Connective field modeling

Cortical field maps across human sensory cortex

Cortical processing pathways for sensory information in the mammalian brain tend to be organized into topographical representations that encode various fundamental sensory dimensions. Numerous laboratories have now shown how these representations are organized into numerous cortical field maps (CMFs) across visual and auditory cortex, with each CFM supporting a specialized computation or set of computations that underlie the associated perceptual behaviors. An individual CFM is defined by two orthogonal topographical gradients that reflect two essential aspects of feature space for that sense. Multiple adjacent CFMs are then organized across visual and auditory cortex into macrostructural patterns termed cloverleaf clusters. CFMs within cloverleaf clusters are thought to share properties such as receptive field distribution, cortical magnification, and processing specialization. Recent measurements point to the likely existence of CFMs in the other senses, as well, with topographical representations of at least one sensory dimension demonstrated in somatosensory, gustatory, and possibly olfactory cortical pathways. Here we discuss the evidence for CFM and cloverleaf cluster organization across human sensory cortex as well as approaches used to identify such organizational patterns. Knowledge of how these topographical representations are organized across cortex provides us with insight into how our conscious perceptions are created from our basic sensory inputs. In addition, studying how these representations change during development, trauma, and disease serves as an important tool for developing improvements in clinical therapies and rehabilitation for sensory deficits.

Retinotopic connectivity maps of human visual cortex with unconstrained eye movements

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

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

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

Extensive topographic remapping and functional sharpening in the adult rat visual pathway upon first visual experience

Understanding the dynamics of stability/plasticity balances during adulthood is pivotal for learning, disease, and recovery from injury. However, the brain-wide topography of sensory remapping remains unknown. Here, using a first-of-its-kind setup for delivering patterned visual stimuli in a rodent magnetic resonance imaging (MRI) scanner, coupled with biologically inspired computational models, we noninvasively mapped brain-wide properties-receptive fields (RFs) and spatial frequency (SF) tuning curves-that were insofar only available from invasive electrophysiology or optical imaging. We then tracked the RF dynamics in the chronic visual deprivation model (VDM) of plasticity and found that light exposure progressively promoted a large-scale topographic remapping in adult rats. Upon light exposure, the initially unspecialized visual pathway progressively evidenced sharpened RFs (smaller and more spatially selective) and enhanced SF tuning curves. Our findings reveal that visual experience following VDM reshapes both structure and function of the visual system and shifts the stability/plasticity balance in adults.

Representational Geometries Reveal Differential Effects of Response Correlations on Population Codes in Neurophysiology and Functional Magnetic Resonance Imaging

Two sensory neurons usually display trial-by-trial spike-count correlations given the repeated representations of a stimulus. The effects of such response correlations on population-level sensory coding have been the focal contention in computational neuroscience over the past few years. In the meantime, multivariate pattern analysis (MVPA) has become the leading analysis approach in functional magnetic resonance imaging (fMRI), but the effects of response correlations among voxel populations remain underexplored. Here, instead of conventional MVPA analysis, we calculate linear Fisher information of population responses in human visual cortex (five males, one female) and hypothetically remove response correlations between voxels. We found that voxelwise response correlations generally enhance stimulus information, a result standing in stark contrast to the detrimental effects of response correlations reported in empirical neurophysiological studies. By voxel-encoding modeling, we further show that these two seemingly opposite effects actually can coexist within the primate visual system. Furthermore, we use principal component analysis to decompose stimulus information in population responses onto different principal dimensions in a high-dimensional representational space. Interestingly, response correlations simultaneously reduce and enhance information on higher- and lower-variance principal dimensions, respectively. The relative strength of the two antagonistic effects within the same computational framework produces the apparent discrepancy in the effects of response correlations in neuronal and voxel populations. Our results suggest that multivariate fMRI data contain rich statistical structures that are directly related to sensory information representation, and the general computational framework to analyze neuronal and voxel population responses can be applied in many types of neural measurements.SIGNIFICANCE STATEMENT Despite the vast research interest in the effect of spike-count noise correlations on population codes in neurophysiology, it remains unclear how the response correlations between voxels influence MVPA in human imaging. We used an information-theoretic approach and showed that unlike the detrimental effects of response correlations reported in neurophysiology, voxelwise response correlations generally improve sensory coding. We conducted a series of in-depth analyses and demonstrated that neuronal and voxel response correlations can coexist within the visual system and share some common computational mechanisms. These results shed new light on how the population codes of sensory information can be evaluated via different neural measurements.

What multiplexing means for the interpretation of functional MRI data

Despite technology advances that have enabled routine acquisition of functional MRI data with sub-millimeter resolution, the inferences that cognitive neuroscientists must make to link fMRI data to behavior are complicated. Thus, a single dataset subjected to different analyses can be interpreted in different ways. This article presents two optical analogies that can be useful for framing fMRI analyses in a way that allows for multiple interpretations of fMRI data to be valid simultaneously without undermining each other. The first is reflection: when an object is reflected in a mirrored surface, it appears as if the reflected object is sharing space with the mirrored object, but of course it is not. This analogy can be a good guide for interpreting the fMRI signal, since even at sub-millimeter resolutions the signal is determined by a mixture of local and long-range neural computations. The second is refraction. If we view an object through a multi-faceted prism or gemstone, our view will change-sometimes dramatically-depending on our viewing angle. In the same way, interpretation of fMRI data (inference of underlying neuronal activity) can and should be different depending on the analysis approach. Rather than representing a weakness of the methodology, or the superiority of one approach over the other (for example, simple regression analysis versus multi-voxel pattern analysis), this is an expected consequence of how information is multiplexed in the neural networks of the brain: multiple streams of information are simultaneously present in each location. The fact that any one analysis typically shows only one view of the data also puts some parentheses around fMRI practitioners' constant search for ground truth against which to compare their data. By holding our interpretations lightly and understanding that many interpretations of the data can all be true at the same time, we do a better job of preparing ourselves to appreciate, and eventually understand, the complexity of the brain and the behavior it produces.

Local neuroplasticity in adult glaucomatous visual cortex

The degree to which the adult human visual cortex retains the ability to functionally adapt to damage at the level of the eye remains ill-understood. Previous studies on cortical neuroplasticity primarily focused on the consequences of foveal visual field defects (VFD), yet these findings may not generalize to peripheral defects such as occur in glaucoma. Moreover, recent findings on neuroplasticity are often based on population receptive field (pRF) mapping, but interpreting these results is complicated in the absence of appropriate control conditions. Here, we used fMRI-based neural modeling to assess putative changes in pRFs associated with glaucomatous VFD. We compared the fMRI-signals and pRF in glaucoma participants to those of controls with case-matched simulated VFD. We found that the amplitude of the fMRI-signal is reduced in glaucoma compared to control participants and correlated with disease severity. Furthermore, while coarse retinotopic structure is maintained in all participants with glaucoma, we observed local pRF shifts and enlargements in early visual areas, relative to control participants. These differences suggest that the adult brain retains some degree of local neuroplasticity. This finding has translational relevance, as it is consistent with VFD masking, which prevents glaucoma patients from noticing their VFD and seeking timely treatment.

