Characterizing auditory receptive fields

In this issue of Neuron, two papers by Atencio et al. and Nagel and Doupe adapt new computational methods to map the spectrotemporal response fields of neurons in the auditory cortex. The papers take different but complementary approaches to apply theoretical techniques to classical methods of receptive field mapping and, in doing so, provide exciting new insights into the way in which sounds are processed in the auditory cortex.     

Spatial summation processes in the receptive fields of visually driven neurons of the cat's cortical area 21a

The spatial summation in receptive fields (RF) of single neurons in cat's extrastriate area 21a was investigated as a basic neurophysiological substrate for central integration processing of visual information. The results showed that the majority of investigated neurons changed their response patterns with gradual increase of applied stimulus size. In approximately 82% of cases the suppression of neuron discharges was observed when the length of the moving strip exceeded that of the RF. In some neurons the increased size of the moving stimulus leads to the changes in the RF substructure. Receptive fields of neurons recorded at the same microelectrode penetration depth showed a great variety of RF superpositions distributed in a spatially asymmetric manner. As a result, every single RF consists of multiple sub-regions within the RF, differing from each other by the number of superimposed RF-s (density factor). We suggest that such complex spatial organization of the RF provides the neurophysiological basis for central integration processing of the visual information.     

Hypothesis on acoustic receptive fields

A hypothesis of acoustic receptive fields is studied, which is based on the fact that the cochlea of the internal ear is a wave guide with traveling waves and the resonance in the critical layer. When a harmonic sound influences the ear, the traveling wave reaches the critical layer for the corresponding frequency and generates there a train of decaying waves about 25 periods in duration, which form a steep slope of the envelope. The funnel-shaped convergence of all neurones innervating the acoustic receptors of the Corti organ along the slope of the envelope gives rise to acoustic receptive fields. The hypothesis is consistent with some other experimental data. Such an acoustic receptive field makes it possible to use the whole train of waves in the critical layer to measure the frequency of the acting sinusoidal sound with the greatest possible accuracy. Similarly, a high accuracy of recognition of short-time sound pulses is provided, which could not be explained earlier.     

Recursive features of circular receptive fields

The distribution of excitability in retinal receptive fields may be well approximated by functions with recursive features. Physiological data do not exclude an implementation of recursive structures in the visual system. It is the most remarkable advantage of a recursive visual system, that cortical receptive fields tuned to different spatial frequencies will have an identical neuronal circuitry. Structural consequences for retina, LGN and visual cortex are discussed.     

A computational theory of visual receptive fields

A receptive field constitutes a region in the visual field where a visual cell or a visual operator responds to visual stimuli. This paper presents a theory for what types of receptive field profiles can be regarded as natural for an idealized vision system, given a set of structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world. These symmetry properties include (i) covariance properties under scale changes, affine image deformations, and Galilean transformations of space–time as occur for real-world image data as well as specific requirements of (ii) temporal causality implying that the future cannot be accessed and (iii) a time-recursive updating mechanism of a limited temporal buffer of the past as is necessary for a genuine real-time system. Fundamental structural requirements are also imposed to ensure (iv) mutual consistency and a proper handling of internal representations at different spatial and temporal scales. It is shown how a set of families of idealized receptive field profiles can be derived by necessity regarding spatial, spatio-chromatic, and spatio-temporal receptive fields in terms of Gaussian kernels, Gaussian derivatives, or closely related operators. Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation. Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations. There are very close similarities between receptive field profiles predicted from this scale-space theory and receptive field profiles found by cell recordings in biological vision. Among the family of receptive field profiles derived by necessity from the assumptions, idealized models with very good qualitative agreement are obtained for (i) spatial on-center/off-surround and off-center/on-surround receptive fields in the fovea and the LGN, (ii) simple cells with spatial directional preference in V1, (iii) spatio-chromatic double-opponent neurons in V1, (iv) space–time separable spatio-temporal receptive fields in the LGN and V1, and (v) non-separable space–time tilted receptive fields in V1, all within the same unified theory. In addition, the paper presents a more general framework for relating and interpreting these receptive fields conceptually and possibly predicting new receptive field profiles as well as for pre-wiring covariance under scaling, affine, and Galilean transformations into the representations of visual stimuli. This paper describes the basic structure of the necessity results concerning receptive field profiles regarding the mathematical foundation of the theory and outlines how the proposed theory could be used in further studies and modelling of biological vision. It is also shown how receptive field responses can be interpreted physically, as the superposition of relative variations of surface structure and illumination variations, given a logarithmic brightness scale, and how receptive field measurements will be invariant under multiplicative illumination variations and exposure control mechanisms.     

