956 resultados para Receptive Fields


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Our percept of visual stability across saccadic eye movements may be mediated by presaccadic remapping. Just before a saccade, neurons that remap become visually responsive at a future field (FF), which anticipates the saccade vector. Hence, the neurons use corollary discharge of saccades. Many of the neurons also decrease their response at the receptive field (RF). Presaccadic remapping occurs in several brain areas including the frontal eye field (FEF), which receives corollary discharge of saccades in its layer IV from a collicular-thalamic pathway. We studied, at two levels, the microcircuitry of remapping in the FEF. At the laminar level, we compared remapping between layers IV and V. At the cellular level, we compared remapping between different neuron types of layer IV. In the FEF in four monkeys (Macaca mulatta), we identified 27 layer IV neurons with orthodromic stimulation and 57 layer V neurons with antidromic stimulation from the superior colliculus. With the use of established criteria, we classified the layer IV neurons as putative excitatory (n = 11), putative inhibitory (n = 12), or ambiguous (n = 4). We found that just before a saccade, putative excitatory neurons increased their visual response at the RF, putative inhibitory neurons showed no change, and ambiguous neurons increased their visual response at the FF. None of the neurons showed presaccadic visual changes at both RF and FF. In contrast, neurons in layer V showed full remapping (at both the RF and FF). Our data suggest that elemental signals for remapping are distributed across neuron types in early cortical processing and combined in later stages of cortical microcircuitry.

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Neuronal receptive fields (RFs) provide the foundation for understanding systems-level sensory processing. In early visual areas, investigators have mapped RFs in detail using stochastic stimuli and sophisticated analytical approaches. Much less is known about RFs in prefrontal cortex. Visual stimuli used for mapping RFs in prefrontal cortex tend to cover a small range of spatial and temporal parameters, making it difficult to understand their role in visual processing. To address these shortcomings, we implemented a generalized linear model to measure the RFs of neurons in the macaque frontal eye field (FEF) in response to sparse, full-field stimuli. Our high-resolution, probabilistic approach tracked the evolution of RFs during passive fixation, and we validated our results against conventional measures. We found that FEF neurons exhibited a surprising level of sensitivity to stimuli presented as briefly as 10 ms or to multiple dots presented simultaneously, suggesting that FEF visual responses are more precise than previously appreciated. FEF RF spatial structures were largely maintained over time and between stimulus conditions. Our results demonstrate that the application of probabilistic RF mapping to FEF and similar association areas is an important tool for clarifying the neuronal mechanisms of cognition.

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Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.

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Tactile discrimination performance depends on the receptive field (RF) size of somatosensory cortical (SI) neurons. Psychophysical masking effects can reveal the RF of an idealized "virtual" somatosensory neuron. Previous studies show that top-down factors strongly affect tactile discrimination performance. Here, we show that non-informative vision of the touched body part influences tactile discrimination by modulating tactile RFs. Ten subjects performed spatial discrimination between touch locations on the forearm. Performance was improved when subjects saw their forearm compared to viewing a neutral object in the same location. The extent of visual information was relevant, since restricted view of the forearm did not have this enhancing effect. Vibrotactile maskers were placed symmetrically on either side of the tactile target locations, at two different distances. Overall, masking significantly impaired discrimination performance, but the spatial gradient of masking depended on what subjects viewed. Viewing the body reduced the effect of distant maskers, but enhanced the effect of close maskers, as compared to viewing a neutral object. We propose that viewing the body improves functional touch by sharpening tactile RFs in an early somatosensory map. Top-down modulation of lateral inhibition could underlie these effects.

