Aggressiveness, inhibitory control, and emotional states: A provocation paradigm.

The current study examines the effects of trait aggressiveness, inhibitory control and emotional states on aggressive behavior in a laboratory paradigm. One hundred and fifty-one adult participants took part (73 men, 71 women, and 7 nondisclosed). Event Related Potentials (ERPs) during a Go/No-Go task were utilized to capture the extent of inhibitory processing, with a laboratory provocation paradigm used to assess aggression. Contrary to the expectations, negative affective responses to provocation were negatively associated only with short-lived aggression and only among those with high past aggressiveness. Furthermore, past aggressiveness was related to a continuous increase in laboratory aggressive behavior regardless of the level of inhibitory control (P3 difference amplitude). However, feeling hostile was associated with short-lived aggressive behavior, only in those with lower levels of inhibitory control. These findings demonstrate the effect of distinct mechanisms on different patterns of aggressive behavior.

Reconfigurable quantum photonic circuits based on quantum dots.

Quantum photonic integrated circuits, composed of linear-optical elements, offer an efficient way for encoding and processing quantum information on-chip. At their core, these circuits rely on reconfigurable phase shifters, typically constructed from classical components such as thermo- or electro-optical materials, while quantum solid-state emitters such as quantum dots are limited to acting as single-photon sources. Here, we demonstrate the potential of quantum dots as reconfigurable phase shifters. We use numerical models based on established literature parameters to show that circuits utilizing these emitters enable high-fidelity operation and are scalable. Despite the inherent imperfections associated with quantum dots, such as imperfect coupling, dephasing, or spectral diffusion, we show that circuits based on these emitters may be optimized such that these do not significantly impact the unitary infidelity. Specifically, they do not increase the infidelity by more than 0.001 in circuits with up to 10 modes, compared to those affected only by standard nanophotonic losses and routing errors. For example, we achieve fidelities of 0.9998 in quantum-dot-based circuits enacting controlled-phase and - not gates without any redundancies. These findings demonstrate the feasibility of quantum emitter-driven quantum information processing and pave the way for cryogenically-compatible, fast, and low-loss reconfigurable quantum photonic circuits.

Emergence of information processing in biological systems and the origin of life.

As every life form is composed of cells, elements of consciousness, namely memory and sentience, must be grounded in mechanisms that are integral to unicellular organisms. Earlier studies indicated that cellular cytoskeletal structures consisting of excitable, flexible, and oscillating polymers such as microtubules, along with quantum events, are potentially responsible for information processing and thus consciousness. This work attempts to solve the unknown, that is, how, at the spark of life, the phenomenon of cellular information processing first appears. This study posits that the spatially distributed wave energy of the molecules of an incepting cell interacts with space and generates a rotating bioinformation field, forming a vortex. This vortex, the local energy maximum, whose inbound and outbound energy fluxes represent signal reception and dispersal, is a critical step in the spark of life responsible for information storage, and with incremental wave superpositions, exhibits information processing. The vorticity of the rotating field is computed, and the obtained field characteristics indicated the emergence of a prebiotic complex to initiate information processing. Furthermore, the developed system model explains how perturbations from the environment are converted into response signals for the emanation of sense, locomotion, nutrition, and asexual reproduction, the fundamental evolutionary building blocks of prokaryotes. Further research directions include explaining how the energy potential available in the bio-information field and the vortex leads to the first formation of genetic material, emergence of cytoskeleton, and extension of bio-information field to multi-cellular organisms.

Development and Effects of Adult Nursing Education Programs Using Virtual Reality Simulations.

A virtual-reality-simulation-based nursing education program incorporating an information processing model helps nursing students develop their learned knowledge as nursing behavior and develop their ability to cope with complex clinical challenges. The purpose of this study is to develop a nursing education program using an immersive virtual reality simulation app for clinical situations based on an information processing model and identify the effects. A non-quantitative control group pretest-post-test design was employed. The programs were developed using the ADDIE model and an information processing model. In order to verify the effectiveness of the program, six adult nursing learning issues were taught to the experimental group over 6 weeks. The nursing education program in this study provides comprehensive experiential learning through advanced virtual simulation, significantly enhancing nursing students' performance confidence, critical-thinking abilities, and problem-solving skills across a wide range of clinical scenarios. By repeatedly engaging with diverse learning topics related to adult nursing, this program not only equips students with essential practical skills but also contributes to the overall improvement of patient safety and the quality of medical care.

