Beyond novelty: Learnability in the interplay between creativity, curiosity and artistic endeavours.

Using art and aesthetics as context, we explore the notion that curiosity and creativity emanate from a single novelty-seeking mechanism and outline support for the idea. However, we also highlight the importance of learning progress tracking in exploratory action and advocate for a nuanced understanding that aligns novelty-seeking with learnability. This, we argue, offers a more comprehensive framework of how curiosity and creativity are related.

Is income inequality linked to infectious disease prevalence? A hypothesis-generating study using tuberculosis.

We study the association between infectious disease incidence and income inequality. We hypothesize that random social mixing in an income-unequal society brings into contact a) susceptible and infected poor and b) the infected-poor and the susceptible-rich, raising infectious disease incidence. We analyzed publicly available, country-level panel data for a large cross-section of countries between 1995 and 2013 to examine whether countries with elevated levels of income inequality have higher rates of pulmonary Tuberculosis (TB) incidence per capita. A "negative control" using anemia and diabetes (both non-communicable diseases and hence impervious to the hypothesized mechanism) is also applied. We find that high levels of income inequality are positively associated with tuberculosis incidence. All else equal, countries with income-Gini coefficients 10% apart show a statistically significant 4% difference in tuberculosis incidence. Income inequality had a null effect on the negative controls. Our cross-country regression results suggest that income inequality may create conditions where TB spreads more easily, and policy action to reduce income inequities could directly contribute to a reduced TB burden.

Autism Detection in Children using Common Spatial Patterns of MEG Signals.

Autism exhibits a wide range of developmental disabilities and is associated with aberrant anatomical and functional neural patterns. To detect autism in young children (4-7 years) in an automatic and non-invasive fashion, we have recorded magnetoencephalogram (MEG) signals from 30 autistic and 30 age-matched typically developing (TD) children. We have used a machine learning classification framework with common spatial pattern (CSP)-based logarithmic band power (LBP) features. When comparing the LBP feature to the conventional logarithmic variance (LV) spatial pattern, CSP + LBP (92.77%) has performed better than CSP + LV (90.66%) in the 1-100 Hz frequency range for distinguishing autistic children from TD children. In frequency band-wise analysis using our proposed method, the high gamma frequency band (50-100 Hz) has shown the highest classification accuracy (97.14%). Our findings reveal that the occipital lobe exhibits the most distinct spatial pattern in autistic children over the whole frequency range. This study shows that spatial brain activation patterns can be utilized as potential biomarkers of autism in young children. The improved performance signifies the clinical relevance of the work for autism detection using MEG signals.

Cortical signatures of visual body representation develop in human infancy.

Human infants cannot report their experiences, limiting what we can learn about their bodily awareness. However, visual cortical responses to the body, linked to visual awareness and selective attention in adults, can be easily measured in infants and provide a promising marker of bodily awareness in early life. We presented 4- and 8-month-old infants with a flickering (7.5 Hz) video of a hand being stroked and recorded steady-state visual evoked potentials (SSVEPs). In half of the trials, the infants also received tactile stroking synchronously with visual stroking. The 8-month-old, but not the 4-month-old infants, showed a significant enhancement of SSVEP responses when they received tactile stimulation concurrent with the visually observed stroking. Follow-up experiments showed that this enhancement did not occur when the visual hand was presented in an incompatible posture with the infant's own body or when the visual stimulus was a body-irrelevant video. Our findings provide a novel insight into the development of bodily self-awareness in the first year of life.

Functional connectivity based machine learning approach for autism detection in young children using MEG signals.

