The timing mega-study: comparing a range of experiment generators, both lab-based and online.

Many researchers in the behavioral sciences depend on research software that presents stimuli, and records response times, with sub-millisecond precision. There are a large number of software packages with which to conduct these behavioral experiments and measure response times and performance of participants. Very little information is available, however, on what timing performance they achieve in practice.

Measuring nonlinear signal combination using EEG.

Relatively little is known about the processes, both linear and nonlinear, by which signals are combined beyond V1. By presenting two stimulus components simultaneously, flickering at different temporal frequencies (frequency tagging) while measuring steady-state visual evoked potentials, we can assess responses to the individual components, including direct measurements of suppression on each other, and various nonlinear responses to their combination found at intermodulation frequencies. The result is a rather rich dataset of frequencies at which responses can be found.

Cue Combination of Conflicting Color and Luminance Edges.

Abrupt changes in the color or luminance of a visual image potentially indicate object boundaries. Here, we consider how these cues to the visual "edge" location are combined when they conflict. We measured the extent to which localization of a compound edge can be predicted from a simple maximum likelihood estimation model using the reliability of chromatic (L-M) and luminance signals alone.

Understanding mid-level representations in visual processing.

It is clear that early visual processing provides an image-based representation of the visual scene: Neurons in Striate cortex (V1) encode nothing about the meaning of a scene, but they do provide a great deal of information about the image features within it. The mechanisms of these "low-level" visual processes are relatively well understood. We can construct plausible models for how neurons, up to and including those in V1, build their representations from preceding inputs down to the level of photoreceptors.

Is it just motion that silences awareness of other visual changes?

When an array of visual elements is changing color, size, or shape incoherently, the changes are typically quite visible even when the overall color, size, or shape statistics of the field may not have changed. When the dots also move, however, the changes become much less apparent; awareness of them is "silenced" (Suchow & Alvarez, 2011). This finding might indicate that the perception of motion is of particular importance to the visual system, such that it is given priority in processing over other forms of visual change.

Luminance cues constrain chromatic blur discrimination in natural scene stimuli.

Introducing blur into the color components of a natural scene has very little effect on its percept, whereas blur introduced into the luminance component is very noticeable. Here we quantify the dominance of luminance information in blur detection and examine a number of potential causes. We show that the interaction between chromatic and luminance information is not explained by reduced acuity or spatial resolution limitations for chromatic cues, the effective contrast of the luminance cue, or chromatic and achromatic statistical regularities in the images.

Transfer of perceptual learning between different visual tasks.

Practice in most sensory tasks substantially improves perceptual performance. A hallmark of this 'perceptual learning' is its specificity for the basic attributes of the trained stimulus and task. Recent studies have challenged the specificity of learned improvements, although transfer between substantially different tasks has yet to be demonstrated.

Using evolutionary algorithms for fitting high-dimensional models to neuronal data.

In the study of neurosciences, and of complex biological systems in general, there is frequently a need to fit mathematical models with large numbers of parameters to highly complex datasets. Here we consider algorithms of two different classes, gradient following (GF) methods and evolutionary algorithms (EA) and examine their performance in fitting a 9-parameter model of a filter-based visual neuron to real data recorded from a sample of 107 neurons in macaque primary visual cortex (V1). Although the GF method converged very rapidly on a solution, it was highly susceptible to the effects of local minima in the error surface and produced relatively poor fits unless the initial estimates of the parameters were already very good.

The timing of binding and segregation of two compound aftereffects.

Temporal information in a scene is thought to be an important cue for visual grouping of local image features into a single object. The majority of studies on this topic have attempted to determine the conditions that facilitate segregation of a figure from a cluttered background. Here we examine the temporal characteristics of two aftereffects that appear to have roles in visual integration: the curvature aftereffect (CAE; Hancock & Peirce, 2008) and plaid-selective contrast adaptation (Peirce & Taylor, 2006).

Ameliorating the combinatorial explosion with spatial frequency-matched combinations of V1 outputs.

Little is known about the way in which the outputs of early orientation-selective neurons are combined. One particular problem is that the number of possible combinations of these outputs greatly outweighs the number of processing units available to represent them. Here we consider two of the possible ways in which the visual system might reduce the impact of this problem.

Global shape processing: which parts form the whole?

Research suggests that detection of low-frequency radial frequency (RF) patterns involves global shape processing and that points of maximum curvature (corners) contribute more than points of minimum curvature (sides). However, this has only been tested with stimuli presented at the threshold of discriminability from a circle. We used RF pattern adaptation to (a) examine whether a supra-threshold RF pattern is processed as a global shape and (b) determine what the critical features are for representing its shape.

