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Over the last several decades, the mammalian visual system has been arguably the most widely studied subject in systems neuroscience. Two additional papers published in this special issue involve novel data acquisition and analysis methods, which will likely push forward future understanding of structure-function relationships in the visual system. This method enables diffeomorphic registration of multiple visual areas, and improves the accuracy of the group analysis of fMRI datasets on the human visual system. Research on the mammalian visual system has provided important insights for our understanding of the brain in general, artificial neural networks (Yamins et al. [31]), and intervention strategies for visual disorders (Beauchamp et al. [4]). [Extracted from the article]

Gene expression gradients radiating from regions of primary sensory cortices have recently been described and are thought to underlie the large-scale organization of the human cerebral cortex. However, the role of transcription in the functional layout of a single region within the adult brain has yet to be clarified, likely owing to the difficulty of identifying a brain region anatomically consistent enough across individuals with dense enough tissue sampling. Overcoming these hurdles in human primary visual cortex (V1), we show a relationship between differential gene expression and the cortical layout of eccentricity in human V1. Interestingly, these genes are unique from those previously identified that contribute to the positioning of cortical areas in the visual processing hierarchy. Enrichment analyses show that a subset of the identified genes encode for structures related to inhibitory interneurons, ion channels, as well as cellular projections, and are expressed more in foveal compared to peripheral portions of human V1. These findings predict that tissue density should be higher in foveal compared to peripheral V1. Using a histological pipeline, we validate this prediction using Nissl-stained sections of postmortem occipital cortex. We discuss these findings relative to previous studies in non-human primates, as well as in the context of an organizational pattern in which the adult human brain employs transcription gradients at multiple spatial scales: across the cerebral cortex, across areas within processing hierarchies, and within single cortical areas. [ABSTRACT FROM AUTHOR]

The noninvasive estimation of neuronal receptive field (RF) properties in vivo allows a detailed understanding of brain organization as well as its plasticity by longitudinal following of potential changes. Visual RFs measured invasively by electrophysiology in animal models have traditionally provided a great extent of our current knowledge about the visual brain and its disorders. Voxel-based estimates of population RF (pRF) by functional magnetic resonance imaging (fMRI) in humans revolutionized the field and have been used extensively in numerous studies. However, current methods cannot estimate single-neuron RF sizes as they reflect large populations of neurons with individual RF scatter. Here, we introduce an approach to estimate RF size using spatial frequency selectivity to checkerboard patterns. This method allowed us to obtain noninvasive, average single-neuron RF estimates over a large portion of human early visual cortex. These estimates were significantly smaller compared with prior pRF methods. Furthermore, fMRI and electrophysiology experiments in nonhuman primates demonstrated an exceptionally good match, validating the approach. [ABSTRACT FROM AUTHOR]

Orientation sensitive properties of extrastriate area 21a neurons were investigated. Special attention was paid to the spatial characteristics of the neuron receptive fields (RF) to the different orientations of visual stimulus motion across neuron RF, defined by presentation of stationary visual stimuli. The results of provided experiments have shown that the neuron RF spatial dimensions undergo essential modulations concerning different orientations of applied visual stimuli. As a result, a high degree of diversification of neuronal response patterns depending of the orientation of moving stimuli was observed. Thus, the processing of visual information in the course of visual image recognition is realized by integrated activity of surrounding cortical networks of visually sensitive neurons. [ABSTRACT FROM AUTHOR]

Abstract Cells in the peripheral retina tend to have higher contrast sensitivity and respond at higher flicker frequencies than those closer to the fovea. Although this predicts increased behavioural temporal contrast sensitivity in the peripheral visual field, this effect is rarely observed in psychophysical experiments. It is unknown how temporal contrast sensitivity is represented across eccentricity within cortical visual field maps and whether such sensitivities reflect the response properties of retinal cells or psychophysical sensitivities. Here, we used functional magnetic resonance imaging (fMRI) to measure contrast sensitivity profiles at four temporal frequencies in five retinotopically-defined visual areas. We also measured population receptive field (pRF) parameters (polar angle, eccentricity, and size) in the same areas. Overall contrast sensitivity, independent of pRF parameters, peaked at 10 Hz in all visual areas. In V1, V2, V3, and V3a, peripherally-tuned voxels had higher contrast sensitivity at a high temporal frequency (20 Hz), while hV4 more closely reflected behavioural sensitivity profiles. We conclude that our data reflect a cortical representation of the increased peripheral temporal contrast sensitivity that is already present in the retina and that this bias must be compensated later in the cortical visual pathway. Highlights • Contrast sensitivity to 20Hz flicker is increased in peripheral voxels, when compared to foveal voxels, within V1, V2, V3, and V3a. • In hV4, contrast sensitivity at 20Hz is unchanged across eccentricity, similar to psychophysical sensitivities. • Our data suggest that the temporal response properties of peripheral retinal cells are represented in the cortical periphery of early visual areas. • Temporal filtering may occur in higher-order ventral visual areas, consistent with an eccentricity-dependent invariance to lower level visual properties such as temporal contrast. [ABSTRACT FROM AUTHOR]

Abstract Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested if feedback signals generalise across different spatial frequencies of feedforward inputs, or if they are tuned to the spatial scale of the visual scene. Using a partial occlusion paradigm, functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) we investigated whether feedback to V1 contains coarse or fine-grained information by manipulating the spatial frequency of the scene surround outside an occluded image portion. We show that feedback transmits both coarse and fine-grained information as it carries information about both low (LSF) and high spatial frequencies (HSF). Further, feedback signals containing LSF information are similar to feedback signals containing HSF information, even without a large overlap in spatial frequency bands of the HSF and LSF scenes. Lastly, we found that feedback carries similar information about the spatial frequency band across different scenes. We conclude that cortical feedback signals contain information which generalises across different spatial frequencies of feedforward inputs. Highlights • The influence of spatial frequency on cortical feedback was investigated. • Both high and low spatial frequency surround information led to meaningful feedback. • Feedback signals can generalise over spatial frequency in the same scene. • Feedback carries similar information about the spatial frequency band across scenes. [ABSTRACT FROM AUTHOR]