Bayesian connective field modeling using a Markov Chain Monte Carlo approach

The majority of neurons in the human brain process signals from neurons elsewhere in the brain. Connective Field (CF) modelling is a biologically-grounded method to describe this essential aspect of the brain's circuitry. It allows characterizing the response of a population of neurons in terms of the activity in another part of the brain. CF modelling translates the concept of the receptive field (RF) into the domain of connectivity by assessing, at the voxel level, the spatial dependency between signals in distinct cortical visual field areas. Thus, the approach enables to characterize the functional cortical circuitry of the human cortex. While already very useful, the present CF modelling approach has some intrinsic limitations due to the fact that it only estimates the model's explained variance and not the probability distribution associated with the estimated parameters. If we could resolve this, CF modelling would lend itself much better for statistical comparisons at the level of single voxels and individuals. This is important when trying to gain a detailed understanding of the neurobiology and pathophysiology of the visual cortex, notably in rare cases. To enable this, we present a Bayesian approach to CF modeling (bCF). Using a Markov Chain Monte Carlo (MCMC) procedure, it estimates the posterior probability distribution underlying the CF parameters. Based on this, bCF quantifies, at the voxel level, the uncertainty associated with each parameter estimate. This information can be used in various ways to increase confidence in the CF model predictions. We applied bCF to BOLD responses recorded in the early human visual cortex using 3T fMRI. We estimated both the CF parameters and their associated uncertainties and show they are only weakly correlated. Moreover, we show how bCF facilitates the use of effect size (beta) as a data-driven parameter that can be used to select the most reliable voxels for further analysis. Finally, to further illustrate the functionality gained by bCF, we apply it to perform a voxel-level comparison of a single, circular symmetric, Gaussian versus a Difference-of-Gaussian model. We conclude that our bCF framework provides a comprehensive tool to study human functional cortical circuitry in health and disease.

An evaluation of how connectopic mapping reveals visual field maps in V1

Abstract

Functional gradients, in which response properties change gradually across the cortical surface, have been proposed as a key organising principle of the brain. However, the presence of these gradients remains undetermined in many brain regions. Resting-state neuroimaging studies have suggested these gradients can be reconstructed from patterns of functional connectivity. Here we investigate the accuracy of these reconstructions and establish whether it is connectivity or the functional properties within a region that determine these “connectopic maps”. Different manifold learning techniques were used to recover visual field maps while participants were at rest or engaged in natural viewing. We benchmarked these reconstructions against maps measured by traditional visual field mapping. We report an initial exploratory experiment of a publicly available naturalistic imaging dataset, followed by a preregistered replication using larger resting-state and naturalistic imaging datasets from the Human Connectome Project. Connectopic mapping accurately predicted visual field maps in primary visual cortex, with better predictions for eccentricity than polar angle maps. Non-linear manifold learning methods outperformed simpler linear embeddings. We also found more accurate predictions during natural viewing compared to resting-state. Varying the source of the connectivity estimates had minimal impact on the connectopic maps, suggesting the key factor is the functional topography within a brain region. The application of these standardised methods for connectopic mapping will allow the discovery of functional gradients across the brain.

Protocol registration

The stage 1 protocol for this Registered Report was accepted in principle on 19 April 2022. The protocol, as accepted by the journal, can be found at 10.6084/m9.figshare.19771717.

Visuospatial coding as ubiquitous scaffolding for human cognition

For more than 100 years we have known that the visual field is mapped onto the surface of visual cortex, imposing an inherently spatial reference frame on visual information processing. Recent studies highlight visuospatial coding not only throughout visual cortex, but also brain areas not typically considered visual. Such widespread access to visuospatial coding raises important questions about its role in wider cognitive functioning. Here, we synthesise these recent developments and propose that visuospatial coding scaffolds human cognition by providing a reference frame through which neural computations interface with environmental statistics and task demands via perception-action loops.

Predictive masking of an artificial scotoma is associated with a system-wide reconfiguration of neural populations in the human visual cortex

The visual brain has the remarkable capacity to complete our percept of the world even when the information extracted from the visual scene is incomplete. This ability to predict missing information based on information from spatially adjacent regions is an intriguing attribute of healthy vision. Yet, it gains particular significance when it masks the perceptual consequences of a retinal lesion, leaving patients unaware of their partial loss of vision and ultimately delaying diagnosis and treatment. At present, our understanding of the neural basis of this masking process is limited which hinders both quantitative modeling as well as translational application. To overcome this, we asked the participants to view visual stimuli with and without superimposed artificial scotoma (AS). We used fMRI to record the associated cortical activity and applied model-based analyzes to track changes in cortical population receptive fields and connectivity in response to the introduction of the AS. We found that throughout the visual field and cortical hierarchy, pRFs shifted their preferred position towards the AS border. Moreover, extrastriate areas biased their sampling of V1 towards sections outside the AS projection zone, thereby effectively masking the AS with signals from spared portions of the visual field. We speculate that the signals that drive these system-wide population modifications originate in extrastriate visual areas and, through feedback, also reconfigure the neural populations in the earlier visual areas.

Population receptive fields in non-human 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.

Functional harmonics reveal multi-dimensional basis functions underlying cortical organization

The human brain consists of specialized areas that flexibly interact to form a multitude of functional networks. Complementary to this notion of modular organization, brain function has been shown to vary along a smooth continuum across the whole cortex. We demonstrate a mathematical framework that accounts for both of these perspectives: harmonic modes. We calculate the harmonic modes of the brain's functional connectivity graph, called "functional harmonics," revealing a multi-dimensional, frequency-ordered set of basis functions. Functional harmonics link characteristics of cortical organization across several spatial scales, capturing aspects of intra-areal organizational features (retinotopy, somatotopy), delineating brain areas, and explaining macroscopic functional networks as well as global cortical gradients. Furthermore, we show how the activity patterns elicited by seven different tasks are reconstructed from a very small subset of functional harmonics. Our results suggest that the principle of harmonicity, ubiquitous in nature, also underlies functional cortical organization in the human brain.

