ResearchPad - electrode-recording Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[The role of frontal and parietal cortex in the performance of gifted and average adolescents in a mental rotation task]]> Visual-spatial abilities are usually neglected in academic settings, even though several studies have shown that their predictive power in science, technology, engineering, and mathematics domains exceeds that of math and verbal ability. This neglect means that many spatially talented youths are not identified and nurtured, at a great cost to society. In the present work, we aim to identify behavioral and electrophysiological markers associated with visual spatial-ability in intellectually gifted adolescents (N = 15) compared to age-matched controls (N = 15). The participants performed a classic three-dimensional mental rotation task developed by Shepard and Metzler (1971) [33] while event-related potentials were measured in both frontal and parietal regions of interest. While response time was similar in the two groups, gifted subjects performed the test with greater accuracy. There was no indication of interhemispheric asymmetry of ERPs over parietal regions in both groups, although interhemispheric differences were observed in the frontal lobes. Moreover, intelligence quotient and working memory measures predicted variance in ERP’s amplitude in the right parietal and frontal hemispheres. We conclude that while gifted adolescents do not display a different pattern of electroencephalographic activity over the parietal cortex while performing the mental rotation task, their performance is correlated with the amplitude of ERPs in the frontal cortex during the execution of this task.

<![CDATA[Towards large scale automated cage monitoring – Diurnal rhythm and impact of interventions on in-cage activity of C57BL/6J mice recorded 24/7 with a non-disrupting capacitive-based technique]]>

Background and aims

Automated recording of laboratory animal’s home cage behavior is receiving increasing attention since such non-intruding surveillance will aid in the unbiased understanding of animal cage behavior potentially improving animal experimental reproducibility.

Material and methods

Here we investigate activity of group held female C57BL/6J mice (mus musculus) housed in standard Individually Ventilated Cages across three test-sites: Consiglio Nazionale delle Ricerche (CNR, Rome, Italy), The Jackson Laboratory (JAX, Bar Harbor, USA) and Karolinska Insititutet (KI, Stockholm, Sweden). Additionally, comparison of female and male C57BL/6J mice was done at KI. Activity was recorded using a capacitive-based sensor placed non-intrusively on the cage rack under the home cage collecting activity data every 250 msec, 24/7. The data collection was analyzed using non-parametric analysis of variance for longitudinal data comparing sites, weekdays and sex.


The system detected an increase in activity preceding and peaking around lights-on followed by a decrease to a rest pattern. At lights off, activity increased substantially displaying a distinct temporal variation across this period. We also documented impact on mouse activity that standard animal handling procedures have, e.g. cage-changes, and show that such procedures are stressors impacting in-cage activity.

These key observations replicated across the three test-sites, however, it is also clear that, apparently minor local environmental differences generate significant behavioral variances between the sites and within sites across weeks. Comparison of gender revealed differences in activity in the response to cage-change lasting for days in male but not female mice; and apparently also impacting the response to other events such as lights-on in males. Females but not males showed a larger tendency for week-to-week variance in activity possibly reflecting estrous cycling.


These data demonstrate that home cage monitoring is scalable and run in real time, providing complementary information for animal welfare measures, experimental design and phenotype characterization.

<![CDATA[Shorter sleep durations in adolescents reduce power density in a wide range of waking electroencephalogram frequencies]]>

Despite sleep’s recognized biological importance, it has been remarkably difficult to demonstrate changes in brain physiology with reduced sleep durations. In a study of adolescents, we varied sleep durations by restricting time in bed for four nights of either 10, 8.5 or 7 h. Shorter sleep durations significantly decreased waking electroencephalogram (EEG) power in a wide range of frequencies with both eyes closed and eyes open in central and occipital leads. These findings suggest new research directions and raise the possibility that waking EEG power density could provide a non-invasive test for biologically sufficient sleep.