Objective.Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, and identifying early autism biomarkers plays a vital role in improving detection and subsequent life outcomes. This study aims to reveal hidden biomarkers in the patterns of functional brain connectivity as recorded by the neuro-magnetic brain responses in children with ASD.Approach.We recorded resting-state magnetoencephalogram signals from thirty children with ASD (4-7 years) and thirty age and gender-matched typically developing (TD) children. We used a complex coherency-based functional connectivity analysis to understand the interactions between different brain regions of the neural system. The work characterizes the large-scale neural activity at different brain oscillations using functional connectivity analysis and assesses the classification performance of coherence-based (COH) measures for autism detection in young children. A comparative study has also been carried out on COH-based connectivity networks both region-wise and sensor-wise to understand frequency-band-specific connectivity patterns and their connections with autism symptomatology. We used artificial neural network (ANN) and support vector machine (SVM) classifiers in the machine learning framework with a five-fold CV technique.Main results.To classify ASD from TD children, the COH connectivity feature yields the highest classification accuracy of 91.66% in the high gamma (50-100 Hz) frequency band. In region-wise connectivity analysis, the second highest performance is in the delta band (1-4 Hz) after the gamma band. Combining the delta and gamma band features, we achieved a classification accuracy of 95.03% and 93.33% in the ANN and SVM classifiers, respectively. Using classification performance metrics and further statistical analysis, we show that ASD children demonstrate significant hyperconnectivity.Significance.Our findings support the weak central coherency theory in autism detection. Further, despite its lower complexity, we show that region-wise COH analysis outperforms the sensor-wise connectivity analysis. Altogether, these results demonstrate the functional brain connectivity patterns as an appropriate biomarker of autism in young children.

A Fusion-Based Machine Learning Approach for Autism Detection in Young Children Using Magnetoencephalography Signals.

In this study, we aimed to find biomarkers of autism in young children. We recorded magnetoencephalography (MEG) in thirty children (4-7 years) with autism and thirty age, gender-matched controls while they were watching cartoons. We focused on characterizing neural oscillations by amplitude (power spectral density, PSD) and phase (preferred phase angle, PPA). Machine learning based classifier showed a higher classification accuracy (88%) for PPA features than PSD features (82%). Further, by a novel fusion method combining PSD and PPA features, we achieved an average classification accuracy of 94% and 98% for feature-level and score-level fusion, respectively. These findings reveal discriminatory patterns of neural oscillations of autism in young children and provide novel insight into autism pathophysiology.

Flow in contemporary musicians: Individual differences in flow proneness, anxiety, and emotional intelligence.

Flow is a highly focussed state of consciousness that is rewarding, fulfilling, and sought after by many, especially musicians. It is characterised by exceptional levels of concentration, loss of self-consciousness, and competent control over one's actions. Several personality and non-cognitive traits have been positively linked with flow proneness, such as emotional intelligence; however, anxiety is thought to be the antithesis of flow, yet the relationship between trait anxiety and flow proneness in musicians is not adequately characterised. This study investigated the individual differences in flow proneness in contemporary musicians (N = 664), focusing on the interaction of trait anxiety and emotional intelligence. We identified a significant negative correlation between trait anxiety and flow. Emotional intelligence was positively correlated with flow proneness and negatively with trait anxiety. Moderation analysis revealed a difference in the relationship between trait anxiety and flow depending on the level of emotional intelligence; there was no correlation in those with low emotional intelligence, whereas a strong negative relationship was found in those with high emotional intelligence. Finally, hierarchical regression indicated that musical training was the most substantial predictor of all the tested variables and that trait anxiety did not add any predictive power on top of the known predictors. Altogether, this study provided new insights into the possible disruption of flow proneness linked to high anxiety and low emotional intelligence in contemporary musicians.

ASMR amplifies low frequency and reduces high frequency oscillations.