The need for fast and dynamic processing of relevant information imposes high demands onto the flexibility and efficiency of the nervous system. A good example for such flexibility is the attention-dependent selection of relevant sensory information. Studies investigating attentional modulations of neuronal responses to simultaneously arriving input showed that neurons respond, as if only the attended stimulus would be present within their receptive fields (RF). However, attention also improves neuronal representation and behavioral performance, when only one stimulus is present. Thus, attention serves for selecting relevant input and changes the neuronal processing of signals representing selected stimuli, ultimately leading to a more efficient behavioral performance. Here, we tested the hypothesis that attention configures the strength of functional coupling between a local neuronal network's neurons specifically for effective processing of signals representing attended stimuli. This coupling is measured as the strength of γ-synchronization between these neurons. The hypothesis predicts that the pattern of synchronization in local networks should depend on which stimulus is attended. Furthermore, we expect this pattern to be similar for the attended stimulus presented alone or together with irrelevant stimuli in the RF. To test these predictions, we recorded spiking-activity and local field potentials (LFP) with closely spaced electrodes in area V4 of monkeys performing a demanding attention task. Our results show that the γ-band phase coherence (γ-PhC) between spiking-activity and the LFP, as well as the spiking-activity of two groups of neurons, strongly depended on which of the two stimuli in the RF was attended. The γ-PhC was almost identical for the attended stimulus presented either alone or together with a distractor. The functional relevance of dynamic γ-band synchronization is further supported by the observation of strongly degraded γ-PhC before behavioral errors, while firing rates were barely affected. These qualitatively different results point toward a failure of attention-dependent top-down mechanisms to correctly synchronize the local neuronal network in V4, even though this network receives the correctly selected input. These findings support the idea of a flexible, demand-dependent dynamic configuration of local neuronal networks, for performing different functions, even on the same sensory input. [ABSTRACT FROM AUTHOR]

Background: The timing of action potentials ("spikes") of cortical neurons has been shown to be aligned to the phase of low-frequency (< 10 Hz) local field potentials (LFPs) in several cortical areas. However, across the areas, this alignment varies and the role of this spike-phase coupling (SPC) in cognitive functions is not well understood. Results: Here, we propose a role in the coordination of neural activity by selective attention. After refining previous analytical methods for measuring SPC, we show that first, SPC is present along the dorsal processing pathway in macaque visual cortex (area MT); second, spikes occur in falling phases of the low-frequency LFP independent of the location of spatial attention; third, switching spatial attention into the receptive field (RF) of MT neurons decreases this coupling; and finally, the LFP phase causally influences the spikes. Conclusions: Here, we show that spikes are coupled to the phase of low-frequency LFP along the dorsal visual pathway. Our data suggest that attention harnesses this spike-LFP coupling to de-synchronize neurons and thereby enhance the neural representation of the attended stimuli. [ABSTRACT FROM AUTHOR]

Visual spatial attention concentrates neural resources at the attended location. Recently, we demonstrated that voluntary spatial attention attracts population receptive fields (pRFs) toward its location throughout the visual hierarchy. Theoretically, both a feed forward or feedback mechanism could underlie pRF attraction in a given cortical area. Here, we use sub-millimeter ultra-high field functional MRI to measure pRF attraction across cortical depth and assess the contribution of feed forward and feedback signals to pRF attraction. In line with previous findings, we find consistent attraction of pRFs with voluntary spatial attention in V1. When assessed as a function of cortical depth, we find pRF attraction in every cortical portion (deep, center and superficial), although the attraction is strongest in deep cortical portions (near the gray-white matter boundary). Following the organization of feed forward and feedback processing across V1, we speculate that a mixture of feed forward and feedback processing underlies pRF attraction in V1. Specifically, we propose that feedback processing contributes to the pRF attraction in deep cortical portions. [ABSTRACT FROM AUTHOR]

Primates sample their visual environment actively through saccades and microsaccades (MSs). Saccadic eye movements not only modulate neural spike rates but might also affect temporal correlations (synchrony) among neurons. Neural synchrony plays a role in neural coding and modulates information transfer between cortical areas. The question arises of how eye movements shape neural synchrony within and across cortical areas and how it affects visual processing. Through local field recordings in macaque early visual cortex while monitoring eye position and through neural network simulations, we find 2 distinct synchrony regimes in early visual cortex that are embedded in a 3- to 4-Hz MS-related rhythm during visual fixation. In the period shortly after an MS (“transient period”), synchrony was high within and between cortical areas. In the subsequent period (“sustained period”), overall synchrony dropped and became selective to stimulus properties. Only mutually connected neurons with similar stimulus responses exhibited sustained narrow-band gamma synchrony (25–80 Hz), both within and across cortical areas. Recordings in macaque V1 and V2 matched the model predictions. Furthermore, our modeling provides predictions on how (micro)saccade-modulated gamma synchrony in V1 shapes V2 receptive fields (RFs). We suggest that the rhythmic alternation between synchronization regimes represents a basic repeating sampling strategy of the visual system. [ABSTRACT FROM AUTHOR]

In the primary visual cortex (V1), neuronal responses to stimuli within the receptive field (RF) are modulated by stimuli in the RF surround. A common effect of surround modulation is surround suppression, which is dependent on the feature difference between stimuli within and surround the RF and is suggested to be involved in the perceptual phenomenon of figure-ground segregation. In this study, we examined the relationship between feature-specific surround suppression of V1 neurons and figure detection behavior based on figure-ground feature difference. We trained freely moving mice to perform a figure detection task using figure and ground gratings that differed in spatial phase. The performance of figure detection increased with the figure-ground phase difference, and was modulated by stimulus contrast. Electrophysiological recordings from V1 in head-fixed mice showed that the increase in phase difference between stimuli within and surround the RF caused a reduction in surround suppression, which was associated with an increase in V1 neural discrimination between stimuli with and without RF-surround phase difference. Consistent with the behavioral performance, the sensitivity of V1 neurons to RF-surround phase difference could be influenced by stimulus contrast. Furthermore, inhibiting V1 by optogenetically activating either parvalbumin (PV)- or somatostatin (SOM)-expressing inhibitory neurons both decreased the behavioral performance of figure detection. Thus, the phase-specific surround suppression in V1 represents a neural correlate of figure detection behavior based on figure-ground phase discontinuity. [ABSTRACT FROM AUTHOR]

