Biomedical subjects

Wim A van de Grind

Publications and source records attributed to Wim A van de Grind.

8 recordsLinked to original sources

PubMed2005

Spatio-temporal requirements for direction selectivity in area 18 and PMLS complex cells.

The spatio-temporal requirements for direction selectivity were studied in two extrastriate motion processing areas in the cat, area 18 and the posteromedial lateral suprasylvian cortex (PMLS). Direction, velocity and pixel size of random pixel arrays (RPA) were adjusted for each neuron and direction selectivity was measured as a function of step size and delay for a given optimal velocity. A subset of direction selective complex cells in area 18 was tuned to intermediate step size and delay combinations rather than the smoothest motion (band-pass cells). Other area 18 complex cells responded best to the smallest value of step size and delay (low-pass cells). Tuning varied with the pixel size of the RPA. Cells with tuning for smaller pixels favoured a preference for non-smooth motion. Area 18 cells with lower spatial resolution showed larger optimal and maximal step sizes. For a subset of the cells in area 18, we measured direction selectivity for extensive step-delay combinations, covering multiple velocities. Results showed that most cells were tuned to narrow range of step-delay combinations, and that the optimal step size was independent of temporal delay. Direction selective complex cells in PMLS were tuned to larger pixel sizes than those in area 18, although the distributions did overlap. In contrast to area 18, PMLS cells preferred the smoothest motion, irrespective of RPA pixel size.

Animals↗

PubMed2004

Dynamics of directional selectivity in area 18 and PMLS of the cat.

Visual latencies and temporal dynamics of area 18 and PMLS direction-selective complex cells were defined with a reverse correlation method. The method allowed us to analyze the time course of responses to motion steps, without confounding temporal integration effects. Several measures of response latency and direction tuning dynamics were quantified: optimal latency (OL), latency of first and last significant responses (FSR, LSR), the increase and decrease of direction sensitivity in time, and the change of direction tuning in time. FSR, OL and LSR values for PMLS and area 18 largely overlapped. The small differences in mean latencies (3-4 ms for FSR and OL and 11.9 ms for the LSR) were not statistically significant. All cells in area 18 and the vast majority of cells in PMLS showed no systematic changes in preferred direction (monophasic neurons). In PMLS 5 out of 41 cells showed a reversal of preferred direction after approximately 56 ms relative to their OL (biphasic neurons). Monophasic cells showed no systematic changes in direction tuning width during the interval from FSR to LSR. In both areas, development of direction sensitivity was significantly faster than return to the non-direction sensitive state, but no significant difference was found between the two areas. We conclude that, for the monophasic type of direction-selective complex cells, the dynamics of primary motion processing are highly comparable for area 18 and PMLS. This suggests that motion information is predominantly processed in parallel, presumably based on input from the fast conducting thalamocortical Y-pathway.

Animals↗

PubMed2004

Storage for free: a surprising property of a simple gain-control model of motion aftereffects.

If a motion aftereffect (MAE) for given adaptation conditions has a duration T s, and the eyes are closed after adaptation during a waiting period tw=T s before testing, an unexpected MAE of a 'residual' duration TrT s is experienced. This effect is called 'storage' and it is often quantified by a storage factor sigma=TrT/T, which can reach values up to about 0.7-0.8. The phenomenon and its name have invited explanations in terms of inhibition of recovery during darkness. We present a model based on the opposite idea, that an effective test stimulus quickens recovery relative to darkness or other ineffective test stimuli. The model is worked out in mathematical detail and proves to explain 'storage' data from the literature, on the static MAE (sMAE: an MAE experienced for static test stimuli). We also present results of a psychophysical experiment with moving random pixel arrays, quantifying storage phenomena both for the sMAE and the dynamic MAE (dMAE: an MAE experienced for a random dynamic noise test stimulus). Storage factors for the dMAE are lower than for the sMAE. Our model also gives an excellent description of these new data on storage of the dMAE. The term 'storage' might therefore be a misnomer. If an effective test stimulus influences all direction tuned motion sensors indiscriminately and thus speeds up equalization of gains, one gets the storage phenomenon for free.

Adaptation, Ocular↗

PubMed2003

The motion reverse correlation (MRC) method: a linear systems approach in the motion domain.

We introduce the motion reverse correlation method (MRC), a novel stimulus paradigm based on a random sequence of motion impulses. The method is tailored to investigate the spatio-temporal dynamics of motion selectivity in cells responding to moving random dot patterns. Effectiveness of the MRC method is illustrated with results obtained from recordings in both anesthetized cats and an awake, fixating macaque monkey. Motion tuning functions are computed by reverse correlating the response of single cells with a rapid sequence of displacements of a random pixel array (RPA). Significant correlations between the cell's responses and various aspects of stimulus motion are obtained at high temporal resolution. These correlations provide a detailed description of the temporal dynamics of, for example, direction tuning and velocity tuning. In addition, with a spatial array of independently moving RPAs, the MRC method can be used to measure spatial as well as temporal receptive field properties. We demonstrate that MRC serves as a powerful and time-efficient tool for quantifying receptive field properties of motion selective cells that yields temporal information that cannot be derived from existing methods.