<![CDATA[Differential recordings of local field potential: A genuine tool to quantify functional connectivity]]>

Local field potential (LFP) recording is a very useful electrophysiological method to study brain processes. However, this method is criticized for recording low frequency activity in a large area of extracellular space potentially contaminated by distal activity. Here, we theoretically and experimentally compare ground-referenced (RR) with differential recordings (DR). We analyze electrical activity in the rat cortex with these two methods. Compared with RR, DR reveals the importance of local phasic oscillatory activities and their coherence between cortical areas. Finally, we show that DR provides a more faithful assessment of functional connectivity caused by an increase in the signal to noise ratio, and of the delay in the propagation of information between two cortical structures.

<![CDATA[Multiscale dynamics of interstimulus interval integration in visual cortex]]>

Although the visual cortex receives information at multiple temporal patterns, much of the research in the field has focused only on intervals shorter than 1 second. Consequently, there is almost no information on what happens at longer temporal intervals. We have tried to address this question recording neuronal populations of the primary visual cortex during visual stimulation with repetitive grating stimuli and intervals ranging from 1 to 7 seconds. Our results showed that firing rate and response stability were dependent of interval duration. In addition, there were collective oscillations with different properties in response to changes in intervals duration. These results suggest that visual cortex could encode visual information at several time scales using oscillations at multiple frequencies.

<![CDATA[Post-Decision Wagering Affects Metacognitive Awareness of Emotional Stimuli: An Event Related Potential Study]]>

The present research investigated metacognitive awareness of emotional stimuli and its psychophysiological correlates. We used a backward masking task presenting participants with fearful or neutral faces. We asked participants for face discrimination and then probed their metacognitive awareness with confidence rating (CR) and post-decision wagering (PDW) scales. We also analysed psychophysiological correlates of awareness with event-related potential (ERP) components: P1, N170, early posterior negativity (EPN), and P3. We have not observed any differences between PDW and CR conditions in the emotion identification task. However, the "aware" ratings were associated with increased accuracy performance. This effect was more pronounced in PDW, especially for fearful faces, suggesting that emotional stimuli awareness may be enhanced by monetary incentives. EEG analysis showed larger N170, EPN and P3 amplitudes in aware compared to unaware trials. It also appeared that both EPN and P3 ERP components were more pronounced in the PDW condition, especially when emotional faces were presented. Taken together, our ERP findings suggest that metacognitive awareness of emotional stimuli depends on the effectiveness of both early and late visual information processing. Our study also indicates that awareness of emotional stimuli can be enhanced by the motivation induced by wagering.

<![CDATA[Auditory steady state responses and cochlear implants: Modeling the artifact-response mixture in the perspective of denoising]]>

Auditory steady state responses (ASSRs) in cochlear implant (CI) patients are contaminated by the spread of a continuous CI electrical stimulation artifact. The aim of this work was to model the electrophysiological mixture of the CI artifact and the corresponding evoked potentials on scalp electrodes in order to evaluate the performance of denoising algorithms in eliminating the CI artifact in a controlled environment. The basis of the proposed computational framework is a neural mass model representing the nodes of the auditory pathways. Six main contributors to auditory evoked potentials from the cochlear level and up to the auditory cortex were taken into consideration. The simulated dynamics were then projected into a 3-layer realistic head model. 32-channel scalp recordings of the CI artifact-response were then generated by solving the electromagnetic forward problem. As an application, the framework’s simulated 32-channel datasets were used to compare the performance of 4 commonly used Independent Component Analysis (ICA) algorithms: infomax, extended infomax, jade and fastICA in eliminating the CI artifact. As expected, two major components were detectable in the simulated datasets, a low frequency component at the modulation frequency and a pulsatile high frequency component related to the stimulation frequency. The first can be attributed to the phase-locked ASSR and the second to the stimulation artifact. Among the ICA algorithms tested, simulations showed that infomax was the most efficient and reliable in denoising the CI artifact-response mixture. Denoising algorithms can induce undesirable deformation of the signal of interest in real CI patient recordings. The proposed framework is a valuable tool for evaluating these algorithms in a controllable environment ahead of experimental or clinical applications.

