Selectivity of N170 for visual words in the right hemisphere: Evidence from single-trial analysis.

Neuroimaging and neuropsychological studies have identified the involvement of the right posterior region in the processing of visual words. Interestingly, in contrast, ERP studies of the N170 typically demonstrate selectivity for words more strikingly over the left hemisphere. Why is right hemisphere selectivity for words during the N170 epoch typically not observed, despite the clear involvement of this region in word processing? One possibility is that amplitude differences measured on averaged ERPs in previous studies may have been obscured by variation in peak latency across trials. This study examined this possibility by using single-trial analysis. Results show that words evoked greater single-trial N170s than control stimuli in the right hemisphere. Additionally, we observed larger trial-to-trial variability on N170 peak latency for words as compared to control stimuli over the right hemisphere. Results demonstrate that, in contrast to much of the prior literature, the N170 can be selective to words over the right hemisphere. This discrepancy is explained in terms of variability in trial-to-trial peak latency for responses to words over the right hemisphere.

Training by visual identification and writing leads to different visual word expertise N170 effects in preliterate Chinese children.

The N170 component of EEG evoked by visual words is an index of perceptual expertise for the visual word across different writing systems. In the present study, we investigated whether these N170 markers for Chinese, a very complex script, could emerge quickly after short-term learning (∼ 100 min) in young Chinese children, and whether early writing experience can enhance the acquisition of these neural markers for expertise. Two groups of preschool children received visual identification and free writing training respectively. Short-term character training resulted in selective enhancement of the N170 to characters, consistent with normal expert processing. Visual identification training resulted in increased N170 amplitude to characters in the right hemisphere, and N170 amplitude differences between characters and faces were decreased; whereas the amplitude difference between characters and tools increased. Writing training led to the disappearance of an initial amplitude difference between characters and faces in the right hemisphere. These results show that N170 markers for visual expertise emerge rapidly in young children after word learning, independent of the type of script young children learn; and visual identification and writing produce different effects.

Comparing face processing strategies between typically-developed observers and observers with autism using sub-sampled-pixels presentation in response classification technique.

In the present study we modified the standard classification image method by subsampling visual stimuli to provide us with a technique capable of examining an individual's face-processing strategy in detail with fewer trials. Experiment 1 confirmed that one testing session (1450 trials) was sufficient to produce classification images that were qualitatively similar to those obtained previously with 10,000 trials (Sekuler et al., 2004). Experiment 2 used this method to compare classification images obtained from observers with autism spectrum disorders (ASD) and typically-developing (TD) observers. As was found in Experiment 1, classification images obtained from TD observers suggested that they all discriminated faces based on information conveyed by pixels in the eyes/brow region. In contrast, classification images obtained from ASD observers suggested that they used different perceptual strategies: three out of five ASD observers used a typical strategy of making use of information in the eye/brow region, but two used an atypical strategy that relied on information in the forehead region. The advantage of using the response classification technique is that there is no restriction to specific theoretical perspectives or a priori hypotheses, which enabled us to see unexpected strategies, like ASD's forehead strategy, and thus showed this technique is particularly useful in the examination of special populations.

Modeling Single-Trial ERP Reveals Modulation of Bottom-Up Face Visual Processing by Top-Down Task Constraints (in Some Subjects).

We studied how task constraints modulate the relationship between single-trial event-related potentials (ERPs) and image noise. Thirteen subjects performed two interleaved tasks: on different blocks, they saw the same stimuli, but they discriminated either between two faces or between two colors. Stimuli were two pictures of red or green faces that contained from 10 to 80% of phase noise, with 10% increments. Behavioral accuracy followed a noise dependent sigmoid in the identity task but was high and independent of noise level in the color task. EEG data recorded concurrently were analyzed using a single-trial ANCOVA: we assessed how changes in task constraints modulated ERP noise sensitivity while regressing out the main ERP differences due to identity, color, and task. Single-trial ERP sensitivity to image phase noise started at about 95-110 ms post-stimulus onset. Group analyses showed a significant reduction in noise sensitivity in the color task compared to the identity task from about 140 ms to 300 ms post-stimulus onset. However, statistical analyses in every subject revealed different results: significant task modulation occurred in 8/13 subjects, one showing an increase and seven showing a decrease in noise sensitivity in the color task. Onsets and durations of effects also differed between group and single-trial analyses: at any time point only a maximum of four subjects (31%) showed results consistent with group analyses. We provide detailed results for all 13 subjects, including a shift function analysis that revealed asymmetric task modulations of single-trial ERP distributions. We conclude that, during face processing, bottom-up sensitivity to phase noise can be modulated by top-down task constraints, in a broad window around the P2, at least in some subjects.

Reliability of ERP and single-trial analyses.