Simple cells in the cat primary visual cortex usually have elongated receptive fields (RFs), and their orientation selectivity can be largely predicted by their RFs. As to the relay cells in cats’ lateral geniculate nucleus (LGN), they also have weak but significant orientation bias (OB). It is thus of interest to investigate the fine spatiotemporal receptive field (STRF) properties in LGN, compare them with the dynamics of orientation tuning, and examine the dynamic relationship between STRF and orientation sensitivity in LGN. We mapped the STRFs of the LGN neurons in cats with white noise and characterized the dynamics of the orientation tuning by flashing gratings. We found that most of the LGN neurons showed elongated RFs and that the elongation axes were consistent with the preferred orientations. STRFs and the dynamics of orientation tuning were closely correlated temporally: the elongation of RFs and OB emerged, peaked and decayed at the same pace, with unchanged elongation axis of RF and preferred orientation but consistently changing aspect ratio of RF and OB strength across time. Importantly, the above consistency between RF and orientation tuning was not influenced by the ablation of the primary visual cortex. Furthermore, biased orientation tuning emerged 20–30 ms earlier than those in the primary visual cortex. These data demonstrated that similar to the primary visual cortex, the orientation sensitivity was closely reflected by the RF properties in LGN. However, the elongated RF and OB in LGN did not originate from the primary visual cortex feedback. [ABSTRACT FROM AUTHOR]

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

The spatial sensitivity of the human visual system depends on stimulus color: achromatic gratings can be resolved at relatively high spatial frequencies while sensitivity to isoluminant color contrast tends to be more low-pass. Models of early spatial vision often assume that the receptive field size of pattern-sensitive neurons is correlated with their spatial frequency sensitivity - larger receptive fields are typically associated with lower optimal spatial frequency. A strong prediction of this model is that neurons coding isoluminant chromatic patterns should have, on average, a larger receptive field size than neurons sensitive to achromatic patterns. Here, we test this assumption using functional magnetic resonance imaging (fMRI). We show that while spatial frequency sensitivity depends on chromaticity in the manner predicted by behavioral measurements, population receptive field (pRF) size measurements show no such dependency. At any given eccentricity, the mean pRF size for neuronal populations driven by luminance, opponent red/green and S-cone isolating contrast, are identical. Changes in pRF size (for example, an increase with eccentricity and visual area hierarchy) are also identical across the three chromatic conditions. These results suggest that fMRI measurements of receptive field size and spatial resolution can be decoupled under some circumstances - potentially reflecting a fundamental dissociation between these parameters at the level of neuronal populations. [ABSTRACT FROM AUTHOR]

Human faces contain multiple sources of information. During speech perception, visual information from the talker's mouth is integrated with auditory information from the talker's voice. By directly recording neural responses from small populations of neurons in patients implanted with subdural electrodes, we found enhanced visual cortex responses to speech when auditory speech was absent (rendering visual speech especially relevant). Receptive field mapping demonstrated that this enhancement was specific to regions of the visual cortex with retinotopic representations of the mouth of the talker. Connectivity between frontal cortex and other brain regions was measured with trial-by-trial power correlations. Strong connectivity was observed between frontal cortex and mouth regions of visual cortex; connectivity was weaker between frontal cortex and non-mouth regions of visual cortex or auditory cortex. These results suggest that top-down selection of visual information from the talker's mouth by frontal cortex plays an important role in audiovisual speech perception. [ABSTRACT FROM AUTHOR]

Activity of cortical inhibitory interneurons is rapidly reduced in response to monocular deprivation during the critical period for ocular dominance plasticity and in response to salient events encountered during learning. In the case of primary sensory cortex, a decrease in mean evoked firing rate of parvalbumin-positive (PV) inhibitory neurons is causally linked to a reorganization of excitatory networks following sensory perturbation. Converging evidence indicates that it is deprivation, and not an imbalance between open- and closed-eye inputs, that triggers rapid plasticity in PV neurons. However, this has not been directly tested in vivo. Using two-photon guided cell-attached recording, we examined the impact of closing both eyes for 24 h on PV neuron response properties in mouse primary visual cortex. We found that binocular deprivation induces a 30% reduction in stimulus-evoked mean firing rate and that this reduction is specific to critical period-aged mice. The number of PV neurons showing detectable tuning to orientation increased after 24 h of deprivation, and this effect was also specific to critical period-aged mice. In contrast to evoked mean firing rate and orientation tuning, measurements of trial-to-trial variability revealed that stimulus-driven decreases in variability are significantly dampened by deprivation during both the critical period and the postcritical period. These data establish that open-eye inputs are not required to drive deprivation-induced weakening of PV neuron evoked activity and that other aspects of in vivo PV neuron activity are malleable throughout life. [ABSTRACT FROM AUTHOR]

The center-surround organization of the receptive fields (RFs) of retinal ganglion cells highlights the presence of local contrast in visual stimuli. As RF of thalamic relay cells follow the same basic functional organization, it is often assumed that they contribute very little to alter the retinal output. However, in many species, thalamic relay cells largely outnumber their retinal inputs, which diverge to contact simultaneously several units at thalamic level. This gain in cell population as well as retinothalamic convergence opens the door to question how information about contrast is transformed at the thalamic stage. Here, we address this question using a realistic dynamic model of the retinothalamic circuit. Our results show that different components of the thalamic RF might implement filters that are analogous to two types of well-known image processing techniques to preserve the quality of a higher resolution version of the image on its way to the primary visual cortex. [ABSTRACT FROM AUTHOR]

