Impact of scattering phase function and polarization on the accuracy of diffuse and sub-diffuse spatial frequency domain imaging.

Significance: Although spatial frequency domain imaging (SFDI) has been well characterized under diffuse optical conditions, tissue measurements made outside the diffuse regime can provide new diagnostic information. Before such measurements can become clinically relevant, however, the behavior of sub-diffuse SFDI and its effect on the accuracy of derived tissue parameters must be assessed. Aim: We aim to characterize the impact that both the assumed scattering phase function (SPF) and the polarization state of the illumination light source have on the accuracy of SFDI-derived optical properties when operating under diffuse or sub-diffuse conditions, respectively. Approach: Through the use of a set of well-characterized optical phantoms, SFDI accuracy was assessed at four wavelengths (395, 545, 625, and 850 nm) and two different spatial frequencies (0.3 and 1.0 mm - 1 ), which provided a broad range of diffuse and sub-diffuse conditions, using three different SPFs. To determine the effects of polarization, the SFDI accuracy was assessed using both unpolarized and cross-polarized illumination. Results: It was found that the assumed SPF has a direct and significant impact on the accuracy of the SFDI-derived optical properties, with the best choice of SPF being dictated by the polarization state. As unpolarized SFDI retains the sub-diffuse portion of the signal, optical properties were found to be more accurate when using the full SPF that includes forward and backscattering components. By contrast, cross-polarized SFDI yielded accurate optical properties when using a forward-scattering SPF, matching the behavior of cross-polarization to attenuate the immediate backscattering of sub-diffuse reflectance. Using the correct pairings of SPF and polarization enabled using a reflectance standard, instead of a more subjective phantom, as the reference measurement. Conclusions: These results provide the foundation for a more thorough understanding of SFDI and enable new applications of this technology in which sub-diffuse conditions dominate (e.g., µ a ≮ µ s ' ) or high spatial frequencies are required.

Reduced spatial frequency differentiation and sex-related specificities in fearful face detection in autism: Insights from EEG and the predictive brain model.

Face processing relies on predictive processes driven by low spatial frequencies (LSF) that convey coarse information prior to fine information conveyed by high spatial frequencies. However, autistic individuals might have atypical predictive processes, contributing to facial processing difficulties. This may be more normalized in autistic females, who often exhibit better socio-communicational abilities than males. We hypothesized that autistic females would display a more typical coarse-to-fine processing for socio-emotional stimuli compared to autistic males. To test this hypothesis, we asked adult participants (44 autistic, 51 non-autistic) to detect fearful faces among neutral faces, filtered in two orders: from coarse-to-fine (CtF) and from fine-to-coarse (FtC). Results show lower d' values and longer reaction times for fearful detection in autism compared to non-autistic (NA) individuals, regardless of the filtering order. Both groups presented shorter P100 latency after CtF compared to FtC, and larger amplitude for N170 after FtC compared to CtF. However, autistic participants presented a reduced difference in source activity between CtF and FtC in the fusiform. There was also a more spatially spread activation pattern in autistic females compared to NA females. Finally, females had faster P100 and N170 latencies, as well as larger occipital activation for FtC sequences than males, irrespective of the group. Overall, the results do not suggest impaired predictive processes from LSF in autism despite behavioral differences in fear detection. However, they do indicate reduced brain modulation by spatial frequency in autism. In addition, the findings highlight sex differences that warrant consideration in understanding autistic females.

On the embodied nature of knowledge: From neurons to numbers.

Interdisciplinary investigations of the human mind through the cognitive sciences have identified a key role of the body in representing knowledge. After characterizing knowledge at grounded, embodied, and situated levels, number knowledge is analyzed from this hierarchical perspective. Lateralized cortical processing of coarse versus fine detail is identified as a grounding substrate for the population stereotype few/left, many/right, which then contributes to number-related sensory and motor biases at the embodied and situated levels. Implications of this perspective for education and rehabilitation are discussed.

Subjective Affective Responses to Natural Scenes Require Understanding, Not Spatial Frequency Bands.