Simultaneous changes in visual acuity, cortical population receptive field size, visual field map size, and retinal thickness in healthy human aging

Healthy human aging is associated with a deterioration of visual acuity, retinal thinning, visual field map shrinkage and increasing population receptive field sizes. Here we ask how these changes are related to each other in a cross-sectional sample of fifty healthy adults aged 20-80 years. We hypothesized that age-related loss of macular retinal ganglion cells may lead to decreased visual field map sizes, and both may lead to increased pRF sizes in the cortical central visual field representation. We measured our participants' perceptual corrected visual acuity using standard ophthalmological letter charts. We then measured their early visual field map (V1, V2 and V3) functional population receptive field (pRF) sizes and structural surface areas using fMRI, and their retinal structure using high-definition optical coherence tomography. With increasing age visual acuity decreased, pRF sizes increased, visual field maps surface areas (but not whole-brain surface areas) decreased, and retinal thickness decreased. Among these measures, only functional pRF sizes predicted perceptual visual acuity, and Bayesian statistics support a null relationship between visual acuity and cortical or retinal structure. However, pRF sizes were in turn predicted by cortical structure only (visual field map surface areas), which were only predicted by retinal structure (thickness). These results suggest that simultaneous disruptions of neural structure and function throughout the early visual system may underlie the deterioration of perceptual visual acuity in healthy aging.

Voxel-to-voxel predictive models reveal unexpected structure in unexplained variance

Encoding models based on deep convolutional neural networks (DCNN) predict BOLD responses to natural scenes in the human visual system more accurately than many other currently available models. However, DCNN-based encoding models fail to predict a significant amount of variance in the activity of most voxels in all visual areas. This failure could reflect limitations in the data (e.g., a noise ceiling), or could reflect limitations of the DCNN as a model of computation in the brain. Understanding the source and structure of the unexplained variance could therefore provide helpful clues for improving models of brain computation. Here, we characterize the structure of the variance that DCNN-based encoding models cannot explain. Using a publicly available dataset of BOLD responses to natural scenes, we determined if the source of unexplained variance was shared across voxels, individual brains, retinotopic locations, and hierarchically distant visual brain areas. We answered these questions using voxel-to-voxel (vox2vox) models that predict activity in a target voxel given activity in a population of source voxels. We found that simple linear vox2vox models increased within-subject prediction accuracy over DCNN-based models for any pair of source/target visual areas, clearly demonstrating that the source of unexplained variance is widely shared within and across visual brain areas. However, vox2vox models were not more accurate than DCNN-based encoding models when source and target voxels came from different brains, demonstrating that the source of unexplained variance was not shared across brains. Importantly, control analyses demonstrated that the source of unexplained variance was not encoded in the mean activity of source voxels, or the activity of voxels in white matter. Interestingly, the weights of vox2vox models revealed preferential connection of target voxel activity to source voxels with adjacent receptive fields, even when source and target voxels were in different functional brain areas. Finally, we found that the prediction accuracy of the vox2vox models decayed with hierarchical distance between the source and target voxels but showed detailed patterns of dependence on hierarchical relationships that we did not observe in DCNNs. Given these results, we argue that the structured variance unexplained by DCNN-based encoding models is unlikely to be entirely caused by non-neural artifacts (e.g., spatially correlated measurement noise) or a failure of DCNNs to approximate the features encoded in brain activity; rather, our results point to a need for brain models that provide both mechanistic and computational explanations for structured ongoing activity in the brain. Keywords: fMRI, encoding models, deep neural networks, functional connectivity.

Assessing Uncertainty and Reliability of Connective Field Estimations From Resting State fMRI Activity at 3T

Connective Field (CF) modeling estimates the local spatial integration between signals in distinct cortical visual field areas. As we have shown previously using 7T data, CF can reveal the visuotopic organization of visual cortical areas even when applied to BOLD activity recorded in the absence of external stimulation. This indicates that CF modeling can be used to evaluate cortical processing in participants in which the visual input may be compromised. Furthermore, by using Bayesian CF modeling it is possible to estimate the co-variability of the parameter estimates and therefore, apply CF modeling to single cases. However, no previous studies evaluated the (Bayesian) CF model using 3T resting-state fMRI data. This is important since 3T scanners are much more abundant and more often used in clinical research compared to 7T scanners. Therefore in this study, we investigate whether it is possible to obtain meaningful CF estimates from 3T resting state (RS) fMRI data. To do so, we applied the standard and Bayesian CF modeling approaches on two RS scans, which were separated by the acquisition of visual field mapping data in 12 healthy participants. Our results show good agreement between RS- and visual field (VF)- based maps using either the standard or Bayesian CF approach. In addition to quantify the uncertainty associated with each estimate in both RS and VF data, we applied our Bayesian CF framework to provide the underlying marginal distribution of the CF parameters. Finally, we show how an additional CF parameter, beta, can be used as a data-driven threshold on the RS data to further improve CF estimates. We conclude that Bayesian CF modeling can characterize local functional connectivity between visual cortical areas from RS data at 3T. Moreover, observations obtained using 3T scanners were qualitatively similar to those reported for 7T. In particular, we expect the ability to assess parameter uncertainty in individual participants will be important for future clinical studies.

Topographic connectivity reveals task-dependent retinotopic processing throughout the human brain

The human visual system is organized as a hierarchy of maps that share the topography of the retina. Known retinotopic maps have been identified using simple visual stimuli under strict fixation, conditions different from everyday vision which is active, dynamic, and complex. This means that it remains unknown how much of the brain is truly visually organized. Here I demonstrate widespread stable visual organization beyond the traditional visual system, in default-mode network and hippocampus. Detailed topographic connectivity with primary visual cortex during movie-watching, resting-state, and retinotopic-mapping experiments revealed that visual-spatial representations throughout the brain are warped by cognitive state. Specifically, traditionally visual regions alternate with default-mode network and hippocampus in preferentially representing the center of the visual field. This visual role of default-mode network and hippocampus would allow these regions to interface between abstract memories and concrete sensory impressions. Together, these results indicate that visual-spatial organization is a fundamental coding principle that structures the communication between distant brain regions.

Convergence Along the Visual Hierarchy Is Altered in Posterior Cortical Atrophy

Purpose

Posterior cortical atrophy (PCA) is a rare neurodegenerative syndrome manifesting with visuospatial processing impairment. We recently suggested that abnormal population receptive field properties are associated with the symptoms of PCA patients. Specifically, simultanagnosia, the inability to perceive multiple items simultaneously, can be explained by smaller peripheral population receptive fields, and foveal crowding, in which nearby distractors interfere with object perception, may result from larger foveal population receptive fields. These effects occurred predominantly in V1, even though atrophy mainly involves high-order areas. In this study, we used connective field modeling to better understand these inter-area interactions.

Methods

We used functional magnetic resonance imaging to scan six PCA patients and eight controls while they viewed drifting bar stimuli. Resting-state data were also collected. Connective field modeling was applied for both conditions: once when the source was V1 and the targets were extrastriate areas and once for the opposite direction. The difference between the two was defined as convergence magnitude.

Results

With stimulus, the convergence magnitude of the controls increased along the visual pathway, suggesting that spatial integration from V1 becomes larger up the visual hierarchy. No such slope was found in the PCA patients. The difference between the groups originated mainly from the dorsal pathway. Without stimulus, the convergence magnitude was negative, slightly more so for the PCA patients, with no slope, suggesting constant divergence along the visual hierarchy.

