Sleep quality relates to emotional reactivity via intracortical myelination

A good quality and amount of sleep are fundamental to preserve cognition and affect. New evidence also indicates that poor sleep is detrimental for brain myelination. In this study, we test the hypothesis that sleep quality and/or quantity relate to variability in cognitive and emotional function via the mediating effect of inter-individuals differences in proxy neuroimaging measures of white-matter integrity and intra-cortical myelination. By employing a demographically and neuropsychologically well-characterized sample of healthy people drawn from the Human Connectome Project (n=974), we found that quality and amount of sleep were only marginally linked to cognitive performance. In contrast, poor quality and short sleep increased negative affect (i.e., anger, fear, and perceived stress) and reduced life satisfaction and positive emotionality. At the brain level, poorer sleep quality and shorter sleep duration related to lower intra-cortical myelin in the mid-posterior cingulate cortex (p=0.038), middle temporal cortex (p=0.024), and anterior orbitofrontal cortex (OFC, p=0.034) but did not significantly affect different measures of white-matter integrity. Finally, lower intra-cortical myelin in the OFC mediated the association between poor sleep quality and negative emotionality (p<0.05). We conclude that intra-cortical myelination is an important mediator of the negative consequences of poor sleep on affective behaviour

Through their eyes: multi-subject Brain Decoding with simple alignment techniques

Previous brain decoding research primarily involves single-subject studies, reconstructing stimuli via fMRI activity from the same subject. Our study aims to introduce a generalization technique for cross-subject brain decoding, facilitated by exploring data alignment methods. We utilized the NSD dataset, a comprehensive 7T fMRI vision experiment involving multiple subjects exposed to 9841 images, 982 of which were viewed by all. Our approach involved training a decoding model on one subject, aligning others' data to this space, and testing the decoding on the second subject. We compared ridge regression, hyper alignment, and anatomical alignment techniques for fMRI data alignment. We established that cross-subject brain decoding is feasible, even using around 10% of the total data, or 982 common images, with comparable performance to single-subject decoding. Ridge regression was the best method for functional alignment. Through subject alignment, we achieved superior brain decoding and a potential 90% reduction in scan time. This could pave the way for more efficient experiments and further advancements in the field, typically requiring an exorbitant 20-hour scan time per subject

Beyond Multilayer Perceptrons: Investigating Complex Topologies in Neural Networks

In this study, we explore the impact of network topology on the approximation capabilities of artificial neural networks (ANNs), with a particular focus on complex topologies. We propose a novel methodology for constructing complex ANNs based on various topologies, including Barab\'asi-Albert, Erd\H{o}s-R\'enyi, Watts-Strogatz, and multilayer perceptrons (MLPs). The constructed networks are evaluated on synthetic datasets generated from manifold learning generators, with varying levels of task difficulty and noise. Our findings reveal that complex topologies lead to superior performance in high-difficulty regimes compared to traditional MLPs. This performance advantage is attributed to the ability of complex networks to exploit the compositionality of the underlying target function. However, this benefit comes at the cost of increased forward-pass computation time and reduced robustness to graph damage. Additionally, we investigate the relationship between various topological attributes and model performance. Our analysis shows that no single attribute can account for the observed performance differences, suggesting that the influence of network topology on approximation capabilities may be more intricate than a simple correlation with individual topological attributes. Our study sheds light on the potential of complex topologies for enhancing the performance of ANNs and provides a foundation for future research exploring the interplay between multiple topological attributes and their impact on model performance

Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion models

Decoding visual representations from human brain activity has emerged as a thriving research domain, particularly in the context of brain-computer interfaces. Our study presents an innovative method that employs to classify and reconstruct images from the ImageNet dataset using electroencephalography (EEG) data from subjects that had viewed the images themselves (i.e. "brain decoding"). We analyzed EEG recordings from 6 participants, each exposed to 50 images spanning 40 unique semantic categories. These EEG readings were converted into spectrograms, which were then used to train a convolutional neural network (CNN), integrated with a knowledge distillation procedure based on a pre-trained Contrastive Language-Image Pre-Training (CLIP)-based image classification teacher network. This strategy allowed our model to attain a top-5 accuracy of 80%, significantly outperforming a standard CNN and various RNN-based benchmarks. Additionally, we incorporated an image reconstruction mechanism based on pre-trained latent diffusion models, which allowed us to generate an estimate of the images which had elicited EEG activity. Therefore, our architecture not only decodes images from neural activity but also offers a credible image reconstruction from EEG only, paving the way for e.g. swift, individualized feedback experiments. Our research represents a significant step forward in connecting neural signals with visual cognition

4Ward: a Relayering Strategy for Efficient Training of Arbitrarily Complex Directed Acyclic Graphs

Thanks to their ease of implementation, multilayer perceptrons (MLPs) have become ubiquitous in deep learning applications. The graph underlying an MLP is indeed multipartite, i.e. each layer of neurons only connects to neurons belonging to the adjacent layer. In contrast, in vivo brain connectomes at the level of individual synapses suggest that biological neuronal networks are characterized by scale-free degree distributions or exponentially truncated power law strength distributions, hinting at potentially novel avenues for the exploitation of evolution-derived neuronal networks. In this paper, we present ``4Ward'', a method and Python library capable of generating flexible and efficient neural networks (NNs) from arbitrarily complex directed acyclic graphs. 4Ward is inspired by layering algorithms drawn from the graph drawing discipline to implement efficient forward passes, and provides significant time gains in computational experiments with various Erd\H{o}s-R\'enyi graphs. 4Ward not only overcomes the sequential nature of the learning matrix method, by parallelizing the computation of activations, but also addresses the scalability issues encountered in the current state-of-the-art and provides the designer with freedom to customize weight initialization and activation functions. Our algorithm can be of aid for any investigator seeking to exploit complex topologies in a NN design framework at the microscale

Surface-based morphometry reveals the neuroanatomical basis of the five-factor model of personality.

The five-factor model (FFM) is a widely used taxonomy of human personality; yet its neuro anatomical basis remains unclear. This is partly because past associations between gray-matter volume and FFM were driven by different surface-based morphometry (SBM) indices (i.e. cortical thickness, surface area, cortical folding or any combination of them). To overcome this limitation, we used Free-Surfer to study how variability in SBM measures was related to the FFM in n = 507 participants from the Human Connectome Project.Neuroticism was associated with thicker cortex and smaller area and folding in prefrontal-temporal regions. Extraversion was linked to thicker pre-cuneus and smaller superior temporal cortex area. Openness was linked to thinner cortex and greater area and folding in prefrontal-parietal regions. Agreeableness was correlated to thinner prefrontal cortex and smaller fusiform gyrus area. Conscientiousness was associated with thicker cortex and smaller area and folding in prefrontal regions. These findings demonstrate that anatomical variability in prefrontal cortices is linked to individual differences in the socio-cognitive dispositions described by the FFM. Cortical thickness and surface area/folding were inversely related each others as a function of different FFM traits (neuroticism, extraversion and consciousness vs openness), which may reflect brain maturational effects that predispose or protect against psychiatric disorders.R.R. was funded by the University ‘Magna Graecia’ of Catanzaro, while L.P. was funded by the Italian National Research Council and the University of Cambridge. AT was funded by the National Institute on Aging (NIA), National Institutes of Health (NIH; 1R03AG051960-01) and by the Florida Department of Health ‘Ed and Ethel Moore Alzheimer’s Disease Research Program’ (6AZ09). Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. Data collection and sharing for this project was provided by the MGHUSC Human Connectome Project (HCP; Principal Investigators: Bruce Rosen, M.D., Ph.D., Arthur W. Toga, Ph.D., Van J. Weeden, MD). The HCP project is supported by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH), and the National Institute of Neurological Disorders and Stroke (NINDS) (Principal Investigators: Bruce Rosen, M.D., Ph.D., Martinos Center at Massachusetts General Hospital; Arthur W. Toga, Ph.D., University of Southern California, Van J. Weeden, MD, Martinos Center at Massachusetts General Hospital). HCP is also the result of efforts of co-investigators from the University of Southern California, Martinos Center for Biomedical Imaging at Massachusetts General Hospital (MGH), Washington University, and the University of Minnesota

