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Developmental science aims to explain development across the lifespan. Jerome Kagan observed that the same behavior can occur for different reasons, and differing behaviors can occur for the same reason. To help account for persistence, desistence, and transformation of behavior across development, Kagan introduced various types of continuity and discontinuity of forms and functions of behavior. This framework provides opportunities for identifying explanatory mechanisms in behavior development. However, misconceptions remain in applying the concepts that Kagan introduced. Much of the literature assumes developmental continuity in constructs without examining whether assumptions are supported, leading to faulty developmental inferences. For instance, the use of the same measure across time to assess development assumes that the behavior occurs for the same reason across time (homotypic continuity). In addition, just because one behavior predicts a different behavior at a later time does not necessarily indicate that age-differing behaviors occur for the same reason (heterotypic continuity). This review aims to advance conceptualizations of continuity and discontinuity from a contemporary perspective with aims to improve mechanistic understanding of behavior development across the lifespan. To better align behaviors, functions, and mechanisms, research should (a) examine (dis)continuity of individual behaviors rather than merely syndromes, (b) identify the function(s) of the given behavior(s), and (c) identify the cognitive and biological processes that underlie the behavior-function pairs. Incorporating examples from research on development of humans and nonhuman animals, I discuss challenges from work that has followed Kagan's ideas and ways to advance understanding of continuity and discontinuity across development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

This article endeavors to provide a useful perspective for Researchers and Authors within the realm of Behavioral Sciences, particularly those engaged in the study of Behavioral Physiology, namely the discipline focusing on the intricate interplay between physiological processes and the related behavioral manifestations. Alongside the prevailing conservatism that has characterized the progression of behavioral sciences in recent decades, it advocates for an additional approach in the study of Behavioral Physiology that revolves around a more inclusive perspective: beyond the analysis of isolated behavioral events as discrete components, akin to scattered pieces of a larger puzzle, emphasis also is placed on elucidating their interconnectedness. It is within these interrelationships that the governing constraints of behavior, whether exhibited by humans or any other species, manifest as a cohesive and functional structure., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Working memory (WM) is essential for the temporary storage and processing of information required for complex cognitive tasks and relies on neuronal theta and gamma oscillations. Given the limited capacity of WM, researchers have investigated various methods to improve it, including transcranial alternating current stimulation (tACS), which modulates brain activity at specific frequencies. One particularly promising approach is theta-gamma peak-coupled-tACS (TGCp-tACS), which simulates the natural interaction between theta and gamma oscillations that occurs during cognitive control in the brain. The aim of this study was to improve WM in healthy young adults with TGCp-tACS, focusing on both behavioral and neurophysiological outcomes. Thirty-one participants completed five WM tasks under both sham and verum stimulation conditions. Electroencephalography (EEG) recordings before and after stimulation showed that TGCp-tACS increased power spectral density (PSD) in the high-gamma region at the stimulation site, while PSD decreased in the theta and delta regions throughout the cortex. From a behavioral perspective, although no significant changes were observed in most tasks, there was a significant improvement in accuracy in the 14-item Sternberg task, indicating an improvement in phonological WM. In conclusion, TGCp-tACS has the potential to promote and improve the phonological component of WM. To fully realize the cognitive benefits, further research is needed to refine the stimulation parameters and account for individual differences, such as baseline cognitive status and hormonal factors., (© 2024. The Author(s).)

Predicting individual behavior is a crucial area of research in neuroscience. Graph Neural Networks (GNNs), as powerful tools for extracting graph-structured features, are increasingly being utilized in various functional connectivity (FC) based behavioral prediction tasks. However, current predictive models primarily focus on enhancing GNNs' ability to extract features from FC networks while neglecting the importance of upstream individual network construction quality. This oversight results in constructed functional networks that fail to adequately represent individual behavioral capacity, thereby affecting the subsequent prediction accuracy. To address this issue, we proposed a new GNN-based behavioral prediction framework, named Dual Multi-Hop Graph Convolutional Network (D-MHGCN). Through the joint training of two GCNs, this framework integrates individual functional network construction and behavioral prediction into a unified optimization model. It allows the model to dynamically adjust the individual functional cortical parcellation according to the downstream tasks, thus creating task-aware, individual-specific FCNs that largely enhance its ability to predict behavior scores. Additionally, we employed multi-hop graph convolution layers instead of traditional single-hop methods in GCN to capture complex hierarchical connectivity patterns in brain networks. Our experimental evaluations, conducted on the large, public Human Connectome Project dataset, demonstrate that our proposed method outperforms existing methods in various behavioral prediction tasks. Moreover, it produces more functionally homogeneous cortical parcellation, showcasing its practical utility and effectiveness. Our work not only enhances the accuracy of individual behavioral prediction but also provides deeper insights into the neural mechanisms underlying individual differences in behavior.

The environment influences brain and mental health, both detrimentally and beneficially. Existing research has emphasised the individual psychosocial 'microenvironment'. Less attention has been paid to 'macroenvironmental' challenges, including climate change, pollution, urbanicity, and socioeconomic disparity. Notably, the implications of climate and pollution on brain and mental health have only recently gained prominence. With the advent of large-scale big-data cohorts and an increasingly dense mapping of macroenvironmental parameters, we are now in a position to characterise the relation between macroenvironment, brain, and behaviour across different geographic and cultural locations globally. This review synthesises findings from recent epidemiological and neuroimaging studies, aiming to provide a comprehensive overview of the existing evidence between the macroenvironment and the structure and functions of the brain, with a particular emphasis on its implications for mental illness. We discuss putative underlying mechanisms and address the most common exposures of the macroenvironment. Finally, we identify critical areas for future research to enhance our understanding of the aetiology of mental illness and to inform effective interventions for healthier environments and mental health promotion., (© 2024. The Author(s).)

