Early Stages Of Process Research Articles

How social innovations emerge in a rigid regulatory context: the case of demand responsive transport in Switzerland

ABSTRACT Demand responsive transport (DRT) solutions may improve rural transport systems. These solutions often emerge as social innovations in rural areas. In Switzerland, their planning process is embedded in a rigid regulatory framework of the public transport system. The objective of this paper is to understand in which way the regulatory framework of the public transport system influences planning processes of a DRT solution in a rural setting. The methodological approach of social innovation biographies helps to examine the necessary planning steps to start mybuxi, a DRT in two Swiss rural municipalities. Our findings show that regulatory constraints dominate the final planning stage of the social innovation. Protections of current public transport regulations hinder federal offices from subsidizing the DRT, having direct implications on the financial sustainability of the system. The findings of this paper help actors to better address regulatory questions in the early stage of the respective innovation process.

Morality or competence is more important? The effect of evaluation dimensions on ERP responses to neutral faces depends on contextual valence and self-relevance

Recent studies have shown that the processing of neutral facial expressions could be modulated by the valence and self-relevance of preceding verbal evaluations. However, these studies have not distinguished the dimension (i.e., morality and competence) from verbal evaluations. In fact, there is a hot controversy about whether morality or competence receives more weight. Therefore, using the ERP technique, the current study aimed to address this issue by comparing the influence of morality and competence evaluations on behavioral and neural responses to neutral facial expressions when these evaluations varied with contextual valence and self-relevance. Our ERP results revealed that the early EPN amplitudes were larger for neutral faces after receiving evaluations about self relative to evaluations about senders. Moreover, the EPN was more negative after a competence evaluation relative to a morality evaluation when these evaluations were positive, while this effect was absent when these evaluations were negative. The late LPP was larger after a morality evaluation compared to a competence evaluation when these evaluations were negative and directed to self. However, no significant LPP effect between morality and competence evaluations was observed when these evaluations were positive. The present study extended previous studies by showing that early and late processing stages of faces are affected by the evaluation dimension in a top-down manner and further modulated by contextual valence and self-relevance.

Impact of niobium addition and non-metallic inclusions’ characteristics on the microstructure and mechanical properties of low-carbon CrNiMnMoB ultrahigh-strength steel: A comprehensive investigation

The effect of cooling rate and Nb addition on the phase transformation, microstructures, and mechanical properties of thermomechanically controlled hot-rolled low-carbon CrNiMnMoB ultrahigh-strength steel were studied. The aspects impeding Nb's benefits on hardenability, phase transformation, and mechanical properties were investigated. The hot rolling process was simulated, and a continuous cooling transformation diagram was constructed for the studied steels. Microstructures were analysed using laser scanning confocal microscopy and field emission scanning electron microscopy, with the latter also used for in-depth investigations of the non-metallic inclusions. Transmission electron microscopy was employed to investigate the precipitate characteristics. The concentrations of Nb in the solution and precipitates were quantified for the martensitic and granular bainitic structures. The effect of Nb in solution on phase transformation and strengthening is diminished, and the hardness is reduced by Nb precipitation at an early processing stage. Decreasing the cooling rate promotes the formation of granular bainitic structures rather than martensite. After being subjected to hot rolling followed by water quenching and air cooling, the microstructures are autotempered martensite and fully granular bainite, respectively. Various non-metallic inclusions, including Al2O3, MnS, and Al2O3–MnS, MnS·BN, Al2O3·BN and MnS·Al2O3·BN were observed. The number density and area fraction of non-metallic inclusions in the Nb-containing steel and the air-cooled samples are higher than those observed in the Nb-free and water-quenched samples. Adding 0.04 wt% of Nb slightly increased the strength, but the toughness properties dropped, mainly due to the higher number density and area fraction of non-metallic inclusions and primary large precipitates.