The receptive fields of Daphnia ommatidia.

1. The focal length and positions of the principal planes of an isolated Daphnia lens were determined, and the refractive index of the rhabdom was measured. 2. The lens can form an image, but this always lies well behind the rhabdom. This was confirmed by direct observation of images inside a clear-eye mutant Daphnia eye. 3. The rhabdom was shown to be unlikely to function as a waveguide, and a ray optics model is proposed to enable the prediction of ommatidial receptive fields from the lens data. 4. The predicted receptive fields have wide plateaus and steep sides, and there are virtually no totally blind gaps between neighbouring ommatidia.     

Two-dimensional substructure of MT receptive fields.

Neurons at progressively higher levels of the visual system have progressively larger, more complicated receptive fields, presumably constructed from simpler antecedent receptive fields. To study this hierarchical organization, we used sparse white noise to map receptive-field substructure (second order Wiener-like kernels) in an extrastriate motion processing area (MT) of alert monkeys. The maps revealed a clear substructure, on a spatial scale comparable to the receptive fields of the V1 inputs. There were both facilitatory and suppressive interactions that differed in spatial organization and time course. Directional interactions were remarkably precise over a very small spatial range, and reversed when successive stimuli reversed contrast--a neural correlate of "reverse phi" motion perception. The maps of some cells had an unexpected, curved shape, which challenges existing models for direction selectivity.     

Experience-dependent asymmetric shape of hippocampal receptive fields

We propose a novel parameter, namely, the skewness, or asymmetry, of the shape of a receptive field to characterize two properties of hippocampal place fields. First, a majority of hippocampal receptive fields on linear tracks are negatively skewed, such that during a single pass the firing rate is low as the rat enters the field but high as it exits. Second, while the place fields are symmetric at the beginning of a session, they become highly asymmetric with experience. Further experiments suggest that these results are likely to arise due to synaptic plasticity during behavior. Using a purely feed forward neural network model, we show that following repeated directional activation, NMDA-dependent long-term potentiation/long-term depotentiation (LTP/LTD) could result in an experience-dependent asymmetrization of receptive fields.     

Learning receptive fields using predictive feedback.

Previously, it was suggested that feedback connections from higher- to lower-level areas carry predictions of lower-level neural activities, whereas feedforward connections carry the residual error between the predictions and the actual lower-level activities [Rao, R.P.N., Ballard, D.H., 1999. Nature Neuroscience 2, 79-87.]. A computational model implementing the hypothesis learned simple cell receptive fields when exposed to natural images. Here, we use predictive feedback to explain tuning properties in medial superior temporal area (MST). We implement the hypothesis using a new, biologically plausible, algorithm based on matching pursuit, which retains all the features of the previous implementation, including its ability to efficiently encode input. When presented with natural images, the model developed receptive field properties as found in primary visual cortex. In addition, when exposed to visual motion input resulting from movements through space, the model learned receptive field properties resembling those in MST. These results corroborate the idea that predictive feedback is a general principle used by the visual system to efficiently encode natural input.     

Building better models of visual cortical receptive fields

Scientists usually study the receptive fields of visual cortical neurons by measuring responses to "optimal stimuli." In this issue of Neuron, Rust and colleagues have taken a promising alternative approach: build a receptive field model based on the cell responses to a stimulus subset and then use the model to predict responses to other stimuli.     

Spatiotemporal elements of macaque v1 receptive fields

Neurons in primary visual cortex (V1) are commonly classified as simple or complex based upon their sensitivity to the sign of stimulus contrast. The responses of both cell types can be described by a general model in which the outputs of a set of linear filters are nonlinearly combined. We estimated the model for a population of V1 neurons by analyzing the mean and covariance of the spatiotemporal distribution of random bar stimuli that were associated with spikes. This analysis reveals an unsuspected richness of neuronal computation within V1. Specifically, simple and complex cell responses are best described using more linear filters than the one or two found in standard models. Many filters revealed by the model contribute suppressive signals that appear to have a predominantly divisive influence on neuronal firing. Suppressive signals are especially potent in direction-selective cells, where they reduce responses to stimuli moving in the nonpreferred direction.     

Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus

We have developed a sparse mathematical representation of speech that minimizes the number of active model neurons needed to represent typical speech sounds. The model learns several well-known acoustic features of speech such as harmonic stacks, formants, onsets and terminations, but we also find more exotic structures in the spectrogram representation of sound such as localized checkerboard patterns and frequency-modulated excitatory subregions flanked by suppressive sidebands. Moreover, several of these novel features resemble neuronal receptive fields reported in the Inferior Colliculus (IC), as well as auditory thalamus and cortex, and our model neurons exhibit the same tradeoff in spectrotemporal resolution as has been observed in IC. To our knowledge, this is the first demonstration that receptive fields of neurons in the ascending mammalian auditory pathway beyond the auditory nerve can be predicted based on coding principles and the statistical properties of recorded sounds.     

Analysis and interpretation of quadratic models of receptive fields

In this protocol, we present a procedure to analyze and visualize models of neuronal input-output functions that have a quadratic, a linear and a constant term, to determine their overall behavior. The suggested interpretations are close to those given by physiological studies of neurons, making the proposed methods particularly suitable for the analysis of receptive fields resulting from physiological measurements or model simulations.     

Spectro-temporal receptive fields of auditory neurons in the grassfrog

The nature of the stimulus-response relation for single auditory neurons is reflected in the properties of the Pre-Event Stimulus Ensemble: the ensemble of stimuli, preceding the occurrence of an action potential (neural event). This paper describes methods to analyse the spectro-temporal properties of this ensemble. These methods are based on the analytic signal representation of acoustic signals and functionals derived from it: the instantaneous amplitude and instantaneous frequency and the dynamic power spectrum. The procedures have been applied to a number of extra-cellular single unit recordings from the grassfrog, Rana temporatia L., recorded during presentation of an ensemble of tonal stimuli. The outcome of this analysis describes the spectro-temporal receptive field of the neuron under the present stimulus conditions. The procedure, based on the dynamic power spectrum is applicable to an arbitrary stimulus ensemble, thus allowing a comparison of the spectrotemporal receptive fields for different types of stimuli.     

Cone contributions to cat retinal ganglion cell receptive fields

Extracellular microelectrode recordings were made from ganglion cells of the intact, in situ eyes of adult common domestic cats. Three different photopic systems, with peak spectral sensitivities at 450, 500, and 556 nm, were observed. All ganglion cells received input from a cone system with a peak spectral sensitivity of 556 nm. The blue-sensitive cone system was observed in about one-half of the ganglion cells studied. In each case the 450-nm cone system contributed to only one functional type of response, either ON or OFF, in the same cell. The other two photopic systems most often contributed to both the ON and OFF responses of an individual ganglion cell. In four cases the 450-nm cone system mediated responses that were opponent to those of the other two photopic systems. The third photopic mechanism has a peak spectral sensitivity at 500 nm and contributed to most receptive field surrounds and many receptive field centers. It is distinguished from the rod system by the occurrence of a break in both dark-adaptation curves and increment-sensitivity curves. No apparent differences in receptive field cone contributions between brisk-sustained and brisk-transient cells were seen.     

Predictions about chromatic receptive fields assuming random cone connections

We hypothesize that color vision depends on random connections between cones containing different pigments and neurons at higher levels in the macaque visual system. This hypothesis predicts the same types and proportions of chromatic receptive fields reported in the physiological literature at least up through the lateral geniculate nucleus. The results suggest that the specificity of connections demanded by the labelled-line model of color coding are unnecessary to account for current physiological data.     

Spectro-temporal receptive fields of auditory neurons in the grassfrog

The stimulus-event relation of single units in the auditory midbrain area, the torus semicircularis, of the anaesthetized grassfrog (Rana temporaria L.) during stimulation with a wide ensemble of natural stimuli, was analysed using first and second order statistical analysis techniques. The average stimulus preceding the occurrence of action potentials, in general, did not prove to give very informative results. The second order procedure consisted in the determination of the average dynamic power spectrum of the pre-event stimuli, following procedures as described elsewhere (Aertsen and Johannesma, 1980; Aertsen et al., 1980). The outcome of this analysis was filtered with the overall power spectrum of the complete stimulus ensemble in order to correct for its non-uniform spectral composition. The stimulus-filtered average pre-event dynamic spectrum gives a first indication of the spectro-temporal receptive field of a neuron under natural stimulus conditions. Results for a limited number of recordings are presented and, globally, compared to the outcome of an analogous analysis of experiments with tonal stimuli.