Topographical Estimation of Visual Population Receptive Fields by fMRI

Visual cortex is retinotopically organized so that neighboring populations of cells map to neighboring parts of the visual field. Functional magnetic resonance imaging allows us to estimate voxel-based population receptive fields (pRF), i.e., the part of the visual field that activates the cells within each voxel. Prior, direct, pRF estimation methods¹ suffer from certain limitations: 1) the pRF model is chosen a-priori and may not fully capture the actual pRF shape, and 2) pRF centers are prone to mislocalization near the border of the stimulus space. Here a new topographical pRF estimation method² is proposed that largely circumvents these limitations. A linear model is used to predict the Blood Oxygen Level-Dependent (BOLD) signal by convolving the linear response of the pRF to the visual stimulus with the canonical hemodynamic response function. PRF topography is represented as a weight vector whose components represent the strength of the aggregate response of voxel neurons to stimuli presented at different visual field locations. The resulting linear equations can be solved for the pRF weight vector using ridge regression³, yielding the pRF topography. A pRF model that is matched to the estimated topography can then be chosen post-hoc, thereby improving the estimates of pRF parameters such as pRF-center location, pRF orientation, size, etc. Having the pRF topography available also allows the visual verification of pRF parameter estimates allowing the extraction of various pRF properties without having to make a-priori assumptions about the pRF structure. This approach promises to be particularly useful for investigating the pRF organization of patients with disorders of the visual system.     

Population receptive field dynamics in human visual cortex

Seminal work in the early nineties revealed that the visual receptive field of neurons in cat primary visual cortex can change in location and size when artificial scotomas are applied. Recent work now suggests that these single neuron receptive field dynamics also pertain to the neuronal population receptive field (pRF) that can be measured in humans with functional magnetic resonance imaging (fMRI). To examine this further, we estimated the pRF in twelve healthy participants while masking the central portion of the visual field. We found that the pRF changes in location and size for two differently sized artificial scotomas, and that these pRF dynamics are most likely due to a combination of the neuronal receptive field position and size scatter as well as modulatory feedback signals from extrastriate visual areas.     

Why do olfactory neurons have unspecific receptive fields?

Biological olfactory neurons are deployed as a population, most responding to a large variety of chemical compounds, that is, they possess unspecific receptive fields. The question of whether this unspecificity results from some physical constraint placed upon chemical transduction, or on the other hand, is beneficial to system performance is unclear. In this paper we employ the notion of Fisher information to address this question by quantifying how both the distribution and the tunings of the receptive fields within olfactory receptor populations affect the optimal estimation performance of the system. Our results show that overlapping sensory neuron tunings that respond to common chemical compounds have better estimation performance than perfectly specific tunings. Our results suggest two phenomena that might represent general principles of organization within biological sensory systems responding to multiple stimuli: maximization of the diversity of tunings and homogeneity in the distribution of these different receptive fields across the stimulus space (independent of the statistics of the input stimuli). Our model predicts that a local randomized mechanism controlling receptor specificities generates optimal multidimensional stimulus estimation, for which there is some experimental evidence from the biology.     

Contextual modulation of V1 receptive fields depends on their spatial symmetry

The apparent receptive field characteristics of sensory neurons depend on the statistics of the stimulus ensemble—a nonlinear phenomenon often called contextual modulation. Since visual cortical receptive fields determined from simple stimuli typically do not predict responses to complex stimuli, understanding contextual modulation is crucial to understanding responses to natural scenes. To analyze contextual modulation, we examined how apparent receptive fields differ for two stimulus ensembles that are matched in first- and second-order statistics, but differ in their feature content: one ensemble is enriched in elongated contours. To identify systematic trends across the neural population, we used a multidimensional scaling method, the Procrustes transformation. We found that contextual modulation of receptive field components increases with their spatial extent. More surprisingly, we also found that odd-symmetric components change systematically, but even-symmetric components do not. This symmetry dependence suggests that contextual modulation is driven by oriented On/Off dyads, i.e., modulation of the strength of intracortically-generated signals. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Organization of receptive fields of motion-senstitive neurons in the cat pulvinar

The distribution of 70 visually sensitive neurons in the cat pulvinar sensitive to motion in the receptive fields was studied. The experimental results showed that components with directional characteristics are present in the structure of these fields of both direction-selective and unselective neurons. In the receptive fields of direction-selective neurons the directional elements of the substructure have identical preferred directions, which coincide with the preferred directions of response to stimulus movement over the entire receptive field. The organization of receptive fields of direction-selective neurons of the visual association structure thus does not differ significantly from that of analogous fields of visual projection neurons. Directional elements of the receptive fields of direction-unselective neurons were found to have different preferred directions, thereby providing a basis for organization of the nondirectional response of the neuron to a stimulus moving across the entire receptive field.L. A. Orbeli Institute of Physiology, Academy of Sciences of the Armenian SSR, Erevan. Translated from Neirofiziologiya, Vol. 14, No. 4, pp. 339–346, July–August, 1982.     

