Behavioral and Neural Correlates of Visual Working Memory Reveal Metacognitive Aspects of Mental Imagery.

Mental imagery (MI) is the ability to generate visual phenomena in the absence of sensory input. MI is often likened to visual working memory (VWM): the ability to maintain and manipulate visual representations. How MI is recruited during VWM is yet to be established. In a modified orientation change-discrimination task, we examined how behavioral (proportion correct) and neural (contralateral delay activity [CDA]) correlates of precision and capacity map onto subjective ratings of vividness and number of items in MI within a VWM task. During the maintenance period, 17 participants estimated the vividness of their MI or the number of items held in MI while they were instructed to focus on either precision or capacity of their representation and to retain stimuli at varying set sizes (1, 2, and 4). Vividness and number ratings varied over set sizes; however, subjective ratings and behavioral performance correlated only for vividness rating at set size 1. Although CDA responded to set size as was expected, CDA did not reflect subjective reports on high and low vividness and on nondivergent (reported the probed number of items in mind) or divergent (reported number of items diverged from probed) rating trials. Participants were more accurate in low set sizes compared with higher set sizes and in coarse (45°) orientation changes compared with fine (15°) orientation changes. We failed to find evidence for a relationship between the subjective sensory experience of precision and capacity of MI and the precision and capacity of VWM.

"I Spy with my Little Eye, Something that is a Face ": A Brain Network for Illusory Face Detection.

The most basic aspect of face perception is simply detecting the presence of a face, which requires the extraction of features that it has in common with other faces. Putatively, it is caused by matching high-dimensional sensory input with internal face templates, achieved through a top-down mediated coupling between prefrontal regions and brain areas in the occipito-temporal cortex ("core system of face perception"). Illusory face detection tasks can be used to study these top-down influences. In the present functional magnetic resonance imaging study, we showed that illusory face perception activated just as real faces the core system, albeit with atypical left-lateralization of the occipital face area. The core system was coupled with two distinct brain regions in the lateral prefrontal (inferior frontal gyrus, IFG) and orbitofrontal cortex (OFC). A dynamic causal modeling (DCM) analysis revealed that activity in the core system during illusory face detection was upregulated by a modulatory face-specific influence of the IFG, not as previously assumed by the OFC. Based on these findings, we were able to develop the most comprehensive neuroanatomical framework of illusory face detection until now.

Developmental changes in the processing of faces as revealed by EEG decoding.

Rapidly and accurately processing information from faces is a critical human function that is known to improve with developmental age. Understanding the underlying drivers of this improvement remains a contentious question, with debate continuing as to the presence of early vs. late maturation of face-processing mechanisms. Recent behavioural evidence suggests an important 'hallmark' of expert face processing - the face inversion effect - is present in very young children, yet neural support for this remains unclear. To address this, we conducted a detailed investigation of the neural dynamics of face processing in children spanning a range of ages (6-11 years) and adults. Uniquely, we applied multivariate pattern analysis (MVPA) to the electroencephalogram signal (EEG) to test for the presence of a distinct neural profile associated with canonical upright faces when compared both to other objects (houses) and to inverted faces. Results revealed robust discrimination profiles, at the individual level, of differentiated neural activity associated with broad face categorization and further with its expert processing, as indexed by the face inversion effect, from the youngest ages tested. This result is consistent with an early functional maturation of broad face processing mechanisms. Yet, clear quantitative differences between the response profile of children and adults is suggestive of age-related refinement of this system with developing face and general expertise. Standard ERP analysis also provides some support for qualitative differences in the neural response to inverted faces in children in contrast to adults. This neural profile is in line with recent behavioural studies that have reported impressively expert early face abilities during childhood, while also providing novel evidence of the ongoing neural specialisation between child and adulthood.

Decoding the dynamic representation of facial expressions of emotion in explicit and incidental tasks.