Fenoldopam-mediated increase in autophagy associates with recruiting WIPI2 protein in early endosomes in vascular smooth muscle cells

Autophagy, a crucial cellular homeostatic process, has protective roles in the pathogenesis of hypertension. Dopamine, a monoamine neurotransmitter, regulates autophagy in the kidney and vascular system. However, the exact roles and mechanisms of dopaminergic system on the regulation of autophagy is not well known. In rat aortic vascular smooth muscle cells, fenoldopam (FEN, 25 nM/15 min), a D1-like receptor agonist, increased the ATG5 and LC3-II (a late autophagosome maker) protein expression. Consistently, FEN decreased p62/SQSTM1 protein expression. The FEN-mediated increase in ATG5 was attenuated by SCH39166 (1 μM/15 min), a D1- like receptor antagonist, indicating that FEN increased autophagy in the autophagosome formation stage through its D1-like receptors. FEN increased the protein expression of WD Repeat Domain, Phosphoinositide Interacting 2 (WIPI2) in a concentration- and time-dependent manner, which is important in the early steps of autophagosome formation. FEN (25 nM, 15 min) increased the WIPI2 puncta fluorescence intensity and the colocalization of WIPI2 with EEA1 (Veh: 7.12±1.1% vs FEN: 9.96±0.9%, N=5, P < 0.001, Student’s t test), a typical phosphatidylinositol-3-phosphate binding protein in early endosomes, indicating that WIPI2 recruitment in early endosomes is important in the early stage of FEN-mediated autophagic process. Taken together, FEN increases autophagy with WIPI2 recruitment in the early endosomes in vascular smooth muscle cells. This work was supported by US National Institutes of Health grants R01DK134574 and R01DK119652. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Effect of Turbulence on the Collision Rate between Settling Ice Crystals and Droplets

Abstract In mixed-phase clouds, graupel forms by riming, a process whereby ice crystals and supercooled water droplets settling through a turbulent flow collide and aggregate. We consider here the early stage of the collision process of small ice crystals with water droplets and determine numerically the geometric collision kernel in turbulent flows (therefore neglecting all interactions between the particles and assuming a collision efficiency equal to unity), over a range of energy dissipation rate 1–250 cm2 s−3 relevant to cloud microphysics. We take into account the effect of small, but nonzero fluid inertia, which is essential since it favors a biased orientation of the crystals with their broad side down. Since water droplets and ice crystals have different masses and shapes, they generally settle with different velocities. Turbulence does not play any significant role on the collision kernel when the difference between the settling velocities of the two sets of particles is larger than a few millimeters per second. The situation is completely different when the settling speeds of droplets and crystals are comparable, in which case turbulence is the main cause of collisions. Our results are compatible with those of recent experiments according to which turbulence does not clearly increase the growth rate of tethered graupel in a flow transporting water droplets.

The Phytophthora parasitica effector AVH195 interacts with ATG8, attenuates host autophagy, and promotes biotrophic infection

BackgroundPlant pathogens secrete effector proteins into host cells to suppress immune responses and manipulate fundamental cellular processes. One of these processes is autophagy, an essential recycling mechanism in eukaryotic cells that coordinates the turnover of cellular components and contributes to the decision on cell death or survival.ResultsWe report the characterization of AVH195, an effector from the broad-spectrum oomycete plant pathogen, Phytophthora parasitica. We show that P. parasitica expresses AVH195 during the biotrophic phase of plant infection, i.e., the initial phase in which host cells are maintained alive. In tobacco, the effector prevents the initiation of cell death, which is caused by two pathogen-derived effectors and the proapoptotic BAX protein. AVH195 associates with the plant vacuolar membrane system and interacts with Autophagy-related protein 8 (ATG8) isoforms/paralogs. When expressed in cells from the green alga, Chlamydomonas reinhardtii, the effector delays vacuolar fusion and cargo turnover upon stimulation of autophagy, but does not affect algal viability. In Arabidopsis thaliana, AVH195 delays the turnover of ATG8 from endomembranes and promotes plant susceptibility to P. parasitica and the obligate biotrophic oomycete pathogen Hyaloperonospora arabidopsidis.ConclusionsTaken together, our observations suggest that AVH195 targets ATG8 to attenuate autophagy and prevent associated host cell death, thereby favoring biotrophy during the early stages of the infection process.

Neural Correlates of Crowding in Macaque Area V4.