Conclusions

Atrophy in one part of the visual system can affect other areas within the network through complex intervisual area interactions, resulting in modulation of population receptive field properties and an ensemble of visuocognitive function impairments.

Triple visual hemifield maps in a case of optic chiasm hypoplasia

In humans, each hemisphere comprises an overlay of two visuotopic maps of the contralateral visual field, one from each eye. Is the capacity of the visual cortex limited to these two maps or are plastic mechanisms available to host more maps? We determined the cortical organization of the visual field maps in a rare individual with chiasma hypoplasia, where visual cortex plasticity is challenged to accommodate three hemifield maps. Using high-resolution fMRI at 7T and diffusion-weighted MRI at 3T, we found three hemiretinal inputs, instead of the normal two, to converge onto the left hemisphere. fMRI-based population receptive field mapping of the left V1-V3 at 3T revealed three superimposed hemifield representations in the left visual cortex, i.e. two representations of opposing visual hemifields from the left eye and one right hemifield representation from the right eye. We conclude that developmental plasticity including the re-wiring of local intra- and cortico-cortical connections is pivotal to support the coexistence and functioning of three hemifield maps within one hemisphere.

Topographic Mapping as a Basic Principle of Functional Organization for Visual and Prefrontal Functional Connectivity

The organization of region-to-region functional connectivity has major implications for understanding information transfer and transformation between brain regions. We extended connective field mapping methodology to 3-D anatomic space to derive estimates of corticocortical functional organization. Using multiple publicly available human (both male and female) resting-state fMRI data samples for model testing and replication analysis, we have three main findings. First, we found that the functional connectivity between early visual regions maintained a topographic relationship along the anterior-posterior dimension, which corroborates previous research. Higher order visual regions showed a pattern of connectivity that supports convergence and biased sampling, which has implications for their receptive field properties. Second, we demonstrated that topographic organization is a fundamental aspect of functional connectivity across the entire cortex, with higher topographic connectivity between regions within a functional network than across networks. The principle gradient of topographic connectivity across the cortex resembled whole-brain gradients found in previous work. Last but not least, we showed that the organization of higher order regions such as the lateral prefrontal cortex demonstrate functional gradients of topographic connectivity and convergence. These organizational features of the lateral prefrontal cortex predict task-based activation patterns, particularly visual specialization and higher order rules. In sum, these findings suggest that topographic input is a fundamental motif of functional connectivity between cortical regions for information processing and transfer, with maintenance of topography potentially important for preserving the integrity of information from one region to another.

Discovering the Computational Relevance of Brain Network Organization

Understanding neurocognitive computations will require not just localizing cognitive information distributed throughout the brain but also determining how that information got there. We review recent advances in linking empirical and simulated brain network organization with cognitive information processing. Building on these advances, we offer a new framework for understanding the role of connectivity in cognition: network coding (encoding/decoding) models. These models utilize connectivity to specify the transfer of information via neural activity flow processes, successfully predicting the formation of cognitive representations in empirical neural data. The success of these models supports the possibility that localized neural functions mechanistically emerge (are computed) from distributed activity flow processes that are specified primarily by connectivity patterns.

Studying Cortical Plasticity in Ophthalmic and Neurological Disorders: From Stimulus-Driven to Cortical Circuitry Modeling Approaches

Unsolved questions in computational visual neuroscience research are whether and how neurons and their connecting cortical networks can adapt when normal vision is compromised by a neurodevelopmental disorder or damage to the visual system. This question on neuroplasticity is particularly relevant in the context of rehabilitation therapies that attempt to overcome limitations or damage, through either perceptual training or retinal and cortical implants. Studies on cortical neuroplasticity have generally made the assumption that neuronal population properties and the resulting visual field maps are stable in healthy observers. Consequently, differences in the estimates of these properties between patients and healthy observers have been taken as a straightforward indication for neuroplasticity. However, recent studies imply that the modeled neuronal properties and the cortical visual maps vary substantially within healthy participants, e.g., in response to specific stimuli or under the influence of cognitive factors such as attention. Although notable advances have been made to improve the reliability of stimulus-driven approaches, the reliance on the visual input remains a challenge for the interpretability of the obtained results. Therefore, we argue that there is an important role in the study of cortical neuroplasticity for approaches that assess intracortical signal processing and circuitry models that can link visual cortex anatomy, function, and dynamics.

Micro-probing enables fine-grained mapping of neuronal populations using fMRI

The characterization of receptive field (RF) properties is fundamental to understanding the neural basis of sensory and cognitive behaviour. The combination of non-invasive imaging, such as fMRI, with biologically inspired neural modelling has enabled the estimation of population RFs directly in humans. However, current approaches require making numerous a priori assumptions, so these cannot reveal unpredicted properties, such as fragmented RFs or subpopulations. This is a critical limitation in studies on adaptation, pathology or reorganization. Here, we introduce micro-probing (MP), a technique for fine-grained and largely assumption free characterization of multiple pRFs within a voxel. It overcomes many limitations of current approaches by enabling detection of unexpected RF shapes, properties and subpopulations, by enhancing the spatial detail with which we analyze the data. MP is based on tiny, fixed-size, Gaussian models that efficiently sample the entire visual space and create fine-grained probe maps. Subsequently, we derived population receptive fields (pRFs) from these maps. We demonstrate the scope of our method through simulations and by mapping the visual fields of healthy participants and of a patient group with highly abnormal RFs due to a congenital pathway disorder. Without using specific stimuli or adapted models, MP mapped the bilateral pRFs characteristic of observers with albinism. In healthy observers, MP revealed that voxels may capture the activity of multiple subpopulations RFs that sample distinct regions of the visual field. Thus, MP provides a versatile framework to visualize, analyze and model, without restrictions, the diverse RFs of cortical subpopulations in health and disease.

Stimulus- and Neural-Referred Visual Receptive Field Properties following Hemispherectomy: A Case Study Revisited

Damage to the visual system can result in (a partial) loss of vision, in response to which the visual system may functionally reorganize. Yet the timing, extent, and conditions under which this occurs are not well understood. Hence, studies in individuals with diverse congenital and acquired conditions and using various methods are needed to better understand this. In the present study, we examined the visual system of a young girl who received a hemispherectomy at the age of three and who consequently suffered from hemianopia. We did so by evaluating the corticocortical and retinocortical projections in the visual system of her remaining hemisphere. For the examination of these aspects, we analyzed the characteristics of the connective fields ("neural-referred" receptive fields) based on both resting-state (RS) and retinotopy data. The evaluation of RS data, reflecting brain activity independent from visual stimulation, is of particular interest as it is not biased by the patient's atypical visual percept. We found that, primarily when the patient was at rest, the connective fields between V1 and both early and late visual areas were larger than normal. These abnormally large connective fields could be a sign either of functional reorganization or of unmasked suppressive feedback signals that are normally masked by interhemispheric signals. Furthermore, we confirmed our previous finding of abnormal retinocortical or "stimulus-referred" projections in both early and late visual areas. More specifically, we found an enlarged foveal representation and smaller population receptive fields. These differences could also be a sign of functional reorganization or rather a reflection of the interruption visual information that travels, via the remainder of the visual pathway, from the retina to the visual cortex. To conclude, while we do find indications for relatively subtle changes in visual field map properties, we found no evidence of large-scale reorganization-even though the patient could have benefitted from this. Our work suggests that at a later developmental stage, large-scale reorganization of the visual system no longer occurs, while small-scale properties may still change to facilitate adaptive processing and viewing strategies.