It is debated whether emotional processing and response depend on semantic identification or are preferentially tied to specific information in natural scenes, such as global features or local details. The present study aimed to further examine the relationship between scene understanding and affective response while manipulating visual content. To this end, we presented affective and neutral natural scenes which were progressively band-filtered to contain global features (low spatial frequencies) or local details (high spatial frequencies) and assessed both affective response and scene understanding. We observed that, if scene content was correctly reported, subjective ratings of arousal and valence were modulated by the affective content of the scene, and this modulation was similar across spatial frequency bands. On the other hand, no affective modulation of subjective ratings was observed if picture content was not correctly reported. The present results indicate that subjective affective response requires content understanding, and it is not tied to a specific spatial frequency range.

Detecting implicit and explicit facial emotions at different ages.

Emotions are processed in the brain through a cortical route, responsible for detailed-conscious recognition and mainly based on image High Spatial Frequencies (HSF), and a subcortical route, responsible for coarse-unconscious processing and based on Low SF (LSF). However, little is known about possible changes in the functioning of the two routes in ageing. In the present go/no-go online task, 112 younger adults and 111 older adults were asked to press a button when a happy or angry face appeared (go) and to inhibit responses for neutral faces (no-go). Facial stimuli were presented unfiltered (broadband image), filtered at HSF and LSF, and hybrids (LSF of an emotional expression superimposed to the HSF of the same face with a neutral expression). All stimuli were also presented rotated on the vertical axis (upside-down) to investigate the global analysis of faces in ageing. Results showed an overall better performance of younger compared to older participants for all conditions except for hybrid stimuli. The expected face-inversion effect was confirmed in both age groups. We conclude that, besides an overall worsening of the perceptual skill with ageing, no specific impairment in the functioning of both the cortical and the subcortical route emerged.

Looming Angry Faces: Preliminary Evidence of Differential Electrophysiological Dynamics for Filtered Stimuli via Low and High Spatial Frequencies.

Looming motion interacts with threatening emotional cues in the initial stages of visual processing. However, the underlying neural networks are unclear. The current study investigated if the interactive effect of threat elicited by angry and looming faces is favoured by rapid, magnocellular neural pathways and if exogenous or endogenous attention influences such processing. Here, EEG/ERP techniques were used to explore the early ERP responses to moving emotional faces filtered for high spatial frequencies (HSF) and low spatial frequencies (LSF). Experiment 1 applied a passive-viewing paradigm, presenting filtered angry and neutral faces in static, approaching, or receding motions on a depth-cued background. In the second experiment, broadband faces (BSF) were included, and endogenous attention was directed to the expression of faces. Our main results showed that regardless of attentional control, P1 was enhanced by BSF angry faces, but neither HSF nor LSF faces drove the effect of facial expressions. Such findings indicate that looming motion and threatening expressions are integrated rapidly at the P1 level but that this processing relies neither on LSF nor on HSF information in isolation. The N170 was enhanced for BSF angry faces regardless of attention but was enhanced for LSF angry faces during passive viewing. These results suggest the involvement of a neural pathway reliant on LSF information at the N170 level. Taken together with previous reports from the literature, this may indicate the involvement of multiple parallel neural pathways during early visual processing of approaching emotional faces.

Simultaneous Dry and Gel-Based High-Density Electroencephalography Recordings.