A comparison of fMRI adaptation and multivariate pattern classification analysis in visual cortex.

Functional magnetic resonance imaging (fMRI) has become a ubiquitous tool in cognitive neuroscience. The technique allows noninvasive measurements of cortical responses in the human brain, but only on the millimeter scale. Because a typical voxel contains many thousands of neurons with varied properties, establishing the selectivity of their responses directly is impossible.

Generating Stimuli for Neuroscience Using PsychoPy.

PsychoPy is a software library written in Python, using OpenGL to generate very precise visual stimuli on standard personal computers. It is designed to allow the construction of as wide a variety of neuroscience experiments as possible, with the least effort. By writing scripts in standard Python syntax users can generate an enormous variety of visual and auditory stimuli and can interact with a wide range of external hardware (enabling its use in fMRI, EEG, MEG etc.

Selective mechanisms for simple contours revealed by compound adaptation.

Neurons in the early stages of visual processing are often thought of as edge detectors for different orientations. Here we investigate the existence of detectors for specific combinations of edges-detectors for specific curvatures. Previous attempts to demonstrate such detectors through aftereffects have ultimately been explained by adaptation to local orientation rather than curvature per se.

Cortical representation of color is binocular.

It is widely believed that the cortical mechanisms of color vision are monocular because stereopsis is poor for isoluminant patterns. By measuring and comparing the chromatic tuning of binocular and monocular neurons in cortical areas V1 and V2 of macaque, we show that this is not the case. Not only are many color-preferring cells in early visual cortex well-driven binocularly, but their color preferences are unusually well-matched in the two eyes.

The potential importance of saturating and supersaturating contrast response functions in visual cortex.

Most cortical visual neurons do not respond linearly with contrast. Generally, they show saturated responses to stimuli of high contrast, a feature often characterized by a divisive normalization function. This nonlinearity is generally thought to be useful in focusing the dynamic response range of the neuron on a particular region of contrast space, optimizing contrast gain.

Two expressions of "surround suppression" in V1 that arise independent of cortical mechanisms of suppression.

The preferred stimulus size of a V1 neuron decreases with increases in stimulus contrast. It has been supposed that stimulus contrast is the primary determinant of such spatial summation in V1 cells, though the extent to which it depends on other stimulus attributes such as orientation and spatial frequency remains untested. We investigated this by recording from single cells in V1 of anaesthetized cats and monkeys, measuring size-tuning curves for high-contrast drifting gratings of optimal spatial configuration, and comparing these curves with those obtained at lower contrast or at sub-optimal orientations or spatial frequencies.

PsychoPy--Psychophysics software in Python.

The vast majority of studies into visual processing are conducted using computer display technology. The current paper describes a new free suite of software tools designed to make this task easier, using the latest advances in hardware and software. PsychoPy is a platform-independent experimental control system written in the Python interpreted language using entirely free libraries.

Profound contrast adaptation early in the visual pathway.

Prior exposure to a moving grating of high contrast led to a substantial and persistent reduction in the contrast sensitivity of neurons in the lateral geniculate nucleus (LGN) of macaque. This slow contrast adaptation was potent in all magnocellular (M) cells but essentially absent in parvocellular (P) cells and neurons that received input from S cones. Simultaneous recordings of M cells and the potentials of ganglion cells driving them showed that adaptation originated in ganglion cells.

The impact of suppressive surrounds on chromatic properties of cortical neurons.

Stimulation of the suppressive surround of a cortical neuron affects the responsivity and tuning of the classical receptive field (CRF) on several stimulus dimensions. In V1 and V2 of macaques prepared for acute electrophysiological experiments, we explored the chromatic sensitivity of the surround and its influence on the chromatic tuning of the CRF. We studied receptive fields of single neurons with patches of drifting grating of optimal spatial frequency and orientation and variable size, modulated along achromatic or isoluminant color directions.

Functional asymmetry in sheep temporal cortex.

Sheep, like humans, show a bias in favour of the left visual field when discriminating familiar faces. This, in humans, is thought to be caused by a right hemisphere dominance for processing faces involving the temporal cortex. We have directly investigated inter-hemispheric differences in face-processing in sheep by recording the frequencies and response profiles of single cells in the temporal cortex which respond selectively to faces.

Residual eye-movements in macaque and their effects on visual responses of neurons.

We recorded continuously, with high precision, the positions of the eyes in anesthetized macaque monkeys prepared for physiological recording. Most recordings were made after the infusion of muscle relaxant to immobilize the eyes; in some cases we also were able to record eye position for periods before the eyes were immobilized. In all monkeys, the eyes moved continuously by as much as 0.