<![CDATA[The Limited Utility of Multiunit Data in Differentiating Neuronal Population Activity]]>

To date, single neuron recordings remain the gold standard for monitoring the activity of neuronal populations. Since obtaining single neuron recordings is not always possible, high frequency or ‘multiunit activity’ (MUA) is often used as a surrogate. Although MUA recordings allow one to monitor the activity of a large number of neurons, they do not allow identification of specific neuronal subtypes, the knowledge of which is often critical for understanding electrophysiological processes. Here, we explored whether prior knowledge of the single unit waveform of specific neuron types is sufficient to permit the use of MUA to monitor and distinguish differential activity of individual neuron types. We used an experimental and modeling approach to determine if components of the MUA can monitor medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) in the mouse dorsal striatum. We demonstrate that when well-isolated spikes are recorded, the MUA at frequencies greater than 100Hz is correlated with single unit spiking, highly dependent on the waveform of each neuron type, and accurately reflects the timing and spectral signature of each neuron. However, in the absence of well-isolated spikes (the norm in most MUA recordings), the MUA did not typically contain sufficient information to permit accurate prediction of the respective population activity of MSNs and FSIs. Thus, even under ideal conditions for the MUA to reliably predict the moment-to-moment activity of specific local neuronal ensembles, knowledge of the spike waveform of the underlying neuronal populations is necessary, but not sufficient.

<![CDATA[Multiplex Networks of Cortical and Hippocampal Neurons Revealed at Different Timescales]]>

Recent studies have emphasized the importance of multiplex networks – interdependent networks with shared nodes and different types of connections – in systems primarily outside of neuroscience. Though the multiplex properties of networks are frequently not considered, most networks are actually multiplex networks and the multiplex specific features of networks can greatly affect network behavior (e.g. fault tolerance). Thus, the study of networks of neurons could potentially be greatly enhanced using a multiplex perspective. Given the wide range of temporally dependent rhythms and phenomena present in neural systems, we chose to examine multiplex networks of individual neurons with time scale dependent connections. To study these networks, we used transfer entropy – an information theoretic quantity that can be used to measure linear and nonlinear interactions – to systematically measure the connectivity between individual neurons at different time scales in cortical and hippocampal slice cultures. We recorded the spiking activity of almost 12,000 neurons across 60 tissue samples using a 512-electrode array with 60 micrometer inter-electrode spacing and 50 microsecond temporal resolution. To the best of our knowledge, this preparation and recording method represents a superior combination of number of recorded neurons and temporal and spatial recording resolutions to any currently available in vivo system. We found that highly connected neurons (“hubs”) were localized to certain time scales, which, we hypothesize, increases the fault tolerance of the network. Conversely, a large proportion of non-hub neurons were not localized to certain time scales. In addition, we found that long and short time scale connectivity was uncorrelated. Finally, we found that long time scale networks were significantly less modular and more disassortative than short time scale networks in both tissue types. As far as we are aware, this analysis represents the first systematic study of temporally dependent multiplex networks among individual neurons.

<![CDATA[Aristotle Meets Zeno: Psychophysiological Evidence]]>

This study, a tribute to Aristotle's 2400 years, used a juxtaposition of valid Aristotelian arguments to the paradoxes formulated by Zeno the Eleatic, in order to investigate the electrophysiological correlates of attentional and /or memory processing effects in the course of deductive reasoning. Participants undertook reasoning tasks based on visually presented arguments which were either (a) valid (Aristotelian) statements or (b) paradoxes. We compared brain activation patterns while participants maintained the premises / conclusions of either the valid statements or the paradoxes in working memory (WM). Event-related brain potentials (ERPs), specifically the P300 component of ERPs, were recorded during the WM phase, during which participants were required to draw a logical conclusion regarding the correctness of the valid syllogisms or the paradoxes. During the processing of paradoxes, results demonstrated a more positive event-related potential deflection (P300) across frontal regions, whereas processing of valid statements was associated with noticeable P300 amplitudes across parieto-occipital regions. These findings suggest that paradoxes mobilize frontal attention mechanisms, while valid deduction promotes parieto-occipital activity associated with attention and/or subsequent memory processing.