Visual crowding refers to the phenomenon where a target object that is easily identifiable in isolation becomes difficult to recognize when surrounded by other stimuli (distractors). Many psychophysical studies have investigated this phenomenon and proposed alternative models for the underlying mechanisms. One prominent hypothesis, albeit with mixed psychophysical support, posits that crowding arises from the loss of information due to pooled encoding of features from target and distractor stimuli in the early stages of cortical visual processing. However, neurophysiological studies have not rigorously tested this hypothesis. We studied the responses of single neurons in macaque (one male, one female) area V4, an intermediate stage of the object-processing pathway, to parametrically designed crowded displays and texture statistics-matched metameric counterparts. Our investigations reveal striking parallels between how crowding parameters-number, distance, and position of distractors-influence human psychophysical performance and V4 shape selectivity. Importantly, we also found that enhancing the salience of a target stimulus could alleviate crowding effects in highly cluttered scenes, and this could be temporally protracted reflecting a dynamical process. Thus, a pooled encoding of nearby stimuli cannot explain the observed responses, and we propose an alternative model where V4 neurons preferentially encode salient stimuli in crowded displays. Overall, we conclude that the magnitude of crowding effects is determined not just by the number of distractors and target-distractor separation but also by the relative salience of targets versus distractors based on their feature attributes-the similarity of distractors and the contrast between target and distractor stimuli.

Exploring the ‘black box’ of anxiety: An ERP study of non-consciously triggered fear generalization

Individuals with anxiety disorders frequently display heightened fear responses, even in situations where there is no imminent danger. We hypothesize that these irrational fear responses are related to automatic processing of fear generalization. The initial automatic detection of stimuli often operates at a non-conscious level. However, whether fear generalization can occur when the cues are not perceived consciously remains unclear. The current study investigated the neurocognitive mechanisms underlying fear conditioning and its non-conscious and conscious generalization using a backward masking paradigm, combined with analysis of event-related potentials from electroencephalographic recordings. Behaviorally, participants showed heightened shock expectancy in response to non-conscious perceived generalization stimuli compared to those perceived consciously. Nonetheless, participants could not consciously distinguish between danger and safe cues in non-conscious trials. Physiologically, danger cues evoked larger frontal N1 amplitudes than safety cues in non-conscious trials, suggesting enhanced attention vigilance towards danger cues in the early sensory processing stage. Meanwhile, when fear generalization was conscious, it was accompanied by a larger P2 amplitude, indicating attention orientation or stimulus evaluation. In addition, fear conditioning was associated with sustained discrimination on P2, P3, and LPP. These findings collectively suggest that non-conscious fear generalization occurs at the neural level, yet additional control conditions are required to confirm this phenomenon on the US expectancy. Thus, non-consciously fear generalization may represent a mechanism that could trigger automatic irrational fear, highlighting the need for further research to explore therapeutic targets in anxiety disorders.

Mid-infrared Properties of Narrow-line Seyfert 1 Galaxies Detected by LoTSS DR2

Narrow-line Seyfert 1 galaxies (NLS1s), a subclass of active galactic nuclei (AGNs) in an early stage of the accretion process, are also found to host relativistic jets. However, currently known jetted NLS1s are rare. The majority of NLS1s are undetected at the radio band. The radio detection rate of NLS1s increases with the LOFAR Two-metre Sky Survey (LoTSS), which provides a good opportunity for finding more jetted NLS1s. The better sensitivity raises the question whether the radio emission of NLS1s with a low radio luminosity originates from the jet activity. In order to clarify the origin of the radio emission for NLS1s and search for more jetted NLS1s, we explore the mid-infrared properties of LoTSS-detected NLS1s by comparing them with known jetted AGNs and star-forming galaxies (SFGs), which are located above and on the well-studied radio/far-infrared correlation, respectively. The majority of NLS1s show mid-infrared (MIR) excess compared with SFGs. Their radio emission shows a significant correlation with the MIR emission. In the MIR color–color diagram, NLS1s overlap flat spectrum radio quasars, but they are well separated from SFGs and optically selected radio galaxies. The flux ratio of the radio and MIR emission of these NLS1s is also similar to that of a radio-quiet quasar with a weak jet. These results imply substantial contributions from the AGN activities for both the radio and MIR emission of NLS1s. A small fraction of NLS1s with relatively higher radio luminosities are located in a similar region as blazars in the radio-MIR diagram, which suggests that the radio emission of these NLS1s is dominated by the jet. We obtain a sample of jetted NLS1 candidates through their radio excess in the radio-MIR diagram.