Neural activity and behavior vary within an individual (states) and between individuals (traits). However, the mapping of state-trait neural variation to behavior is not well understood. To address this gap, we quantify moment-to-moment changes in brain-wide co-activation patterns derived from resting-state functional magnetic resonance imaging. In healthy young adults, we identify reproducible spatiotemporal features of co-activation patterns at the single-subject level. We demonstrate that a joint analysis of state-trait neural variations and feature reduction reveal general motifs of individual differences, encompassing state-specific and general neural features that exhibit day-to-day variability. The principal neural variations co-vary with the principal variations of behavioral phenotypes, highlighting cognitive function, emotion regulation, alcohol and substance use. Person-specific probability of occupying a particular co-activation pattern is reproducible and associated with neural and behavioral features. This combined analysis of state-trait variations holds promise for developing reproducible neuroimaging markers of individual life functional outcome., Competing Interests: K.L. consults for Manifest Technologies. A.A. and J.D.M. hold equity with Neumora Therapeutics (formerly BlackThorn Therapeutics), Manifest Technologies, and are co-inventors on the following patents: Anticevic A, Murray JD, Ji JL: Systems and Methods for Neuro-Behavioral Relationships in Dimensional Geometric Embedding(N-BRIDGE), PCT International Application No.PCT/US2119/022110, filed March 13, 2019 and Murray JD, Anticevic A, Martin WJ: Methods and tools for detecting, diagnosing, predicting, prognosticating, or treating a neurobehavioral phenotype in a subject, U.S. Application No.16/149,903, filed on October 2, 664 2018, U.S. Application for PCT International Application No.18/054, 009 filed on October 2, 2018. J.L.J. is an employee of Manifest Technologies, has previously worked for Neumora, and is a co-inventor on the following patent: Anticevic A, Murray JD, Ji JL: Systems and Methods for Neuro-Behavioral Relationships in Dimensional Geometric Embedding (N-BRIDGE), PCT International Application No.PCT/US2119/022110, filed March 13, 2019. C.F. consults for Manifest Technologies and formerly consulted for RBNC (formerly BlackThorn Therapeutics). G.R. consults for and holds equity in Neumora and Manifest Technologies. L.P. is an employee of Manifest Technologies. J.H.K. holds equity in Biohaven Pharmaceuticals, Biohaven Pharmaceuticals Medical Sciences, Clearmind Medicine, EpiVario, Neumora Therapeutics, Tempero Bio, Terran Biosciences, Tetricus, and Spring Care. J.H.K. consults for AE Research Foundation, Aptinyx, Biohaven Pharmaceuticals, Biogen, Bionomics, Limited (Australia), BioXcel Therapeutics, Boehringer Ingelheim International, Cerevel Therapeutics, Clearmind Medicine, Cybin IRL, Delix Therapeutics, Eisai, Enveric Biosciences, Epiodyne, EpiVario, Evidera, Freedom Biosciences, Janssen Research & Development, Jazz Pharmaceuticals, Leal Therapeutics, Neumora Therapeutics, Neurocrine Biosciences, Novartis Pharmaceuticals Corporation, Otsuka America Pharmaceutical, Perception Neuroscience, Praxis Precision Medicines, PsychoGenics, Spring Care, Sunovion Pharmaceuticals, Takeda Industries, Tempero Bio, Terran Biosciences, and Tetricus. All other co-authors declare no competing interests., (Copyright: © 2024 Lee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Notwithstanding the huge progress in molecular and cellular neuroscience, our ability to understand the brain and develop effective treatments promoting mental health is still limited. This can be partially ascribed to the reductionist, deterministic and mechanistic approaches in neuroscience that struggle with the complexity of the central nervous system. Here, I introduce the Context theory of constrained systems proposing a novel role of contextual factors and genetic, molecular and neural substrates in determining brain functioning and behavior. This theory entails key conceptual implications. First, context is the main driver of behavior and mental states. Second, substrates, from genes to brain areas, have no direct causal link to complex behavioral responses as they can be combined in multiple ways to produce the same response and different responses can impinge on the same substrates. Third, context and biological substrates play distinct roles in determining behavior: context drives behavior, substrates constrain the behavioral repertoire that can be implemented. Fourth, since behavior is the interface between the central nervous system and the environment, it is a privileged level of control and orchestration of brain functioning. Such implications are illustrated through the Kitchen metaphor of the brain. This theoretical framework calls for the revision of key concepts in neuroscience and psychiatry, including causality, specificity and individuality. Moreover, at the clinical level, it proposes treatments inducing behavioral changes through contextual interventions as having the highest impact to reorganize the complexity of the human mind and to achieve a long-lasting improvement in mental health., (© 2024 The Author. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Abnormal behavior recognition is an important technology used to detect and identify activities or events that deviate from normal behavior patterns. It has wide applications in various fields such as network security, financial fraud detection, and video surveillance. In recent years, Deep Convolution Networks (ConvNets) have been widely applied in abnormal behavior recognition algorithms and have achieved significant results. However, existing abnormal behavior detection algorithms mainly focus on improving the accuracy of the algorithms and have not explored the real-time nature of abnormal behavior recognition. This is crucial to quickly identify abnormal behavior in public places and improve urban public safety. Therefore, this paper proposes an abnormal behavior recognition algorithm based on three-dimensional (3D) dense connections. The proposed algorithm uses a multi-instance learning strategy to classify various types of abnormal behaviors, and employs dense connection modules and soft-threshold attention mechanisms to reduce the model's parameter count and enhance network computational efficiency. Finally, redundant information in the sequence is reduced by attention allocation to mitigate its negative impact on recognition results. Experimental verification shows that our method achieves a recognition accuracy of 95.61% on the UCF-crime dataset. Comparative experiments demonstrate that our model has strong performance in terms of recognition accuracy and speed.