Autonomous sensory meridian response (ASMR) describes an atypical multisensory experience of calming, tingling sensations in response to a specific subset of social audiovisual triggers. To date, the electrophysiological (EEG) correlates of ASMR remain largely unexplored. Here we sought to provide source-level signatures of oscillatory changes induced by this phenomenon and investigate potential decay effects-oscillatory changes in the absence of self-reported ASMR. We recorded brain activity using EEG as participants watched ASMR-inducing videos and self-reported changes in their state: no change (Baseline); enhanced relaxation (Relaxed); and ASMR sensations (ASMR). Statistical tests in the sensor-space were used to inform contrasts in the source-space, executed with beamformer reconstruction. ASMR modulated oscillatory power by decreasing high gamma (52-80 Hz) relative to Relaxed and by increasing alpha (8-13 Hz) and decreasing delta (1-4 Hz) relative to Baseline. At the source level, ASMR increased power in the low-mid frequency ranges (8-18 Hz) and decreased power in high frequency (21-80 Hz). ASMR decay effects reduced gamma (30-80 Hz) and in the source-space reduced high-beta/gamma power (21-80 Hz). The temporal profile of ASMR modulations in high-frequency power later shifts to lower frequencies (1-8 Hz), except for an enhanced alpha, which persists for up to 45 min post self-reported ASMR. Crucially, these results provide the first evidence that the cortical sources of ASMR tingling sensations may arise from decreases in higher frequency oscillations and that ASMR may induce a sustained relaxation state.

Multivariate patterns and long-range temporal correlations of alpha oscillations are associated with flexible manipulation of visual working memory representations.

The ability to flexibly manipulate memory representations is embedded in visual working memory (VWM) and can be tested using paradigms with retrospective cues. Although valid retrospective cues often facilitate memory recall, invalid ones may or may not result in performance costs. We investigated individual differences in utilising retrospective cues and evaluated how these individual differences are associated with brain oscillatory activity at rest. At the behavioural level, we operationalised flexibility as the ability to make effective use of retrospective cues or disregard them if required. At the neural level, we tested whether individual differences in such flexibility were associated with properties of resting-state alpha oscillatory activity (8-12 Hz). To capture distinct aspects of these brain oscillations, we evaluated their power spectral density and temporal dynamics using long-range temporal correlations (LRTCs). In addition, we performed multivariate patterns analysis (MVPA) to classify individuals' level of behavioural flexibility based on these neural measures. We observed that alpha power alone (magnitude) at rest was not associated with flexibility. However, we found that the participants' ability to manipulate VWM representations was correlated with alpha LRTC and could be decoded using MVPA on patterns of alpha power. Our findings suggest that alpha LRTC and multivariate patterns of alpha power at rest may underlie some of the individual differences in using retrospective cues in working memory tasks.

A rational-choice model of Covid-19 transmission with endogenous quarantining and two-sided prevention.

This paper offers a parsimonious, rational-choice model to study the effect of pre-existing inequalities on the transmission of COVID-19. Agents decide whether to "go out" (or self-quarantine) and, if so, whether to wear protection such as masks. Three elements distinguish the model from existing work. First, non-symptomatic agents do not know if they are infected. Second, some of these agents unknowingly transmit infections. Third, we permit two-sided prevention via the use of non-pharmaceutical interventions: the probability of a person catching the virus from another depends on protection choices made by each. We find that a mean-preserving increase in pre-existing income inequality unambiguously increases the equilibrium proportion of unprotected, socializing agents and may increase or decrease the proportion who self-quarantine. Strikingly, while higher pre-COVID inequality may or may not raise the overall risk of infection, it increases the risk of disease in social interactions.

Exponential-growth prediction bias and compliance with safety measures related to COVID-19.