<![CDATA[Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays]]>

Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible.

<![CDATA[Target and Non-Target Processing during Oddball and Cyberball: A Comparative Event-Related Potential Study]]>

The phenomenon of social exclusion can be investigated by using a virtual ball-tossing game called Cyberball. In neuroimaging studies, structures have been identified which are activated during social exclusion. But to date the underlying mechanisms are not fully disclosed. In previous electrophysiological studies it was shown that the P3 complex is sensitive to exclusion manipulations in the Cyberball paradigm and that there is a correlation between P3 amplitude and self-reported social pain. Since this posterior event-related potential (ERP) was widely investigated using the oddball paradigm, we directly compared the ERP effects elicited by the target (Cyberball: “ball possession”) and non-target (Cyberball: “ball possession of a co-player) events in both paradigms. Analyses mainly focused on the effect of altered stimulus probabilities of the target and non-target events between two consecutive blocks of the tasks. In the first block, the probability of the target and non-target event was 33% (Cyberball: inclusion), in the second block target probability was reduced to 17%, and accordingly, non-target probability was increased to 66% (Cyberball: exclusion). Our results indicate that ERP amplitude differences between inclusion and exclusion are comparable to ERP amplitude effects in a visual oddball task. We therefore suggest that ERP effects–especially in the P3 range–in the Oddball and Cyberball paradigm rely on similar mechanisms, namely the probability of target and non-target events. Since the simulation of social exclusion (Cyberball) did not trigger a unique ERP response, the idea of an exclusion-specific neural alarm system is not supported. The limitations of an ERP-based approach will be discussed.

<![CDATA[Narrow microtunnel technology for the isolation and precise identification of axonal communication among distinct hippocampal subregion networks]]>

Communication between different sub regions of the hippocampus is fundamental to learning and memory. However accurate knowledge about information transfer between sub regions from access to the activity in individual axons is lacking. MEMS devices with microtunnels connecting two sub networks have begun to approach this problem but the commonly used 10 μm wide tunnels frequently measure signals from multiple axons. To reduce this complexity, we compared polydimethylsiloxane (PDMS) microtunnel devices each with a separate tunnel width of 2.5, 5 or 10 μm bridging two wells aligned over a multi electrode array (MEA). Primary rat neurons were grown in the chambers with neurons from the dentate gyrus on one side and hippocampal CA3 on the other. After 2–3 weeks of culture, spontaneous activity in the axons inside the tunnels was recorded. We report electrophysiological, exploratory data analysis for feature clustering and visual evidence to support the expectation that 2.5 μm wide tunnels have fewer axons per tunnel and therefore more clearly delineated signals than 10 or 5 μm wide tunnels. Several measures indicated that fewer axons per electrode enabled more accurate detection of spikes. A clustering analysis comparing the variations of spike height and width for different tunnel widths revealed tighter clusters representing unique spikes with less height and width variation when measured in narrow tunnels. Wider tunnels tended toward more diffuse clusters from a continuum of spike heights and widths. Standard deviations for multiple cluster measures, such as Average Dissimilarity, Silhouette Value (S) and Separation Factor (average dissimilarity/S value), support a conclusion that 2.5 μm wide tunnels containing fewer axons enable more precise determination of individual action potential peaks, their propagation direction, timing, and information transfer between sub networks.

<![CDATA[Intraoperative Electroretinograms before and after Core Vitrectomy]]>


To evaluate retinal function by intraoperative electroretinograms (ERGs) before and after core vitrectomy.