When light falls within a neuronal visual receptive field (RF) the resulting activity is referred to as the visual response. Recent work suggests this activity is in response to both the visual stimulation and the abrupt appearance, or salience, of the presentation. Here we present a novel method for distinguishing the two, based on the timing of random and nonrandom presentations. We examined these contributions in frontal eye field (FEF; N = 51) and as a comparison, an early stage in the primary visual cortex (V1; N = 15) of male monkeys (Macaca mulatto). An array of identical stimuli was presented within and outside the neuronal RF while we manipulated salience by varying the time between stimulus presentations. We hypothesized that the rapid presentation would reduce salience (the sudden appearance within the visual field) of a stimulus at any one location, and thus decrease responses driven by salience in the RF. We found that when the interstimulus interval decreased from 500 to 16 ms there was an approximate 79% reduction in the FEF response compared with an estimated 17% decrease in V1. This reduction in FEF response for rapid presentation was evident even when the random sequence preceding a stimulus did not stimulate the RF for 500 ms. The time course of these response changes in FEF suggest that salience is represented much earlier (< 100 ms following stimulus onset) than previously estimated. Our results suggest that the contribution of salience dominates at higher levels of the visual system. [ABSTRACT FROM AUTHOR]

Thalamocortical conduction times are short, but layer 6 corticothalamic axons display an enormous range of conduction times, some exceeding 40-50 ms. Here, we investigate (1) how axonal conduction times of corticogeniculate (CG) neurons are related to the visual information conveyed to the thalamus, and (2) how alert versus nonalert awake brain states affect visual processing across the spectrum of CG conduction times. In awake female Dutch-Belted rabbits, we found 58% of CG neurons to be visually responsive, and 42% to be unresponsive. All responsive CG neurons had simple, orientation-selective receptive fields, and generated sustained responses to stationary stimuli. CG axonal conduction times were strongly related to modulated firing rates (FI values) generated by drifting grating stimuli, and their associated interspike interval distributions, suggesting a continuum of visual responsiveness spanning the spectrum of axonal conduction times. CG conduction times were also significantly related to visual response latency, contrast sensitivity (C-50 values), directional selectivity, and optimal stimulus velocity. Increasing alertness did not cause visually unresponsive CG neurons to become responsive and did not change the response linearity (F1/F0 ratios) of visually responsive CG neurons. However, for visually responsive CG neurons, increased alertness nearly doubled the modulated response amplitude to optimal visual stimulation (F1 values), significantly shortened response latency, and dramatically increased response reliability. These effects of alertness were uniform across the broad spectrum of CG axonal conduction times. [ABSTRACT FROM AUTHOR]

Selective visual attentionenables organisms to enhance the representationof behaviorally relevant stimuli by altering the encoding properties of single receptive fields (RFs).Yetwe knowlittle about how the attentional modulations of singleRFs contribute to the encoding of an entire visual scene. Addressing this issue requires (1)measuring a group of RFs that tile a continuous portion of visual space, (2) constructing a population-level measurement of spatial representations based on these RFs, and (3) linking how different types of RF attentionalmodulations change the population-level representation. To accomplish these aims,we used fMRI to characterize the responses of thousands of voxels in retinotopically organized human cortex. First, we found that the responsemodulations of voxel RFs (vRFs) depend on the spatial relationship between the RF center and the visual location of the attended target. Second,we used two analyses to assess the spatial encoding quality of a population of voxels. We found that attention increased fine spatial discriminability and representational fidelity near the attended target. Third, we linked these findings bymanipulating the observed vRF attentionalmodulations and recomputing ourmeasures of the fidelity of population codes. Surprisingly, we discovered that attentional enhancements of population-level representations largely depend on position shifts of vRFs, rather than changes in size or gain. Our data suggest that position shifts of single RFs are a principalmechanismby which attention enhances population-level representations in visual cortex. [ABSTRACT FROM AUTHOR]

Contrast sensitivity is fundamental to natural visual processing and an important tool for characterizing both visual function and clinical disorders. We simultaneously measured contrast sensitivity and neural contrast response functions and compared measurements in common laboratory conditions with naturalistic conditions. In typical experiments, a subject holds fixation and a stimulus is flashed on, whereas in natural vision, saccades bring stimuli into view. Motivated by our previous V1 findings, we tested the hypothesis that perceptual contrast sensitivity is lower in natural vision and that this effect is associated with corresponding changes in V1 activity. We found that contrast sensitivity and V1 activity are correlated and that the relationship is similar in laboratory and naturalistic paradigms. However, in the more natural situation, contrast sensitivity is reduced up to 25% compared with that in a standard fixation paradigm, particularly at lower spatial frequencies, and this effect correlates with significant reductions in V1 responses. Our data suggest that these reductions in natural vision result from fast adaptation on one fixation that lowers the response on a subsequent fixation. This is the first demonstration of rapid, natural-image adaptation that carries across saccades, a process that appears to constantly influence visual sensitivity in natural vision. [ABSTRACT FROM AUTHOR]

Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional modulations for time-courses were induced by selective enhancement of early-level features due to interactions between V1 and PP. Our proposed model suggests fundamental roles of surrounding suppression/facilitation based on feedforward inputs as well as the interactions between early and parietal visual areas with respect to the ambiguity dependence of the neural dynamics in intermediate-level vision. [ABSTRACT FROM AUTHOR]

In this article, we review functional organization in sensory cortical regions—how the cortex represents the world. We consider four interrelated aspects of cortical organization: (1) the set of receptive fields of individual cortical sensory neurons, (2) how lateral interaction between cortical neurons reflects the similarity of their receptive fields, (3) the spatial distribution of receptive-field properties across the horizontal extent of the cortical tissue, and (4) how the spatial distributions of different receptive-field properties interact with one another. We show how these data are generally well explained by the theory of input-driven self-organization, with a family of computational models of cortical maps offering a parsimonious account for a wide range of map-related phenomena. We then discuss important challenges to this explanation, with respect to the maps present at birth, maps present under activity blockade, the limits of adult plasticity, and the lack of some maps in rodents. Because there is not at present another credible general theory for cortical map development, we conclude by proposing key experiments to help uncover other mechanisms that might also be operating during map development. [ABSTRACT FROM AUTHOR]