Population receptive field and connectivity properties of the early visual cortex in human albinism

In albinism, the pathological decussation of the temporal retinal afferents at the optic chiasm leads to superimposed representations of opposing hemifields in the visual cortex. Here, we assessed the equivalence of the two representations and the cortico-cortical connectivity of the early visual areas. Applying fMRI-based population receptive field (pRF)-mapping (both hemifield and bilateral mapping) and connective field (CF)-modeling, we investigated the early visual cortex in 6 albinotic participants and 4 controls. In albinism, superimposed retinotopic representations of the contra- and ipsilateral visual hemifield were observed on the hemisphere contralateral to the stimulated eye. This was confirmed by the observation of bilateral pRFs during bilateral mapping. Hemifield mapping revealed similar pRF-sizes for both hemifield representations throughout V1 to V3. The typical increase of V1-sampling extent for V3 compared to V2 was not found for the albinotic participants. The similarity of the pRF-sizes for opposing visual hemifield representations highlights the equivalence of the two maps in the early visual cortex. The altered V1-sampling extent in V3 might indicate the adaptation of cortico-cortical connections to visual pathway abnormalities in albinism. These findings thus suggest that conservative developmental mechanisms are complemented by alterations of the extrastriate cortico-cortical connectivity.

Population receptive field tuning properties of visual cortex during childhood

Visuospatial abilities such as contrast sensitivity and Vernier acuity improve until late in childhood, but the neural mechanisms supporting these changes are poorly understood. We tested to which extent this development might reflect improved spatial sensitivity of neuronal populations in visual cortex. To do this, we measured BOLD-responses in areas V1-V4 and V3a, whilst 6- to 12-year-old children and adults watched large-field wedge and ring stimuli in the MRI scanner, and then fitted population receptive field (pRF) tuning functions to these data (Dumoulin and Wandell, 2008). Cortical magnification and pRF tuning width changed with eccentricity at all ages, as expected. However, there were no significant age differences in pRF size, shape, cortical magnification, or map consistency in any visual region. These findings thus strongly suggest that spatial vision in late childhood is not substantially limited by the spatial tuning of neuronal populations in early visual cortex. Instead, improvements in performance may reflect more efficient read-out of spatial information in early visual regions by higher-level processing stages, or prolonged tuning to more complex visual properties such as orientation. Importantly, this in-depth characterisation of the pRF tuning profiles across childhood, paves the way for in-vivo-testing of atypical visual cortex development and plasticity.

How Visual Cortical Organization Is Altered by Ophthalmologic and Neurologic Disorders

Receptive fields are a core property of cortical organization. Modern neuroimaging allows routine access to visual population receptive fields (pRFs), enabling investigations of clinical disorders. Yet how the underlying neural circuitry operates is controversial. The controversy surrounds observations that measurements of pRFs can change in healthy adults as well as in patients with a range of ophthalmological and neurological disorders. The debate relates to the balance between plasticity and stability of the underlying neural circuitry. We propose that to move the debate forward, the field needs to define the implied mechanism. First, we review the pRF changes in both healthy subjects and those with clinical disorders. Then, we propose a computational model that describes how pRFs can change in healthy humans. We assert that we can correctly interpret the pRF changes in clinical disorders only if we establish the capabilities and limitations of pRF dynamics in healthy humans with mechanistic models that provide quantitative predictions.

Organization of area hV5/MT+ in subjects with homonymous visual field defects

Damage to the primary visual cortex (V1) leads to a visual field loss (scotoma) in the retinotopically corresponding part of the visual field. Nonetheless, a small amount of residual visual sensitivity persists within the blind field. This residual capacity has been linked to activity observed in the middle temporal area complex (V5/MT+). However, it remains unknown whether the organization of hV5/MT+ changes following early visual cortical lesions. We studied the organization of area hV5/MT+ of five patients with dense homonymous defects in a quadrant of the visual field as a result of partial V1+ or optic radiation lesions. To do so, we developed a new method, which models the boundaries of population receptive fields directly from the BOLD signal of each voxel in the visual cortex. We found responses in hV5/MT+ arising inside the scotoma for all patients and identified two possible sources of activation: 1) responses might originate from partially lesioned parts of area V1 corresponding to the scotoma, and 2) responses can also originate independent of area V1 input suggesting the existence of functional V1-bypassing pathways. Apparently, visually driven activity observed in hV5/MT+ is not sufficient to mediate conscious vision. More surprisingly, visually driven activity in corresponding regions of V1 and early extrastriate areas including hV5/MT+ did not guarantee visual perception in the group of patients with post-geniculate lesions that we examined. This suggests that the fine coordination of visual activity patterns across visual areas may be an important determinant of whether visual perception persists following visual cortical lesions.

Probing Human Visual Deficits with Functional Magnetic Resonance Imaging

Much remains to be understood about visual system malfunction following injury. The resulting deficits range from dense, visual field scotomas to mild dysfunction of visual perception. Despite the predictive value of anatomical localization studies, much patient-to-patient variability remains regarding (a) perceptual abilities following injury and (b) the capacity of individual patients for visual rehabilitation. Visual field perimetry is used to characterize the visual field deficits that result from visual system injury. However, standard perimetry mapping does not always precisely correspond to underlying anatomical or functional deficits. Functional magnetic resonance imaging can be used to probe the function of surviving visual circuits, allowing us to classify better how the pattern of injury relates to residual visual perception. Identifying pathways that are potentially modifiable by training may guide the development of improved strategies for visual rehabilitation. This review discusses primary visual cortex lesions, which cause dense contralateral scotomas.

Cognitive task information is transferred between brain regions via resting-state network topology

Resting-state network connectivity has been associated with a variety of cognitive abilities, yet it remains unclear how these connectivity properties might contribute to the neurocognitive computations underlying these abilities. We developed a new approach—information transfer mapping—to test the hypothesis that resting-state functional network topology describes the computational mappings between brain regions that carry cognitive task information. Here, we report that the transfer of diverse, task-rule information in distributed brain regions can be predicted based on estimated activity flow through resting-state network connections. Further, we find that these task-rule information transfers are coordinated by global hub regions within cognitive control networks. Activity flow over resting-state connections thus provides a large-scale network mechanism for cognitive task information transfer and global information coordination in the human brain, demonstrating the cognitive relevance of resting-state network topology.