Retrospective consecutive case series.


Full-field photopic ERGs were recorded prior to the beginning and just after core vitrectomy using a sterilized contact lens electrode in 20 eyes that underwent non-complicated vitreous surgery. A light-emitted diode was embedded into the contact lens, and a stimulus of 150 ms on and 350 ms off at 2 Hz was delivered. The amplitudes and latencies of the a-, b-, and d-waves, photopic negative response (PhNR), and oscillatory potentials (OPs) were analyzed. The intraocular temperature at the mid-vitreous was measured at the beginning and just after the surgery with a thermoprobe.


The intraocular temperature was 33.2 ± 1.3°C before and 29.4 ± 1.7°C after the vitrectomy. The amplitudes of the PhNR and OPs were significantly smaller after surgery, and the latencies of all components were prolonged after the surgery. These changes were not significantly correlated with the changes of the temperature.


Retinal function is reduced just after core vitrectomy in conjunction with significant temperature reduction. The differences in the degree of alterations of each ERG component suggests different sensitivity of each type of retinal neuron.

<![CDATA[Doping Polypyrrole Films with 4-N-Pentylphenylboronic Acid to Enhance Affinity towards Bacteria and Dopamine]]>

Here we demonstrate the use of a functional dopant as a fast and simple way to tune the chemical affinity and selectivity of polypyrrole films. More specifically, a boronic-functionalised dopant, 4-N-Pentylphenylboronic Acid (PBA), was used to provide to polypyrrole films with enhanced affinity towards diols. In order to prove the proposed concept, two model systems were explored: (i) the capture and the electrochemical detection of dopamine and (ii) the adhesion of bacteria onto surfaces. The chemisensor, based on overoxidised polypyrrole boronic doped film, was shown to have the ability to capture and retain dopamine, thus improving its detection; furthermore the chemisensor showed better sensitivity in comparison with overoxidised perchlorate doped films. The adhesion of bacteria, Deinococcus proteolyticus, Escherichia coli, Streptococcus pneumoniae and Klebsiella pneumoniae, onto the boric doped polypyrrole film was also tested. The presence of the boronic group in the polypyrrole film was shown to favour the adhesion of sugar-rich bacterial cells when compared with a control film (Dodecyl benzenesulfonate (DBS) doped film) with similar morphological and physical properties. The presented single step synthesis approach is simple and fast, does not require the development and synthesis of functional monomers, and can be easily expanded to the electrochemical, and possibly chemical, fabrication of novel functional surfaces and interfaces with inherent pre-defined sensing and chemical properties.

<![CDATA[A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina]]>

Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.

<![CDATA[Decoding the Locus of Covert Visuospatial Attention from EEG Signals]]>

Visuospatial attention can be deployed to different locations in space independently of ocular fixation, and studies have shown that event-related potential (ERP) components can effectively index whether such covert visuospatial attention is deployed to the left or right visual field. However, it is not clear whether we may obtain a more precise spatial localization of the focus of attention based on the EEG signals during central fixation. In this study, we used a modified Posner cueing task with an endogenous cue to determine the degree to which information in the EEG signal can be used to track visual spatial attention in presentation sequences lasting 200 ms. We used a machine learning classification method to evaluate how well EEG signals discriminate between four different locations of the focus of attention. We then used a multi-class support vector machine (SVM) and a leave-one-out cross-validation framework to evaluate the decoding accuracy (DA). We found that ERP-based features from occipital and parietal regions showed a statistically significant valid prediction of the location of the focus of visuospatial attention (DA = 57%, p < .001, chance-level 25%). The mean distance between the predicted and the true focus of attention was 0.62 letter positions, which represented a mean error of 0.55 degrees of visual angle. In addition, ERP responses also successfully predicted whether spatial attention was allocated or not to a given location with an accuracy of 79% (p < .001). These findings are discussed in terms of their implications for visuospatial attention decoding and future paths for research are proposed.