OBJECTIVE: We define prediction bias as the systematic error arising from an incorrect prediction of the number of positive COVID cases x-weeks hence when presented with y-weeks of prior, actual data on the same. Our objective is to investigate the importance of an exponential-growth prediction bias (EGPB) in understanding why the COVID-19 outbreak has exploded. To that end, our goal is to document EGPB in the comprehension of disease data, study how it evolves as the epidemic progresses, and connect it with compliance of personal safety guidelines such as the use of face coverings and social distancing. We also investigate whether a behavioral nudge, cost less to implement, can significantly reduce EGPB. RATIONALE: The scientific basis for our inquiry is the received wisdom that infectious disease spread, especially in the initial stages, follows an exponential function meaning few positive cases can explode into a widespread pandemic if the disease is sufficiently transmittable. If people suffer from EGPB, they will likely make incorrect judgments about their infection risk, which in turn, may lead to reduced compliance of safety protocols. METHOD: To collect data on prediction bias, we ran an incentivized, experiment on a global, online platform with participation from people in forty-three countries, each at different stages of progression of COVID-19. We also constructed several indices of compliance by surveying participants about their frequency of hand-washing and use of sanitizers and masks; their willingness to pay for masks; their view about the social appropriateness of others' behavior; and their like/dislike of government responses. The prediction data was used to construct several measures of EGPB. Our experimental design permits us to identify the root of under-prediction as EGPB arising from the general tendency to underestimate the speed at which exponential processes unfold. RESULTS: Respondents make predictions about the path of the disease using a model that is substantially less convex than the actual data generating process. This creates significant EGPB, which, in turn, is significantly and negatively associated with non-compliance with safety measures. The bias is significantly higher for respondents from countries at a later stage relative to those at an early stage of disease progression. A simple behavioral nudge that shows prior data in terms of raw numbers, as opposed to a graph, causally reduces EGPB. CONCLUSION: Behavioral biases concerning the comprehension of disease data are quantitatively important, and act as severe impediments to effective policy action against the spread of COVID-19. Clear communication of future infection risk via raw numbers could increase the accuracy of risk perception, in turn, facilitating compliance with suggested protective behaviors.

Causally linking neural dominance to perceptual dominance in a multisensory conflict.

When different senses are in conflict, one sense may dominate the perception of other sense, but it is not known whether the sensory cortex associated with the dominant modality exerts directional influence, at the functional brain level, over the sensory cortex associated with the dominated modality; in short, the link between sensory dominance and neuronal dominance is not established. In a task involving audio-visual conflict, using magnetoencephalography recordings in humans, we first demonstrated that the neuronal dominance - auditory cortex functionally influencing visual cortex - was associated with the sensory dominance - sound qualitatively altering visual perception. Further, we found that prestimulus auditory-to-visual connectivity could predict the perceptual outcome on a trial-by-trial basis. Subsequently, we performed an effective connectivity-guided neurofeedback electroencephalography experiment and showed that participants who were briefly trained to increase the neuronal dominance from auditory to visual cortex showed higher sensory, that is auditory, dominance during the conflict task immediately after the training. These results shed new light into the interactive neuronal nature of multisensory integration and open up exciting opportunities by enhancing or suppressing targeted mental functions subserved by effective connectivity.

Auditory but Not Audiovisual Cues Lead to Higher Neural Sensitivity to the Statistical Regularities of an Unfamiliar Musical Style.

It is still a matter of debate whether visual aids improve learning of music. In a multisession study, we investigated the neural signatures of novel music sequence learning with or without aids (auditory-only: AO, audiovisual: AV). During three training sessions on three separate days, participants (nonmusicians) reproduced (note by note on a keyboard) melodic sequences generated by an artificial musical grammar. The AV group (n = 20) had each note color-coded on screen, whereas the AO group (n = 20) had no color indication. We evaluated learning of the statistical regularities of the novel music grammar before and after training by presenting melodies ending on correct or incorrect notes and by asking participants to judge the correctness and surprisal of the final note, while EEG was recorded. We found that participants successfully learned the new grammar. Although the AV group, as compared to the AO group, reproduced longer sequences during training, there was no significant difference in learning between groups. At the neural level, after training, the AO group showed a larger N100 response to low-probability compared with high-probability notes, suggesting an increased neural sensitivity to statistical properties of the grammar; this effect was not observed in the AV group. Our findings indicate that visual aids might improve sequence reproduction while not necessarily promoting better learning, indicating a potential dissociation between sequence reproduction and learning. We suggest that the difficulty induced by auditory-only input during music training might enhance cognitive engagement, thereby improving neural sensitivity to the underlying statistical properties of the learned material.

Switch or stay? Automatic classification of internal mental states in bistable perception.