Resting-state functional connections have been associated with cognitive abilities but it is unclear how these connections contribute to cognition. Here Ito et al present a new approach, information transfer mapping, showing that task-relevant information can be predicted by estimated activity flow through resting-state networks.

Phase-synchronization-based parcellation of resting state fMRI signals reveals topographically organized clusters in early visual cortex

Resting-state fMRI is widely used to study brain function and connectivity. However, interpreting patterns of resting state (RS) fMRI activity remains challenging as they may arise from different neuronal mechanisms than those triggered by exogenous events. Currently, this limits the use of RS-fMRI for understanding cortical function in health and disease. Here, we examine the phase synchronization (PS) properties of blood-oxygen level dependent (BOLD) signals obtained during visual field mapping (VFM) and RS with 7T fMRI. This data-driven approach exploits spatiotemporal covariations in the phase of BOLD recordings to establish the presence of clusters of synchronized activity. We find that, in both VFM and RS data, selecting the most synchronized neighboring recording sites identifies spatially localized PS clusters that follow the topographic organization of the visual cortex. However, in activity obtained during VFM, PS is spatially more extensive than in RS activity, likely reflecting stimulus-driven interactions between local responses. Nevertheless, the similarity of the PS clusters obtained for RS and stimulus-driven fMRI suggest that they share a common neuroanatomical origin. Our finding justifies and facilitates direct comparison of RS and stimulus-evoked activity.

The impact of ultra-high field MRI on cognitive and computational neuroimaging

The ability to measure functional brain responses non-invasively with ultra high field MRI (7 T and above) represents a unique opportunity in advancing our understanding of the human brain. Compared to lower fields (3 T and below), ultra high field MRI has an increased sensitivity, which can be used to acquire functional images with greater spatial resolution, and greater specificity of the blood oxygen level dependent (BOLD) signal to the underlying neuronal responses. Together, increased resolution and specificity enable investigating brain functions at a submillimeter scale, which so far could only be done with invasive techniques. At this mesoscopic spatial scale, perception, cognition and behavior can be probed at the level of fundamental units of neural computations, such as cortical columns, cortical layers, and subcortical nuclei. This represents a unique and distinctive advantage that differentiates ultra high from lower field imaging and that can foster a tighter link between fMRI and computational modeling of neural networks. So far, functional brain mapping at submillimeter scale has focused on the processing of sensory information and on well-known systems for which extensive information is available from invasive recordings in animals. It remains an open challenge to extend this methodology to uniquely human functions and, more generally, to systems for which animal models may be problematic. To succeed, the possibility to acquire high-resolution functional data with large spatial coverage, the availability of computational models of neural processing as well as accurate biophysical modeling of neurovascular coupling at mesoscopic scale all appear necessary.

Objective analysis of the topological organization of the human cortical visual connectome suggests three visual pathways

The cortical visual system is composed of many areas serving various visual functions. In non-human primates, these are broadly organised into two distinct processing pathways: a ventral pathway for object recognition, and a dorsal pathway for action. In humans, recent theoretical proposals suggest the possible existence of additional pathways, but direct empirical evidence has yet to be presented. Here, we estimated the connectivity patterns between 22 human visual areas using resting-state functional MRI data of 470 individuals, leveraging the unprecedented data quantity and quality of the Human Connectome Project and a novel probabilistic atlas. An objective, data-driven analysis into the topological organisation of connectivity and subsequent quantitative confirmation revealed a highly significant triple dissociation between the retinotopic areas on the dorsal, ventral and lateral surfaces of the human occipital lobe. This suggests that the functional organisation of the human visual system involves not two but three cortical pathways.

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.

Partial Correlation-Based Retinotopically Organized Resting-State Functional Connectivity Within and Between Areas of the Visual Cortex Reflects More Than Cortical Distance

Numerous studies have demonstrated functional magnetic resonance imaging (fMRI)-based resting-state functional connectivity (RSFC) between cortical areas. Recent evidence suggests that synchronous fluctuations in blood oxygenation level-dependent fMRI reflect functional organization at a scale finer than that of visual areas. In this study, we investigated whether RSFCs within and between lower visual areas are retinotopically organized and whether retinotopically organized RSFC merely reflects cortical distance. Subjects underwent retinotopic mapping and separately resting-state fMRI. Visual areas V1, V2, and V3, were subdivided into regions of interest (ROIs) according to quadrants and visual field eccentricity. Functional connectivity (FC) was computed based on Pearson's linear correlation (correlation), and Pearson's linear partial correlation (correlation between two time courses after the time courses from all other regions in the network are regressed out). Within a quadrant, within visual areas, all correlation and nearly all partial correlation FC measures showed statistical significance. Consistently in V1, V2, and to a lesser extent in V3, correlation decreased with increasing eccentricity separation. Consistent with previously reported monkey anatomical connectivity, correlation/partial correlation values between regions from adjacent areas (V1-V2 and V2-V3) were higher than those between nonadjacent areas (V1-V3). Within a quadrant, partial correlation showed consistent significance between regions from two different areas with the same or adjacent eccentricities. Pairs of ROIs with similar eccentricity showed higher correlation/partial correlation than pairs distant in eccentricity. Between dorsal and ventral quadrants, partial correlation between common and adjacent eccentricity regions within a visual area showed statistical significance; this extended to more distant eccentricity regions in V1. Within and between quadrants, correlation decreased approximately linearly with increasing distances separating the tested ROIs. Partial correlation showed a more complex dependence on cortical distance: it decreased exponentially with increasing distance within a quadrant, but was best fit by a quadratic function between quadrants. We conclude that RSFCs within and between lower visual areas are retinotopically organized. Correlation-based FC is nonselectively high across lower visual areas, even between regions that do not share direct anatomical connections. The mechanisms likely involve network effects caused by the dense anatomical connectivity within this network and projections from higher visual areas. FC based on partial correlation, which minimizes network effects, follows expectations based on direct anatomical connections in the monkey visual cortex better than correlation. Last, partial correlation-based retinotopically organized RSFC reflects more than cortical distance effects.

Systematic variation of population receptive field properties across cortical depth in human visual cortex

Receptive fields (RFs) in visual cortex are organized in antagonistic, center-surround, configurations. RF properties change systematically across eccentricity and between visual field maps. However, it is unknown how center-surround configurations are organized in human visual cortex across lamina. We use sub-millimeter resolution functional MRI at 7Tesla and population receptive field (pRF) modeling to investigate the pRF properties in primary visual cortex (V1) across cortical depth. pRF size varies according to a U-shaped function, indicating smaller pRF center size in the middle compared to superficial and deeper intra-cortical portions of V1, consistent with non-human primate neurophysiological measurements. Moreover, a similar U-shaped function is also observed for pRF surround size. However, pRF center-surround ratio remains constant across cortical depth. Simulations suggest that this pattern of results can be directly linked to the flow of signals across cortical depth, with the visual input reaching the middle of cortical depth and then spreading towards superficial and deeper layers of V1. Conversely, blood-oxygenation-level-dependent (BOLD) signal amplitude increases monotonically towards the pial surface, in line with the known vascular organization across cortical depth. Independent estimates of the haemodynamic response function (HRF) across cortical depth show that the center-surround pRF size estimates across cortical depth cannot be explained by variations in the full-width half maximum (FWHM) of the HRF.