Population receptive field (pRF) analysis is a popular method to infer spatial selectivity of voxels in visual cortex. However, it remains largely untested how stable pRF estimates are over time. Here we measured the intersession reliability of pRF parameter estimates for the central visual field and near periphery, using a combined wedge and ring stimulus containing natural images. Sixteen healthy human participants completed two scanning sessions separated by 10–114 days. Individual participants showed very similar visual field maps for V1-V4 on both sessions. Intersession reliability for eccentricity and polar angle estimates was close to ceiling for most visual field maps ( r >.8 for V1-3). PRF size and cortical magnification (CMF) estimates showed strong but lower overall intersession reliability ( r ≈.4–.6). Group level results for pRF size and CMF were highly similar between sessions. Additional control experiments confirmed that reliability does not depend on the carrier stimulus used and that reliability for pRF size and CMF is high for sessions acquired on the same day ( r >.6). Ou r results demonstrate that pRF mapping is highly reliable across sessions. [ABSTRACT FROM AUTHOR]

Summary In primary visual cortex, a subset of neurons responds when a particular stimulus is encountered in a certain location in visual space. This activity can be modeled using a visual receptive field. In addition to visually driven activity, there are neurons in visual cortex that integrate visual and motor-related input to signal a mismatch between actual and predicted visual flow. Here we show that these mismatch neurons have receptive fields and signal a local mismatch between actual and predicted visual flow in restricted regions of visual space. These mismatch receptive fields are aligned to the retinotopic map of visual cortex and are similar in size to visual receptive fields. Thus, neurons with mismatch receptive fields signal local deviations of actual visual flow from visual flow predicted based on self-motion and could therefore underlie the detection of objects moving relative to the visual flow caused by self-motion. Video Abstract [ABSTRACT FROM AUTHOR]

Summary The primary visual cortex (V1) encodes a diverse set of visual features, including orientation, ocular dominance (OD), and spatial frequency (SF), whose joint organization must be precisely structured to optimize coverage within the retinotopic map. Prior experiments have only identified efficient coverage based on orthogonal maps. Here we used two-photon calcium imaging to reveal an alternative arrangement for OD and SF maps in macaque V1; their gradients run parallel but with unique spatial periods, whereby low-SF regions coincide with monocular regions. Next we mapped receptive fields and found surprisingly precise micro-retinotopy that yields a smaller point-image and requires more efficient inter-map geometry, thus underscoring the significance of map relationships. While smooth retinotopy is constraining, studies suggest that it improves both wiring economy and the V1 population code read downstream. Altogether, these data indicate that connectivity within V1 is finely tuned and precise at the level of individual neurons. [ABSTRACT FROM AUTHOR]

Across animal phyla, motion vision relies on neurons that respond preferentially to stimuli moving in one, preferred direction over the opposite, null direction. In the elementary motion detector of Drosophila, direction selectivity emerges in two neuron types, T4 and T5, but the computational algorithm underlying this selectivity remains unknown. We find that the receptive fields of both T4 and T5 exhibit spatiotemporally offset light-preferring and dark-preferring subfields, each obliquely oriented in spacetime. In a linear-nonlinear modeling framework, the spatiotemporal organization of the T5 receptive field predicts the activity of T5 in response to motion stimuli. These findings demonstrate that direction selectivity emerges from the enhancement of responses to motion in the preferred direction, as well as the suppression of responses to motion in the null direction. Thus, remarkably, T5 incorporates the essential algorithmic strategies used by the Hassenstein-Reichardt correlator and the Barlow-Levick detector. Our model for T5 also provides an algorithmic explanation for the selectivity of T5 for moving dark edges: our model captures all two- and three-point spacetime correlations relevant to motion in this stimulus class. More broadly, our findings reveal the contribution of input pathway visual processing, specifically centersurround, temporally biphasic receptive fields, to the generation of direction selectivity in T5. As the spatiotemporal receptive field of T5 in Drosophila is common to the simple cell in vertebrate visual cortex, our stimulus-response model of T5 will inform efforts in an experimentally tractable context to identify more detailed, mechanistic models of a prevalent computation. [ABSTRACT FROM AUTHOR]

The responses of cortical neurons to a stimulus in a classical receptive field (CRF) can be modulated by stimulating the non-CRF (nCRF) of neurons in the primary visual cortex (V1). In the very early stages (at around 40 ms), a neuron in V1 exhibits strong responses to a small set of stimuli. Later, however (after 100 ms), the neurons in V1 become sensitive to the scene's global organization. As per these visual cortical mechanisms, a contour detection model based on the spatial summation properties is proposed. Unlike in previous studies, the responses of the nCRF to the higher visual cortex that results in the inhibition of the neuronal responses in the primary visual cortex by the feedback pathway are considered. In this model, the individual neurons in V1 receive global information from the higher visual cortex to participate in the inhibition process. Computationally, global Gabor energy features are involved, leading to the more coherent physiological characteristics of the nCRF. We conducted an experiment where we compared our model with those proposed by other researchers. Our model explains the role of the mutual inhibition of neurons in V1, together with an approach for object recognition in machine vision. ©2016 SPIE and IS&T [DDI: 10.1117/1.JEI.25.4.043018] [ABSTRACT FROM AUTHOR]

