Validation of a clinical aberrometer

How musical expertise shapes speech perception: evidence from auditory classification images

It is now well established that extensive musical training percolates to higher levels of cognition, such as speech processing. However, the lack of a precise technique to investigate the specific listening strategy involved in speech comprehension has made it difficult to determine how musicians' higher performance in non-speech tasks contributes to their enhanced speech comprehension. The recently developed Auditory Classification Image approach reveals the precise time-frequency regions used by participants when performing phonemic categorizations in noise. Here we used this technique on 19 non-musicians and 19 professional musicians. We found that both groups used very similar listening strategies, but the musicians relied more heavily on the two main acoustic cues, at the first formant onset and at the onsets of the second and third formants onsets. Additionally, they responded more consistently to stimuli. These observations provide a direct visualization of auditory plasticity resulting from extensive musical training and shed light on the level of functional transfer between auditory processing and speech perception.

Human pitch detectors are tuned on a fine scale, but are perceptually accessed on a coarse scale

Single neurons in auditory cortex display highly selective spectrotemporal properties: their receptive fields modulate over small fractions of an octave and integrate across temporal windows of 100-200 ms. We investigated how these characteristics impact auditory behavior. Human observers were asked to detect a specific sound frequency masked by broadband noise; we adopted an experimental design which required the engagement of frequency-selective mechanisms to perform above chance. We then applied psychophysical reverse correlation to derive spectrotemporal perceptual filters for the assigned task. We were able to expose signatures of neuronal-like spectrotemporal tuning on a scale of 1/10 octave and 50-100 ms, but detailed modeling of our results showed that observers were not able to rely on the explicit output of these channels. Instead, human observers pooled from a large bank of highly selective channels via a weighting envelope poorly tuned for frequency (on a scale of 1.5 octave) with sluggish temporal dynamics, followed by a highly nonlinear max-like operation. We conclude that human detection of specific frequencies embedded within complex sounds suffers from a high degree of intrinsic spectrotemporal uncertainty, resulting in low efficiency values (<1 %) for this perceptual ability. Signatures of the underlying neural circuitry can be exposed, but there does not appear to be a direct line for accessing individual neural channels on a fine scale.

The temporal weighting of loudness: effects of the level profile

In four experiments, we studied the influence of the level profile of time-varying sounds on temporal perceptual weights for loudness. The sounds consisted of contiguous wideband noise segments on which independent random-level perturbations were imposed. Experiment 1 showed that in sounds with a flat level profile, the first segment receives the highest weight (primacy effect). If, however, a gradual increase in level (fade-in) was imposed on the first few segments, the temporal weights showed a delayed primacy effect: The first unattenuated segment received the highest weight, while the fade-in segments were virtually ignored. This pattern argues against a capture of attention to the onset as the origin of the primacy effect. Experiment 2 demonstrated that listeners adjust their temporal weights to the level profile on a trial-by-trial basis. Experiment 3 ruled out potentially inferior intensity resolution at lower levels as the cause of the delayed primacy effect. Experiment 4 showed that the weighting patterns cannot be explained by perceptual segmentation of the sounds into a variable and a stable part. The results are interpreted in terms of memory and attention processes. We demonstrate that the prediction of loudness can be improved significantly by allowing for nonuniform temporal weights.

How inherently noisy is human sensory processing?

Like any physical information processing device, the human brain is inherently noisy: If a participant is presented with the same sensory stimulus multiple times and is asked to press one of two buttons in response to some property of the stimulus, the response may vary even though the stimulus did not. This response variability can be used to estimate the amount of so-called internal noise-that is, noise that is not present in the stimulus (such as random dynamic dots on the screen) but in the participant's brain. How large is this internally generated noise? We obtained >400 independent estimates on 40 participants for a range of protocols (yes/no, two-, four-, and eight-alternative forced choice), modalities (auditory and visual), attentional state, adaptation state, stimulus types (static, moving, stereoscopic), and other parameters (timing, size, contrast). Our final estimate at ~1.3 (units of external noise standard deviation) is generally somewhat larger than that previously inferred from smaller and less varied data sets. We discuss the impact of high levels of internal noise on a number of experimental and computational efforts aimed at understanding and characterizing human sensory processing.

Evidence for joint encoding of motion and disparity in human visual perception

Electrophysiological recordings have established that motion and disparity signals are jointly encoded by subpopulations of neurons in visual cortex. However, the question of whether these neurons play a perceptual role has proven challenging and remains open. To answer this question we combined two powerful psychophysical techniques: perceptual adaptation and reverse correlation. Our results provide a detailed picture of how visual information about motion and disparity is processed by human observers, and how this processing is modified by prolonged sensory stimulation. We were able to isolate two perceptual components: a separable component, supported by separate motion and disparity signals, and an inseparable joint component, supported by motion and disparity signals that are concurrently represented at the level of the same neural mechanism. Both components are involved in the perception of stimuli containing motion and disparity information in line with the known existence of corresponding neuronal subpopulations in visual cortex.

An efficient technique for revealing visual search strategies with classification images

We propose a novel variant of the classification image paradigm that allows us to rapidly reveal strategies used by observers in visual search tasks. We make use of eye tracking, 1/f noise, and a grid-like stimulus ensemble and also introduce a new classification taxonomy that distinguishes between foveal and peripheral processes. We tested our method for 3 human observers and two simple shapes used as search targets. The classification images obtained show the efficacy of the proposed method by revealing the features used by the observers in as few as 200 trials. Using two control experiments, we evaluated the use of naturalistic 1/f noise with classification images, in comparison with the more commonly used white noise, and compared the performance of our technique with that of an earlier approach without a stimulus grid.

Temporal dynamics of figure-ground segregation in human vision

The segregation of figure from ground is arguably one of the most fundamental operations in human vision. Neural signals reflecting this operation appear in cortex as early as 50 ms and as late as 300 ms after presentation of a visual stimulus, but it is not known when these signals are used by the brain to construct the percepts of figure and ground. We used psychophysical reverse correlation to identify the temporal window for figure-ground signals in human perception and found it to lie within the range of 100-160 ms. Figure enhancement within this narrow temporal window was transient rather than sustained as may be expected from measurements in single neurons. These psychophysical results prompt and guide further electrophysiological studies.

Visual noise reveals category representations

How are categories represented in human memory? Exemplar models assume that a category is represented by individual instances from that category that have been experienced. More generally, a category might be represented by multiple templates stored in memory. A new item is classified according to its similarity to these templates. Prototype models represent a category with a single summary abstraction (i.e., a single template), often the central tendency of the experienced items. A new item is classified according to its similarity to these category prototypes. Here, we show how a technique for correlating observers' responses with external noise can be used not only to distinguish single- from multiple-template representations, but also to induce the form of these templates. The technique is applied to two tasks requiring categorization of simple visual patterns; the results demonstrate that observers used multiple traces to represent their categories, and thus highlight the procedure's potential for use in more complex settings.