Does neuronal synchrony underlie visual feature grouping?

Previous research suggests that synchronous neural activity underlies perceptual grouping of visual image features. The generality of this mechanism is unclear, however, as previous studies have focused on pairs of neurons with overlapping or collinear receptive fields. By sampling more broadly and employing stimuli that contain partially occluded objects, we have conducted a more incisive test of the binding by synchrony hypothesis in area MT. We find that synchrony in spiking activity shows little dependence on feature grouping, whereas gamma band synchrony in field potentials can be significantly stronger when features are grouped. However, these changes in gamma band synchrony are small relative to the variability of synchrony across recording sites and do not provide a robust population signal for feature grouping. Moreover, these effects are reduced when stimulus differences nearby the receptive fields are eliminated using partial occlusion. Our findings suggest that synchrony does not constitute a general mechanism of visual feature binding.     

Structure of receptive fields of cat pulvinar neurons sensitive to photic stimulation

Receptive fields of 262 pulvinar neurons were studied. Receptive fields of 142 of these neurons were studied in detail with the aid of a stationary spot of light, flashing in different parts of the receptive field. Depending on responses to presentation of the stationary stimulus the neurons were divided into six groups. The first group included neurons with on—off responses to photic stimulation (44 of 142), the second group neurons with off responses only (42 of 142). In cells of the third group (19 of 142) an on response only was recorded in all structures of the receptive field tested. Neurons of the fourth group (eight of 142) had a receptive field of similar structure to that of the simple receptive fields of neurons in cortical area 17. The fifth group (10 of 142) included neurons with a receptive field of concentric structure, the sixth (19 of 142) consisted of neurons with receptive fields with multiple discharge centers. The structure of the receptive field of these neurons was mosaic, with an irregular distribution of exciting and "silent" zones. The mean response latency of the pulvinar neurons was 40–70 msec. Responses of neurons with shorter (20 msec) and longer (130–160 msec) latent periods also were recorded.L. A. Orbeli Institute of Physiology, Academy of Sciences of the Armenian SSR, Erevan. Translated from Neirofiziologiya, Vol. 11, No. 1, pp. 3–10, January–February, 1979.     

Visual analysis in unspecialized receptive fields as an orthogonal series expansion

It was postulated on the basis of results obtained by investigating retinal receptive fields of cats that experimental data reflecting the pattern of sensitivity of the receptive field coincide with certain orthogonal polynomials. These special functions have certain properties which can be regarded as spatial characteristics of the receptive fields whose differential sensitivity they describe. Within the framework of the suggested hypothesis visual analysis in the retina from the mathematical point of view can be regarded as a process of expansion of the curve of spatial distribution of brightness within the receptive fields in an orthogonal series. Physiologically speaking the retinal receptive fields can be interpreted as filters distinguishing an elementary orthogonal harmonic from the signal. This method of analysis results in maximal economy of the coding of visual information in the retina. The concepts put forward provide a fresh explanation of a number of physiological facts and they provide precise quantitative evaluations of the response of the receptive field to an arbitrary stimulus.     

Stimulus size selectivity and receptive field organization of ectostriatal neurons in the pigeon

The avian ectostriatum is the telencephalic recipient zone of the tectofugal pathway, which may be homologous to the colliculo-pulvinar-cortical pathway in mammals. The present paper studies the visual response properties and receptive field organization of ectostriatal cells in pigeons with extracellular recording and computer mapping techniques. The results indicate that 90% of ectostriatal cells prefer forward, downward and upward motion of visual stimuli at velocities in the range of 16-128 degrees s(-1). They respond optimally to small stimuli (1-4 degrees visual angle), mostly preferring a target of 2 degrees. Most cells (78.8%) have one excitatory receptive field that usually possesses one or two hotspots, some cells (13.5%) have two excitatory receptive fields each having one or two hotspots, and a few cells (7.7%) have one excitatory receptive field with an unresponsive region in the center. An inhibitory receptive field is not found surrounding the excitatory receptive field in the ectostriatal cells examined. These response properties and receptive field organization may reflect the possible roles of the ectostriatum in stimulus discrimination and visual cognition.     