The role of extrinsic and intrinsic factors in perceptual filling-in of the blind-spot with variegated color and texture stimuli.

Vision scientists dedicated their efforts to unraveling the mechanism of filling-in at the blind-spot (BS) through numerous psychophysical experiments. The prevalent interpretation, emphasizing active filling-in, has spurred extensive research endeavors. In a parallel vein, a pertinent study highlighted the predominance of the nasal Visual Field (VF) over the temporal one and postulated the role of the Cortical Magnification Factor (CMF) in explaining the asymmetry of filling-in. In this study, we first replicated this experiment and then conducted BS-specific psychophysical experiments employing various bi-colored and bi-textured (patterned) stimuli. We observed that nasal dominance is not persistent in the context of the spread of perception for BS filling-in. We posit that the visual information processing priority index (VIPPI), comprising the CMF (an intrinsic factor unaffected by stimulus characteristics) and relative luminance (an extrinsic factor dependent on stimulus characteristics), governs the spread of perception for filling-in in case of diverse neighborhoods of the BS.

Optimized efficient attention-based network for facial expressions analysis in neurological health care.

Facial Expression Analysis (FEA) plays a vital role in diagnosing and treating early-stage neurological disorders (NDs) like Alzheimer's and Parkinson's. Manual FEA is hindered by expertise, time, and training requirements, while automatic methods confront difficulties with real patient data unavailability, high computations, and irrelevant feature extraction. To address these challenges, this paper proposes a novel approach: an efficient, lightweight convolutional block attention module (CBAM) based deep learning network (DLN) to aid doctors in diagnosing ND patients. The method comprises two stages: data collection of real ND patients, and pre-processing, involving face detection and an attention-enhanced DLN for feature extraction and refinement. Extensive experiments with validation on real patient data showcase compelling performance, achieving an accuracy of up to 73.2%. Despite its efficacy, the proposed model is lightweight, occupying only 3MB, making it suitable for deployment on resource-constrained mobile healthcare devices. Moreover, the method exhibits significant advancements over existing FEA approaches, holding tremendous promise in effectively diagnosing and treating ND patients. By accurately recognizing emotions and extracting relevant features, this approach empowers medical professionals in early ND detection and management, overcoming the challenges of manual analysis and heavy models. In conclusion, this research presents a significant leap in FEA, promising to enhance ND diagnosis and care.The code and data used in this work are available at: https://github.com/munsif200/Neurological-Health-Care.

Self-Controlled Feedback in Motor Learning: The Effects Depend on the Frequency of Request.

The benefits of allowing learners to control when to receive knowledge of results (KR) compared to a yoked group has been recently challenged and postulated to be mild at best. A potential explanation for such dissident findings is that individuals differentially utilize the autonomy provided by the self-controlled condition, which, in its turn, affects the outcomes. Therefore, the present study investigated the effects of self-controlled KR on motor learning focusing on the frequency of KR requests when performing an anticipatory timing task. Self-controlled groups were created based on participants' KR frequency of request (High, Medium, and Low referring to fifth, third, and first quintile) and, then, Yoked groups were created self-control condition pairing the KR request of the Self-controlled groups. We also measured self-efficacy and processing time as means to verify potential correlates. The results supported the expected interaction. While no difference between self-controlled and yoked groups were found for low frequencies of KR, a moderate amount of KR request was related to better results for the self-controlled group. Nonetheless, the opposite trend was observed for high frequencies of KR; the yoked group was superior to the self-controlled group. The results of this study allow us to conclude that the choices made, and not just the possibility of choosing, seem to define the benefits of KR self-control in motor learning.

Nanoironing van der Waals Heterostructures toward Electrically Controlled Quantum Dots.