Accurate estimation of neuronal receptive fields is essential for understanding sensory processing in the early visual system. Yet a full characterization of receptive fields is still incomplete, especially with regard to natural visual stimuli and in complete populations of cortical neurons. While previous work has incorporated known structural properties of the early visual system, such as lateral connectivity, or imposing simple-cell-like receptive field structure, no study has exploited the fact that nearby V1 neurons share common feed-forward input from thalamus and other upstream cortical neurons. We introduce a new method for estimating receptive fields simultaneously for a population of V1 neurons, using a model-based analysis incorporating knowledge of the feed-forward visual hierarchy. We assume that a population of V1 neurons shares a common pool of thalamic inputs, and consists of two layers of simple and complex-like V1 neurons. When fit to recordings of a local population of mouse layer 2/3 V1 neurons, our model offers an accurate description of their response to natural images and significant improvement of prediction power over the current state-of-the-art methods. We show that the responses of a large local population of V1 neurons with locally diverse receptive fields can be described with surprisingly limited number of thalamic inputs, consistent with recent experimental findings. Our structural model not only offers an improved functional characterization of V1 neurons, but also provides a framework for studying the relationship between connectivity and function in visual cortical areas. [ABSTRACT FROM AUTHOR]

Neurons in area MT/V5 of the macaque visual cortex encode visual motion. Some cells are selective for the motion of oriented features (component direction-selective, CDS); others respond to the true direction of complex patterns (pattern-direction selective, PDS). There is a continuum of selectivity in MT, with CDS cells at one extreme and PDS cells at the other; we compute a pattern index that captures this variation. It is unknown how a neuron's pattern index is related to its other tuning characteristics. We therefore analyzed the responses of 792 MT cells recorded in the course of other experiments from opiate-anesthetized macaque monkeys, as a function of the direction, spatial frequency, drift rate, size, and contrast of sinusoidal gratings and of the direction and speed of random-dot textures. We also compared MT responses to those of 718 V1 cells. As expected, MT cells with higher pattern index tended to have stronger direction selectivity and broader direction tuning to gratings, and they responded better to plaids than to gratings. Strongly PDS cells also tended to have smaller receptive fields and stronger surround suppression. Interestingly, they also responded preferentially to higher drift rates and higher speeds of moving dots. The spatial frequency preferences of PDS cells depended strongly on their preferred temporal frequencies, whereas these preferences were independent in component-selective cells. Pattern direction selectivity is statistically associated with many response properties of MT cells but not strongly associated with any particular property. Pattern-selective signals are thus available in association with most other signals exported by MT. [ABSTRACT FROM AUTHOR]

From the earliest stages of sensory processing, neurons show inherent non-linearities: the response to a complex stimulus is not a sum of the responses to a set of constituent basis stimuli. These non-linearities come in a number of forms and have been explained in terms of a number of functional goals. The family of spatial non-linearities have included interactions that occur both within and outside of the classical receptive field. They include, saturation, cross orientation inhibition, contrast normalization, end-stopping and a variety of non-classical effects. In addition, neurons show a number of facilitatory and invariance related effects such as those exhibited by complex cells (integration across position). Here, we describe an approach that attempts to explain many of the non-linearities under a single geometric framework. In line with Zetzsche and colleagues (e.g., Zetzsche et al., 1999) we propose that many of the principal non-linearities can be described by a geometry where the neural response space has a simple curvature. In this paper, we focus on the geometry that produces both increased selectivity (curving outward) and increased tolerance (curving inward). We demonstrate that overcomplete sparse coding with both low-dimensional synthetic data and high-dimensional natural scene data can result in curvature that is responsible for a variety of different known non-classical effects including end-stopping and gain control. We believe that this approach provides a more fundamental explanation of these non-linearities and does not require that one postulate a variety of explanations (e.g., that gain must be controlled or the ends of lines must be detected). In its standard form, sparse coding does not however, produce invariance/tolerance represented by inward curvature. We speculate on some of the requirements needed to produce such curvature. [ABSTRACT FROM AUTHOR]

Visual attention has many effects on neural responses, producing complex changes in firing rates, as well as modifying the structure and size of receptive fields, both in topological and feature space. Several existing models of attention suggest that these effects arise from selective modulation of neural inputs. However, anatomical and physiological observations suggest that attentional modulation targets higher levels of the visual system (such as V4 or MT) rather than input areas (such as V1). Here we propose a simple mechanism that explains how a top-down attentional modulation, falling on higher visual areas, can produce the observed effects of attention on neural responses. Our model requires only the existence of modulatory feedback connections between areas, and short-range lateral inhibition within each area. Feedback connections redistribute the top-down modulation to lower areas, which in turn alters the inputs of other higher-area cells, including those that did not receive the initial modulation. This produces firing rate modulations and receptive field shifts. Simultaneously, short-range lateral inhibition between neighboring cells produce competitive effects that are automatically scaled to receptive field size in any given area. Our model reproduces the observed attentional effects on response rates (response gain, input gain, biased competition automatically scaled to receptive field size) and receptive field structure (shifts and resizing of receptive fields both spatially and in complex feature space), without modifying model parameters. Our model also makes the novel prediction that attentional effects on response curves should shift from response gain to contrast gain as the spatial focus of attention drifts away from the studied cell. [ABSTRACT FROM AUTHOR]

Visual processing depends critically on the receptive field (RF) properties of visual neurons. However, comprehensive characterization of RFs beyond the primary visual cortex (V1) remains a challenge. Here we report fine RF structures in secondary visual cortex (V2) of awake macaque monkeys, identified through a projection pursuit regression analysis of neuronal responses to natural images. We found that V2 RFs could be broadly classified as V1-like (typical Gaborshaped subunits), ultralong (subunits with high aspect ratios), or complex-shaped (subunits with multiple oriented components). Furthermore, single-unit recordings from functional domains identified by intrinsic optical imaging showed that neurons with ultralong RFs were primarily localized within pale stripes, whereas neurons with complex-shaped RFs were more concentrated in thin stripes. Thus, by combining single-unit recording with optical imaging and a computational approach, we identified RF subunits underlying spatial feature selectivity of V2 neurons and demonstrated the functional organization of these RF properties. [ABSTRACT FROM AUTHOR]