Discriminative Learning of Receptive Fields from Responses to Non-Gaussian Stimulus Ensembles

Analysis of sensory neurons'' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron''s receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron''s receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design.     

‘Vector white noise’: a technique for mapping the motion receptive fields of direction-selective visual neurons

A technique is described and tested for mapping the sensitivities and preferred directions of motion at different locations within the receptive fields of direction-selective motion-detecting visual neurons. The procedure is to record the responses to a number of visual stimuli, each stimulus presentation consisting of a set of short, randomly-oriented, moving bars arranged in a square grid. Each bar moves perpendicularly to its long axis. The vector describing the sensitivity and preferred direction of motion at each grid location is obtained as a sum of the unit vectors defining the directions of motion of the bars in each of the stimuli at that location, weighted by the strengths of the corresponding responses. The resulting vector field specifies the optimum flow field for the neuron. The advantage of this technique over the conventional approach of probing the receptive field sequentially at each grid location is that the parallel nature of the stimulus is sensitive to nonlinear interactions (such as shunting inhibition for mutual facilitation) between different regions of the visual field. The technique is used to determine accurately the motion receptive fields of direction-selective motion detecting neurons in the optic lobes of insects. It is potentially applicable to motion-sensitive neurons with highly structured receptive fields, such as those in the optic tectum of the pigeon or in area MST of the monkey.     

Receptive field properties of neurons in the electrosensory lateral line lobe of the weakly electric fish, <Emphasis Type="Italic">Gnathonemus petersii</Emphasis>

The receptive field of a sensory neuron is known as that region in sensory space where a stimulus will alter the response of the neuron. We determined the spatial dimensions and the shape of receptive fields of electrosensitive neurons in the medial zone of the electrosensory lateral line lobe of the African weakly electric fish, Gnathonemus petersii, by using single cell recordings. The medial zone receives input from sensory cells which encode the stimulus amplitude. We analysed the receptive fields of 71 neurons. The size and shape of the receptive fields were determined as a function of spike rate and first spike latency and showed differences for the two analysis methods used. Spatial diameters ranged from 2 to 36 mm (spike rate) and from 2.45 to 14.12 mm (first spike latency). Some of the receptive fields were simple consisting only of one uniform centre, whereas most receptive fields showed a complex and antagonistic centre-surround organisation. Several units had a very complex structure with multiple centres and surrounding-areas. While receptive field size did not correlate with peripheral receptor location, the complexity of the receptive fields increased from rostral to caudal along the fish's body.     

Correlation of spatial event plots with simulated population responses of mechanoreceptive fibers

The experimental setup for generating spatial event plots (SEPs) from single mechanoreceptive fibers of the skin was computationally simulated. The generic fibers used in the simulations were similar to the rapidly adapting fibers (RAs), and had variable refractoriness and receptive-field size. The speed, lateral shift, and the contact width of the drum scanned across the receptive field of the fiber are adjustable parameters. The stimulus patterns used on the drum mimicked stimuli used by several other investigators. These were dot patterns, grating patterns, and the letter "E". First, the effects of simulation parameters on the SEPs were studied. The simulation output confirms the results of physiological experiments that SEPs contain information on the spatiotemporal resolution of the fiber. The next series of simulations involved generating SEPs of fibers obtained from the same or varying spatial distributions of receptive fields. Three hypothetical distributions were used: homogeneous rectangular, uniformly random, and Gaussian. The momentary population response at each case was found using the technique by Johansson and Vallbo (Brain Res 184: 353-366, 1980). The population responses were not isomorphic images of the stimulus patterns due to the variations in field sizes and locations. However, every fiber, no matter which distribution it came from, generated almost identical SEPs given similar response properties. Furthermore, the SEPs looked like the outline of the stimulus. These observations show that SEPs do not contain information about the population response. Therefore, reconstructing the population response using SEPs can result in misleading conclusions on central-nervous-system processing and should be viewed cautiously when formulating psychophysical/physiological linking hypotheses.     