Faces transmit a wealth of important social signals. While previous studies have elucidated the network of cortical regions important for perception of facial expression, and the associated temporal components such as the P100, N170 and EPN, it is still unclear how task constraints may shape the representation of facial expression (or other face categories) in these networks. In the present experiment, we used Multivariate Pattern Analysis (MVPA) with EEG to investigate the neural information available across time about two important face categories (expression and identity) when those categories are either perceived under explicit (e.g. decoding facial expression category from the EEG when task is on expression) or incidental task contexts (e.g. decoding facial expression category from the EEG when task is on identity). Decoding of both face categories, across both task contexts, peaked in time-windows spanning 91-170 ms (across posterior electrodes). Peak decoding of expression, however, was not affected by task context whereas peak decoding of identity was significantly reduced under incidental processing conditions. In addition, errors in EEG decoding correlated with errors in behavioral categorization under explicit processing for both expression and identity, however under incidental conditions only errors in EEG decoding of expression correlated with behavior. Furthermore, decoding time-courses and the spatial pattern of informative electrodes showed consistently better decoding of identity under explicit conditions at later-time periods, with weak evidence for similar effects for decoding of expression at isolated time-windows. Taken together, these results reveal differences and commonalities in the processing of face categories under explicit Vs incidental task contexts and suggest that facial expressions are processed to a richer degree under incidental processing conditions, consistent with prior work indicating the relative automaticity by which emotion is processed. Our work further demonstrates the utility in applying multivariate decoding analyses to EEG for revealing the dynamics of face perception.

Transmitting and decoding facial expressions of emotion during healthy aging: More similarities than differences.

Older adults tend to perform more poorly than younger adults on emotional expression identification tasks. The goal of the present study was to test a processing mechanism that might explain these differences in emotion recognition-specifically, age-related variation in the utilization of specific visual cues. Seventeen younger and 17 older adults completed a reverse-correlation emotion categorization task (Bubbles paradigm), consisting of a large number of trials in each of which only part of the visual information used to convey an emotional facial expression was revealed to participants. The task allowed us to pinpoint the visual features each group used systematically to correctly recognize the emotional expressions shown. To address the possibility that faces of different age groups are differently processed by younger and older adults, we included younger, middle-aged, and older adult face models displaying happy, fearful, angry, disgusted, and sad facial expressions. Our results reveal strong similarity in the utilization of visual information by younger and older adult participants in decoding the emotional expressions from faces across ages-particularly for happy and fear emotions. These findings suggest that age-related differences in strategic information use are unlikely to contribute to the decline of facial expression recognition skills observed in later life.

A "spoon full of sugar" helps the medicine go down: How a participant friendly version of a psychophysics task significantly improves task engagement, performance and data quality in a typical adult sample.

Few would argue that the unique insights brought by studying the typical and atypical development of psychological processes are essential to building a comprehensive understanding of the brain. Often, however, the associated challenges of working with non-standard adult populations results in the more complex psychophysical paradigms being rejected as too complex. Recently we created a child- (and clinical group) friendly implementation of one such technique - the reverse-correlation Bubbles approach - and noted an associated performance boost in adult participants. Here, we compare the administration of three different versions of this participant-friendly task in the same adult participants to empirically confirm that introducing elements in the experiment with the sole purpose of improving the participant experience, not only boosts the participant's engagement and motivation for the task but results in a significantly improved objective task performance and stronger statistical results.

Neuronal avalanches in the resting MEG of the human brain.