The human brain goes through numerous cognitive states, most of these being hidden or implicit while performing a task, and understanding them is of great practical importance. However, identifying internal mental states is quite challenging as these states are difficult to label, usually short-lived, and generally, overlap with other tasks. One such problem pertains to bistable perception, which we consider to consist of two internal mental states, namely, transition and maintenance. The transition state is short-lived and represents a change in perception while the maintenance state is comparatively longer and represents a stable perception. In this study, we proposed a novel approach for characterizing the duration of transition and maintenance states and classified them from the neuromagnetic brain responses. Participants were presented with various types of ambiguous visual stimuli on which they indicated the moments of perceptual switches, while their magnetoencephalogram (MEG) data were recorded. We extracted different spatio-temporal features based on wavelet transform, and classified transition and maintenance states on a trial-by-trial basis. We obtained a classification accuracy of 79.58% and 78.40% using SVM and ANN classifiers, respectively. Next, we investigated the temporal fluctuations of these internal mental representations as captured by our classifier model and found that the accuracy showed a decreasing trend as the maintenance state was moved towards the next transition state. Further, to identify the neural sources corresponding to these internal mental states, we performed source analysis on MEG signals. We observed the involvement of sources from the parietal lobe, occipital lobe, and cerebellum in distinguishing transition and maintenance states. Cross-conditional classification analysis established generalization potential of wavelet features. Altogether, this study presents an automatic classification of endogenous mental states involved in bistable perception by establishing brain-behavior relationships at the single-trial level.

Investigating Age-Related Neural Compensation During Emotion Perception Using Electroencephalography.

Previous research suggests declines in emotion perception in older as compared to younger adults, but the underlying neural mechanisms remain unclear. Here, we address this by investigating how "face-age" and "face emotion intensity" affect both younger and older participants' behavioural and neural responses using event-related potentials (ERPs). Sixteen young and fifteen older adults viewed and judged the emotion type of facial images with old or young face-age and with high- or low- emotion intensities while EEG was recorded. The ERP results revealed that young and older participants exhibited significant ERP differences in two neural clusters: the left frontal and centromedial regions (100-200 ms stimulus onset) and frontal region (250-900 ms) when perceiving neutral faces. Older participants also exhibited significantly higher ERPs within these two neural clusters during anger and happiness emotion perceptual tasks. However, while this pattern of activity supported neutral emotion processing, it was not sufficient to support the effective processing of facial expressions of anger and happiness as older adults showed reductions in performance when perceiving these emotions. These age-related changes are consistent with theoretical models of age-related changes in neurocognitive abilities and may reflect a general age-related cognitive neural compensation in older adults, rather than a specific emotion-processing neural compensation.

From learning to creativity: Identifying the behavioural and neural correlates of learning to predict human judgements of musical creativity.

Human creativity is intricately linked to acquired knowledge. However, to date learning a new musical style and subsequent musical creativity have largely been studied in isolation. We introduced a novel experimental paradigm combining behavioural, electrophysiological, and computational methods, to examine the neural correlates of unfamiliar music learning, and to investigate how neural and computational measures can predict human creativity. We investigated music learning by training non-musicians (N = 40) on an artificial music grammar. Participants' knowledge of the grammar was tested before and after three training sessions on separate days by assessing explicit recognition of the notes of the grammar, while additionally recording their EEG. After each training session, participants created their own musical compositions, which were later evaluated by human experts. A computational model of auditory expectation was used to quantify the statistical properties of both the grammar and the compositions. Results showed that participants successfully learned the new grammar. This was also reflected in the N100, P200, and P3a components, which were higher in response to incorrect than correct notes. The delta band (2.5-4.5 Hz) power in response to grammatical notes during first exposure to the grammar positively correlated with learning, suggesting a potential neural mechanism of encoding. On the other hand, better learning was associated with lower alpha and higher beta band power after training, potentially reflecting neural mechanisms of retrieval. Importantly, learning was a significant predictor of creativity, as judged by experts. There was also an inverted U-shaped relationship between percentage of correct intervals and creativity, as compositions with an intermediate proportion of correct intervals were associated with the highest creativity. Finally, the P200 in response to incorrect notes was predictive of creativity, suggesting a link between the neural correlates of learning, and creativity. Overall, our findings shed light on the neural mechanisms of learning an unfamiliar music grammar, and offer novel contributions to the associations between learning measures and creative compositions based on learned materials.