Previous neuroimaging research has established associations between urban exposure during early life and alterations in brain function and structure. However, the molecular mechanisms and behavioral relevance of these associations remain largely unknown. Here, we aimed to address this question using a combined analysis of multimodal data. Initially, we calculated amplitude of low-frequency fluctuations (ALFF) and gray matter volume (GMV) using resting-state functional and structural MRI to investigate their associations with early-life urbanization in a large sample of 511 healthy young adults. Then, we examined the spatial relationships of the identified neural correlates of early-life urbanization with gene expression, neurotransmitter, and behavioral domain atlases. Results showed that higher early-life urbanization scores were correlated with increased ALFF of the right fusiform gyrus and decreased GMV of the left dorsal medial prefrontal cortex and left precuneus. Remarkably, the identified neural correlates of early-life urbanization were spatially correlated with expression of gene categories primarily involving immune system process, signal transduction, and cellular metabolic process. Concurrently, there were significant associations between the neural correlates and specific neurotransmitter systems including dopamine, acetylcholine, and serotonin. Finally, we found that the ALFF correlates were associated with behavioral terms including "perception," "sensory," "cognitive control," and "reasoning." Apart from expanding existing knowledge of early-life urban environmental risk for mental disorders and health in general, our findings may contribute to an emerging framework for integrating social science, neuroscience, genetics, and public policy to respond to the major health challenge of world urbanization., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Finding an interpretable and compact representation of complex neuroimaging data is extremely useful for understanding brain behavioral mapping and hence for explaining the biological underpinnings of mental disorders. However, hand-crafted representations, as well as linear transformations, may inadequately capture the considerable variability across individuals. Here, we implemented a data-driven approach using a three-dimensional autoencoder on two large-scale datasets. This approach provides a latent representation of high-dimensional task-fMRI data which can account for demographic characteristics whilst also being readily interpretable both in the latent space learned by the autoencoder and in the original voxel space. This was achieved by addressing a joint optimization problem that simultaneously reconstructs the data and predicts clinical or demographic variables. We then applied normative modeling to the latent variables to define summary statistics ('latent indices') and establish a multivariate mapping to non-imaging measures. Our model, trained with multi-task fMRI data from the Human Connectome Project (HCP) and UK biobank task-fMRI data, demonstrated high performance in age and sex predictions and successfully captured complex behavioral characteristics while preserving individual variability through a latent representation. Our model also performed competitively with respect to various baseline models including several variants of principal components analysis, independent components analysis and classical regions of interest, both in terms of reconstruction accuracy and strength of association with behavioral variables., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zabihi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Due to the increasing severity of aging populations in modern society, the accurate and timely identification of, and responses to, sudden abnormal behaviors of the elderly have become an urgent and important issue. In the current research on computer vision-based abnormal behavior recognition, most algorithms have shown poor generalization and recognition abilities in practical applications, as well as issues with recognizing single actions. To address these problems, an MSCS-DenseNet-LSTM model based on a multi-scale attention mechanism is proposed. This model integrates the MSCS (Multi-Scale Convolutional Structure) module into the initial convolutional layer of the DenseNet model to form a multi-scale convolution structure. It introduces the improved Inception X module into the Dense Block to form an Inception Dense structure, and gradually performs feature fusion through each Dense Block module. The CBAM attention mechanism module is added to the dual-layer LSTM to enhance the model's generalization ability while ensuring the accurate recognition of abnormal actions. Furthermore, to address the issue of single-action abnormal behavior datasets, the RGB image dataset RIDS (RGB image dataset) and the contour image dataset CIDS (contour image dataset) containing various abnormal behaviors were constructed. The experimental results validate that the proposed MSCS-DenseNet-LSTM model achieved an accuracy, sensitivity, and specificity of 98.80%, 98.75%, and 98.82% on the two datasets, and 98.30%, 98.28%, and 98.38%, respectively.

Neurophysiology and neuromodulation strive to understand the neural basis of behavior through a one-to-one correspondence between a particular brain and its behavioral output. Within this framework, studies with few subjects but sufficient sample sizes can be both rigorous and impactful., Competing Interests: Declaration of interests W.F.A. holds patents in the domains of neurosurgery and neuromodulation (US9675783B2 and US9675783B2) and is site principal investigator for industry-funded clinical trials of deep brain stimulation and stem cell circuit therapy (Functional Neuromodulation, Inc.; Enspire, Inc.; and Bluerock Therapeutics). S.A.S. is a consultant for Boston Scientific, Zimmer Biomet, Koh Young, Varian Medical, Neuropace, and Sensoria Therapeutic and is cofounder of Motif Neurotech., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Should policymaking assume humans are irrational? Using empirical, theoretical, and philosophical arguments, we suggest a more useful frame is that human behavior is reasonable. Through identifying goals and systemic factors shaping behavior, we suggest that assuming people are reasonable enables behavioral science to be more effective in shaping public policy., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Negation is key for cognition but has no physical basis, raising questions about its neural origins. A new study in PLOS Biology on the negation of scalar adjectives shows that negation acts in part by altering the response to the adjective it negates., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Coopmans et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Human body core temperature is tightly regulated within approximately 37 °C. Global near surface temperature has increased by over 1.2 °C between 1850 and 2020. In light of the challenge this poses to human thermoregulation, the present perspective article sought to provide an overview on the effects of varying ambient and body temperature on cognitive, affective, and behavioural domains of functioning. To this end, an overview of observational and experimental studies in healthy individuals and individuals with mental disorders was provided. Within body core temperature at approximately 37 °C, relatively lower ambient and skin temperatures appear to evoke a need for social connection, whereas comparably higher temperatures appear to facilitate notions of other as closer and more sociable. Above-average ambient temperatures are associated with increased conflicts as well as incident psychotic and depressive symptoms, mental disorders, and suicide. With mild hypo- and hyperthermia, paradoxical effects are observed: whereas the acute states are generally characterised by impairments in cognitive performance, anxiety, and irritability, individuals with depression experience longer-term symptom improvements with treatments deliberately inducing these states for brief amounts of time. When taken together, it has thus become clear that temperature is inexorably associated with human cognition, affect, and (potentially) behaviour. Given the projected increase in global warming, further research into the affective and behavioural sequelae of heat and the mechanisms translating it into mental health outcomes is urgently warranted., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: The central nervous system's influence on cardiac function is well described; however, direct evidence for signaling from heart to brain remains sparse. Mice with cardiac-selective overexpression of adenylyl cyclase type 8 (TGAC8) display elevated heart rate/contractility and altered neuroautonomic surveillance., Objectives: In this study the authors tested whether elevated adenylyl cyclase type 8-dependent signaling at the cardiac cell level affects brain activity and behavior., Methods: A telemetry system was used to record electrocardiogram (ECG) and electroencephalogram (EEG) in TGAC8 and wild-type mice simultaneously. The Granger causality statistical approach evaluated variations in the ECG/EEG relationship. Mouse behavior was assessed via elevated plus maze, open field, light-dark box, and fear conditioning tests. Transcriptomic and proteomic analyses were performed on brain tissue lysates., Results: Behavioral testing revealed increased locomotor activity in TGAC8 that included a greater total distance traveled (+43%; P < 0.01), a higher average speed (+38%; P < 0.01), and a reduced freezing time (-45%; P < 0.01). Dual-lead telemetry recording confirmed a persistent heart rate elevation with a corresponding reduction in ECG-R-waves interval variability and revealed increased EEG-gamma activity in TGAC8 vs wild-type. Bioinformatic assessment of hippocampal tissue indicated upregulation of dopamine 5, gamma-aminobutyric acid A, and metabotropic glutamate 1/5 receptors, major players in gamma activity generation. Granger causality analyses of ECG and EEG recordings showed a marked increase in informational flow between the TGAC8 heart and brain., Conclusions: Perturbed signals arising from the heart cause changes in brain activity, altering mouse behavior. More specifically, the brain interprets augmented myocardial humoral/functional output as a "sustained exercise-like" situation and responds by activating central nervous system output controlling locomotion., Competing Interests: Funding Support and Author Disclosures This research was supported by NIH (R01 HL136918 to NP). The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023. Published by Elsevier Inc.)