Assembling two-dimensional van der Waals (vdW)-layered materials into heterostructures is an exciting development that sparked the discovery of rich correlated electronic phenomena. vdW heterostructures also offer possibilities for designer device applications in areas such as optoelectronics, valley- and spintronics, and quantum technology. However, realizing the full potential of these heterostructures requires interfaces with exceptionally low disorder which is challenging to engineer. Here, we show that thermal scanning probes can be used to create pristine interfaces in vdW heterostructures. Our approach is compatible at both the material- and device levels, and monolayer WS2 transistors show up to an order of magnitude improvement in electrical performance from this technique. We also demonstrate vdW heterostructures with low interface disorder enabling the electrical formation and control of quantum dots that can be tuned from macroscopic current flow to the single-electron tunneling regime.

Corrigendum: Differential effects of attachment security on visual fixation to facial expressions of emotion in 14-month-old infants: an eye-tracking study.

[This corrects the article DOI: 10.3389/fpsyg.2024.1302657.].

From unstructured accident reports to a hybrid decision support system for occupational risk management: The consensus converging approach.

INTRODUCTION: Workplace accidents in the petroleum industry can cause catastrophic damage to people, property, and the environment. Earlier studies in this domain indicate that the majority of the accident report information is available in unstructured text format. Conventional techniques for the analysis of accident data are time-consuming and heavily dependent on experts' subject knowledge, experience, and judgment. There is a need to develop a machine learning-based decision support system to analyze the vast amounts of unstructured text data that are frequently overlooked due to a lack of appropriate methodology. METHOD: To address this gap in the literature, we propose a hybrid methodology that uses improved text-mining techniques combined with an un-bias group decision-making framework to combine the output of objective weights (based on text mining) and subjective weights (based on expert opinion) of risk factors to prioritize them. Based on the contextual word embedding models and term frequencies, we extracted five important clusters of risk factors comprising more than 32 risk sub-factors. A heterogeneous group of experts and employees in the petroleum industry were contacted to obtain their opinions on the extracted risk factors, and the best-worst method was used to convert their opinions to weights. CONCLUSIONS AND PRACTICAL APPLICATIONS: The applicability of our proposed framework was tested on the data compiled from the accident data released by the petroleum industries in India. Our framework can be extended to accident data from any industry, to reduce analysis time and improve the accuracy in classifying and prioritizing risk factors.

Effects of User Experience in Automated Information Processing on Perceived Usefulness of Digital Contact-Tracing Apps: Cross-Sectional Survey Study.

BACKGROUND: In pandemic situations, digital contact tracing (DCT) can be an effective way to assess one's risk of infection and inform others in case of infection. DCT apps can support the information gathering and analysis processes of users aiming to trace contacts. However, users' use intention and use of DCT information may depend on the perceived benefits of contact tracing. While existing research has examined acceptance in DCT, automation-related user experience factors have been overlooked. OBJECTIVE: We pursued three goals: (1) to analyze how automation-related user experience (ie, perceived trustworthiness, traceability, and usefulness) relates to user behavior toward a DCT app, (2) to contextualize these effects with health behavior factors (ie, threat appraisal and moral obligation), and (3) to collect qualitative data on user demands for improved DCT communication. METHODS: Survey data were collected from 317 users of a nationwide-distributed DCT app during the COVID-19 pandemic after it had been in app stores for >1 year using a web-based convenience sample. We assessed automation-related user experience. In addition, we assessed threat appraisal and moral obligation regarding DCT use to estimate a partial least squares structural equation model predicting use intention. To provide practical steps to improve the user experience, we surveyed users' needs for improved communication of information via the app and analyzed their responses using thematic analysis. RESULTS: Data validity and perceived usefulness showed a significant correlation of r=0.38 (P<.001), goal congruity and perceived usefulness correlated at r=0.47 (P<.001), and result diagnosticity and perceived usefulness had a strong correlation of r=0.56 (P<.001). In addition, a correlation of r=0.35 (P<.001) was observed between Subjective Information Processing Awareness and perceived usefulness, suggesting that automation-related changes might influence the perceived utility of DCT. Finally, a moderate positive correlation of r=0.47 (P<.001) was found between perceived usefulness and use intention, highlighting the connection between user experience variables and use intention. Partial least squares structural equation modeling explained 55.6% of the variance in use intention, with the strongest direct predictor being perceived trustworthiness (ß=.54; P<.001) followed by moral obligation (ß=.22; P<.001). Based on the qualitative data, users mainly demanded more detailed information about contacts (eg, place and time of contact). They also wanted to share information (eg, whether they wore a mask) to improve the accuracy and diagnosticity of risk calculation. CONCLUSIONS: The perceived result diagnosticity of DCT apps is crucial for perceived trustworthiness and use intention. By designing for high diagnosticity for the user, DCT apps could improve their support in the action regulation of users, resulting in higher perceived trustworthiness and use in pandemic situations. In general, automation-related user experience has greater importance for use intention than general health behavior or experience.