Evaluations of new dry, high-density EEG caps have only been performed so far with serial measurements and not with simultaneous (parallel) measurements. For a first comparison of gel-based and dry electrode performance in simultaneous high-density EEG measurements, we developed a new EEG cap comprising 64 gel-based and 64 dry electrodes and performed simultaneous measurements on ten volunteers. We analyzed electrode-skin impedances, resting state EEG, triggered eye blinks, and visual evoked potentials (VEPs). To overcome the issue of different electrode positions in the comparison of simultaneous measurements, we performed spatial frequency analysis of the simultaneously measured EEGs using spatial harmonic analysis (SPHARA). The impedances were 516 ± 429 kOhm (mean ± std) for the dry electrodes and 14 ± 8 kOhm for the gel-based electrodes. For the dry EEG electrodes, we obtained a channel reliability of 77%. We observed no differences between dry and gel-based recordings for the alpha peak frequency and the alpha power amplitude, as well as for the VEP peak amplitudes and latencies. For the VEP, the RMSD and the correlation coefficient between the gel-based and dry recordings were 1.7 ± 0.7 µV and 0.97 ± 0.03, respectively. We observed no differences in the cumulative power distributions of the spatial frequency components for the N75 and P100 VEP peaks. The differences for the N145 VEP peak were attributed to the different noise characteristics of gel-based and dry recordings. In conclusion, we provide evidence for the equivalence of simultaneous dry and gel-based high-density EEG measurements.

Detection of emotional faces: The role of spatial frequencies and local features.

Models of emotion processing suggest that threat-related stimuli such as fearful faces can be detected based on the rapid extraction of low spatial frequencies. However, this remains debated as other models argue that the decoding of facial expressions occurs with a more flexible use of spatial frequencies. The purpose of this study was to clarify the role of spatial frequencies and differences in luminance contrast between spatial frequencies, on the detection of facial emotions. We used a saccadic choice task in which emotional-neutral face pairs were presented and participants were asked to make a saccade toward the neutral or the emotional (happy or fearful) face. Faces were displayed either in low, high, or broad spatial frequencies. Results showed that participants were better to saccade toward the emotional face. They were also better for high or broad than low spatial frequencies, and the accuracy was higher with a happy target. An analysis of the eye and mouth saliency ofour stimuli revealed that the mouth saliency of the target correlates with participants' performance. Overall, this study underlines the importance of local more than global information, and of the saliency of the mouth region in the detection of emotional and neutral faces.

Effects of head modeling errors on the spatial frequency representation of MEG.

Objectives.We aim to investigate the effects of head model inaccuracies on signal and source reconstruction accuracies for various sensor array distances to the head. This allows for the assessment of the importance of head modeling for next-generation magnetoencephalography (MEG) sensors, optically-pumped magnetometers (OPM).Approach.A 1-shell boundary element method (BEM) spherical head model with 642 vertices of radius 9 cm and conductivity of 0.33 S m-1was defined. The vertices were then randomly perturbed radially up to 2%, 4%, 6%, 8% and 10% of the radius. For each head perturbation case, the forward signal was calculated for dipolar sources located at 2 cm, 4 cm, 6 cm and 8 cm from the origin (center of the sphere), and for a 324 sensor array located at 10 cm to 15 cm from the origin. Equivalent current dipole (ECD) source localization was performed for each of these forward signals. The signal for each perturbed spherical head case was then analyzed in the spatial frequency domain, and the signal and ECD errors were quantified relative to the unperturbed case.Main results.In the noiseless and high signal-to-noise ratio (SNR) case of approximately ≥6 dB, inaccuracies in our spherical BEM head conductor models lead to increased signal and ECD inaccuracies when sensor arrays are placed closer to the head. This is true especially in the case of deep and superficial sources. In the noisy case however, the higher SNR for closer sensor arrays allows for an improved ECD fit and outweighs the effects of head geometry inaccuracies.Significance.OPMs may be placed directly on the head, as opposed to the more commonly used superconducting quantum interference device sensors which must be placed a few centimeters away from the head. OPMs thus allow for signals of higher spatial resolution to be captured, resulting in potentially more accurate source localizations. Our results suggest that an increased emphasis on accurate head modeling for OPMs may be necessary to fully realize its improved source localization potential.

"Left and right prefrontal routes to action comprehension".