Background: The ability to correctly associate cues and contexts with threat is critical for survival, and the inability to do so can result in threat-related disorders such as posttraumatic stress disorder. The prefrontal cortex (PFC) and hippocampus are well known to play critical roles in cued and contextual threat memory processing. However, the circuits that mediate prefrontal-hippocampal modulation of context discrimination during cued threat processing are less understood. Here, we demonstrate the role of a previously unexplored projection from the ventromedial region of PFC (vmPFC) to the lateral entorhinal cortex (LEC) in modulating the gain of behavior in response to contextual information during threat retrieval and encoding., Methods: We used optogenetics followed by in vivo calcium imaging in male C57/B6J mice to manipulate and monitor vmPFC-LEC activity in response to threat-associated cues in different contexts. We then investigated the inputs to, and outputs from, vmPFC-LEC cells using Rabies tracing and channelrhodopsin-assisted electrophysiology., Results: vmPFC-LEC cells flexibly and bidirectionally shaped behavior during threat expression, shaping sensitivity to contextual information to increase or decrease the gain of behavioral output in response to a threatening or neutral context, respectively., Conclusions: Glutamatergic vmPFC-LEC cells are key players in behavioral gain control in response to contextual information during threat processing and may provide a future target for intervention in threat-based disorders., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Noninvasive, reversible stimulation of neural circuits can regulate behavior.

The so-called 'missing heritability problem' is often characterized by behavior geneticists as a numerical discrepancy between alternative kinds of heritability. For example, while 'traditional heritability' derived from twin and family studies indicates that approximately ∼50% of variation in intelligence is attributable to genetics, 'SNP heritability' derived from genome-wide association studies indicates that only ∼10% of variation in intelligence is attributable to genetics. This 40% gap in variance accounted for by alternative kinds of heritability is frequently referred to as what's "missing." Philosophers have picked up on this reading, suggesting that "dissolving" the missing heritability problem is merely a matter of closing the numerical gap between traditional and molecular kinds of heritability. We argue that this framing of the problem undervalues the severity of the many challenges to scientific understanding of the "heritability" of human behavior. On our view, resolving the numerical discrepancies between alternative kinds of heritability will do little to advance scientific explanation and understanding of behavior genetics. Thus, we propose a new conceptual framework of the missing heritability problem that comprises three independent methodological and explanatory challenges: the numerical gap, the prediction gap, and the mechanism gap., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

In order to obtain good quality products, the swine production system should prioritize the animals welfare. Changes are necessary to meet society's demand and expand domestic and foreign markets. The swine's welfare can be assessed by behavioral and physiological traits related to health and production. Thus, our goal is to review in the literature what are the scientific criteria that are used to indicate the swine welfare in the production systems. [ABSTRACT FROM AUTHOR]

In humans, ageing is characterized by decreased brain signal variability and increased behavioral variability. To understand how reduced brain variability segregates with increased behavioral variability, we investigated the association between reaction time variability, evoked brain responses and ongoing brain signal dynamics, in young (N=36) and older adults (N=39). We studied the electroencephalogram (EEG) and pupil size fluctuations to characterize the cortical and arousal responses elicited by a cued go/no-go task. Evoked responses were strongly modulated by slow (<2 Hz) fluctuations of the ongoing signals, which presented reduced power in the older participants. Although variability of the evoked responses was lower in the older participants, once we adjusted for the effect of the ongoing signal fluctuations, evoked responses were equally variable in both groups. Moreover, the modulation of the evoked responses caused by the ongoing signal fluctuations had no impact on reaction time, thereby explaining why although ongoing brain signal variability is decreased in older individuals, behavioral variability is not. Finally, we showed that adjusting for the effect of the ongoing signal was critical to unmask the link between neural responses and behavior as well as the link between task-related evoked EEG and pupil responses., Competing Interests: MR, MC No competing interests declared, (© 2022, Ribeiro and Castelo-, Ribeiro and Castelo-Branco.)

Canonical Correlation Analysis (CCA) and its regularised versions have been widely used in the neuroimaging community to uncover multivariate associations between two data modalities (e.g., brain imaging and behaviour). However, these methods have inherent limitations: (1) statistical inferences about the associations are often not robust; (2) the associations within each data modality are not modelled; (3) missing values need to be imputed or removed. Group Factor Analysis (GFA) is a hierarchical model that addresses the first two limitations by providing Bayesian inference and modelling modality-specific associations. Here, we propose an extension of GFA that handles missing data, and highlight that GFA can be used as a predictive model. We applied GFA to synthetic and real data consisting of brain connectivity and non-imaging measures from the Human Connectome Project (HCP). In synthetic data, GFA uncovered the underlying shared and specific factors and predicted correctly the non-observed data modalities in complete and incomplete data sets. In the HCP data, we identified four relevant shared factors, capturing associations between mood, alcohol and drug use, cognition, demographics and psychopathological measures and the default mode, frontoparietal control, dorsal and ventral networks and insula, as well as two factors describing associations within brain connectivity. In addition, GFA predicted a set of non-imaging measures from brain connectivity. These findings were consistent in complete and incomplete data sets, and replicated previous findings in the literature. GFA is a promising tool that can be used to uncover associations between and within multiple data modalities in benchmark datasets (such as, HCP), and easily extended to more complex models to solve more challenging tasks., (Copyright © 2021. Published by Elsevier Inc.)