A hierarchy index for networks in the brain reveals a complex entangled organizational structure.

Networks involved in information processing often have their nodes arranged hierarchically, with the majority of connections occurring in adjacent levels. However, despite being an intuitively appealing concept, the hierarchical organization of large networks, such as those in the brain, is difficult to identify, especially in absence of additional information beyond that provided by the connectome. In this paper, we propose a framework to uncover the hierarchical structure of a given network, that identifies the nodes occupying each level as well as the sequential order of the levels. It involves optimizing a metric that we use to quantify the extent of hierarchy present in a network. Applying this measure to various brain networks, ranging from the nervous system of the nematode Caenorhabditis elegans to the human connectome, we unexpectedly find that they exhibit a common network architectural motif intertwining hierarchy and modularity. This suggests that brain networks may have evolved to simultaneously exploit the functional advantages of these two types of organizations, viz., relatively independent modules performing distributed processing in parallel and a hierarchical structure that allows sequential pooling of these multiple processing streams. An intriguing possibility is that this property we report may be common to information processing networks in general.

Modification of temporal pattern sensitivity for inputs from medial entorhinal cortex by lateral inputs in hippocampal granule cells.

The medial dendrites (MDs) of granule cells (GCs) receive spatial information through the medial entorhinal cortex (MEC) from the entorhinal cortex in the rat hippocampus while the distal dendrites (DDs) of GCs receive non-spatial information (sensory inputs) through the lateral entorhinal cortex (LEC). However, it is unclear how information processing through the two pathways is managed in GCs. In this study, we investigated associative information processing between two independent inputs to MDs and DDs. First, in physiological experiments, to compare response characteristics between MDs and DDs, electrical stimuli comprising five pulses were applied to the MPP or LPP in rat hippocampal slices. These stimuli transiently decreased the excitatory postsynaptic potentials (EPSPs) of successive input pulses to MDs, whereas EPSPs to DDs showed sustained responses. Next, in computational experiments using a local network model obtained by fitting of the physiological experimental data, we compared associative information processing between DDs and MDs. The results showed that the temporal pattern sensitivity for burst inputs to MDs depended on the frequency of the random pulse inputs applied to DDs. On the other hand, with lateral inhibition to GCs from interneurons, the temporal pattern sensitivity for burst inputs to MDs was enhanced or tuned up according to the frequency of the random pulse inputs to the other cells. Thus, our results suggest that the temporal pattern sensitivity of spatial information depends on the non-spatial inputs to GCs.

Dynamic causal modeling analysis reveals the modulation of motor cortex and integration in superior temporal gyrus during multisensory speech perception.

The processing of speech information from various sensory modalities is crucial for human communication. Both left posterior superior temporal gyrus (pSTG) and motor cortex importantly involve in the multisensory speech perception. However, the dynamic integration of primary sensory regions to pSTG and the motor cortex remain unclear. Here, we implemented a behavioral experiment of classical McGurk effect paradigm and acquired the task functional magnetic resonance imaging (fMRI) data during synchronized audiovisual syllabic perception from 63 normal adults. We conducted dynamic causal modeling (DCM) analysis to explore the cross-modal interactions among the left pSTG, left precentral gyrus (PrG), left middle superior temporal gyrus (mSTG), and left fusiform gyrus (FuG). Bayesian model selection favored a winning model that included modulations of connections to PrG (mSTG → PrG, FuG → PrG), from PrG (PrG → mSTG, PrG → FuG), and to pSTG (mSTG → pSTG, FuG → pSTG). Moreover, the coupling strength of the above connections correlated with behavioral McGurk susceptibility. In addition, significant differences were found in the coupling strength of these connections between strong and weak McGurk perceivers. Strong perceivers modulated less inhibitory visual influence, allowed less excitatory auditory information flowing into PrG, but integrated more audiovisual information in pSTG. Taken together, our findings show that the PrG and pSTG interact dynamically with primary cortices during audiovisual speech, and support the motor cortex plays a specifically functional role in modulating the gain and salience between auditory and visual modalities. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-023-09945-z.