A reliable measure is one we can trust in the long run. Thus, the reliability of measurements is as important as their validity. Here we investigated the reliability of brain electrical visual evoked responses to faces and noise textures. For the first time, we provide reliability measures for the full time course of event-related potentials (ERPs). Our analyses were also performed on a R(2)(t) metric that reflects results from single-trial analyses, therefore providing the first reliability analysis of ERP single-trial analyses. Results show that ERPs and R(2)(t) are highly reliable (cross-correlation ~0.9, lag ~4/6ms, intra-class correlation ~0.9) but also idiosyncratic: ERPs and R(2)(t) are highly reproducible within subjects, who differ reliably from each other and the grand average across subjects. Consequently, grand averages, although highly reliable, can be misleading because they might not reflect the actual brain dynamic of any subjects.

Healthy aging delays scalp EEG sensitivity to noise in a face discrimination task.

We used a single-trial ERP approach to quantify age-related changes in the time-course of noise sensitivity. A total of 62 healthy adults, aged between 19 and 98, performed a non-speeded discrimination task between two faces. Stimulus information was controlled by parametrically manipulating the phase spectrum of these faces. Behavioral 75% correct thresholds increased with age. This result may be explained by lower signal-to-noise ratios in older brains. ERP from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The fit of the model, indexed by R(2), was computed at multiple post-stimulus time points. The time-course of the R(2) function showed significantly delayed noise sensitivity in older observers. This age effect is reliable, as demonstrated by test-retest in 24 subjects, and started about 120 ms after stimulus onset. Our analyses suggest also a qualitative change from a young to an older pattern of brain activity at around 47 ± 4 years old.

How do amplitude spectra influence rapid animal detection?

Amplitude spectra might provide information for natural scene classification. Amplitude does play a role in animal detection because accuracy suffers when amplitude is normalized. However, this effect could be due to an interaction between phase and amplitude, rather than to a loss of amplitude-only information. We used an amplitude-swapping paradigm to establish that animal detection is partly based on an interaction between phase and amplitude. A difference in false alarms for two subsets of our distractor stimuli suggests that the classification of scene environment (man-made versus natural) may also be based on an interaction between phase and amplitude. Examples of interaction between amplitude and phase are discussed.

Age-related delay in information accrual for faces: evidence from a parametric, single-trial EEG approach.

BACKGROUND: In this study, we quantified age-related changes in the time-course of face processing by means of an innovative single-trial ERP approach. Unlike analyses used in previous studies, our approach does not rely on peak measurements and can provide a more sensitive measure of processing delays. Young and old adults (mean ages 22 and 70 years) performed a non-speeded discrimination task between two faces. The phase spectrum of these faces was manipulated parametrically to create pictures that ranged between pure noise (0% phase information) and the undistorted signal (100% phase information), with five intermediate steps. RESULTS: Behavioural 75% correct thresholds were on average lower, and maximum accuracy was higher, in younger than older observers. ERPs from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The earliest age-related ERP differences occurred in the time window of the N170. Older observers had a significantly stronger N170 in response to noise, but this age difference decreased with increasing phase information. Overall, manipulating image phase information had a greater effect on ERPs from younger observers, which was quantified using a hierarchical modelling approach. Importantly, visual activity was modulated by the same stimulus parameters in younger and older subjects. The fit of the model, indexed by R2, was computed at multiple post-stimulus time points. The time-course of the R2 function showed a significantly slower processing in older observers starting around 120 ms after stimulus onset. This age-related delay increased over time to reach a maximum around 190 ms, at which latency younger observers had around 50 ms time lead over older observers. CONCLUSION: Using a component-free ERP analysis that provides a precise timing of the visual system sensitivity to image structure, the current study demonstrates that older observers accumulate face information more slowly than younger subjects. Additionally, the N170 appears to be less face-sensitive in older observers.

The effects of face inversion and contrast-reversal on efficiency and internal noise.

Inverted and contrast-reversed faces are identified less accurately and less rapidly than normal, upright faces. The effects of inversion and contrast-reversal may reflect different sampling strategies and/or different levels of internal noise. To test these alternative hypotheses, we used a combination of noise-masking and response-consistency techniques to measure the internal noise and high-noise efficiency associated with the identification of upright, inverted, and contrast-reversed faces. We found that both face inversion and contrast-reversal reduced efficiency, but did not change internal noise.

Inversion leads to quantitative, not qualitative, changes in face processing.

Humans are remarkably adept at recognizing objects across a wide range of views. A notable exception to this general rule is that turning a face upside down makes it particularly difficult to recognize. This striking effect has prompted speculation that inversion qualitatively changes the way faces are processed. Researchers commonly assume that configural cues strongly influence the recognition of upright, but not inverted, faces. Indeed, the assumption is so well accepted that the inversion effect itself has been taken as a hallmark of qualitative processing differences. Here, we took a novel approach to understand the inversion effect. We used response classification to obtain a direct view of the perceptual strategies underlying face discrimination and to determine whether orientation effects can be explained by differential contributions of nonlinear processes. Inversion significantly impaired performance in our face discrimination task. However, surprisingly, observers utilized similar, local regions of faces for discrimination in both upright and inverted face conditions, and the relative contributions of nonlinear mechanisms to performance were similar across orientations. Our results suggest that upright and inverted face processing differ quantitatively, not qualitatively; information is extracted more efficiently from upright faces, perhaps as a by-product of orientation-dependent expertise.