In the visual cortex, stimuli outside the classical receptive field (CRF) modulate the neural firing rate, without driving the neuron by themselves. In the primary visual cortex (V1), such contextual modulation can be parametrized with an area summation function (ASF): increasing stimulus size causes first an increase and then a decrease of firing rate before reaching an asymptote. Earlier work has reported increase of sparseness when CRF stimulation is extended to its surroundings. However, there has been no clear connection between the ASF and network efficiency. Here we aimed to investigate possible link between ASF and network efficiency. In this study, we simulated the responses of a biomimetic spiking neural network model of the visual cortex to a set of natural images. We varied the network parameters, and compared the V1 excitatory neuron spike responses to the corresponding responses predicted from earlier single neuron data from primate visual cortex. The network efficiency was quantified with firing rate (which has direct association to neural energy consumption), entropy per spike and population sparseness. All three measures together provided a clear association between the network efficiency and the ASF. The association was clear when varying the horizontal connectivity within V1, which influenced both the efficiency and the distance to ASF, DAS. Given the limitations of our biophysical model, this association is qualitative, but nevertheless suggests that an ASF-like receptive field structure can cause efficient population response. [ABSTRACT FROM AUTHOR]

Human cognition has a limited capacity that is often attributed to the brain having finite cognitive resources, but the nature of these resources is usually not specified. Here, we show evidence that perceptual interference between items can be predicted by known receptive field properties of the visual cortex, suggesting that competition within representational maps is an important source of the capacity limitations of visual processing. Across the visual hierarchy, receptive fields get larger and represent more complex, high-level features. Thus, when presented simultaneously, high-level items (e.g., faces) will often land within the same receptive fields, while low-level items (e.g., color patches) will often not. Using a perceptual task, we found long-range interference between high-level items, but only short-range interference for low-level items, with both types of interference being weaker across hemifields. Finally, we show that long-range interference between items appears to occur primarily during perceptual encoding and not during working memory maintenance. These results are naturally explained by the distribution of receptive fields and establish a link between perceptual capacity limits and the underlying neural architecture. [ABSTRACT FROM AUTHOR]

Neurons in primary visual cortex (V1) can be indirectly affected by visual stimulation positioned outside their receptive fields. Although this contextual modulation has been intensely studied, we have little notion of how it manifests with naturalistic stimulation. Here, we investigated how the V1 response to a natural image fragment is affected by spatial context that is consistent or inconsistent with the scene from which it was extracted. Using functional magnetic resonance imaging at 7 T, we measured the blood oxygen level-dependent signal in human V1 (n = 8) while participants viewed an array of apertures. Most apertures showed fragments from a single scene, yielding a dominant perceptual interpretation which participants were asked to categorize, and the remaining apertures each showed fragments drawn from a set of 20 scenes. We find that the V1 response was significantly increased for apertures showing image structure that was coherent with the dominant scene relative to the response to the same image structure when it was non-coherent. Additional analyses suggest that this effect was mostly evident for apertures in the periphery of the visual field, that it peaked towards the centre of the aperture, and that it peaked in the middle to superficial regions of the cortical grey matter. These findings suggest that knowledge of typical spatial relationships is embedded in the circuitry of contextual modulation. Such mechanisms, possibly augmented by contributions from attentional factors, serve to increase the local V1 activity under conditions of contextual consistency. [ABSTRACT FROM AUTHOR]

Ponzo illusion is a well-known perceptual phenomenon in which the perceived sizes of visual objects are altered by visual depth cues created by converging lines at the horizon. One possible neural mechanism of the Ponzo illusion is the receptive field position shifts of V1 neurons, as supported by a recent monkey electrophysiological study (Ni et al. in Curr Biol 24(14):1653-1658, ). Here, we used fMRI-based population receptive field (pRF) mapping technique in combination of psychophysics to investigate this idea. We found that, relative to the close apparent depth in a 3D scene, the far apparent depth in the scene caused the pRF positions of voxels in V1-V3 to shift toward the fovea, in line with subjects' percept of the Ponzo illusion. Moreover, the pRF position shift in V1 significantly correlated with the magnitude of the Ponzo illusion across individual subjects. Our findings thus provide evidence for the close association between the perceived object size and the pRF position shift in human visual areas, especially in V1, lending further support for the receptive field position shift explanation for the Ponzo illusion. [ABSTRACT FROM AUTHOR]

In the primary visual cortex (V1), orientation-selective neurons can be categorized into simple and complex cells primarily based on their receptive field (RF) structures. In mouse V1, although previous studies have examined the excitatory/inhibitory interplay underlying orientation selectivity (OS) of simple cells, the synaptic bases for that of complex cells have remained obscure. Here, by combining in vivo loose-patch and whole-cell recordings, we found that complex cells, identified by their overlapping on/off subfields, had significantly weaker OS than simple cells at both spiking and subthreshold membrane potential response levels. Voltage-clamp recordings further revealed that although excitatory inputs to complex and simple cells exhibited a similar degree of OS, inhibition in complex cells was more narrowly tuned than excitation, whereas in simple cells inhibition was more broadly tuned than excitation. The differential inhibitory tuning can primarily account for the difference in OS between complex and simple cells. Interestingly, the differential synaptic tuning correlated well with the spatial organization of synaptic input: the inhibitory visual RF in complex cells was more elongated in shape than its excitatory counterpart and also was more elongated than that in simple cells. Together, our results demonstrate that OS of complex and simple cells is differentially shaped by cortical inhibition based on its orientation tuning profile relative to excitation, which is contributed at least partially by the spatial organization of RFs of presynaptic inhibitory neurons. [ABSTRACT FROM AUTHOR]