What constitutes normal cortical dynamics in healthy human subjects is a major question in systems neuroscience. Numerous in vitro and in vivo animal studies have shown that ongoing or resting cortical dynamics are characterized by cascades of activity across many spatial scales, termed neuronal avalanches. In experiment and theory, avalanche dynamics are identified by two measures: (1) a power law in the size distribution of activity cascades with an exponent of -3/2 and (2) a branching parameter of the critical value of 1, reflecting balanced propagation of activity at the border of premature termination and potential blowup. Here we analyzed resting-state brain activity recorded using noninvasive magnetoencephalography (MEG) from 124 healthy human subjects and two different MEG facilities using different sensor technologies. We identified large deflections at single MEG sensors and combined them into spatiotemporal cascades on the sensor array using multiple timescales. Cascade size distributions obeyed power laws. For the timescale at which the branching parameter was close to 1, the power law exponent was -3/2. This relationship was robust to scaling and coarse graining of the sensor array. It was absent in phase-shuffled controls with the same power spectrum or empty scanner data. Our results demonstrate that normal cortical activity in healthy human subjects at rest organizes as neuronal avalanches and is well described by a critical branching process. Theory and experiment have shown that such critical, scale-free dynamics optimize information processing. Therefore, our findings imply that the human brain attains an optimal dynamical regime for information processing.

Effects of expectation on face perception and its association with expertise.

Perceptual decisions are derived from the combination of priors and sensorial input. While priors are broadly understood to reflect experience/expertise developed over one's lifetime, the role of perceptual expertise at the individual level has seldom been directly explored. Here, we manipulate probabilistic information associated with a high and low expertise category (faces and cars respectively), while assessing individual level of expertise with each category. 67 participants learned the probabilistic association between a color cue and each target category (face/car) in a behavioural categorization task. Neural activity (EEG) was then recorded in a similar paradigm in the same participants featuring the previously learned contingencies without the explicit task. Behaviourally, perception of the higher expertise category (faces) was modulated by expectation. Specifically, we observed facilitatory and interference effects when targets were correctly or incorrectly expected, which were also associated with independently measured individual levels of face expertise. Multivariate pattern analysis of the EEG signal revealed clear effects of expectation from 100 ms post stimulus, with significant decoding of the neural response to expected vs. not stimuli, when viewing identical images. Latency of peak decoding when participants saw faces was directly associated with individual level facilitation effects in the behavioural task. The current results not only provide time sensitive evidence of expectation effects on early perception but highlight the role of higher-level expertise on forming priors.

Randomness impacts the building of specific priors, visual exploration, and perception in object recognition.

Recognising objects is a vital skill on which humans heavily rely to respond quickly and adaptively to their environment. Yet, we lack a full understanding of the role visual information sampling plays in this process, and its relation to the individual's priors. To bridge this gap, the eye-movements of 18 adult participants were recorded during a free-viewing object-recognition task using Dots stimuli1. Participants viewed the stimuli in one of three orders: from most visible to least (Descending), least visible to most (Ascending), or in a randomised order (Random). This dictated the strength of their priors along the experiment. Visibility order influenced the participants' recognition performance and visual exploration. In addition, we found that while orders allowing for stronger priors generally led participants to visually sample more informative locations, this was not the case of Random participants. Indeed, they appeared to behave naïvely, and their use of specific object-related priors was fully impaired, while they maintained the ability to use general, task-related priors to guide their exploration. These findings have important implications for our understanding of perception, which appears to be influenced by complex cognitive processes, even at the basic level of visual sampling during object recognition.

Rapid processing of emotional expressions without conscious awareness.

Rapid accurate categorization of the emotional state of our peers is of critical importance and as such many have proposed that facial expressions of emotion can be processed without conscious awareness. Typically, studies focus selectively on fearful expressions due to their evolutionary significance, leaving the subliminal processing of other facial expressions largely unexplored. Here, I investigated the time course of processing of 3 facial expressions (fearful, disgusted, and happy) plus an emotionally neutral face, during objectively unaware and aware perception. Participants completed the challenging "which expression?" task in response to briefly presented backward-masked expressive faces. Although participant's behavioral responses did not differentiate between the emotional content of the stimuli in the unaware condition, activity over frontal and occipitotemporal (OT) brain regions indicated an emotional modulation of the neuronal response. Over frontal regions this was driven by negative facial expressions and was present on all emotional trials independent of later categorization. Whereas the N170 component, recorded on lateral OT electrodes, was enhanced for all facial expressions but only on trials that would later be categorized as emotional. The results indicate that emotional faces, not only fearful, are processed without conscious awareness at an early stage and highlight the critical importance of considering categorization response when studying subliminal perception.