What insights can fMRI offer into the structure and function of mid-tier visual areas?

Inferring neural responses from functional magnetic resonance imaging (fMRI) data is challenging. Even if we take advantage of high-field systems to acquire data with submillimeter resolution, we are still acquiring data in which a single datum summarizes the responses of tens of thousands of neurons. Excitation and inhibition, spikes and subthreshold membrane potential modulations, local and long-range computations, and tuned and nonselective responses are mixed together in one signal. With a priori knowledge of the underlying neural population responses, careful experiment design allows us to manipulate the experiment or task design so that subpopulations are selectively modulated, and our experiments can reveal those tuning functions. However, because we want to be able to use fMRI to discover new kinds of tuning functions and selectivity, we cannot limit ourselves to experiments in which we already know what we are looking for. Broadly speaking, analyses that rely on classification of responses that are distributed across the local neural population [multi-voxel pattern analyses (MVPA)] offer the ability to discover new kinds of information representation and selectivities in neural subpopulations. There is, however, no way to determine how the information discovered with MVPA or other analyses is related to the underlying neuronal tuning functions. Therefore, we must continue to rely on behavioral, computational, and animal models to develop theories of information representation in mid-tier visual cortical areas. Once encoding models exist, fMRI can be powerful for testing these a priori models of information representation. As an aide in developing these models, an important contribution that fMRI can make to our understanding of mid-tier visual areas is derived from connectivity analyses and experiments that study information sharing between visual areas. This ability to quantify localized population average responses throughout the brain is the strength we can best leverage to discover new properties of local and long-range neural networks.

Preserved retinotopic brain connectivity in macular degeneration

PURPOSE

The eye disease macular degeneration (MD) is a leading cause of blindness worldwide. There is no cure for MD, but several promising treatments aimed at restoring vision at the level of the retina are currently under investigation. These treatments assume that the patient's brain can still process appropriately the retinal input once it is restored, but whether this assumption is correct has yet to be determined.

METHODS

We used functional magnetic resonance imaging (fMRI) and connective field modelling to determine whether the functional connectivity between the input-deprived portions of primary visual cortex (V1) and early extrastriate areas (V2/3) is still retinotopically organised. Specifically, in both patients with juvenile macular degeneration and age-matched controls with simulated retinal lesions, we assessed the extent to which the V1-referred connective fields of extrastriate voxels, as estimated on the basis of spontaneous fMRI signal fluctuations, adhered to retinotopic organisation.

RESULTS

We found that functional connectivity between the input-deprived portions of visual areas V1 and extrastriate cortex is still largely retinotopically organised in MD, although on average less so than in controls. Patients with stable fixation exhibited normal retinotopic connectivity, however, suggesting that for the patients with unstable fixation, eye-movements resulted in spurious, homogeneous signal modulations across the entire input-deprived cortex, which would have hampered our ability to assess their spatial structure of connectivity.

CONCLUSIONS

Despite the prolonged loss of visual input due to MD, the cortico-cortical connections of input-deprived visual cortex remain largely intact. This suggests that the restoration of sight in macular degeneration can rely on a largely unchanged retinotopic representation in early visual cortex following loss of central retinal function.

Is the Cortical Deficit in Amblyopia Due to Reduced Cortical Magnification, Loss of Neural Resolution, or Neural Disorganization?

The neural basis of amblyopia is a matter of debate. The following possibilities have been suggested: loss of foveal cells, reduced cortical magnification, loss of spatial resolution of foveal cells, and topographical disarray in the cellular map. To resolve this we undertook a population receptive field (pRF) functional magnetic resonance imaging analysis in the central field in humans with moderate-to-severe amblyopia. We measured the relationship between averaged pRF size and retinal eccentricity in retinotopic visual areas. Results showed that cortical magnification is normal in the foveal field of strabismic amblyopes. However, the pRF sizes are enlarged for the amblyopic eye. We speculate that the pRF enlargement reflects loss of cellular resolution or an increased cellular positional disarray within the representation of the amblyopic eye.

SIGNIFICANCE STATEMENT

The neural basis of amblyopia, a visual deficit affecting 3% of the human population, remains a matter of debate. We undertook the first population receptive field functional magnetic resonance imaging analysis in participants with amblyopia and compared the projections from the amblyopic and fellow normal eye in the visual cortex. The projection from the amblyopic eye was found to have a normal cortical magnification factor, enlarged population receptive field sizes, and topographic disorganization in all early visual areas. This is consistent with an explanation of amblyopia as an immature system with a normal complement of cells whose spatial resolution is reduced and whose topographical map is disordered. This bears upon a number of competing theories for the psychophysical defect and affects future treatment therapies.

Resting-State Retinotopic Organization in the Absence of Retinal Input and Visual Experience

Early visual areas have neuronal receptive fields that form a sampling mosaic of visual space, resulting in a series of retinotopic maps in which the same region of space is represented in multiple visual areas. It is not clear to what extent the development and maintenance of this retinotopic organization in humans depend on retinal waves and/or visual experience. We examined the corticocortical receptive field organization of resting-state BOLD data in normally sighted, early blind, and anophthalmic (in which both eyes fail to develop) individuals and found that resting-state correlations between V1 and V2/V3 were retinotopically organized for all subject groups. These results show that the gross retinotopic pattern of resting-state connectivity across V1-V3 requires neither retinal waves nor visual experience to develop and persist into adulthood. Significance statement: Evidence from resting-state BOLD data suggests that the connections between early visual areas develop and are maintained even in the absence of retinal waves and visual experience.

Computational neuroimaging and population receptive fields

Functional magnetic resonance imaging (fMRI) noninvasively measures human brain activity at millimeter resolution. Scientists use different approaches to take advantage of the remarkable opportunities presented by fMRI. Here, we describe progress using the computational neuroimaging approach in human visual cortex, which aims to build models that predict the neural responses from the stimulus and task. We focus on a particularly active area of research, the use of population receptive field (pRF) models to characterize human visual cortex responses to a range of stimuli, in a variety of tasks and different subject populations.

Visual attention mitigates information loss in small- and large-scale neural codes

The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires that sensory signals are processed in a manner that protects information about relevant stimuli from degradation. Such selective processing--or selective attention--is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, thereby providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding.