Dynamic properties of resting-state functional connectivity (FC) provide rich information on brain-behavior relationships. Dynamic mode decomposition (DMD) has been used as a method to characterize FC dynamics. However, it remains unclear whether dynamic modes (DMs), spatial-temporal coherent patterns computed by DMD, provide information about individual behavioral differences. This study established a methodological approach to predict individual differences in behavior using DMs. Furthermore, we investigated the contribution of DMs within each of seven specific frequency bands (0-0.1,...,0.6-0.7 Hz) for prediction. To validate our approach, we tested whether each of 59 behavioral measures could be predicted by performing multivariate pattern analysis on a Gram matrix, which was created using subject-specific DMs computed from resting-state functional magnetic resonance imaging (rs-fMRI) data of individuals. DMD successfully predicted behavior and outperformed temporal and spatial independent component analysis, which is the conventional data decomposition method for extracting spatial activity patterns. Most of the behavioral measures that were predicted with significant accuracy in a permutation test were related to cognition. We found that DMs within frequency bands <0.2 Hz primarily contributed to prediction and had spatial structures similar to several common resting-state networks. Our results indicate that DMD is efficient in extracting spatiotemporal features from rs-fMRI data., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

The parasubthalamic nucleus (PSTN), a small nucleus located on the lateral edge of the posterior hypothalamus, has emerged in recent years as a highly interconnected node within the network of brain regions sensing and regulating autonomic function and homeostatic needs. Furthermore, the strong integration of the PSTN with extended amygdala circuits makes it ideally positioned to serve as an interface between interoception and emotions. While PSTN neurons are mostly glutamatergic, some of them also express neuropeptides that have been associated with stress-related affective and motivational dysfunction, including substance P, corticotropin-releasing factor, and pituitary adenylate-cyclase activating polypeptide. PSTN neurons respond to food ingestion and anorectic signals, as well as to arousing and distressing stimuli. Functional manipulation of defined pathways demonstrated that the PSTN serves as a central hub in multiple physiologically relevant networks and is notably implicated in appetite suppression, conditioned taste aversion, place avoidance, impulsive action, and fear-induced thermoregulation. We also discuss the putative role of the PSTN in interoceptive dysfunction and negative urgency. This review aims to synthesize the burgeoning preclinical literature dedicated to the PSTN and to stimulate interest in further investigating its influence on physiology and behavior., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Can our brain perceive a sense of ownership towards an independent supernumerary limb; one that can be moved independently of any other limb and provides its own independent movement feedback? Following the rubber-hand illusion experiment, a plethora of studies have shown that the human representation of "self" is very plastic. But previous studies have almost exclusively investigated ownership towards "substitute" artificial limbs, which are controlled by the movements of a real limb and/or limbs from which non-visual sensory feedback is provided on an existing limb. Here, to investigate whether the human brain can own an independent artificial limb, we first developed a novel independent robotic "sixth finger." We allowed participants to train using the finger and examined whether it induced changes in the body representation using behavioral as well as cognitive measures. Our results suggest that unlike a substitute artificial limb (like in the rubber hand experiment), it is more difficult for humans to perceive a sense of ownership towards an independent limb. However, ownership does seem possible, as we observed clear tendencies of changes in the body representation that correlated with the cognitive reports of the sense of ownership. Our results provide the first evidence to show that an independent supernumerary limb can be embodied by humans., (© 2022. The Author(s).)

Disrupting memory reconsolidation provides an opportunity to abruptly reduce the behavioural expression of fear memories with long-lasting effects. The success of a reconsolidation intervention is, however, not guaranteed as it strongly depends on the destabilization of the memory. Identifying the necessary conditions to trigger destabilization remains one of the critical challenges in the field. We aimed to replicate a study from our lab, showing that the occurrence of a prediction error (PE) during reactivation is necessary but not sufficient for destabilization. We tested the effectiveness of a reactivation procedure consisting of a single PE, compared to two control groups receiving no or multiple PEs. All participants received propranolol immediately after reactivation and were tested for fear retention 24 h later. In contrast to the original results, we found no evidence for a reconsolidation effect in the single PE group, but a straightforward interpretation of these results is complicated by the lack of differential fear retention in the control groups. Our results corroborate other failed reconsolidation studies and exemplify the complexity of experimentally investigating this process in humans. Thorough investigation of the interaction between learning and memory reactivation is essential to understand the inconsistencies in the literature and to improve reconsolidation interventions., (© 2022. The Author(s).)

Theta oscillations (~ 4-12 Hz) are dynamically modulated by speed and direction in freely moving animals. However, due to the paucity of electrophysiological recordings of freely moving humans, this mechanism remains poorly understood. Here, we combined mobile-EEG with fully immersive virtual-reality to investigate theta dynamics in 22 healthy adults (aged 18-29 years old) freely navigating a T-maze to find rewards. Our results revealed three dynamic periods of theta modulation: (1) theta power increases coincided with the participants' decision-making period; (2) theta power increased for fast and leftward trials as subjects approached the goal location; and (3) feedback onset evoked two phase-locked theta bursts over the right temporal and frontal-midline channels. These results suggest that recording scalp EEG in freely moving humans navigating a simple virtual T-maze can be utilized as a powerful translational model by which to map theta dynamics during "real-life" goal-directed behavior in both health and disease., (© 2022. The Author(s).)

In memory, our continuous experiences are broken up into discrete events. Boundaries between events are known to influence the temporal organization of memory. However, how and through which mechanism event boundaries shape temporal order memory (TOM) remains unknown. Across four experiments, we show that event boundaries exert a dual role: improving TOM for items within an event and impairing TOM for items across events. Decreasing event length in a list enhances TOM, but only for items at earlier local event positions, an effect we term the local primacy effect. A computational model, in which items are associated to a temporal context signal that drifts over time but resets at boundaries captures all behavioural results. Our findings provide a unified algorithmic mechanism for understanding how and why event boundaries affect TOM, reconciling a long-standing paradox of why both contextual similarity and dissimilarity promote TOM., (© 2022. The Author(s).)