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Assessments of spinal nociceptive withdrawal reflexes can be used in human research both to evaluate the effect of analgesics and explore pain mechanisms related to sensitization. Before the reflex can be used as a clinical tool, normative values need to be determined in large scale studies. The aim of this study was to determine the reference values of spinal nociceptive reflexes and subjective pain thresholds (to single and repeated stimulation), and of the area of the reflex receptive fields (RRF) in 300 pain-free volunteers. The influences of gender, age, height, weight, body-mass index (BMI), body side of testing, depression, anxiety, catastrophizing and parameters of Short-Form 36 (SF-36) were analyzed by multiple regressions. The 95% confidence intervals were determined for all the tests as normative values. Age had a statistically and quantitatively significant impact on the subjective pain threshold to single stimuli. The reflex threshold to single stimulus was lower on the dominant compared to the non-dominant side. Depression had a negative impact on the subjective pain threshold to single stimuli. All the other analyses either did not reveal statistical significance or displayed quantitatively insignificant correlations. In conclusion, normative values of parameters related to the spinal nociceptive reflex were determined. This allows their clinical application for assessing central hyperexcitability in individual patients. The parameters investigated explore different aspects of sensitization processes that are largely independent of demographic characteristics, cognitive and affective factors.

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Widespread central hypersensitivity is present in chronic pain and contributes to pain and disability. According to animal studies, expansion of receptive fields of spinal cord neurons is involved in central hypersensitivity. We recently developed a method to quantify nociceptive receptive fields in humans using spinal withdrawal reflexes. Here we hypothesized that patients with chronic pelvic pain display enlarged reflex receptive fields. Secondary endpoints were subjective pain thresholds and nociceptive withdrawal reflex thresholds after single and repeated (temporal summation) electrical stimulation. 20 patients and 25 pain-free subjects were tested. Electrical stimuli were applied to 10 sites on the foot sole for evoking reflexes in the tibialis anterior muscle. The reflex receptive field was defined as the area of the foot (fraction of the foot sole) from which a muscle contraction was evoked. For the secondary endpoints, the stimuli were applied to the cutaneous innervation area of the sural nerve. Medians (25-75 percentiles) of fraction of the foot sole in patients and controls were 0.48 (0.38-0.54) and 0.33 (0.27-0.39), respectively (P=0.008). Pain and reflex thresholds after sural nerve stimulation were significantly lower in patients than in controls (P<0.001 for all measurements). This study provides for the first time evidence for widespread expansion of reflex receptive fields in chronic pain patients. It thereby identifies a mechanism involved in central hypersensitivity in human chronic pain. Reverting the expansion of nociceptive receptive fields and exploring the prognostic meaning of this phenomenon may become future targets of clinical research.

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A method for quantifying nociceptive withdrawal reflex receptive fields in human volunteers and patients is described. The reflex receptive field (RRF) for a specific muscle denotes the cutaneous area from which a muscle contraction can be evoked by a nociceptive stimulus. The method is based on random stimulations presented in a blinded sequence to 10 stimulation sites. The sensitivity map is derived by interpolating the reflex responses evoked from the 10 sites. A set of features describing the size and location of the RRF is presented based on statistical analysis of the sensitivity map within every subject. The features include RRF area, volume, peak location and center of gravity. The method was applied to 30 healthy volunteers. Electrical stimuli were applied to the sole of the foot evoking reflexes in the ankle flexor tibialis anterior. The RRF area covered a fraction of 0.57+/-0.06 (S.E.M.) of the foot and was located on the medial, distal part of the sole of the foot. An intramuscular injection into flexor digitorum brevis of capsaicin was performed in one spinal cord injured subject to attempt modulation of the reflex receptive field. The RRF area, RRF volume and location of the peak reflex response appear to be the most sensitive measures for detecting modulation of spinal nociceptive processing. This new method has important potential applications for exploring aspects of central plasticity in volunteers and patients. It may be utilized as a new diagnostic tool for central hypersensitivity and quantification of therapeutic interventions.