Architecture-level energy model for high-capacity STT-MRAM memory

ABSTRACT Nowadays, STT-MRAM has emerged as one of the leading contenders for next-generation memory technologies. However, STT-MRAM still exhibits high energy consumption due to its peripheral circuits, including the read/write and the sample amplifier (SA) circuits. Therefore, it is crucial to accurately evaluate the energy consumption of memory architectures during the early stages of the design process. Traditionally, energy evaluation can be conducted using the NVSim platform. However, the peripheral read/write circuitry of STT-MRAM undergoes iterative improvements, which cannot be promptly incorporated into NVSim. To addreGss this limitation and to enable comprehensive energy consumption evaluations spanning from device-level to architecture-level for STT-MRAM, an architecture-level energy consumption model is proposed in this paper. The model offers high accuracy and flexibility for the STT-MRAM memory array structure, abstracting the influences of read/write circuits for power evaluations. Comparative analysis is performed between the proposed model and the traditional approaches. When estimating a memory array with 128 × 64, the deviation using the proposed model is less than 2%, showing improved accuracy compared to that with analytical formulas. Notably, the proposed model offers up to 97% time savings in the whole circuit simulation, thus enhancing efficiency in the design and evaluation process.

A Unifying Model for Discordant and Concordant Results in Human Neuroimaging Studies of Facial Viewpoint Selectivity.

Recognizing faces regardless of their viewpoint is critical for social interactions. Traditional theories hold that view-selective early visual representations gradually become tolerant to viewpoint changes along the ventral visual hierarchy. Newer theories, based on single-neuron monkey electrophysiological recordings, suggest a three-stage architecture including an intermediate face-selective patch abruptly achieving invariance to mirror-symmetric face views. Human studies combining neuroimaging and multivariate pattern analysis (MVPA) have provided convergent evidence of view selectivity in early visual areas. However, contradictory conclusions have been reached concerning the existence in humans of a mirror-symmetric representation like that observed in macaques. We believe these contradictions arise from low-level stimulus confounds and data analysis choices. To probe for low-level confounds, we analyzed images from two face databases. Analyses of image luminance and contrast revealed biases across face views described by even polynomials-i.e., mirror-symmetric. To explain major trends across neuroimaging studies, we constructed a network model incorporating three constraints: cortical magnification, convergent feedforward projections, and interhemispheric connections. Given the identified low-level biases, we show that a gradual increase of interhemispheric connections across network-layers is sufficient to replicate view-tuning in early processing stages and mirror-symmetry in later stages. Data analysis decisions-pattern dissimilarity measure and data recentering-accounted for the inconsistent observation of mirror-symmetry across prior studies. Pattern analyses of human fMRI data (of either sex) revealed biases compatible with our model. The model provides a unifying explanation of MVPA studies of viewpoint selectivity and suggests observations of mirror-symmetry originate from ineffectively normalized signal imbalances across different face views.

Dearomatization drives complexity generation in freshwater organic matter

Dissolved organic matter (DOM) is one of the most complex, dynamic and abundant sources of organic carbon, but its chemical reactivity remains uncertain1–3. Greater insights into DOM structural features could facilitate understanding its synthesis, turnover and processing in the global carbon cycle4,5. Here we use complementary multiplicity-edited 13C nuclear magnetic resonance (NMR) spectra to quantify key substructures assembling the carbon skeletons of DOM from four main Amazon rivers and two mid-size Swedish boreal lakes. We find that one type of reaction mechanism, oxidative dearomatization (ODA), widely used in organic synthetic chemistry to create natural product scaffolds6–10, is probably a key driver for generating structural diversity during processing of DOM that are rich in suitable polyphenolic precursor molecules. Our data suggest a high abundance of tetrahedral quaternary carbons bound to one oxygen and three carbon atoms (OCqC3 units). These units are rare in common biomolecules but could be readily produced by ODA of lignin-derived and tannin-derived polyphenols. Tautomerization of (poly)phenols by ODA creates non-planar cyclohexadienones, which are subject to immediate and parallel cycloadditions. This combination leads to a proliferation of structural diversity of DOM compounds from early stages of DOM processing, with an increase in oxygenated aliphatic structures. Overall, we propose that ODA is a key reaction mechanism for complexity acceleration in the processing of DOM molecules, creation of new oxygenated aliphatic molecules and that it could be prevalent in nature.

Neuronal cell cycle reentry events in the aging brain are more prevalent in neurodegeneration and lead to cellular senescence.