Impaired memory is a hallmark of prodromal Alzheimer's disease (AD). Prior knowledge associated with the memoranda improves memory in healthy individuals, but we ignore whether the same occurs in early AD. We used functional MRI to investigate whether prior knowledge enhances memory encoding in early AD, and whether the nature of this prior knowledge matters. Patients with early AD and Controls underwent a task-based fMRI experiment where they learned face-scene associations. Famous faces carried pre-experimental knowledge (PEK), while unknown faces with which participants were familiarized prior to learning carried experimental knowledge (EK). Surprisingly, PEK strongly enhanced subsequent memory in healthy controls, but importantly not in patients. Partly nonoverlapping brain networks supported PEK vs. EK associative encoding in healthy controls. No such networks were identified in patients. In addition, patients displayed impaired activation in a right sub hippocampal region where activity predicted successful associative memory formation for PEK stimuli. Despite the limited sample sizes of this study, these findings suggest that the role prior knowledge in new learning might have been so far overlooked and underestimated in AD patients. Prior knowledge may drive critical differences in the way healthy elderly and early AD patients learn novel associations., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Currently used antidepressant drugs target and facilitate the action of monoamine neurotransmission. However, approximately 30% of patients do not respond to these drugs. Therefore, there is an urgent need to develop novel therapeutic targets. Several clinical studies have reported that inflammatory cytokines and neutrophils are increased in the blood of patients with major depression. Since social and environmental stress is a risk factor for mental illnesses such as major depression, many research groups have employed chronic stress models in which mice are repeatedly exposed to stressful events. Chronic stress induces neuroinflammation originating from microglia in the medial prefrontal cortex, leading to depressive-like behavior. Moreover, chronic stress influences peripheral immune cells by activating the sympathetic nervous system and the hypothalamus-pituitary-adrenal gland axis. The infiltration of monocytes expressing interleukin (IL)-1β into the brain is involved in chronic stress-induced elevated anxiety. The penetration of IL-6 derived from monocytes into the nucleus accumbens is involved in chronic stress-induced depression-like behavior. Furthermore, cell-cell and peripheral brain interactions and their molecular basis have been discovered. These findings may pave the way for the development of biological markers and therapeutic drugs., Competing Interests: Declaration of competing interest I have no conflict of interest regarding this manuscript., (Copyright © 2021 The Authors. Production and hosting by Elsevier B.V. All rights reserved.)

One of the main goals of current systems neuroscience is to understand how neuronal populations integrate sensory information to inform behavior. However, estimating stimulus or behavioral information that is encoded in high-dimensional neuronal populations is challenging. We propose a method based on parametric copulas which allows modeling joint distributions of neuronal and behavioral variables characterized by different statistics and timescales. To account for temporal or spatial changes in dependencies between variables, we model varying copula parameters by means of Gaussian Processes (GP). We validate the resulting Copula-GP framework on synthetic data and on neuronal and behavioral recordings obtained in awake mice. We show that the use of a parametric description of the high-dimensional dependence structure in our method provides better accuracy in mutual information estimation in higher dimensions compared to other non-parametric methods. Moreover, by quantifying the redundancy between neuronal and behavioral variables, our model exposed the location of the reward zone in an unsupervised manner (i.e., without using any explicit cues about the task structure). These results demonstrate that the Copula-GP framework is particularly useful for the analysis of complex multidimensional relationships between neuronal, sensory and behavioral variables., Competing Interests: The authors have declared that no competing interests exist.

Prism Adaptation (PA) is used to alleviate spatial neglect. We combined immersive virtual reality with a depth-sensing camera to develop virtual prism adaptation therapy (VPAT), which block external visual cues and easily quantify and monitor errors than conventional PA. We conducted a feasibility study to investigate whether VPAT can induce behavioral adaptations by measuring after-effect and identifying which cortical areas were most significantly activated during VPAT using functional near-infrared spectroscopy (fNIRS). Fourteen healthy subjects participated in this study. The experiment consisted of four sequential phases (pre-VPAT, VPAT-10°, VPAT-20°, and post-VPAT). To compare the most significantly activated cortical areas during pointing in different phases against pointing during the pre-VPAT phase, we analyzed changes in oxyhemoglobin concentration using fNIRS during pointing. The pointing errors of the virtual hand deviated to the right-side during early pointing blocks in the VPAT-10° and VPAT-20° phases. There was a left-side deviation of the real hand to the target in the post-VPAT phase, demonstrating after-effect. The most significantly activated channels during pointing tasks were located in the right hemisphere, and possible corresponding cortical areas included the dorsolateral prefrontal cortex and frontal eye field. In conclusion, VPAT may induce behavioral adaptation with modulation of the dorsal attentional network., (© 2022. The Author(s).)

The nature of brain-behavior covariations with increasing age is poorly understood. In the current study, we used a multivariate approach to investigate the covariation between behavioral-health variables and brain features across adulthood. We recruited healthy adults aged 20-73 years-old (29 younger, mean age = 25.6 years; 30 older, mean age = 62.5 years), and collected structural and functional MRI (s/fMRI) during a resting-state and three tasks. From the sMRI, we extracted cortical thickness and subcortical volumes; from the fMRI, we extracted activation peaks and functional network connectivity (FNC) for each task. We conducted canonical correlation analyses between behavioral-health variables and the sMRI, or the fMRI variables, across all participants. We found significant covariations for both types of neuroimaging phenotypes ( ps = 0.0004) across all individuals, with cognitive capacity and age being the largest opposite contributors. We further identified different variables contributing to the models across phenotypes and age groups. Particularly, we found behavior was associated with different neuroimaging patterns between the younger and older groups. Higher cognitive capacity was supported by activation and FNC within the executive networks in the younger adults, while it was supported by the visual networks' FNC in the older adults. This study highlights how the brain-behavior covariations vary across adulthood and provides further support that cognitive performance relies on regional recruitment that differs between older and younger individuals.