Orientation effects support specialist processing of upright unfamiliar faces in children and adults.

It is considerably harder to generalize identity across different pictures of unfamiliar faces, compared with familiar faces. This finding hints strongly at qualitatively distinct processing of unfamiliar face stimuli-for which we have less expertise. Yet, the extent to which face selective versus generic visual processes drive outcomes during this task has yet to be determined. To explore the relative contributions of each, we contrasted performance on a version of the popular Telling Faces Together unfamiliar face matching task, implemented in both upright and inverted orientations. Furthermore, we included different age groups (132 British children ages 6 to 11 years [69.7% White], plus 37 British White adults) to investigate how participants' experience with faces as a category influences their selective utilization of specialized processes for unfamiliar faces. Results revealed that unfamiliar face matching is highly orientation-selective. Accuracy was higher for upright compared with inverted faces from 6 years of age, which is consistent with selective utilization of specialized processes for upright versus inverted unfamiliar faces during this task. The effect of stimulus orientation did not interact significantly with age, and there was no graded increase in the magnitude of inversion effects observed across childhood. Still, a numerically larger inversion effect in adults compared to children provides a degree of support for developmental changes in these specialized face abilities with increasing age/experience. Differences in the pattern of errors across age groups are also consistent with a qualitative shift in unfamiliar face processing that occurs some time after 11 years of age. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Face recognition ability is manifest in early dynamic decoding of face-orientation selectivity-Evidence from multi-variate pattern analysis of the neural response.

Although humans are considered to be face experts, there is a well-established reliable variation in the degree to which neurotypical individuals are able to learn and recognise faces. While many behavioural studies have characterised these differences, studies that seek to relate the neuronal response to standardised behavioural measures of ability remain relatively scarce, particularly so for the time-resolved approaches and the early response to face stimuli. In the present study we make use of a relatively recent methodological advance, multi-variate pattern analysis (MVPA), to decode the time course of the neural response to faces compared to other object categories (inverted faces, objects). Importantly, for the first time, we directly relate metrics of this decoding assessed at the individual level to gold-standard measures of behavioural face processing ability assessed in an independent task. Thirty-nine participants completed the behavioural Cambridge Face Memory Test (CFMT), then viewed images of faces and houses (presented upright and inverted) while their neural activity was measured via electroencephalography. Significant decoding of both face orientation and face category were observed in all individual participants. Decoding of face orientation, a marker of more advanced face processing, was earlier and stronger in participants with higher levels of face expertise, while decoding of face category information was earlier but not stronger for individuals with greater face expertise. Taken together these results provide a marker of significant differences in the early neuronal response to faces from around 100 ms post stimulus as a function of behavioural expertise with faces.

Cognitive effort drives workspace configuration of human brain functional networks.

Effortful cognitive performance is theoretically expected to depend on the formation of a global neuronal workspace. We tested specific predictions of workspace theory, using graph theoretical measures of network topology and physical distance of synchronization, in magnetoencephalographic data recorded from healthy adult volunteers (N = 13) during performance of a working memory task at several levels of difficulty. We found that greater cognitive effort caused emergence of a more globally efficient, less clustered, and less modular network configuration, with more long-distance synchronization between brain regions. This pattern of task-related workspace configuration was more salient in the ß-band (16-32 Hz) and γ-band (32-63 Hz) networks, compared with both lower (α-band; 8-16 Hz) and higher (high γ-band; 63-125 Hz) frequency intervals. Workspace configuration of ß-band networks was also greater in faster performing participants (with correct response latency less than the sample median) compared with slower performing participants. Processes of workspace formation and relaxation in relation to time-varying demands for cognitive effort could be visualized occurring in the course of task trials lasting <2 s. These experimental results provide support for workspace theory in terms of complex network metrics and directly demonstrate how cognitive effort breaks modularity to make human brain functional networks transiently adopt a more efficient but less economical configuration.