Rabbit visual cortical neurons with simple and complex receptive fields

Receptive fields of neurons of the rabbit visual cortex selective for stimulus orientation were investigated. These receptive fields were less well differentiated than those of the analogous neurons of the cat visual cortex (large in size and circular in shape). Two mechanisms of selectivity for stimulus orientation were observed: inhibition between on and off zones of the receptive field (sample type) and oriented lateral inhibition within the same zone of the receptive field (complex type). Lateral inhibition within the same zone of the receptive field also took place in unselective neurons; "complex" selective neurons differed from them in the orientation of this inhibition. A combination of both mechanisms was possible in the receptive field of the same neuron. It is suggested that both simple and complex receptive fields are derivatives of unselective receptive fields and that "complex" neurons are not the basis for a higher level of analysis of visual information than in "simple" neurons.A. N. Severtsov Institute of Evolutionary Morphology and Ecology of Animals, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 10, No. 1, pp. 13–21, January–February, 1978.     

Relationship between Size Summation Properties,Contrast Sensitivity and Response Latency in the Dorsomedial and Middle Temporal Areas of the Primate Extrastriate Cortex

Analysis of the physiological properties of single neurons in visual cortex has demonstrated that both the extent of their receptive fields and the latency of their responses depend on stimulus contrast. Here, we explore the question of whether there are also systematic relationships between these response properties across different cells in a neuronal population. Single unit recordings were obtained from the middle temporal (MT) and dorsomedial (DM) extrastriate areas of anaesthetized marmoset monkeys. For each cell, spatial integration properties (length and width summation, as well as the presence of end- and side-inhibition within 15° of the receptive field centre) were determined using gratings of optimal direction of motion and spatial and temporal frequencies, at 60% contrast. Following this, contrast sensitivity was assessed using gratings of near-optimal length and width. In both areas, we found a relationship between spatial integration and contrast sensitivity properties: cells that summated over smaller areas of the visual field, and cells that displayed response inhibition at larger stimulus sizes, tended to show higher contrast sensitivity. In a sample of MT neurons, we found that cells showing longer latency responses also tended to summate over larger expanses of visual space in comparison with neurons that had shorter latencies. In addition, longer-latency neurons also tended to show less obvious surround inhibition. Interestingly, all of these effects were stronger and more consistent with respect to the selectivity for stimulus width and strength of side-inhibition than for length selectivity and end-inhibition. The results are partially consistent with a hierarchical model whereby more extensive receptive fields require convergence of information from larger pools of “feedforward” afferent neurons to reach near-optimal responses. They also suggest that a common gain normalization mechanism within MT and DM is involved, the spatial extent of which is more evident along the cell’s preferred axis of motion.     

Are receptive fields of the visual cortex detectors or spatial frequency filters?

Besides its principal maximum, the spatial frequency characteristic curve of the complex visual cortical receptive field of curarized cats also has additional maxima and also negative regions, as predicted by the theory of piecewise Fourier analysis. Comparison of responses of the complex receptive field to sinusoidal gratings completely and incompletely contained in the field and comparison of responses to sinusoidal and square-wave gratings indicate that the receptive field, as a spatial frequency filter, has linear properties. The response of the complex receptive field rises with an increase in the number of periods of the sinusoidal grating. Several periods of optimal frequency match the complex field. Receptive fields tuned to a broad band of spatial frequencies were found in neuron columns. The results confirm the view that complex receptive fields are spatial frequency filters and not detectors.I. P. Pavlov Institute of Physiology, Academy of Sciences of the USSR, Leningrad. Translated from Neirofiziologiya, Vol. 11, No. 5, pp. 403–411, September–October, 1979.     

Unit responses of the squirrel visual cortex to shaped visual stimuli

Visual cortical unit responses of the squirrelSciurus vulgaris to shaped visual stimuli (stationary and moving spots and bands) were studied. Neurons responding selectively to the direction of stimulus movement and orientation of lines and those not responding selectively to these features were distinguished. Many neurons, whether responding selectively or not to movement direction, were specifically sensitive to high speeds of movement, of the order of hundreds of degrees per second. This selectivity in neurons responding selectively to movement direction persisted at these high speeds, despite the short time taken by the stimulus to move across the receptive field. Neurons responding selectively to line orientation were sensitive to lower speeds of stimulus movement — from units to tens of degrees per second. Neuronal sensitivity to high speeds of stimulus movement is achieved through rapid summation of excitation from large areas of the receptive field crossed by the fast-moving stimulus. Selectivity of the response to movement direction is produced under these conditions with the aid of directed short-latency inhibition, inhibiting unit activity for stimulus movement in "zero" direction.