Organizations nowadays are under immense external pressure due to advancements in information technology, making it precarious. It also inserts extra pressure to keep the employees motivated and productive. Therefore, while information technology benefits the organization, it also challenges the organization and employees more. In order to meet these challenges, many organizations have begun to flatten their organizational structures and decentralized their management approaches. This study collected 336 valid questionnaires from 20 service companies. The reliability and validity of the questionnaire were tested. In addition, the exploratory factor analysis and confirmatory factor analysis. Relevant analysis and empirical analysis were also carried out using hierarchical regression. The study finds that (1) Goal-setting participation positively affects employees' proactive behavior. (2) Perceived insider status plays a mediating role between goal-setting participation and employee proactive behavior. (3) The power distance positively modifies the goal-setting participation in the relationship of employee's perceived insider status. (4) Power distance positively moderates perceived insider status in the relationship of goal-setting participation on employee proactive behavior through perceived insider status. This research applies goal-setting theory and social cognition theory to build a theoretical framework for the influence mechanism of goal-setting participation on employee's proactive behavior. Expands the application scope of fundamental theoretical research and improve understanding of the relationship between goal-setting participation and employee's proactive behavior. The research conclusions help organizations understand the formation mechanism of employees' proactive behaviors, strengthen the focus on goal-setting participation, and optimize the relationship between leaders and employees., Competing Interests: All authors declare no other competing interests.

We examined the influence of lifestyle on brain aging after nearly 30 years, and tested the hypothesis that young adult general cognitive ability (GCA) would moderate these effects. In the community-dwelling Vietnam Era Twin Study of Aging (VETSA), 431 largely non-Hispanic white men completed a test of GCA at mean age 20. We created a modifiable lifestyle behavior composite from data collected at mean age 40. During VETSA, MRI-based measures at mean age 68 included predicted brain age difference (PBAD), Alzheimer's disease (AD) brain signature, and abnormal white matter scores. There were significant main effects of young adult GCA and lifestyle on PBAD and the AD signature (ps ≤ 0.012), and a GCA-by-lifestyle interaction on both (ps ≤ 0.006). Regardless of GCA level, having more favorable lifestyle behaviors predicted less advanced brain age and less AD-like brain aging. Unfavorable lifestyles predicted advanced brain aging in those with lower age 20 GCA, but did not affect brain aging in those with higher age 20 GCA. Targeting early lifestyle modification may promote dementia risk reduction, especially among lower reserve individuals., (Copyright © 2021. Published by Elsevier Inc.)

Roughly 10% of the human population is left-handed, and this rate is increased in some brain-related disorders. The neuroanatomical correlates of hand preference have remained equivocal. We resampled structural brain image data from 28,802 right-handers and 3,062 left-handers (UK Biobank population dataset) to a symmetrical surface template, and mapped asymmetries for each of 8,681 vertices across the cerebral cortex in each individual. Left-handers compared to right-handers showed average differences of surface area asymmetry within the fusiform cortex, the anterior insula, the anterior middle cingulate cortex, and the precentral cortex. Meta-analyzed functional imaging data implicated these regions in executive functions and language. Polygenic disposition to left-handedness was associated with two of these regional asymmetries, and 18 loci previously linked with left-handedness by genome-wide screening showed associations with one or more of these asymmetries. Implicated genes included six encoding microtubule-related proteins: TUBB , TUBA1B , TUBB3 , TUBB4A , MAP2 , and NME7 -mutations in the latter can cause left to right reversal of the visceral organs. There were also two cortical regions where average thickness asymmetry was altered in left-handedness: on the postcentral gyrus and the inferior occipital cortex, functionally annotated with hand sensorimotor and visual roles. These cortical thickness asymmetries were not heritable. Heritable surface area asymmetries of language-related regions may link the etiologies of hand preference and language, whereas nonheritable asymmetries of sensorimotor cortex may manifest as consequences of hand preference., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Actions with identical goals can be executed in different ways (gentle, rude, vigorous, etc.), which D. N. Stern called vitality forms [D. N. Stern, Forms of Vitality Exploring Dynamic Experience in Psychology, Arts, Psychotherapy, and Development (2010)]. Vitality forms express the agent's attitudes toward others. In a series of fMRI studies, we found that the dorso-central insula (DCI) is the region that is selectively active during both vitality form observation and execution. In one previous experiment, however, the middle cingulate gyrus also exhibited activation. In the present study, in order to assess the role of the cingulate cortex in vitality form processing, we adopted a classical vitality form paradigm, but making the control condition devoid of vitality forms using jerky movements. Participants performed two different tasks: Observation of actions performed gently or rudely and execution of the same actions. The results showed that in addition to the insula, the middle cingulate cortex (MCC) was strongly activated during both action observation and execution. Using a voxel-based analysis, voxels showing a similar trend of the blood-oxygen-level-dependent (BOLD) signal in both action observation and execution were found in the DCI and in the MCC. Finally, using a multifiber tractography analysis, we showed that the active sites in MCC and DCI are reciprocally connected., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Adolescent inhalant misuse has a known association with suicidal thoughts and behaviour. This association persists even after inhalant misuse has ceased. Previous studies have hypothesised that this association may derive from socioeconomic disadvantage or vulnerability, and potentially mediated by impulsivity. This association may also be due to the central nervous system depressant effects of inhalants. This review takes a behavioural toxicology perspective, focussed particularly on the serotonergic system and the Hypothalamic-Pituitary-Adrenal (HPA) axis, as potential links between adolescent inhalant misuse and suicidal behaviour. The challenges of bridging the pre-clinical and clinical literature in this area are discussed, along with promising avenues for future research; ultimately aimed at reducing suicide risk in a vulnerable adolescent population group., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Because the spread of pandemics depends heavily on human choices and behaviors, dealing with COVID-19 requires insights from cognitive science which integrates psychology, neuroscience, computer modeling, philosophy, anthropology, and linguistics. Cognitive models can explain why scientists adopt hypotheses about the causes and treatments of disease based on explanatory coherence. Irrational deviations from good reasoning are explained by motivated inference in which conclusions are influenced by personal goals that contribute to emotional coherence. Decisions about COVID-19 can also be distorted by well-known psychological and neural mechanisms. Cognitive science provides advice about how to improve human behavior in pandemics by changing beliefs and by improving behaviors that result from intention-action gaps., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Between 2005 and 2009, several research groups identified a strikingly dense inhibitory input to midbrain dopamine neurons arising from a previously uncharted region posterior to the ventral tegmental area (VTA). This region is now denoted as either the rostromedial tegmental nucleus (RMTg) or the "tail of the VTA" (tVTA), and is recognized to express distinct genetic markers, encode negative "prediction errors" (inverse to dopamine neurons), and play critical roles in behavioral inhibition and punishment learning. RMTg neurons are also influenced by many categories of abused drugs, and may drive some aversive responses to such drugs, particularly cocaine and alcohol. However, despite much progress, many important questions remain about RMTg molecular/genetic properties, diversity of projection targets, and applications to addiction, depression, and other neuropsychiatric disorders. This article is part of the special Issue on 'Neurocircuitry Modulating Drug and Alcohol Abuse'., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Increasing statutory retirement ages around the world are forcing employees to prolong their working lives. We study the different ways in which mid- and late-career workers respond to such changes. We distinguish between negative emotions about working longer, cognitive engagement with prolonged employment, and proactive behavior to facilitate longer working lives. We analyze data from 1,351 employees aged 40-66 from the Netherlands. We estimate a structural equation model to identify in which ways experiences of age discrimination, accessibility of accommodative HR facilities, and social norms in the workers' social networks are related to the three different types of responses. Results show that when employees do not experience age discrimination, when their employer offers easily accessible accommodative HR facilities, and the social norms support prolonged employment, employees have fewer negative emotional reactions and are more likely to behaviorally respond to facilitate longer working lives. When these contexts are misaligned, the reverse is generally found. We also find socioeconomic differences in the ways employees respond to the prospect of prolonged employment. This study shows the importance of supportive contexts at different levels-societally, in organizations, and in individuals' own lives-for policy changes such as increasing statutory retirement ages to be effective. Different responses between different socioeconomic groups may lead to growing long-term inequality., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2021 Jaap Oude Mulders et al.)