Summary report on sensory-related socio-economic and sensory science literature about organic food products

Organic food’s initial attraction to the public was that it was perceived to be healthier and tastier, but scientists and policy makers have mainly stressed the benefits to the environment of organic and sustainable farming. Scientific support for marketing actions addressed to those who want to be healthier and who want to enjoy better taste, and are willing to pay more for these benefits is scarce. Past research has produced little clear evidence about the importance of sensory characteristics such as taste, smell, appearance etc in consumers’ preferences with regard to organic food. The Ecropolis project, funded by the E.U., was set up with the aim of investigating the role of the senses in consumers’ preferences regarding organic food, and leading to research into how best to satisfy those preferences. This deliverable is aimed at providing a solid basis for such research with an in-depth review of, and two reports on, the relevant scientific literature. The first report (Annex I) regards what consumers expect from organic products in terms of taste, smell, appearance, etc and how these expectations are (or are not) met; the second is about the science of the senses (Annex II). The first project tasks included creating and agreeing on a glossary of terms, deciding on search criteria (key words, etc.), setting up a bibliographical data base, preparing then circulating the above-mentioned reports, and finally preparing a summary of the reports. The report on consumers expectations highlights the suggestion that while organic food has traditionally been marketed through specialized retailers, its market share will only grow significantly if it is promoted by multiple retailers. Research literature from all over the world seems to agree in indicating that consumers’ choices are largely motivated by health, the environment, price and social status. Other considerations include ethics, the localness of the product and lifestyle choices. The literature also indicates that the organic market will expand significantly only if consumers are more willing, and able, to recognize quality, but this presents serious issues. When buying the product they cannot personally verify its quality and genuineness and thus must rely on regulation and inspection bodies. The recognition of quality can also be encouraged by effective communication by producers and retailers through appropriate branding, labelling and presentation. There are connections between this information and questions of sense perception, but researchers disagree about how important the latter is in influencing the customer, and in which ways it does so. The following report focuses, in fact, on the science of the senses, which tries to analyze in detail people’s responses to food, despite the many potential pitfalls in carrying out the research which might influence the reliability of the results. There is broad agreement on two points: - there is no proof that organic food is more nutritious or safer, and - most studies that have compared the taste and organoleptic quality of organic andconventional foods report no consistent or significant differences between organic and conventional produce. Therefore, claiming that all organic food tastes different from all conventional food would not be correct. However, among the well-designed studies with respect to fruits and vegetables that have found differences, the vast majority favour organic produce. Organic produce tends to store better and has longer shelf life, probably because of lower levels of nitrates and higher average levels of antioxidants. The former can accelerate food spoilage, while antioxidants help preserve the integrity of cells and some are natural antibiotics. The first conclusion may, however, depend on factors not directly connected to organic farming, such as harvesting and storage methods and the type of land used for growing the food. About the second finding it must be considered that measuring organoleptic quality is difficult and inherently subjective and evaluations may be clouded by the influence of numerous factors on the consumer’s perceptions of the food and not just its appearance and taste. Experimental research indicates that the information that a food is organic confers upon it a “halo effect” (making it seem better sense-wise simply because it is organic) which might make consumers like it more. Ecropolis researchers will analyze in detail which senses are indeed impacted on, and how, and try to match them to consumer needs and expectations in order to be able to offer suggestions for future policy, including how the food is stored, transported and presented, which is also essential for maintaining sensory properties. The workpackage WP1 has also produced a specific report on how organic food sensory aspects are regulated. International standards, with some important exceptions, are largely in line with European ones. Differences in standards usually regard whether there is orientation towards freshness “per se” as opposed to increasing shelf-life, or quality standardization as opposed to quality differentiation. Differences in regulations regard such aspects as ingredients, additives, processing aids and methods, packaging, storage and transport. The lack of harmony among the different regulatory systems often reflects different traditions and market conditions, however, more complicated compliance procedures result in higher costs for importers. Greater homogeneity would not only reduce such costs but would also increase consumer confidence in international standards. Ecropolis will also investigate the effect of different regulations on how people perceive organic goods sense-wise. The work done to date is seen as a starting point for future research aimed at producing practical results in the organic food market. Ecropolis will try to bring together separate strands of research concerning how organic goods are regulated and marketed with regard to taste, appearance, etc., and how consumers themselves are affected by such factors. The aim is to find optimal matches between the two, and thus to greatly increase organic food’s share of the food market