Aperiodic activity differences in individuals with high and low temporal processing efficiency.

It is known that Temporal Information Processing (TIP) underpins our cognitive functioning. Previous research has focused on the relationship between TIP efficiency and oscillatory brain activity, especially the gamma rhythm; however, non-oscillatory (aperiodic or 1/f) brain activity has often been missed. Recent studies have identified the 1/f component as being important for the functioning of the brain. Therefore, the current study aimed to verify whether TIP efficiency is associated with specific EEG resting state cortical activity patterns, including oscillatory and non-oscillatory (aperiodic) brain activities. To measure individual TIP efficiency, we used two behavioral tasks in which the participant judges the order of two sounds separated by millisecond intervals. Based on the above procedure, participants were classified into two groups with high and low TIP efficiency. Using cluster-based permutation analyses, we examined between-group differences in oscillatory and non-oscillatory (aperiodic) components across the 1-90 Hz range. The results revealed that the groups differed in the aperiodic component across the 30-80 Hz range in fronto-central topography. In other words, participants with low TIP efficiency exhibited higher levels of aperiodic activity, and thus a flatter frequency spectrum compared to those with high TIP efficiency. We conclude that participants with low TIP efficiency display higher levels of 'neural noise', which is associated with poorer quality and speed of neural processing.

Peak alpha frequency in schizophrenia, bipolar disorder, and healthy volunteers: Associations with visual information processing and cognition.

BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are associated with information processing abnormalities, including visual perceptual and cognitive impairments, that impact daily functioning. Recent work in healthy samples suggests that peak alpha frequency (PAF) is an electrophysiological index of visual information processing speed that is also correlated with cognitive ability. There is evidence that PAF is slowed in SCZ, but it remains unclear whether PAF is reduced in BD, or if slower PAF is associated with impaired visual perception and cognition in these clinical disorders. METHODS: The current study recorded resting-state brain activity (both eyes open and closed) with electroencephalography (EEG) in 90 SCZ participants, 62 BD participants, and 69 healthy controls. Most participants also performed a visual perception task (backward masking) and cognitive testing (MATRICS Consensus Cognitive Battery). RESULTS: We replicated previous findings of reduced PAF in SCZ compared with healthy controls. In contrast, PAF in BD did not significantly differ from healthy controls. Further, PAF was significantly correlated with performance on the perceptual and cognitive measures in SCZ, but not BD. PAF was also correlated with visual perception in the healthy control group, and showed a trend-level correlation with cognition. CONCLUSIONS: Together, these results suggest that PAF deficits characterize SCZ, but not BD, and that individual differences in PAF relate to abnormalities in visual information processing and cognition in SCZ.

Systems Genome: Coordinated Gene Activity Networks, Recurring Coordination Modules, and Genome Homeostasis in Developing Neurons.

As human progenitor cells differentiate into neurons, the activities of many genes change; these changes are maintained within a narrow range, referred to as genome homeostasis. This process, which alters the synchronization of the entire expressed genome, is distorted in neurodevelopmental diseases such as schizophrenia. The coordinated gene activity networks formed by altering sets of genes comprise recurring coordination modules, governed by the entropy-controlling action of nuclear FGFR1, known to be associated with DNA topology. These modules can be modeled as energy-transferring circuits, revealing that genome homeostasis is maintained by reducing oscillations (noise) in gene activity while allowing gene activity changes to be transmitted across networks; this occurs more readily in neuronal committed cells than in neural progenitors. These findings advance a model of an "entangled" global genome acting as a flexible, coordinated homeostatic system that responds to developmental signals, is governed by nuclear FGFR1, and is reprogrammed in disease.

Clinical and neuropsychological correlates of theta-band functional excitation-inhibition ratio in autism: An EEG study.