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Abstract. Receptive fields of retinal and other sensory neurons show a large variety of spatiotemporal linear and non linear types of responses to local stimuli. In visual neurons, these responses present either asymmetric sensitive zones or center-surround organization. In most cases, the nature of the responses suggests the existence of a kind of distributed computation prior to the integration by the final cell which is evidently supported by the anatomy. We describe a new kind of discrete and continuous filters to model the kind of computations taking place in the receptive fields of retinal cells. To show their performance in the analysis of diferent non-trivial neuron-like structures, we use a computer tool specifically programmed by the authors to that efect. This tool is also extended to study the efect of lesions on the whole performance of our model nets.

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Edge blur is an important perceptual cue, but how does the visual system encode the degree of blur at edges? Blur could be measured by the width of the luminance gradient profile, peak ^ trough separation in the 2nd derivative profile, or the ratio of 1st-to-3rd derivative magnitudes. In template models, the system would store a set of templates of different sizes and find which one best fits the `signature' of the edge. The signature could be the luminance profile itself, or one of its spatial derivatives. I tested these possibilities in blur-matching experiments. In a 2AFC staircase procedure, observers adjusted the blur of Gaussian edges (30% contrast) to match the perceived blur of various non-Gaussian test edges. In experiment 1, test stimuli were mixtures of 2 Gaussian edges (eg 10 and 30 min of arc blur) at the same location, while in experiment 2, test stimuli were formed from a blurred edge sharpened to different extents by a compressive transformation. Predictions of the various models were tested against the blur-matching data, but only one model was strongly supported. This was the template model, in which the input signature is the 2nd derivative of the luminance profile, and the templates are applied to this signature at the zero-crossings. The templates are Gaussian derivative receptive fields that covary in width and length to form a self-similar set (ie same shape, different sizes). This naturally predicts that shorter edges should look sharper. As edge length gets shorter, responses of longer templates drop more than shorter ones, and so the response distribution shifts towards shorter (smaller) templates, signalling a sharper edge. The data confirmed this, including the scale-invariance implied by self-similarity, and a good fit was obtained from templates with a length-to-width ratio of about 1. The simultaneous analysis of edge blur and edge location may offer a new solution to the multiscale problem in edge detection.

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Detection of a tactile stimulus on one finger is impaired when a concurrent stimulus (masker) is presented on an additional finger of the same or the opposite hand. This phenomenon is known to be finger-specific at the within-hand level. However, whether this specificity is also maintained at the between-hand level is not known. In four experiments, we addressed this issue by combining a Bayesian adaptive staircase procedure (QUEST) with a two-interval forced choice (2IFC) design in order to establish threshold for detecting 200ms, 100Hz sinusoidal vibrations applied to the index or little fingertip of either hand (targets). We systematically varied the masker finger (index, middle, ring, or little finger of either hand), while controlling the spatial location of the target and masker stimuli. Detection thresholds varied consistently as a function of the masker finger when the latter was on the same hand (Experiments 1 and 2), but not when on different hands (Experiments 3 and 4). Within the hand, detection thresholds increased for masker fingers closest to the target finger (i.e., middle>ring when the target was index). Between the hands, detection thresholds were higher only when the masker was present on any finger as compared to when the target was presented in isolation. The within hand effect of masker finger is consistent with the segregation of different fingers at the early stages of somatosensory processing, from the periphery to the primary somatosensory cortex (SI). We propose that detection is finger-specific and reflects the organisation of somatosensory receptive fields in SI within, but not between the hands.

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Many prefrontal (PF) neurons convey information about both an object’s identity (what) and its location (where). To explore how they represent conjunctions of what and where, we explored the receptive fields of their mnemonic activity (i.e., their “memory fields”) by requiring monkeys to remember both an object and its location at many positions throughout a wide portion of central vision. Many PF neurons conveyed object information and had highly localized memory fields that emphasized the contralateral, but not necessarily foveal, visual field. These results indicate that PF neurons can simultaneously convey precise location and object information and thus may play a role in constructing a unified representation of a visual scene.

