing within lateral areas preceding the processing within ventral areas. Here, we tested the alternative hypothesis that this structure better reflects distinct high-level representations of the upper (ventral surface) and lower (lateral surface) contralateral quadrants of the visual field, consistent with anatomical projections from early visual areas to these surfaces in monkey. Using complex natural scenes, we provide converging evidence from three independent functional imaging and behavioral studies. First, population receptive field mapping revealed strong biases for the contralateral upper and lower quadrant within the ventral and lateral scene-selective regions, respectively. Second, these same biases were observed in the position information available both in the magnitude and multivoxel response across these areas. Third, behavioral judgments of a scene property strongly represented within the ventral scene-selective area (open/closed), but not another equally salient property (manmade/natural), were more accurate in the upper than the lower field. Such differential representation of visual space poses a substantial challenge to the idea of a strictly hierarchical organization between lateral and ventral scene-selective regions. Moreover, such retinotopic biases seem to extend beyond these regions throughout both surfaces. Thus, the large-scale organization of high-level extrastriate cortex likely reflects the need for both specialized representations of particular categories and constraints from the structure of early vision. SIGNIFICANCE STATEMENT One of the most striking findings in fMRI has been the presence of matched category-selective regions on the lateral and ventral surfaces of human occipitotemporal cortex. Here, we focus on scene-selective regions and provide converging evidence for a retinotopic explanation of this organization. Specifically, we demonstrate that scene-selective regions exhibit strong biases for different portions of the visual field, with the lateral region representing the contralateral lower visual field and the ventral region the contralateral upper visual field. These biases are consistent with the retinotopy found in the early visual areas that lie directly antecedent to category-selective areas on both surfaces. Furthermore, these biases extend beyond scene-selective cortex and provide a retinotopic basis for the large-scale organization of occipitotemporal cortex.

Contributions of low- and high-level properties to neural processing of visual scenes in the human brain

Visual scene analysis in humans has been characterized by the presence of regions in extrastriate cortex that are selectively responsive to scenes compared with objects or faces. While these regions have often been interpreted as representing high-level properties of scenes (e.g. category), they also exhibit substantial sensitivity to low-level (e.g. spatial frequency) and mid-level (e.g. spatial layout) properties, and it is unclear how these disparate findings can be united in a single framework. In this opinion piece, we suggest that this problem can be resolved by questioning the utility of the classical low- to high-level framework of visual perception for scene processing, and discuss why low- and mid-level properties may be particularly diagnostic for the behavioural goals specific to scene perception as compared to object recognition. In particular, we highlight the contributions of low-level vision to scene representation by reviewing (i) retinotopic biases and receptive field properties of scene-selective regions and (ii) the temporal dynamics of scene perception that demonstrate overlap of low- and mid-level feature representations with those of scene category. We discuss the relevance of these findings for scene perception and suggest a more expansive framework for visual scene analysis. This article is part of the themed issue ‘Auditory and visual scene analysis’.

Evaluating the correspondence between face-, scene-, and object-selectivity and retinotopic organization within lateral occipitotemporal cortex.

The organization of human lateral occipitotemporal cortex (lOTC) has been characterized largely according to two distinct principles: retinotopy and category-selectivity. Whereas category-selective regions were originally thought to exist beyond retinotopic maps, recent evidence highlights overlap. Here, we combined detailed mapping of retinotopy, using population receptive fields (pRF), and category-selectivity to examine and contrast the retinotopic profiles of scene- (occipital place area, OPA), face- (occipital face area, OFA) and object- (lateral occipital cortex, LO) selective regions of lOTC. We observe striking differences in the relationship each region has to underlying retinotopy. Whereas OPA overlapped multiple retinotopic maps (including V3A, V3B, LO1, and LO2), and LO overlapped two maps (LO1 and LO2), OFA overlapped almost none. There appears no simple consistent relationship between category-selectivity and retinotopic maps, meaning category-selective regions are not constrained spatially to retinotopic map borders consistently. The multiple maps that overlap OPA suggests it is likely not appropriate to conceptualize it as a single scene-selective region, whereas the inconsistency in any systematic map overlapping OFA suggests it may constitute a more uniform area. Beyond their relationship to retinotopy, all three regions evidenced strongly retinotopic voxels, with pRFs exhibiting a significant bias towards the contralateral lower visual field, despite differences in pRF size, contributing to an emerging literature suggesting this bias is present across much of lOTC. Taken together, these results suggest that whereas category-selective regions are not constrained to consistently contain ordered retinotopic maps, they nonetheless likely inherit retinotopic characteristics of the maps from which they draw information.