Successful action comprehension requires the integration of motor information and semantic cues about objects in context. Previous evidence suggests that while motor features are dorsally encoded in the fronto-parietal action observation network (AON); semantic features are ventrally processed in temporal structures. Importantly, these dorsal and ventral routes seem to be preferentially tuned to low (LSF) and high (HSF) spatial frequencies, respectively. Recently, we proposed a model of action comprehension where we hypothesized an additional route to action understanding whereby coarse LSF information about objects in context is projected to the dorsal AON via the prefrontal cortex (PFC), providing a prediction signal of the most likely intention afforded by them. Yet, this model awaits for experimental testing. To this end, we used a perturb-and-measure continuous theta burst stimulation (cTBS) approach, selectively disrupting neural activity in the left and right PFC and then evaluating the participant's ability to recognize filtered action stimuli containing only HSF or LSF. We find that stimulation over PFC triggered different spatial-frequency modulations depending on lateralization: left-cTBS and right-cTBS led to poorer performance on HSF and LSF action stimuli, respectively. Our findings suggest that left and right PFC exploit distinct spatial frequencies to support action comprehension, providing evidence for multiple routes to social perception in humans.

Impact of glaucoma on the spatial frequency processing of scenes in central vision.

Glaucoma is an eye disease characterized by a progressive vision loss usually starting in peripheral vision. However, a deficit for scene categorization is observed even in the preserved central vision of patients with glaucoma. We assessed the processing and integration of spatial frequencies in the central vision of patients with glaucoma during scene categorization, considering the severity of the disease, in comparison to age-matched controls. In the first session, participants had to categorize scenes filtered in low-spatial frequencies (LSFs) and high-spatial frequencies (HSFs) as a natural or an artificial scene. Results showed that the processing of spatial frequencies was impaired only for patients with severe glaucoma, in particular for HFS scenes. In the light of proactive models of visual perception, we investigated how LSF could guide the processing of HSF in a second session. We presented hybrid scenes (combining LSF and HSF from two scenes belonging to the same or different semantic category). Participants had to categorize the scene filtered in HSF while ignoring the scene filtered in LSF. Surprisingly, results showed that the semantic influence of LSF on HSF was greater for patients with early glaucoma than controls, and then disappeared for the severe cases. This study shows that a progressive destruction of retinal ganglion cells affects the spatial frequency processing in central vision. This deficit may, however, be compensated by increased reliance on predictive mechanisms at early stages of the disease which would however decline in more severe cases.

High spatial frequencies disrupt conscious visual recognition: evidence from an attentional blink paradigm.

In this article, we tested the respective importance of low spatial frequencies (LSF) and high spatial frequencies (HSF) for conscious visual recognition of emotional stimuli by using an attentional blink paradigm. Thirty-eight participants were asked to identify and report two targets (happy faces) embedded in a rapid serial visual presentation of distractors (angry faces). During attentional blink, conscious perception of the second target (T2) is usually altered when the lag between the two targets is short (200-500 ms) but is restored at longer lags. The distractors between T1 and T2 were either non-filtered (broad spatial frequencies, BSF), low-pass filtered (LSF), or high-pass filtered (HSF). Assuming that prediction abilities could be at the root of conscious visual recognition, we expected that LSF distractors could result in a greater disturbance of T2 reporting than HSF distractors. Results showed that both LSF and HSF play a role in the emergence of exogenous consciousness in the visual system. Furthermore, HSF distractors strongly affected T1 and T2 reporting irrespective of the lag between targets, suggesting their role for facial emotion processing. We discuss these results with regards to other models of visual recognition. .

Both low and high spatial frequencies drive the early posterior negativity in response to snake stimuli.