Brain-Derived Neurotrophic Factor Val66Met Polymorphism Is Associated With a Reduced ERP Component Indexing Emotional Recollection.

The Met allele of the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism is associated with reduced functioning of the amygdala and hippocampus. It has been linked to major psychiatric conditions, including depression and post-traumatic stress disorder, and is associated with deficits in episodic memory. The precise mechanisms of the BDNF gene's influence on emotional memory are not well characterized, especially its impact on recognition. Two electrophysiological experiments of emotional memory were run on two independent samples genotyped for BDNF Val66Met. Event-related potentials (ERPs) corresponding to the recognition of negative and neutral words (Experiment 1, N = 37) and negative and positive words (Experiment 2, N = 23) were recorded, and the late parietal component (LPC), typically associated with conscious recollection, was analyzed. In Experiment 1, a reduced LPC was observed in Met carriers (N = 12) compared to Val homozygotes (N = 25) in the negative condition, but the group difference was not present in the neutral condition. In Experiment 2, the reduced LPC was seen in Met carriers (N = 12) compared to Val homozygotes (N = 11) across both conditions. This study provides the first evidence of an association between the BDNF Val66Met genotype and the late parietal electrophysiological component, suggesting that the conscious experience of emotional recollection may differ according to BDNF Val66Met genotype. Further, these results suggest that this effect is likely due to emotional arousal rather than valence polarity. Results were discussed with reference to the possible mechanisms by which emotional recollection deficits may contribute to psychopathology.

The influence of motor preparation on the processing of action-relevant visual features.

Action preparation can facilitate performance in tasks of visual perception, for instance by speeding up responses to action-relevant stimulus features. However, it is unknown whether this facilitation reflects an influence on early perceptual processing, or instead post-perceptual processes. In three experiments, a combination of psychophysics and electroencephalography was used to investigate whether visual features are influenced by action preparation at the perceptual level. Participants were cued to prepare oriented reach-to-grasp actions before discriminating target stimuli oriented in the same direction as the prepared grasping action (congruent) or not (incongruent). As expected, stimuli were discriminated faster if their orientation was congruent, compared to incongruent, with the prepared action. However, action-congruency had no influence on perceptual sensitivity, regardless of cue-target interval and discrimination difficulty. The reaction time effect was not accompanied by modulations of early visual-evoked potentials. Instead, beta-band (13-30 Hz) synchronization over sensorimotor brain regions was influenced by action preparation, indicative of improved response preparation. Together, the results suggest that action preparation may not modulate early visual processing of orientation, but likely influences higher order response or decision related processing. While early effects of action on spatial perception are well documented, separate mechanisms appear to govern non-spatial feature selection.

Neural entrainment is associated with subjective groove and complexity for performed but not mechanical musical rhythms.

Both movement and neural activity in humans can be entrained by the regularities of an external stimulus, such as the beat of musical rhythms. Neural entrainment to auditory rhythms supports temporal perception, and is enhanced by selective attention and by hierarchical temporal structure imposed on rhythms. However, it is not known how neural entrainment to rhythms is related to the subjective experience of groove (the desire to move along with music or rhythm), the perception of a regular beat, the perception of complexity, and the experience of pleasure. In two experiments, we used musical rhythms (from Steve Reich's Clapping Music) to investigate whether rhythms that are performed by humans (with naturally variable timing) and rhythms that are mechanical (with precise timing), elicit differences in (1) neural entrainment, as measured by inter-trial phase coherence, and (2) subjective ratings of the complexity, preference, groove, and beat strength of rhythms. We also combined results from the two experiments to investigate relationships between neural entrainment and subjective perception of musical rhythms. We found that mechanical rhythms elicited a greater degree of neural entrainment than performed rhythms, likely due to the greater temporal precision in the stimulus, and the two types only elicited different ratings for some individual rhythms. Neural entrainment to performed rhythms, but not to mechanical ones, correlated with subjective desire to move and subjective complexity. These data, therefore, suggest multiple interacting influences on neural entrainment to rhythms, from low-level stimulus properties to high-level cognition and perception.