Fast reconfiguration of high-frequency brain networks in response to surprising changes in auditory input.

How do human brain networks react to dynamic changes in the sensory environment? We measured rapid changes in brain network organization in response to brief, discrete, salient auditory stimuli. We estimated network topology and distance parameters in the immediate central response period, <1 s following auditory presentation of standard tones interspersed with occasional deviant tones in a mismatch-negativity (MMN) paradigm, using magnetoencephalography (MEG) to measure synchronization of high-frequency (gamma band; 33-64 Hz) oscillations in healthy volunteers. We found that global small-world parameters of the networks were conserved between the standard and deviant stimuli. However, surprising or unexpected auditory changes were associated with local changes in clustering of connections between temporal and frontal cortical areas and with increased interlobar, long-distance synchronization during the 120- to 250-ms epoch (coinciding with the MMN-evoked response). Network analysis of human MEG data can resolve fast local topological reconfiguration and more long-range synchronization of high-frequency networks as a systems-level representation of the brain's immediate response to salient stimuli in the dynamically changing sensory environment.

Dynamics of visual information integration in the brain for categorizing facial expressions.

A key to understanding visual cognition is to determine when, how, and with what information the human brain distinguishes between visual categories. So far, the dynamics of information processing for categorization of visual stimuli has not been elucidated. By using an ecologically important categorization task (seven expressions of emotion), we demonstrate, in three human observers, that an early brain event (the N170 Event Related Potential, occurring 170 ms after stimulus onset) integrates visual information specific to each expression, according to a pattern. Specifically, starting 50 ms prior to the ERP peak, facial information tends to be integrated from the eyes downward in the face. This integration stops, and the ERP peaks, when the information diagnostic for judging a particular expression has been integrated (e.g., the eyes in fear, the corners of the nose in disgust, or the mouth in happiness). Consequently, the duration of information integration from the eyes down determines the latency of the N170 for each expression (e.g., with "fear" being faster than "disgust," itself faster than "happy"). For the first time in visual categorization, we relate the dynamics of an important brain event to the dynamics of a precise information-processing function.

Information processing algorithms in the brain.

If the brain is a machine that processes information, then its cognitive activity can be interpreted as a set of information processing states linking stimulus to response (i.e. as a mechanism or an algorithm). The cornerstone of this research agenda is the existence of a method to translate the measurable states of brain activity into the information processing states of a cognitive theory. Here, we contend that reverse correlation methods can provide this translation and we frame the transitions between information processing states in the context of automata theory. We illustrate, using examples from visual cognition, how this novel framework can be applied to understand the information processing algorithms of the brain in cognitive neuroscience.

Broadband criticality of human brain network synchronization.

Self-organized criticality is an attractive model for human brain dynamics, but there has been little direct evidence for its existence in large-scale systems measured by neuroimaging. In general, critical systems are associated with fractal or power law scaling, long-range correlations in space and time, and rapid reconfiguration in response to external inputs. Here, we consider two measures of phase synchronization: the phase-lock interval, or duration of coupling between a pair of (neurophysiological) processes, and the lability of global synchronization of a (brain functional) network. Using computational simulations of two mechanistically distinct systems displaying complex dynamics, the Ising model and the Kuramoto model, we show that both synchronization metrics have power law probability distributions specifically when these systems are in a critical state. We then demonstrate power law scaling of both pairwise and global synchronization metrics in functional MRI and magnetoencephalographic data recorded from normal volunteers under resting conditions. These results strongly suggest that human brain functional systems exist in an endogenous state of dynamical criticality, characterized by a greater than random probability of both prolonged periods of phase-locking and occurrence of large rapid changes in the state of global synchronization, analogous to the neuronal "avalanches" previously described in cellular systems. Moreover, evidence for critical dynamics was identified consistently in neurophysiological systems operating at frequency intervals ranging from 0.05-0.11 to 62.5-125 Hz, confirming that criticality is a property of human brain functional network organization at all frequency intervals in the brain's physiological bandwidth.