Animals↗

PubMed2003

Influence of viewing distance on aftereffects of moving random pixel arrays.

Viewing-distance invariance of visual perception has evolutionary advantages, but it is of necessity limited by spatial and temporal resolution. Even within these resolution limits viewing-distance invariance might not be perfect or even good, but there are remarkably few studies of its precise limits. Here we ask to what extent viewing-distance invariance holds for motion aftereffects (MAEs). There are (at least) two different MAEs: one can be seen on a static test pattern (sMAE) and is tuned to low speeds, the other only becomes manifest on a dynamic noise test stimulus (dMAE) and is sensitive to higher adaptation speeds. We show that each of these MAEs has a limited viewing-distance invariance, the dMAE only for higher screen-speeds and the sMAE only for lower screen-speeds. In both cases upper angular-speed limits shift to higher values for smaller viewing-distances (lower spatial frequencies, larger fields). This upper limit is constant, independent of viewing distance, if expressed in terms of screen-speed. On the other hand the lower speed limit is fixed in angular-speed and variable in screen-speed terms. Explanations for these findings are provided. We show that there is no fixed optimum viewing-distance or optimum angular stimulus-size for either of the two MAEs.

Computer Graphics↗

PubMed2003

Velocity dependence of the interocular transfer of dynamic motion aftereffects.

It is well established that motion aftereffects (MAEs) can show interocular transfer (IOT); that is, motion adaptation in one eye can give a MAE in the other eye. Different quantification methods and different test stimuli have been shown to give different IOT magnitudes, varying from no to almost full IOT. In this study, we examine to what extent IOT of the dynamic MAE (dMAE), that is the MAE seen with a dynamic noise test pattern, varies with velocity of the adaptation stimulus. We measured strength of dMAE by a nulling method. The aftereffect induced by adaptation to a moving random-pixel array was compensated (nulled), during a brief dynamic test period, by the same kind of motion stimulus of variable luminance signal-to-noise ratio (LSNR). The LSNR nulling value was determined in a Quest-staircase procedure. We found that velocity has a strong effect on the magnitude of IOT for the dMAE. For increasing speeds from 1.5 deg s(-1) to 24 deg s(-1) average IOT values increased about linearly from 18% to 63% or from 32% to 83%, depending on IOT definition. The finding that dMAEs transfer to an increasing extent as speed increases, suggests that binocular cells play a more dominant role at higher speeds.

Adaptation, Physiological↗

PubMedDate not supplied

On the velocity tuning of area 18 complex cell responses to moving textures.

Unlike simple cells, complex cells of area 18 give a directionally selective response to motion of random textures, indicating that they may play a special role in motion detection. We therefore investigated how texture motion, and especially its velocity, is represented by area 18 complex cells. Do these cells have separable spatial and temporal tunings or are these nonseparable? To answer this question, we measured responses to moving random pixel arrays as a function of both pixel size and velocity, for a set of 63 directionally selective complex cells. Complex cells generally responded to a fairly wide range of pixel sizes and velocities. Variations in pixel size of the random pixel array only caused minor changes in the cells' preferred velocity. For nearly all cells the data much better fitted a model in which pixel size and velocity act separately, than a model in which pixel size and velocity interact so as to keep temporal-frequency sensitivity constant. Our conclusion is that the studied population of special complex cells in area 18 are true motion detectors, rather than temporal-frequency tuned neurons.

Animals↗

PubMedDate not supplied

Temporal interactions in direction-selective complex cells of area 18 and the posteromedial lateral suprasylvian cortex (PMLS) of the cat.

Temporal interactions in direction-sensitive complex cells in area 18 and the posteromedial lateral suprasylvian cortex (PMLS) were studied using a reverse correlation method. Reverse correlograms to combinations of two temporally separated motion directions were examined and compared in the two areas. A comparison to the first-order reverse correlograms allowed us to identify nonlinear suppression or facilitation due to pairwise combinations of motion directions. Results for area 18 and PMLS were very different. Area 18 showed a single type of nonlinear behavior: similar directions facilitated and opposite directions suppressed spike probability. This effect was most pronounced for motion steps that followed each other immediately and decreased with increasing delay between steps. In PMLS, the picture was much more diverse. Some cells exhibited nonlinear interactions, that were opposite to those in area 18 (facilitation for opposite directions and suppression for similar ones), while the majority did not show a systematic interaction profile. We conclude that nonlinear second-order reverse correlation characteristics reveal different functional properties, despite similarities in the first-order reverse correlation profiles. Directional interactions in time revealed optimal integration of similar directions in area 18, but motion opponency--at least in some cells--in PMLS.

Animals↗