Widespread correlation patterns of fMRI signal across visual cortex reflect eccentricity organization

The human visual system can be divided into over two-dozen distinct areas, each of which contains a topographic map of the visual field. A fundamental question in vision neuroscience is how the visual system integrates information from the environment across different areas. Using neuroimaging, we investigated the spatial pattern of correlated BOLD signal across eight visual areas on data collected during rest conditions and during naturalistic movie viewing. The correlation pattern between areas reflected the underlying receptive field organization with higher correlations between cortical sites containing overlapping representations of visual space. In addition, the correlation pattern reflected the underlying widespread eccentricity organization of visual cortex, in which the highest correlations were observed for cortical sites with iso-eccentricity representations including regions with non-overlapping representations of visual space. This eccentricity-based correlation pattern appears to be part of an intrinsic functional architecture that supports the integration of information across functionally specialized visual areas.

DOI:http://dx.doi.org/10.7554/eLife.03952.001

Imagine you are looking out over a scenic landscape. The image you perceive is actually made up of many different visual components—for example color and movement—that are processed across many different areas in a region of the brain called the visual cortex. An important question for neuroscience is how the visual system combines information from so many different areas to create a coherent picture of the world around us.

Many areas of the visual cortex have their own map of what we see (the visual field). These maps allow the brain to maintain its representation of the visual field as the information passes from one processing area to the next. Areas that process corresponding parts of the visual field are physically interconnected, and tend to be active at the same time, which suggests that they are working together in some way. In addition, areas of the visual cortex that process different sections of the visual field can be activated at the same time, but it is not clear how this works.

Here, Arcaro et al. used a technique called functional magnetic resonance imaging (fMRI) to image the brains of people as they watched movies and while they rested. The images showed that seemingly unrelated areas of the visual cortex respond in similar ways if they are processing sections of the visual field that are the same distance from the center of the person's gaze. For example, if you look directly at the center of a computer screen parts of the brain that process the top of the screen are active at the same time as parts that process the bottom.

Arcaro et al.'s findings suggest that the brain uses the distance from the center of our gaze to bring together information from different areas of the visual cortex. This offers a new insight into how the brain assembles the many pieces of the visual jigsaw to make a complete picture. Future work will investigate how the architecture of the visual cortex is able to support this coupling of different areas, and how it might influence our perception of the visual world.

DOI:http://dx.doi.org/10.7554/eLife.03952.002

Topographic organization of areas V3 and V4 and its relation to supra-areal organization of the primate visual system

Areas V3 and V4 are commonly thought of as individual entities in the primate visual system, based on definition criteria such as their representation of visual space, connectivity, functional response properties, and relative anatomical location in cortex. Yet, large-scale functional and anatomical organization patterns not only emphasize distinctions within each area, but also links across visual cortex. Specifically, the visuotopic organization of V3 and V4 appears to be part of a larger, supra-areal organization, clustering these areas with early visual areas V1 and V2. In addition, connectivity patterns across visual cortex appear to vary within these areas as a function of their supra-areal eccentricity organization. This complicates the traditional view of these regions as individual functional "areas." Here, we will review the criteria for defining areas V3 and V4 and will discuss functional and anatomical studies in humans and monkeys that emphasize the integration of individual visual areas into broad, supra-areal clusters that work in concert for a common computational goal. Specifically, we propose that the visuotopic organization of V3 and V4, which provides the criteria for differentiating these areas, also unifies these areas into the supra-areal organization of early visual cortex. We propose that V3 and V4 play a critical role in this supra-areal organization by filtering information about the visual environment along parallel pathways across higher-order cortex.

Human V4 and ventral occipital retinotopic maps

The ventral surface of the human occipital lobe contains multiple retinotopic maps. The most posterior of these maps is considered a potential homolog of macaque V4, and referred to as human V4 ("hV4"). The location of the hV4 map, its retinotopic organization, its role in visual encoding, and the cortical areas it borders have been the subject of considerable investigation and debate over the last 25 years. We review the history of this map and adjacent maps in ventral occipital cortex, and consider the different hypotheses for how these ventral occipital maps are organized. Advances in neuroimaging, computational modeling, and characterization of the nearby anatomical landmarks and functional brain areas have improved our understanding of where human V4 is and what kind of visual representations it contains.

Cortical connective field estimates from resting state fMRI activity

One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that—despite some variability in CF estimates between RS scans—neural properties such as CF maps and CF size can be derived from resting state data.

Frequency Selectivity of Voxel-by-Voxel Functional Connectivity in Human Auditory Cortex

While functional connectivity in the human cortex has been increasingly studied, its relationship to cortical representation of sensory features has not been documented as much. We used functional magnetic resonance imaging to demonstrate that voxel-by-voxel intrinsic functional connectivity (FC) is selective to frequency preference of voxels in the human auditory cortex. Thus, FC was significantly higher for voxels with similar frequency tuning than for voxels with dissimilar tuning functions. Frequency-selective FC, measured via the correlation of residual hemodynamic activity, was not explained by generic FC that is dependent on spatial distance over the cortex. This pattern remained even when FC was computed using residual activity taken from resting epochs. Further analysis showed that voxels in the core fields in the right hemisphere have a higher frequency selectivity in within-area FC than their counterpart in the left hemisphere, or than in the noncore-fields in the same hemisphere. Frequency-selective FC is consistent with previous findings of topographically organized FC in the human visual and motor cortices. The high degree of frequency selectivity in the right core area is in line with findings and theoretical proposals regarding the asymmetry of human auditory cortex for spectral processing.

Visual cortex in aging and Alzheimer's disease: changes in visual field maps and population receptive fields

Although several studies have suggested that cortical alterations underlie such age-related visual deficits as decreased acuity, little is known about what changes actually occur in visual cortex during healthy aging. Two recent studies showed changes in primary visual cortex (V1) during normal aging; however, no studies have characterized the effects of aging on visual cortex beyond V1, important measurements both for understanding the aging process and for comparison to changes in age-related diseases. Similarly, there is almost no information about changes in visual cortex in Alzheimer's disease (AD), the most common form of dementia. Because visual deficits are often reported as one of the first symptoms of AD, measurements of such changes in the visual cortex of AD patients might improve our understanding of how the visual system is affected by neurodegeneration as well as aid early detection, accurate diagnosis and timely treatment of AD. Here we use fMRI to first compare the visual field map (VFM) organization and population receptive fields (pRFs) between young adults and healthy aging subjects for occipital VFMs V1, V2, V3, and hV4. Healthy aging subjects do not show major VFM organizational deficits, but do have reduced surface area and increased pRF sizes in the foveal representations of V1, V2, and hV4 relative to healthy young control subjects. These measurements are consistent with behavioral deficits seen in healthy aging. We then demonstrate the feasibility and first characterization of these measurements in two patients with mild AD, which reveal potential changes in visual cortex as part of the pathophysiology of AD. Our data aid in our understanding of the changes in the visual processing pathways in normal aging and provide the foundation for future research into earlier and more definitive detection of AD.