<![CDATA[Contributions of Subsurface Cortical Modulations to Discrimination of Executed and Imagined Grasp Forces through Stereoelectroencephalography]]>

Stereoelectroencephalographic (SEEG) depth electrodes have the potential to record neural activity from deep brain structures not easily reached with other intracranial recording technologies. SEEG electrodes were placed through deep cortical structures including central sulcus and insular cortex. In order to observe changes in frequency band modulation, participants performed force matching trials at three distinct force levels using two different grasp configurations: a power grasp and a lateral pinch. Signals from these deeper structures were found to contain information useful for distinguishing force from rest trials as well as different force levels in some participants. High frequency components along with alpha and beta bands recorded from electrodes located near the primary motor cortex wall of central sulcus and electrodes passing through sensory cortex were found to be the most useful for classification of force versus rest although one participant did have significant modulation in the insular cortex. This study electrophysiologically corroborates with previous imaging studies that show force-related modulation occurs inside of central sulcus and insular cortex. The results of this work suggest that depth electrodes could be useful tools for investigating the functions of deeper brain structures as well as showing that central sulcus and insular cortex may contain neural signals that could be used for control of a grasp force BMI.

<![CDATA[A Low-Correlation Resting State of the Striatum during Cortical Avalanches and Its Role in Movement Suppression]]>

During quiet resting behavior, involuntary movements are suppressed. Such movement control is attributed to cortico-basal ganglia loops, yet population dynamics within these loops during resting and their relation to involuntary movements are not well characterized. Here, we show by recording cortical and striatal ongoing population activity in awake rats during quiet resting that intrastriatal inhibition maintains a low-correlation striatal resting state in the presence of cortical neuronal avalanches. Involuntary movements arise from disturbed striatal resting activity through two different population dynamics. Nonselectively reducing intrastriatal γ-aminobutyric acid (GABA) receptor-A inhibition synchronizes striatal dynamics, leading to involuntary movements at low rate. In contrast, reducing striatal interneuron (IN)-mediated inhibition maintains decorrelation and induces intermittent involuntary movements at high rate. This latter scenario was highly effective in modulating cortical dynamics at a subsecond timescale. To distinguish intrastriatal processing from loop dynamics, cortex-striatum-midbrain cultures, which lack feedback to cortex, were used. Cortical avalanches in vitro were accompanied by low-correlated resting activity in the striatum and nonselective reduction in striatal inhibition synchronized striatal neurons similar to in vivo. Importantly, reduction of inhibition from striatal INs maintained low correlations in the striatum while reorganizing functional connectivities among striatal neurons. Our results demonstrate the importance of two major striatal microcircuits in distinctly regulating striatal and cortical resting state dynamics. These findings suggest that specific functional connectivities of the striatum that are maintained by local inhibition are important in movement control.

<![CDATA[Effects of Caricaturing in Shape or Color on Familiarity Decisions for Familiar and Unfamiliar Faces]]>

Recent evidence suggests that while reflectance information (including color) may be more diagnostic for familiar face recognition, shape may be more diagnostic for unfamiliar face identity processing. Moreover, event-related potential (ERP) findings suggest an earlier onset for neural processing of facial shape compared to reflectance. In the current study, we aimed to explore specifically the roles of facial shape and color in a familiarity decision task using pre-experimentally familiar (famous) and unfamiliar faces that were caricatured either in shape-only, color-only, or both (full; shape + color) by 15%, 30%, or 45%. We recorded accuracies, mean reaction times, and face-sensitive ERPs. Performance data revealed that shape caricaturing facilitated identity processing for unfamiliar faces only. In the ERP data, such effects of shape caricaturing emerged earlier than those of color caricaturing. Unsurprisingly, ERP effects were accentuated for larger levels of caricaturing. Overall, our findings corroborate the importance of shape for identity processing of unfamiliar faces and demonstrate an earlier onset of neural processing for facial shape compared to color.