Previous event-related potential (ERP) studies have shown that snake pictures elicit greater early posterior negativity (EPN) compared to other animal pictures. The EPN reflects early selective visual processing of emotionally significant stimuli. Evidence for the role that high and low spatial frequencies play in the early detection of snakes is still inconsistent. The current study aims to clarify this by studying the effect of high and low spatial frequencies on the elevated EPN for snakes separately. Using a rapid serial visual presentation paradigm, participants viewed images of snakes, spiders and birds in three different conditions of filtered spatial frequencies: high spatial frequency, low spatial frequency, and full spatial frequency (the original image). P1 and mean EPN activity in a time window of 225-300 ms after stimulus onset were measured at the occipital cluster (O1, O2, Oz). The results show smaller P1 amplitudes and shorter P1 latencies in response to full-spectrum snake pictures compared to full-spectrum spider and bird pictures, and an increased EPN in response to snake pictures compared to spider and bird pictures in all three filtering conditions. The EPN in response to full-spectrum snake pictures was larger than the EPN in response to filtered snake images. No difference in EPN was found between the snake pictures in the high and low spatial frequency conditions. The results suggest that the roles of high and low spatial frequencies in early automatic attention to snakes are equally important.

The Predictive Role of Low Spatial Frequencies in Automatic Face Processing: A Visual Mismatch Negativity Investigation.

Visual processing is thought to function in a coarse-to-fine manner. Low spatial frequencies (LSF), conveying coarse information, would be processed early to generate predictions. These LSF-based predictions would facilitate the further integration of high spatial frequencies (HSF), conveying fine details. The predictive role of LSF might be crucial in automatic face processing, where high performance could be explained by an accurate selection of clues in early processing. In the present study, we used a visual Mismatch Negativity (vMMN) paradigm by presenting an unfiltered face as standard stimulus, and the same face filtered in LSF or HSF as deviant, to investigate the predictive role of LSF vs. HSF during automatic face processing. If LSF are critical for predictions, we hypothesize that LSF deviants would elicit less prediction error (i.e., reduced mismatch responses) than HSF deviants. Results show that both LSF and HSF deviants elicited a mismatch response compared with their equivalent in an equiprobable sequence. However, in line with our hypothesis, LSF deviants evoke significantly reduced mismatch responses compared to HSF deviants, particularly at later stages. The difference in mismatch between HSF and LSF conditions involves posterior areas and right fusiform gyrus. Overall, our findings suggest a predictive role of LSF during automatic face processing and a critical involvement of HSF in the fusiform during the conscious detection of changes in faces.

Diagnostic Features for Human Categorisation of Adult and Child Faces.

Knowing how humans differentiate children from adults has useful implications in many areas of both forensic and cognitive psychology. Yet, how we extract age from faces has been surprisingly underexplored in both disciplines. Here, we used a novel data-driven experimental technique to objectively measure the facial features human observers use to categorise child and adult faces. Relying on more than 35,000 trials, we used a reverse correlation technique that enabled us to reveal how specific features which are known to be important in face-perception - position, spatial-frequency (SF), and orientation - are associated with accurate child and adult discrimination. This showed that human observers relied on evidence in the nasal bone and eyebrow area for accurate adult categorisation, while they relied on the eye and jawline area to accurately categorise child faces. For orientation structure, only facial information of vertical orientation was linked to face-adult categorisation, while features of horizontal and, to a lesser extent oblique orientations, were more diagnostic of a child face. Finally, we found that SF diagnosticity showed a U-shaped pattern for face-age categorisation, with information in low and high SFs being diagnostic of child faces, and mid SFs being diagnostic of adult faces. Through this first characterisation of the facial features of face-age categorisation, we show that important information found in psychophysical studies of face-perception in general (i.e., the eye area, horizontals, and mid-level SFs) is crucial to the practical context of face-age categorisation, and present data-driven procedures through which face-age classification training could be implemented for real-world challenges.

High spatial frequency filtered primes hastens happy faces categorization in autistic adults.

Coarse information of a visual stimulus is conveyed by Low Spatial Frequencies (LSF) and is thought to be rapidly extracted to generate predictions. This may guide fast recognition with the subsequent integration of fine information, conveyed by High Spatial Frequencies (HSF). In autism, emotional face recognition is challenging, and might be related to alterations in LSF predictive processes. We analyzed the data of 27 autistic and 34 non autistic (NA) adults on an emotional Stroop task (i.e., emotional face with congruent or incongruent emotional word) with spatially filtered primes (HSF vs.LSF). We hypothesized that LSF primes would generate predictions leading to faster categorization of the target face compared to HSF primes, in the NA group but not in autism. Surprisingly, HSF primes led to faster categorization than LSF primes in both groups. Moreover, the advantage of HSF vs.LSF primes was stronger for angry than happy faces in NA, but was stronger for happy than angry faces in autistic participants. Drift diffusion modelling confirmed HSF advantage and showed a longer non-decision time (e.g., encoding) in autism. Despite LSF predictive impairments in autism was not corroborated, our analyses suggest low level processing specificities in autism.