OBJECTIVE: How abnormal brain signaling impacts cognition in autism spectrum disorder (ASD) remained elusive. This study aimed to investigate the local and global brain signaling in ASD indicated by theta-band functional excitation-inhibition (fE/I) ratio and explored psychophysiological relationships between fE/I, cognitive deficits, and ASD symptomatology. METHODS: A total of 83 ASD and typically developing (TD) individuals participated in this study. Participants' interference control and set-shifting abilities were assessed. Resting-state electroencephalography (EEG) was used for estimating theta-band fE/I ratio. RESULTS: ASD individuals (n = 31 without visual EEG abnormality; n = 22 with visual EEG abnormality) generally performed slower in a cognitive task tapping interference control and set-maintenance abilities, but only ASD individuals with visually abnormal EEG performed significantly slower than their TD counterparts (Bonferroni-corrected ps < .001). Heightened theta-band fE/I ratios at the whole-head level, left and right hemispheres were observed in the ASD subgroup without visual EEG abnormality only (Bonferroni-corrected ps < .001), which remained highly significant when only data from medication-naïve participants were analyzed. In addition, higher left hemispheric fE/I ratios in ASD individuals without visual EEG abnormality were significantly correlated with faster interference control task performance, in turn faster reaction time was significantly associated with less severe restricted, repetitive behavior (Bonferroni-corrected ps ≤ .0017). CONCLUSIONS: Differential theta-band fE/I within the ASD population. Heightened theta-band fE/I in ASD without visual EEG abnormality may be associated with more efficient filtering of distractors and a less severe ASD symptom manifestation. SIGNIFICANCE: Brain signaling, indicated by theta-band fE/I, was different in ASD subgroups. Only ASD with visually-normal EEG showed heightened theta-band fE/I, which was associated with faster processing of visual distractors during a cognitive task. More efficient distractor filtering was associated with less restricted, repetitive behaviors.

Attention and sensory integration for gait in young adults with autism spectrum disorder.

INTRODUCTION: Altered sensorimotor function is a common feature of autism spectrum disorder (ASD). As a result, spatiotemporal walking patterns are typically affected. Attentional processes relevant for locomotion may be altered in people with ASD. This study assessed the extent to which gait alterations observed under sensory challenging conditions are due to reduced attention-related processes in young adults with ASD. METHODS: Twenty-one adults with ASD and 21 age- and sex-matched neurotypical participants walked at a self-selected pace on a 10-m walkway under 12 sensory/attention conditions: hard or carpet flooring; well-lit or dim lighting; no attention task, an auditory choice-reaction time information-processing task, or a simple reaction time information-processing task. Gait data were collected with a 12-marker motion capture set and a trunk accelerometer. Spatiotemporal characteristics of gait were derived and compared between the two groups across gait conditions. RESULTS: Floor/light conditions impacted gait speed, average step length, average stance time, average step width, and step width variability similarly in both groups (p<0.05). The information processing tasks impacted average step length, gait speed, and step length variability (p<0.05). Group differences were found in step length metrics: the ASD group had decreased average step length during the simple reaction time information-processing task and neurotypical participants did not (p=0.039); the ASD group had increased variability on carpet compared to hard floor and the neurotypical group had no change in variability due to floor (p=0.015). SIGNIFICANCE: These results suggest that attentional set-shifting and somatosensory inputs may play an important role in ASD-related gait alterations. Step length metrics appear to be sensitive to group differences between ASD and neurotypical adults during sensory challenging conditions.

The roles of phishing knowledge, cue utilization, and decision styles in phishing email detection.

This study investigated the roles of phishing knowledge, cue utilization, and decision styles in contributing to phishing email detection. Participants (N = 145) completed an online email sorting task, and measures of phishing knowledge, email decision styles, cue utilization, and email security awareness. Cue utilization was the only factor that uniquely predicted the capacity to discriminate phishing from genuine emails. Phishing knowledge was associated with greater phishing detection and a bias towards classifying all emails as phishing. A preference for intuitive decision making predicted lower detection of phishing emails, driven by a greater tendency to classify emails as genuine. These findings support the proposition that cue utilization is a distinct cognitive process that enables expert performance. The outcomes indicate that, in addition to increasing phishing knowledge and developing safe behavioral patterns, anti-phishing training needs to provide opportunities for trainees to develop meaningful cue associations.