Increasing evidence indicates that terminally differentiated neurons in the brain may recommit to a cell cycle-like process during neuronal aging and under disease conditions. Because of the rare existence and random localization of these cells in the brain, their molecular profiles and disease-specific heterogeneities remain unclear. Through a bioinformatics approach that allows integrated analyses of multiple single-nucleus transcriptome datasets from human brain samples, these rare cell populations were identified and selected for further characterization. Our analyses indicated that these cell cycle-related events occur predominantly in excitatory neurons and that cellular senescence is likely their immediate terminal fate. Quantitatively, the number of cell cycle re-engaging and senescent neurons decreased during the normal brain aging process, but in the context of late-onset Alzheimer's disease (AD), these cells accumulate instead. Transcriptomic profiling of these cells suggested that disease-specific differences were predominantly tied to the early stage of the senescence process, revealing that these cells presented more proinflammatory, metabolically deregulated, and pathology-associated signatures in disease-affected brains. Similarly, these general features of cell cycle re-engaging neurons were also observed in a subpopulation of dopaminergic neurons identified in the Parkinson's disease (PD)-Lewy body dementia (LBD) model. An extended analysis conducted in a mouse model of brain aging further validated the ability of this bioinformatics approach to determine the robust relationship between the cell cycle and senescence processes in neurons in this cross-species setting.

Real-time multibody simulation of vehicle wheel suspensions of different topologies with elastokinematic properties

AbstractDriving simulators are becoming increasingly important in vehicle development, as they allow test drivers to evaluate the driving characteristics of a vehicle at an early stage of the development process. Vehicle dynamics models used for such real-time applications are usually simplified to achieve sufficiently low computation times, especially with respect to the elastokinematic properties of the wheel suspension. This contribution introduces a real-time capable multibody simulation model for wheel suspensions taking into account their elastokinematics. The underlying data model allows the parametrization of different suspension topologies. Linear-implicit integration methods enable real-time capable integration of the underlying numerically stiff equation of motion without major model simplifications. It is shown how the computational effort of linear-implicit integration can be reduced by explicitly taking the suspension topology into account. A versatile process for the analytical online-linearization of the equation of motion of arbitrary suspension topologies is presented. Both a double wishbone and a multilink suspension are simulated with very high accuracy in real-time on a standard PC.

A simulation-based performance evaluation of new generation dynamic shading devices with multi-objective optimization

Shading devices are the integrated components of building envelopes, which are designed to protect interiors from the excessive amount of direct and indirect solar radiation. Blocking the sunlight, these devices reduce the operational cost of cooling systems, which implies an inverse proportionality between the cooling energy consumption and desired thermal comfort. Therefore, in this study, a unique design for dynamic shading devices of an office building, located in the hot and humid climatic region, is proposed and presented from the early stages of the architectural design process. Above all, an innovative parametric model is created using the Grasshopper algorithmic modeling environment with the Honeybee and Ladybug plug-ins to overcome all difficulties of the manual design process. By employing the optimization plug-in of the Grasshopper software named Octopus, a performance evaluation based multi-objective optimization (MOO) method is introduced to find different cell dimensions of the devices for various orientations, south, east and west, of the office building. This research also investigates the potential of the proposed shading devices based on two major performance aspects, reducing the cooling load while increasing the thermal comfort of the office building, located at Bayrakli, Izmir, Turkey, latitude: 38° 27′ 44.00″ N and longitude: 27° 10′ 0.00″ E. The lowest cooling energy consumption is estimated as 8.35 kWh for 22nd of July 12:00 a.m. for the west orientation with the dimension of 100 × 100 cm, among other cell dimensions, which are 50 × 200 cm and 200 × 50 cm. The novelty lies behind the optimization of the conflicting performance features and the design of the new generation dynamic shading devices which would shed light on new shading device era.

Brain mechanisms underlying the emotion processing bias in treatment-resistant depression

Depression is associated with a cognitive bias towards negative information and away from positive information. This biased emotion processing may underlie core depression symptoms, including persistent feelings of sadness and a reduced capacity to experience pleasure. The neural mechanisms responsible for this biased emotion processing remain unknown. Here we had a unique opportunity to record stereotactic electroencephalography signals in the amygdala and prefrontal cortex (PFC) from 5 patients with treatment-resistant depression (TRD) and 12 patients with epilepsy (as control) while they participated in an affective bias task in which happy and sad faces were evaluated. First, compared with the control group, patients with TRD showed increased amygdala responses to sad faces in the early stage (around 300 ms) and decreased amygdala responses to happy faces in the late stage (around 600 ms) following the onset of faces. Furthermore, during the late stage of happy-face processing, alpha-band activity in the PFC as well as alpha-phase locking between the amygdala and the PFC were significantly greater in patients with TRD compared with the control group. The increased amygdala activation during the early stage of sad-face processing suggests an overactive bottom-up processing system in TRD. Meanwhile, the reduced amygdala response during the late stage of happy-face processing could be attributed to increased top-down inhibition by the PFC through alpha-band oscillation, which may be relieved following deep brain stimulation in the subcallosal cingulate and the ventral capsule/ventral striatum.