Heritability of human "directed" functional connectome

IntroductionThe functional connectivity patterns in the brain are highly heritable; however, it is unclear how genetic factors influence the directionality of such "information flows." Studying the "directionality" of the brain functional connectivity and assessing how heritability modulates it can improve our understanding of the human connectome. MethodsHere, we investigated the heritability of "directed" functional connections using a state-space formulation of Granger causality (GC), in conjunction with blind deconvolution methods accounting for local variability in the hemodynamic response function. Such GC implementation is ideal to explore the directionality of functional interactions across a large number of networks. Resting-state functional magnetic resonance imaging data were drawn from the Human Connectome Project (total n = 898 participants). To add robustness to our findings, the dataset was randomly split into a "discovery" and a "replication" sample (each with n = 449 participants). The two cohorts were carefully matched in terms of demographic variables and other confounding factors (e.g., education). The effect of shared environment was also modeled. ResultsThe parieto- and prefronto-cerebellar, parieto-prefrontal, and posterior-cingulate to hippocampus connections showed the highest and most replicable heritability effects with little influence by shared environment. In contrast, shared environmental factors significantly affected the visuo-parietal and sensory-motor directed connectivity. ConclusionWe suggest a robust role of heritability in influencing the directed connectivity of some cortico-subcortical circuits implicated in cognition. Further studies, for example using task-based fMRI and GC, are warranted to confirm the asymmetric effects of genetic factors on the functional connectivity within cognitive networks and their role in supporting executive functions and learning

Cortical thickness, surface area, and folding alterations in male youths with conduct disorder and varying levels of callous-unemotional traits

Purpose: previous studies have reported changes in gray matter volume in youths with conduct disorder (CD), although these differences are difficult to interpret as they may have been driven by alterations in cortical thickness, surface area (SA), or folding. The objective of this study was to use surface-based morphometry (SBM) methods to compare male youths with CD and age and sex-matched healthy controls (HCs) in cortical thickness, SA, and folding. We also tested for structural differences between the childhood-onset and adolescence-onset subtypes of CD and performed regression analyses to assess for relationships between CD symptoms and callous-unemotional (CU) traits and SBM-derived measures. Methods: we acquired structural neuroimaging data from 20 HC and 36 CD participants (18 with childhood-onset CD and 18 with adolescence-onset CD) and analysed the data using FreeSurfer. Results: relative to HCs, youths with CD showed reduced cortical thickness in the superior temporal gyrus, reduced SA in the orbitofrontal cortex (OFC), and increased cortical folding in the insula. There were no significant differences between the childhood-onset and adolescence-onset CD subgroups in cortical thickness or SA, but several frontal and temporal regions showed increased cortical folding in childhood-onset relative to adolescence-onset CD participants. CD symptoms were negatively correlated with OFC SA whereas CU traits were positively correlated with insula folding.Conclusions: cortical thinning in the superior temporal gyrus may contribute to the social cognitive impairments displayed by youths with CD, whereas reduced OFC SA may lead to impairments in emotion regulation and reward processing in youths with CD. The increased cortical folding observed in the insula may reflect a maturational delay in this region and could mediate the link between CU traits and empathy deficits. Altered cortical structure was observed in childhood-onset and adolescence-onset forms of C