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PURPOSE: To explore the effects of glaucoma and aging on low-spatial-frequency contrast sensitivity by using tests designed to assess performance of either the magnocellular (M) or parvocellular (P) visual pathways. METHODS: Contrast sensitivity was measured for spatial frequencies of 0.25 to 2 cyc/deg by using a published steady- and pulsed-pedestal approach. Sixteen patients with glaucoma and 16 approximately age-matched control subjects participated. Patients with glaucoma were tested foveally and at two midperipheral locations: (1) an area of early visual field loss, and (2) an area of normal visual field. Control subjects were assessed in matched locations. An additional group of 12 younger control subjects (aged 20-35 years) were also tested. RESULTS: Older control subjects demonstrated reduced sensitivity relative to the younger group for the steady (presumed M)- and pulsed (presumed P)-pedestal conditions. Sensitivity was reduced foveally and in the midperiphery across the spatial frequency range. In the area of early visual field loss, the glaucoma group demonstrated further sensitivity reduction relative to older control subjects across the spatial frequency range for both the steady- and pulsed-pedestal tasks. Sensitivity was also reduced in the midperipheral location of "normal" visual field for the pulsed condition. CONCLUSIONS: Normal aging results in a reduction of contrast sensitivity for the low-spatial-frequency-sensitive components of both the M and P pathways. Glaucoma results in a further reduction of sensitivity that is not selective for M or P function. The low-spatial-frequency-sensitive channels of both pathways, which are presumably mediated by cells with larger receptive fields, are approximately equivalently impaired in early glaucoma.

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The paradigm of computational vision hypothesizes that any visual function -- such as the recognition of your grandparent -- can be replicated by computational processing of the visual input. What are these computations that the brain performs? What should or could they be? Working on the latter question, this dissertation takes the statistical approach, where the suitable computations are attempted to be learned from the natural visual data itself. In particular, we empirically study the computational processing that emerges from the statistical properties of the visual world and the constraints and objectives specified for the learning process. This thesis consists of an introduction and 7 peer-reviewed publications, where the purpose of the introduction is to illustrate the area of study to a reader who is not familiar with computational vision research. In the scope of the introduction, we will briefly overview the primary challenges to visual processing, as well as recall some of the current opinions on visual processing in the early visual systems of animals. Next, we describe the methodology we have used in our research, and discuss the presented results. We have included some additional remarks, speculations and conclusions to this discussion that were not featured in the original publications. We present the following results in the publications of this thesis. First, we empirically demonstrate that luminance and contrast are strongly dependent in natural images, contradicting previous theories suggesting that luminance and contrast were processed separately in natural systems due to their independence in the visual data. Second, we show that simple cell -like receptive fields of the primary visual cortex can be learned in the nonlinear contrast domain by maximization of independence. Further, we provide first-time reports of the emergence of conjunctive (corner-detecting) and subtractive (opponent orientation) processing due to nonlinear projection pursuit with simple objective functions related to sparseness and response energy optimization. Then, we show that attempting to extract independent components of nonlinear histogram statistics of a biologically plausible representation leads to projection directions that appear to differentiate between visual contexts. Such processing might be applicable for priming, \ie the selection and tuning of later visual processing. We continue by showing that a different kind of thresholded low-frequency priming can be learned and used to make object detection faster with little loss in accuracy. Finally, we show that in a computational object detection setting, nonlinearly gain-controlled visual features of medium complexity can be acquired sequentially as images are encountered and discarded. We present two online algorithms to perform this feature selection, and propose the idea that for artificial systems, some processing mechanisms could be selectable from the environment without optimizing the mechanisms themselves. In summary, this thesis explores learning visual processing on several levels. The learning can be understood as interplay of input data, model structures, learning objectives, and estimation algorithms. The presented work adds to the growing body of evidence showing that statistical methods can be used to acquire intuitively meaningful visual processing mechanisms. The work also presents some predictions and ideas regarding biological visual processing.