Inverse mapping the neuronal substrates of face categorizations.

Face perception is a complex process involving a network of brain structures, dynamically processing information to enable judgments about a face to be made (e.g., familiarity, identity, and expression). Here we introduce an analysis methodology that makes it possible to directly study this information processing in the brain from spatially and temporally resolved magnetoencephalographic signals. We apply our methodology to the study of 2 face categorization tasks, gender and expressiveness, and track the processing of 3 key visual features that underlie behavioral performance, over time and throughout the cortex. We find information processing correlates beginning from 90 ms following stimulus onset, where features are processed in isolation in occipital extrastriate regions. Over time, processing of successively more features and feature combinations takes place in occipitotemporal regions, with maximal information processing of visual information coinciding with the well-established face-selective M170 component at 170 ms. Later still, around 250-400 ms, cortical activity responds significantly more to task-specific features and their complex combinations. These results indicate a complex process of visual information processing during face perception with face parts processed in isolation at very early stages, and task-specific processing of combinations of features taking place within 300 ms. Crucially, our approach specifically establishes which information in the visual stimulus the brain signal is responding to and how this varies with time, cortical location, and task demands to establish a more precise tracking of information processing mechanisms in the cortex during face perception.

Characterizing the neural signature of face processing in Williams syndrome via multivariate pattern analysis and event related potentials.

Face recognition ability is often reported to be a relative strength in Williams syndrome (WS). Yet methodological issues associated with the supporting research, and evidence that atypical face processing mechanisms may drive outcomes 'in the typical range', challenge these simplistic characterisations of this important social ability. Detailed investigations of face processing abilities in WS both at a behavioural and neural level provide critical insights. Here, we behaviourally characterised face recognition ability in 18 individuals with WS comparatively to typically developing children and adult control groups. A subset of 11 participants with WS as well as chronologically age matched typical adults further took part in an EEG task where they were asked to attentively view a series of upright and inverted faces and houses. State-of-the-art multivariate pattern analysis (MVPA) was used alongside standard ERP analysis to obtain a detailed characterisation of the neural profile associated with 1) viewing faces as an overall category (by examining neural activity associated with upright faces and houses), and to 2) the canonical upright configuration of a face, critically associated with expertise in typical development and often linked with holistic processing (upright and inverted faces). Our results show that while face recognition ability is not on average at a chronological age-appropriate level in individuals with WS, it nonetheless appears to be a relative strength within their cognitive profile. Furthermore, all participants with WS revealed a differential pattern of neural activity to faces compared to objects, showing a distinct response to faces as a category, as well as a differential neural pattern for upright vs. inverted faces. Nonetheless, an atypical profile of face orientation classification was found in WS, suggesting that this group differs from typical individuals in their face processing mechanisms. Through this innovative application of MVPA, alongside the high temporal resolution of EEG, we provide important new insights into the neural processing of faces in WS.

Body image and sexual orientation: The experiences of lesbian and bisexual women.

Western cultures promote a thin and curvaceous ideal body size that most women find difficult to achieve by healthy measures, resulting in poor body image and increased risk for eating pathology. Research focusing on body image in lesbian and bisexual women has yielded inconsistent results. In total, 11 lesbian and bisexual women were interviewed regarding their experiences with body image. Interpretative phenomenological analysis revealed that these women experienced similar mainstream pressures to conform to a thin body ideal. Furthermore, participants perceived additional pressure to conform to heteronormative standards of beauty since the normalisation of homosexuality and the increase in Lesbian, Gay, Bisexual and Transgender representation in mainstream media.