Scene-Selectivity and Retinotopy in Medial Parietal Cortex

Functional imaging studies in human reliably identify a trio of scene-selective regions, one on each of the lateral [occipital place area (OPA)], ventral [parahippocampal place area (PPA)], and medial [retrosplenial complex (RSC)] cortical surfaces. Recently, we demonstrated differential retinotopic biases for the contralateral lower and upper visual fields within OPA and PPA, respectively. Here, using functional magnetic resonance imaging, we combine detailed mapping of both population receptive fields (pRF) and category-selectivity, with independently acquired resting-state functional connectivity analyses, to examine scene and retinotopic processing within medial parietal cortex. We identified a medial scene-selective region, which was contained largely within the posterior and ventral bank of the parieto-occipital sulcus (POS). While this region is typically referred to as RSC, the spatial extent of our scene-selective region typically did not extend into retrosplenial cortex, and thus we adopt the term medial place area (MPA) to refer to this visually defined scene-selective region. Intriguingly MPA co-localized with a region identified solely on the basis of retinotopic sensitivity using pRF analyses. We found that MPA demonstrates a significant contralateral visual field bias, coupled with large pRF sizes. Unlike OPA and PPA, MPA did not show a consistent bias to a single visual quadrant. MPA also co-localized with a region identified by strong differential functional connectivity with PPA and the human face-selective fusiform face area (FFA), commensurate with its functional selectivity. Functional connectivity with OPA was much weaker than with PPA, and similar to that with face-selective occipital face area (OFA), suggesting a closer link with ventral than lateral cortex. Consistent with prior research, we also observed differential functional connectivity in medial parietal cortex for anterior over posterior PPA, as well as a region on the lateral surface, the caudal inferior parietal lobule (cIPL). However, the differential connectivity in medial parietal cortex was found principally anterior of MPA. We suggest that there is posterior–anterior gradient within medial parietal cortex, with posterior regions in the POS showing retinotopically based scene-selectivity and more anterior regions showing connectivity that may be more reflective of abstract, navigationally pertinent and possibly mnemonic representations.

Bayesian population receptive field modelling

ABSTRACT 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. HIGHLIGHTSWe introduce a Bayesian toolbox for population receptive field (pRF) mapping.Neuronal and haemodynamic parameters are estimated per voxel or per region.Hypotheses can be tested by comparing pRF models based on their evidence.The uncertainty over parameters (such as pRF size) is estimated and visualised.We establish face validity using simulations and test‐rest reliability with 7 T fMRI.

The impact of reward and punishment on skill learning depends on task demands.

Reward and punishment motivate behavior, but it is unclear exactly how they impact skill performance and whether the effect varies across skills. The present study investigated the effect of reward and punishment in both a sequencing skill and a motor skill context. Participants trained on either a sequencing skill (serial reaction time task) or a motor skill (force-tracking task). Skill knowledge was tested immediately after training, and again 1 hour, 24–48 hours, and 30 days after training. We found a dissociation of the effects of reward and punishment on the tasks, primarily reflecting the impact of punishment. While punishment improved serial reaction time task performance, it impaired force-tracking task performance. In contrast to prior literature, neither reward nor punishment benefitted memory retention, arguing against the common assumption that reward ubiquitously benefits skill retention. Collectively, these results suggest that punishment impacts skilled behavior more than reward in a complex, task dependent fashion.

Understanding the topography of face and body selectivity in human ventral temporal cortex.

Faces and body-parts are amongst the most salient visual stimuli in our environment. Research from human and non-human primates has reported multiple clusters of selectivity for faces and body-parts in the ventral visual pathway. Body-selective regions are often found close to face-selective regions, suggesting some sort of organizational principle. However, the nature of this organizational principle is not well established. Here, we investigated the topographical organization and specificity of body- and face-selective regions in visual temporal cortex at high resolution (1.2 mm isotropic voxels) using a 7T MRI scanner. First, we identified regions selective for faces and body-parts. Given prior reports of a body-part topography in lateral occipital cortex, we separately tested both hands and feet, which might be expected to have the most distinct representations. Second, we mapped population receptive fields in each participant to determine the extent to which the location of face- and body-selectivity reflect underlying retinotopic biases. Third, we tested the representational structure in face- and body-selective regions in a condition-rich event-related experiment. As expected, we found that faces elicited strong responses along the mid fusiform sulcus, in a region that has often been referred to as the Fusiform Face Area. This face selectivity coincided with a foveal representation of the visual field, while hands and feet produced robust responses adjacent and lateral to the face selectivity. We found little evidence for alternating patches of face and limb selectivity. Instead, we observed parallel streams of limb and face selectivity, extending from lateral to medial areas of the ventral cortex. Further, analysis of the representational structure of limb and face selective regions revealed striking differences. Our findings highlight the fine-grained organizational structure in ventral temporal and the importance of underlying retinotopic biases. Meeting abstract presented at VSS 2015.