The neuronal activity evoked by stimuli confined in a receptive field can be modulated by surround stimuli of the extra-classical receptive field (eCRF). The surrounding modulation, hypothesized to be the basis of visual feature integration and figure-ground segregation, has drawn much attention in the field of neuroscience and engineering. However, most studies focused on surround modulation of individual neuronal response. In this study, we analyzed surround modulation of the population response recorded from rat primary visual cortex, and further investigated dynamic functional connectivity modulated by the surrounding stimuli. The functional connectivity was estimated using Granger causality (GC) and then determined by thresholding the p -matrix with different significance α values. Four scalar indexes were calculated to describe the functional connectivity of neuronal population: averaged connection strength (mGC), connection density ( D ), clustering coefficient ( C ) and path length ( L ). The statistical results from 5 rats showed that these network characteristics were dynamically changed during modulation of surrounding stimuli, which suggested that the neuronal population may connect in a dynamic way during modulation of eCRF. We further guessed that the neurons may happened to be organized in a more efficient way underlying surrounding modulation conditions, which helps to process larger images efficiently with the same number of neurons. This study provided new insights for a better understanding of the underlying neural mechanisms responsible for surround modulation. [ABSTRACT FROM AUTHOR]

The rat visual system comprises cortical and subcortical pathways. The receptive field properties of cells in the visual cortex have been extensively studied; however, the fundamental roles of the two circuits in visual information processing are not well understood. To address this question, we have applied quantitative methods to compare and characterize the spatiotemporal receptive field (RF) properties of neurons in primary visual cortex (V1) cells and superficial layers of the superior colliculus (SC) in rats by means of extracellular recordings. An analysis of visual stimulus processing revealed distinct functional characteristics of the two visual circuits. RF diameters of SC neurons were significantly larger than those of V1 cells. Most cells in both regions had high orientation selectivity, but the mean orientation bandwidth of the SC was broader than that of V1 cells (101.5° vs. 60.2°). The mean optimal spatial frequency (SF) of SC cells was lower but had a broader bandwidth than that of V1 cells (0.03 vs. 0.068 cpd). The majority of SC and V1 cells (70% and 68%, respectively) had RFs with band-pass temporal frequency (TF) tuning profiles and similar optimal TFs. However, temporal band-pass profiles of the SC showed narrower mean temporal bandwidths than those of V1 cells (1.42 vs. 2.36 octaves). The majority of neurons in visual cortical and subcortical structures were activated in response to high-contrast, drifting gratings in the preferred orientation. The percentage of V1 neurons with a low-contrast threshold was larger than the proportion of SC neurons (45.6% vs. 30%), indicating that the former adapt better to contrast. The substantial overlap in latency distributions between SC and V1 areas suggests that the two visual systems process and analyze visual signals in parallel. However, the two areas use different neural encoding mechanisms based on different latency distribution trends. These results indicate that SC cells have poor spatial acuity and are better suited to detecting high-contrast, moving stimuli in larger visual fields. In contrast, V1 cells are adapted to extracting shape information and detailed features of objects. [ABSTRACT FROM AUTHOR]

The receptive fields of the clear majority of neurons in the primary visual cortex (V1) of cats contain silent surround regions beyond the classical receptive field (CRF). When stimulated on their own, the silent surround regions do not generate action potentials (spikes); instead, they modulate (and usually partially suppress) spike responses to stimuli presented in the CRF. In the present study, we subdivided our sample of single V1 neurons recorded from anesthetized cats into two distinct categories: surround-suppressive (SS) cells and surround-non-suppressive (SN) cells. Consistent with previous reports, we found a negative correlation between the size of the CRF and the optimal spatial frequency (SF) of circular patches of achromatic gratings presented in the cells’ receptive fields. Furthermore, we found a positive correlation between the strength of the surround suppression and the optimal spatial frequency of the achromatic gratings presented in the cells’ receptive fields. The correlation between the strength of surround suppression and the optimal spatial frequency was stronger in neurons with suppressive regions located in the so-called ‘end’ zones. The functional implications of these relationships are discussed. [ABSTRACT FROM AUTHOR]

The spatial topography of visual attention is a distinguishing and critical feature of many theoretical models of visuospatial attention. Previous fMRI-based measurements of the topography of attention have typically been too crude to adequately test the predictions of different competing models. This study demonstrates a new technique to make detailed measurements of the topography of visuospatial attention from single-voxel, fMRI time courses. Briefly, this technique involves first estimating a voxel's population receptive field (pRF) and then "drifting" attention through the pRF such that the modulation of the voxel's fMRI time course reflects the spatial topography of attention. The topography of the attentional field (AF) is then estimated using a time-course modeling procedure. Notably, we are able to make these measurements in many visual areas including smaller, higher order areas, thus enabling a more comprehensive comparison of attentional mechanisms throughout the full hierarchy of human visual cortex. Using this technique, we show that the AF scales with eccentricity and varies across visual areas. We also show that voxels in multiple visual areas exhibit suppressive attentional effects that are well modeled by an AF having an enhancing Gaussian center with a suppressive surround. These findings provide extensive, quantitative neurophysiological data for use in modeling the psychological effects of visuospatial attention. [ABSTRACT FROM AUTHOR]

In primary visual cortex (V1), neuronal responses are sensitive to context. For example, responses to stimuli presented within the receptive field (RF) center are often suppressed by stimuli within the RF surround, and this suppression tends to be strongest when the center and surround stimuli match. We sought to identify the mechanism that gives rise to these properties of surround modulation. To do so, we exploited the stability of implanted multielectrode arrays to record from neurons in V1 of alert monkeys with multiple stimulus sets that more exhaustively probed center-surround interactions. We first replicated previous results concerning center-surround similarity using gratings representing all combinations of center and surround orientation. With this stimulus set, the surround simply scaled population responses to the center, such that the overall population tuning curve had the same shape and peak response. However, when the center contained two superimposed gratings (i.e., a visual "plaid"), one component of which always matched the surround orientation, suppression selectively affected the portion of the response driven by the matching center component, thereby producing shifts in the peak of the population orientation tuning curve. In effect, the surround caused neurons to respond predominantly to the component grating of the center plaid that was unmatched to the surround grating, as if by reducing the effective strength of whichever stimulus attributes were matched to the surround. These results provide key physiological support for theoretical models that propose feature-specific, input-gain control as the mechanism underlying surround suppression. [ABSTRACT FROM AUTHOR]