For animals to survive, they must interact with their environment, taking in sensory information and making appropriate motor responses. Early on during vertebrate evolution, this was accomplished with neural circuits located mostly within the spinal cord and brainstem. As the cerebral cortex evolved, it provided additional and powerful advantages for assessing environmental cues and guiding appropriate responses. Importantly, the cerebral cortex was added onto an already functional nervous system. Moreover, every cortical area, including areas traditionally considered sensory, provides input to the subcortical motor structures that are bottlenecks for driving action. These facts have important ramifications for cognitive aspects of motor control. Here we consider the evolution of cortical mechanisms for attention from the perspective of having to work through these subcortical bottlenecks. From this perspective, many features of attention can be explained, including the preferential engagement of some cortical areas at the cost of disengagement from others to improve appropriate behavioral responses., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Some evidence suggests that people behave more cooperatively and generously when observed or in the presence of images of eyes (termed the 'watching eyes' effect). Eye images are thought to trigger feelings of observation, which in turn motivate people to behave more cooperatively to earn a good reputation. However, several recent studies have failed to find evidence of the eyes effect. One possibility is that inconsistent evidence in support of the eyes effect is a product of individual differences in sensitivity or susceptibility to the cue. In fact, some evidence suggests that people who are generally more prosocial are less susceptible to situation-specific reputation-based cues of observation. In this paper, we sought to (1) replicate the eyes effect, (2) replicate the past finding that people who are dispositionally less prosocial are more responsive to observation than people who are more dispositionally more prosocial, and (3) determine if this effect extends to the watching eyes effect. Results from a pre-registered study showed that people did not give more money in a dictator game when decisions were made public or in the presence of eye images, even though participants felt more observed when decisions were public. That is, we failed to replicate the eyes effect and observation effect. An initial, but underpowered, interaction model suggests that egoists give less than prosocials in private, but not public, conditions. This suggests a direction for future research investigating if and how individual differences in prosociality influence observation effects., Competing Interests: The authors have declared that no competing interests exist.

A standard view in the literature is that decisions are the result of a process that accumulates evidence in favor of each alternative until such accumulation reaches a threshold and a decision is made. However, this view has been recently questioned by an alternative proposal that suggests that, instead of accumulated, evidence is combined with an urgency signal. Both theories have been mathematically formalized and supported by a variety of decision-making tasks with constant information. However, recently, tasks with changing information have shown to be more effective to study the dynamics of decision making. Recent research using one of such tasks, the tokens task, has shown that decisions are better described by an urgency mechanism than by an accumulation one. However, the results of that study could depend on a task where all fundamental information was noiseless and always present, favoring a mechanism of non-integration, such as the urgency one. Here, we wanted to address whether the same conclusions were also supported by an experimental paradigm in which sensory evidence was removed shortly after it was provided, making working memory necessary to properly perform the task. Here, we show that, under such condition, participants' behavior could be explained by an urgency-gating mechanism that low-pass filters the mnemonic information and combines it with an urgency signal that grows with time but not by an accumulation process that integrates the same mnemonic information. Thus, our study supports the idea that, under certain situations with dynamic sensory information, decisions are better explained by an urgency-gating mechanism than by an accumulation one., Competing Interests: The authors have declared that no competing interests exist.

Behavioral gender differences have been found for a wide range of human activities including the way people communicate, move, provision themselves, or organize leisure activities. Using mobile phone data from 1.2 million devices in Austria (15% of the population) across the first phase of the COVID-19 crisis, we quantify gender-specific patterns of communication intensity, mobility, and circadian rhythms. We show the resilience of behavioral patterns with respect to the shock imposed by a strict nation-wide lock-down that Austria experienced in the beginning of the crisis with severe implications on public and private life. We find drastic differences in gender-specific responses during the different phases of the pandemic. After the lock-down gender differences in mobility and communication patterns increased massively, while circadian rhythms tended to synchronize. In particular, women had fewer but longer phone calls than men during the lock-down. Mobility declined massively for both genders, however, women tended to restrict their movement stronger than men. Women showed a stronger tendency to avoid shopping centers and more men frequented recreational areas. After the lock-down, males returned back to normal quicker than women; young age-cohorts return much quicker. Differences are driven by the young and adolescent population. An age stratification highlights the role of retirement on behavioral differences. We find that the length of a day of men and women is reduced by 1 h. We interpret and discuss these findings as signals for underlying social, biological and psychological gender differences when coping with crisis and taking risks., (© 2021. The Author(s).)