In pursuit of visual attention: SSVEP frequency-tagging moving targets.

Previous research has shown that visual attention does not always exactly follow gaze direction, leading to the concepts of overt and covert attention. However, it is not yet clear how such covert shifts of visual attention to peripheral regions impact the processing of the targets we directly foveate as they move in our visual field. The current study utilised the co-registration of eye-position and EEG recordings while participants tracked moving targets that were embedded with a 30 Hz frequency tag in a Steady State Visually Evoked Potentials (SSVEP) paradigm. When the task required attention to be divided between the moving target (overt attention) and a peripheral region where a second target might appear (covert attention), the SSVEPs elicited by the tracked target at the 30 Hz frequency band were significantly, but transiently, lower than when participants did not have to covertly monitor for a second target. Our findings suggest that neural responses of overt attention are only briefly reduced when attention is divided between covert and overt areas. This neural evidence is in line with theoretical accounts describing attention as a pool of finite resources, such as the perceptual load theory. Altogether, these results have practical implications for many real-world situations where covert shifts of attention may discretely reduce visual processing of objects even when they are directly being tracked with the eyes

How to use fMRI functional localizers to improve EEG/MEG source estimation

EEG and MEG have excellent temporal resolution, but the estimation of the neural sources that generate the signals recorded by the sensors is a difficult, ill-posed problem. The high spatial resolution of functional MRI makes it an ideal tool to improve the localization of the EEG/MEG sources using data fusion. However, the combination of the two techniques remains challenging, as the neural generators of the EEG/MEG and BOLD signals might in some cases be very different. Here we describe a data fusion approach that was developed by our team over the last decade in which fMRI is used to provide source constraints that are based on functional areas defined individually for each subject. This mini-review describes the different steps that are necessary to perform source estimation using this approach. It also provides a list of pitfalls that should be avoided when doing fMRI-informed EEG/MEG source imaging. Finally, it describes the advantages of using a ROI-based approach for group-level analysis and for the study of sensory systems

Separable effects of inversion and contrast-reversal on face detection thresholds and response functions:a sweep VEP study

The human brain rapidly detects faces in the visual environment. We recently presented a sweep visual evoked potential approach to objectively define face detection thresholds as well as suprathreshold response functions (Ales, Farzin, Rossion, & Norcia, 2012). Here we determined these parameters are affected by orientation (upright vs. inverted) and contrast polarity (positive vs. negative), two manipulations that disproportionately disrupt the perception of faces relative to other object categories. Face stimuli parametrically increased in visibility through phase - descrambling while alternating with scrambled images at a fixed presentation rate of 3 Hz (6 images/s). The power spectrum and mean luminance of all stimuli were equalized. As a face gradually emerged during a stimulation sequence, EEG responses at 3 Hz appeared at ≈ 35% phase coherence over right occipito-temporal channels, replicating previous observations. With inversion and contrast-reversal, the 3-Hz amplitude decreased by ≈ 20%-50% and the face detection threshold increased by ≈ 30%-60% coherence. Furthermore, while the 3-Hz response emerged abruptly and saturated quickly for normal faces, suggesting a categorical neural response, the response profile for inverted and negative polarity faces was shallower and more linear, indicating gradual and continuously increasing activation of the underlying neural population. These findings demonstrate that inversion and contrast-reversal increase the threshold and modulate the suprathreshold response function of face detection

L’image de Dieu dans le roman contemporain

Contrast polarity inversion (i.e., turning dark regions light and vice versa) impairs face perception. We investigated the perceptual asymmetry between positive and negative polarity faces (matched for overall luminance) using a sweep VEP approach in the context of face detection (Journal of Vision 12 (2012) 1– 18). Phase-scrambled face stimuli alternated at a rate of 3 Hz (6 images/s). The phase coherence of every other stimulus was parametrically increased so that a face gradually emerged over a 20-s stimulation sequence, leading to a 3 Hz response reflecting face detection. Contrary to the 6 Hz response, reflecting low-level visual processing, this 3 Hz response was larger and emerged earlier over right occipito-temporal channels for positive than negative polarity faces. Moreover, the 3 Hz response emerged abruptly to positive polarity faces, whereas it increased linearly for negative polarity faces. In another condition, alternating between a positive and a negative polarity face also elicited a strong 3 Hz response, indicating an asymmetrical representation of positive and negative polarity faces even at supra-threshold levels (i.e., when both stimuli were perceived as faces). Overall, these findings demonstrate distinct perceptual representations of positive and negative polarity faces, independently of low-level cues, and suggest qualitatively different detection processes (template-based matching for positive polarity faces vs. linear accumulation of evidence for negative polarity faces)

The effect of contrast polarity reversal on face detection:evidence of perceptual asymmetry from sweep VEP

Contrast polarity inversion (i.e., turning dark regions light and vice versa) impairs face perception. We investigated the perceptual asymmetry between positive and negative polarity faces (matched for overall luminance) using a sweep VEP approach in the context of face detection (Journal of Vision 12 (2012) 1-18). Phase-scrambled face stimuli alternated at a rate of 3. Hz (6. images/s). The phase coherence of every other stimulus was parametrically increased so that a face gradually emerged over a 20-s stimulation sequence, leading to a 3. Hz response reflecting face detection. Contrary to the 6. Hz response, reflecting low-level visual processing, this 3. Hz response was larger and emerged earlier over right occipito-temporal channels for positive than negative polarity faces. Moreover, the 3. Hz response emerged abruptly to positive polarity faces, whereas it increased linearly for negative polarity faces. In another condition, alternating between a positive and a negative polarity face also elicited a strong 3. Hz response, indicating an asymmetrical representation of positive and negative polarity faces even at supra-threshold levels (i.e., when both stimuli were perceived as faces). Overall, these findings demonstrate distinct perceptual representations of positive and negative polarity faces, independently of low-level cues, and suggest qualitatively different detection processes (template-based matching for positive polarity faces vs. linear accumulation of evidence for negative polarity faces)

Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates

Children make faster and more accurate decisions about perceptual information as they get older, but it is unclear how different aspects of the decision-making process change with age. Here, we used hierarchical Bayesian diffusion models to decompose performance in a perceptual task into separate processing components, testing age-related differences in model parameters and links to neural data. We collected behavioural and EEG data from 96 6- to 12-year-old children and 20 adults completing a motion discrimination task. We used a component decomposition technique to identify two response-locked EEG components with ramping activity preceding the response in children and adults: one with activity that was maximal over centro-parietal electrodes and one that was maximal over occipital electrodes. Younger children had lower drift rates (reduced sensitivity), wider boundary separation (increased response caution) and longer non-decision times than older children and adults. Yet, model comparisons suggested that the best model of children’s data included age effects only on drift rate and boundary separation (not non-decision time). Next, we extracted the slope of ramping activity in our EEG components and covaried these with drift rate. The slopes of both EEG components related positively to drift rate, but the best model with EEG covariates included only the centro-parietal component. By decomposing performance into distinct components and relating them to neural markers, diffusion models have the potential to identify the reasons why children with developmental conditions perform differently to typically developing children and to uncover processing differences inapparent in the response time and accuracy data alone