Do Humans and Deep Convolutional Neural Networks Use Visual Information Similarly for the Categorization of Natural Scenes?

The investigation of visual categorization has recently been aided by the introduction of deep convolutional neural networks (CNNs), which achieve unprecedented accuracy in picture classification after extensive training. Even if the architecture of CNNs is inspired by the organization of the visual brain, the similarity between CNN and human visual processing remains unclear. Here, we investigated this issue by engaging humans and CNNs in a two-class visual categorization task. To this end, pictures containing animals or vehicles were modified to contain only low/high spatial frequency (HSF) information, or were scrambled in the phase of the spatial frequency spectrum. For all types of degradation, accuracy increased as degradation was reduced for both humans and CNNs; however, the thresholds for accurate categorization varied between humans and CNNs. More remarkable differences were observed for HSF information compared to the other two types of degradation, both in terms of overall accuracy and image-level agreement between humans and CNNs. The difficulty with which the CNNs were shown to categorize high-passed natural scenes was reduced by picture whitening, a procedure which is inspired by how visual systems process natural images. The results are discussed concerning the adaptation to regularities in the visual environment (scene statistics); if the visual characteristics of the environment are not learned by CNNs, their visual categorization may depend only on a subset of the visual information on which humans rely, for example, on low spatial frequency information.

Spatially Filtered Emotional Faces Dominate during Binocular Rivalry.

The present investigation explores the role of bottom-up and top-down factors in the recognition of emotional facial expressions during binocular rivalry. We manipulated spatial frequencies (SF) and emotive features and asked subjects to indicate whether the emotional or the neutral expression was dominant during binocular rivalry. Controlling the bottom-up saliency with a computational model, physically comparable happy and fearful faces were presented dichoptically with neutral faces. The results showed the dominance of emotional faces over neutral ones. In particular, happy faces were reported more frequently as the first dominant percept even in the presence of coarse information (at a low SF level: 2-6 cycle/degree). Following current theories of emotion processing, the results provide further support for the influence of positive compared to negative meaning on binocular rivalry and, for the first time, showed that individuals perceive the affective quality of happiness even in the absence of details in the visual display. Furthermore, our findings represent an advance in knowledge regarding the association between the high- and low-level mechanisms behind binocular rivalry.

Fearful expressions of rapidly presented hybrid-faces modulate the lag 1 sparing in the attentional blink.

There is evidence that emotional stimuli impair attention for subsequent stimuli when presented in rapid visual succession. We investigated whether non-visible emotions of hybrid faces showing either happy or afraid expressions only in their Low Spatial Frequencies (LSF) and neutral expressions in their High Spatial Frequencies (HSF) modulate temporal selective attention. In a Rapid Serial Visual Presentation (RSVP) paradigm, two target-faces (T1 and T2) were presented briefly at different temporal distances (lags) in a stream of inverted distractor-faces: T1s were either neutral, happy-hybrid or afraid-hybrid faces; T2s were always neutral faces. When participants reported T1 and T2 gender, performance was impaired across all early lags, especially after afraid-hybrid faces. When participants reported T1 orientation and T2 gender, results showed that the LSF emotion of T1s affected temporal selective attention engendering a longer AB (over lag 2 and lag 3) than neutral T1s. Interestingly, only afraid-hybrid T1s improved processing of T2 at lag 1 (i.e., sparing). Our findings show that some core emotional content is implicitly processed from the LSF of hybrid T1s since the effects on temporal selective attention are emotion specific.