Blobs versus bars:psychophysical evidence supports two types of orientation response in human color vision

The classic hypothesis of Livingstone and Hubel (1984, 1987) proposed two types of color pathways in primate visual cortex based on recordings from single cells: a segregated, modularpathway that signals color but provides little information about shape or form and a second pathway that signals color differences and so defines forms without the need to specify their colors. A major problem has been to reconcile this neurophysiological hypothesis with the behavioral data. A wealth of psychophysical studies has demonstrated that color vision has orientation-tuned responses and little impairment on form related tasks, but these have not revealed any direct evidence for nonoriented mechanisms. Here we use a psychophysical method of subthreshold summation across orthogonal orientations for isoluminant red-green gratings in monocular and dichoptic viewing conditions to differentiate between nonoriented and orientation-tuned responses to color contrast. We reveal nonoriented color responses at low spatial frequencies (0.25-0.375 c/deg) under monocular conditions changing to orientation-tuned responses at higher spatial frequencies (1.5 c/deg) and under binocular conditions. We suggest that two distinct pathways coexist in color vision at the behavioral level, revealed at different spatial scales: one is isotropic, monocular, and best equipped for the representation of surface color, and the other is orientation-tuned, binocular, and selective for shape and form. This advances our understanding of the organization of the neural pathways involved in human color vision and provides a strong link between neurophysiological and behavioral data

A reevaluation of achromatic spatio-temporal vision: nonoriented filters are monocular, they adapt, and can be used for decision making at high flicker speeds

Masking, adaptation, and summation paradigms have been used to investigate the characteristics of early spatio-temporal vision. Each has been taken to provide evidence for (i) oriented and (ii) nonoriented spatial-filtering mechanisms. However, subsequent findings suggest that the evidence for nonoriented mechanisms has been misinterpreted: those experiments might have revealed the characteristics of suppression (eg, gain control), not excitation, or merely the isotropic subunits of the oriented detecting mechanisms. To shed light on this, we used all three paradigms to focus on the ‘high-speed’ corner of spatio-temporal vision (low spatial frequency, high temporal frequency), where cross-oriented achromatic effects are greatest. We used flickering Gabor patches as targets and a 2IFC procedure for monocular, binocular, and dichoptic stimulus presentations. To account for our results, we devised a simple model involving an isotropic monocular filter-stage feeding orientation-tuned binocular filters. Both filter stages are adaptable, and their outputs are available to the decision stage following nonlinear contrast transduction. However, the monocular isotropic filters (i) adapt only to high-speed stimuli—consistent with a magnocellular subcortical substrate—and (ii) benefit decision making only for high-speed stimuli (ie, isotropic monocular outputs are available only for high-speed stimuli). According to this model, the visual processes revealed by masking, adaptation, and summation are related but not identical

Stochastic resonance and finite resolution in a network of leaky integrate-and-fire neurons.

This thesis is a study of stochastic resonance (SR) in a discrete implementation of a leaky integrate-and-fire (LIF) neuron network. The aim was to determine if SR can be realised in limited precision discrete systems implemented on digital hardware. How neuronal modelling connects with SR is discussed. Analysis techniques for noisy spike trains are described, ranging from rate coding, statistical measures, and signal processing measures like power spectrum and signal-to-noise ratio (SNR). The main problem in computing spike train power spectra is how to get equi-spaced sample amplitudes given the short duration of spikes relative to their frequency. Three different methods of computing the SNR of a spike train given its power spectrum are described. The main problem is how to separate the power at the frequencies of interest from the noise power as the spike train encodes both noise and the signal of interest. Two models of the LIF neuron were developed, one continuous and one discrete, and the results compared. The discrete model allowed variation of the precision of the simulation values allowing investigation of the effect of precision limitation on SR. The main difference between the two models lies in the evolution of the membrane potential. When both models are allowed to decay from a high start value in the absence of input, the discrete model does not completely discharge while the continuous model discharges to almost zero. The results of simulating the discrete model on an FPGA and the continuous model on a PC showed that SR can be realised in discrete low resolution digital systems. SR was found to be sensitive to the precision of the values in the simulations. For a single neuron, we find that SR increases between 10 bits and 12 bits resolution after which it saturates. For a feed-forward network with multiple input neurons and one output neuron, SR is stronger with more than 6 input neurons and it saturates at a higher resolution. We conclude that stochastic resonance can manifest in discrete systems though to a lesser extent compared to continuous systems

Effect of Background Synaptic Activity on Excitatory-Postsynaptic Potential-Spike Coupling