Differential impact of reward and punishment on functional connectivity after skill learning

Reward and punishment shape behavior, but the mechanisms underlying their effect on skill learning are not well understood. Here, we tested whether the functional connectivity of premotor cortex (PMC), a region known to be critical for learning of sequencing skills, after training is altered by reward or punishment given during training. Resting-state fMRI was collected before and after 72 participants trained on either a serial reaction time or force-tracking task with reward, punishment, or control feedback. In each task, training-related change in PMC functional connectivity was compared across feedback groups. Reward and punishment differentially affected PMC functional connectivity in a task-specific manner. For the SRTT, training with reward increased PMC connectivity with cerebellum and striatum, while training with punishment increased PMC-medial temporal lobe connectivity. For the FTT, training with control and reward increased PMC connectivity with parietal and temporal cortices after training, while training with punishment increased PMC connectivity with ventral striatum. These findings suggest that reward and punishment influence spontaneous brain activity after training, and that the regions implicated depend on the task learned.Reward and punishment shape behavior, but the neural mechanisms underlying their effect on skill learning are not well understood. The premotor cortex (PMC) is known to play a central role in sequence learning and has a diverse set of structural and connections with cortical (e.g. medial temporal/parietal lobes) and subcortical (caudate/cerebellum) memory systems that might be modulated by valenced feedback. Here, we tested whether the functional connectivity of PMC immediately after training with reward or punishment predicted memory retention across two different tasks. Resting-state fMRI was collected before and after 72 participants trained on either a serial reaction time or force-tracking task with reward, punishment, or control feedback. Training-related change in PMC functional connectivity was compared across feedback groups. Reward and punishment differentially affected PMC functional connectivity: PMC-cerebellum connectivity increased following training with reward, while PMC-medial temporal lobe connectivity increased after training with punishment. Moreover, feedback impacted the relationship between PMC-caudate connectivity and 24-48hour skill memory. These results were consistent across the tasks, suggestive of a general, non-task-specific mechanism by which feedback modulates skill learning. These findings illustrate dissociable roles for the medial temporal lobe and cerebellum in skill memory retention and suggest novel ways to optimize behavioral training.

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.

Comparing Clinical Perimetry and Population Receptive Field Measures in Patients with Choroideremia

Purpose Choroideremia (CHM) is an X-linked recessive form of hereditary retinal degeneration, which, at advanced stages, leaves only small central islands of preserved retinal tissue. Unlike many other retinal diseases, the spared tissue in CHM supports excellent central vision and stable fixation. Such spared topography in CHM presents an ideal platform to explore the relationship between preserved central retinal structure and the retinotopic organization of visual cortex by using functional magnetic resonance imaging (fMRI). Methods fMRI was conducted in four participants with CHM and four healthy control participants while they viewed drifting contrast pattern stimuli monocularly. A single ∼3-minute fMRI run was collected for each eye separately. fMRI data were analyzed using the population receptive field (pRF) modeling approach. Participants also underwent ophthalmic evaluations of visual acuity and static automatic perimetry. Results The spatial distribution and strength of pRF estimates correlated positively and significantly with clinical outcome measures in most participants with CHM. Importantly, the positive relationship between clinical and pRF measurements increased with increasing disease progression. A less consistent relationship was observed for control participants. Conclusions Although reflecting only a small sample size, clinical evaluations of visual function in participants with CHM were well characterized by the spatial distribution and strength of pRF estimates by using a single ∼3-minute fMRI experiment. fMRI data analyzed with pRF modeling may be an efficient and objective outcome measure to complement current ophthalmic evaluations. Specifically, pRF modeling may be a feasible approach for evaluating the impact of interventions to restore visual function.