Impressing Artificial Intelligence: Automated Job Interview Training in Professional English Subjects

More organizations are using automated job interview platforms to screen candidates at the early stages of the recruitment process. These platforms enable job candidates to take automated video interviews remotely using their personal devices. The interviews are analysed by artificial intelligence (AI) powered algorithms to produce analytics which inform hiring decisions. In this article, we explore the use of automated job interviewing within professional English subjects delivered to undergraduate students in Hong Kong. The innovation was introduced to help students to keep up with recruitment practices, provide speaking practice and explore AI-powered evaluation as a form of feedback. As well as outlining how automated interviewing was integrated into our teaching practice, we discuss student feedback on the experience and offer suggestions for future teaching practice with this technology. We also highlight considerations for practitioners such as the acceptance and adoption of AI technologies into language learning provision and the development of AI literacy skills. AI technologies have much potential for language teaching and this article offers a practical exploration into one such technology: automated job interviewing.

Ultrafast Resonant Photon Emission from a Molecule Driven by a Strong Coherent Field in Terms of Complex Spectral Analysis

In this study, we investigate the time–frequency-resolved resonant photon emission from a molecular vibrational oscillator driven by a monochromatic coherent external field. Using the complex spectral analysis of the Liouvillian, which integrates irreversible dissipative phenomena into quantum theory, we elucidate the fundamental processes of photon emission. Indeed, our analytical approach successfully decomposes the emission spectrum into two intrinsic contributions: one from a resonance eigenmode and another from continuous eigenmodes. These components are responsible for incoherent luminescence and coherent scattering photon emission processes, respectively. Our results show that while spontaneous emission dominates in the early stages of the emission process, coherent scattering gradually becomes more pronounced with time. Furthermore, destructive quantum interference between the two components plays a key role in determining the overall shape of the emission spectrum.

Cross-language Exploration: a way to explore the use of L1 in the classroom at a Southeastern Mexican University

The place of the First Language (L1), in the classroom has been studied by many researchers in relation to the advantages and disadvantages of the use of the mother tongue in foreign language (FL) courses. This study aimed at uncovering the main reasons for which participants use the L1, in this case Spanish in an EFL course and finding out students’ perceptions of the use of their L1 in an EFL course. This study was carried out at a Mexican undergraduate programme. Participants were 11 students who were enrolled in a basic English course from a business and economics undergraduate programmes during the first semester of 2019. The study used a qualitative method and followed an action research design. Data were collected through observation in situ, a questionnaire and a cross-language exploration assessment task. Findings reveal that the participants have a great acceptance of the Spanish use in the English class. Most of the participants agreed that they use Spanish for different reasons: to translate vocabulary, to socialize, to ask questions, to participate, to compare answers or vocabulary, and to compare similarities and differences between L1 and EFL. All in all, the use of the Spanish is something that is always present in language courses. Despite the generalized idea of it causing detrimental effects on the target language learning; this study showed that it can render positive effects, at least at early stages of the EFL learning process.

Dynamic brain communication underwriting face pareidolia

Face pareidolia is a tendency to seeing faces in nonface images that reflects high tuning to a face scheme. Yet, studies of the brain networks underwriting face pareidolia are scarce. Here, we examined the time course and dynamic topography of gamma oscillatory neuromagnetic activity while administering a task with nonface images resembling a face. Images were presented either with canonical orientation or with display inversion that heavily impedes face pareidolia. At early processing stages, the peaks in gamma activity (40 to 45 Hz) to images either triggering or not face pareidolia originate mainly from the right medioventral and lateral occipital cortices, rostral and caudal cuneus gyri, and medial superior occipital gyrus. Yet, the difference occurred at later processing stages in the high-frequency range of 80 to 85 Hz over a set of the areas constituting the social brain. The findings speak rather for a relatively late neural network playing a key role in face pareidolia. Strikingly, a cutting-edge analysis of brain connectivity unfolding over time reveals mutual feedforward and feedback intra- and interhemispheric communication not only within the social brain but also within the extended large-scale network of down- and upstream regions. In particular, the superior temporal sulcus and insula strongly engage in communication with other brain regions either as signal transmitters or recipients throughout the whole processing of face-pareidolia images.