Neurons receive large amount of synaptic inputs in vivo, which may impact the coupling between EPSPs and spikes. We mimicked the in vivo synaptic activity of the cell with the dynamic clamp system. We recorded from pyramidal cells in neocortical slices in vitro to investigate how timing and probability of spike generation in response to an EPSP is affected by background synaptic conductance under these conditions. We found that near threshold, background synaptic conductance improved the precision of spike timing by reducing the depolarization-related prolongation of the EPSP. In cells with ongoing spike activity and background synaptic conductances, an EPSP rapidly increased the probability of firing. The time window of the spike probability increase was comparable to the EPSP rise time and was followed by a long period of reduced firing. We found that the net synaptic gain was determined not only by the amplitude of the EPSP, but also by the firing frequency of the cell. In addition, a background fluctuating conductance reduced the time window of perturbation of spike patterns generated by EPSP related spikes. Taken together, these results indicate that in vivo, the level of the background synaptic activity may regulate spike-timing precision and affect synaptic gain

Form specific adaptation and pattern recognition: an experimental and theoretical study

Among the theories of visual pattern recognition are structural theories which propose that patterns are encoded in terras of features and their spatial relationships (relations). Structural theories are examined here with both adaptation and pattern recognition techniques. In particular, the effects of changes in the relational- structure of patterns formed from bear and disc features are examined. For this purpose a novel adaptation technique is developed and used for measurements of the contrast threshold elevation effect.Data are presented which show that the visual system is adaptationally sensitive to the shape of local features, but adaptationally insensitive to their relative positions. An exception to the latter conclusion was the finding of adaptational sensitivity to local periodicity. It is argued, however, that this periodicity sensitivity may simply be a result of size selectivity.Data are also presented which were obtained in a discrimination- under-uncertainty experiment in which stimuli analogous to those in the adaptation experiments were used. These data reveal sensitivity to local feature changes and insensitivity to feature relative- position changes. Because of the similarity in results from the adaptation and discrimination-under-uncertainty experiments it is argued that both techniques reveal the properties of the initial stages of pattern processing. It is also argued that these results show a fundamental difference in the way in which features and relations are processed prior to pattern recognition.To investigate how structural theories may be applied in a pattern recognition task a relational-structure encoding model is developed and its predicted pattern recognition performance is compared with experimental data. Once equipped with the capability of performing certain discrete operations on the relational-structure representation this model-provides a good fit to the experimental data

Towards linking perception research and image quality

Image quality as a general notion relates both to elementary and to complex visual functions. In this paper we deal with a few of them, which correspond to some lines of research at our Institute. We start with threshold predictions in time and space domains by means of elementary response functions, which have been recently developed considerably, although full generalization has not yet been achieved. As to suprathreshold stimuli, the responses of subjects usually have to be scaled. Here we deal with some problems connected with scaling techniques. After a brief discussion of the applicability of notions on visual conspicuity and visual search to image quality problems, we finally discuss reading from alphanumeric displays

The nature of anisotropy in gain control pools.

When observers view a naturalistic (l/f) broadband image, the various spatial components present in the image stimulate many detecting-mechanisms that suppress each other. This suppression is anisotropic, being relatively greater for mechanisms that detect horizontal components and least for oblique-detecting mechanisms (c.f., Essock et al., 2009; Haun & Essock, 2010; Kim et al., 2010), and leads to better sensitivity to and greater salience of obliquely-oriented structure when viewed in the presence of broadband background (the \u27horizontal effect\u27, Essock et al., 2003). It is thought that anisotropic suppression reflects a gain control mechanism whose output is intended to equalize the neural response to the orientation content biases in natural scenes. Here we further investigate the dependence of this gain control anisotropy on temporal and spatial frequency by measuring tuning properties of these pools. Experiment 1 evaluates (1) the shape and the peak suppression of temporal frequency tuning functions for grating targets at 10 fixed spatio-temporal combinations by varying the temporal frequency of the l/f broadband masks, and (2) whether the observed suppression show the horizontal effect. Experiment 2 evaluates the same properties for spatial frequency tuning. The results showed that multiple local gain control pools across the spatiotemporal locations are tuned in temporal frequency and spatial frequency, and all of these pools are stronger at horizontal. Surprisingly, results showed that multiple temporally tuned pools are revealed with a broadband mask, whereas prior studies using very narrowband masks have shown only 2 (or 3) temporally-tuned channels (e.g., Lehky, 1985; Hess & Snowden, 1992; Fredericksen & Hess, 1998; Cass & Alias, 2006; Cass et al., 2009). We proposed that to drive these pools, the use of an appropriate broadband mask which can rise above a certain detection threshold of each of the underlying many, unknown, and lesser sensitive temporal detectors is crucial, and thereby can create strong suppression between detectors tuned to similar temporal rates which form local (\u27 tuned \u27) pools