• Neuroinformatics
• 2023-2023close
• Open Access close

Anxiety and fear are evolutionarily conserved emotions that increase the likeli-hood of an organism surviving threatening situations. Anxiety and vigilance states are regulated by neural networks involving multiple brain regions. In anx-iety disorders, this intricate regulatory system is disturbed, leading to excessive or prolonged anxiety or fear. Anxiety disorders have both genetic and environ-mental risk factors. Genetic research has the potential to identify specific genetic variants causally associated with specific phenotypes. In recent decades, genome-wide association studies (GWASs) have revealed variants predisposing to neuropsychiatric disorders, suggesting novel neurobiological pathways in the etiology of these disorders. Here, we review recent human GWASs of anxiety dis -orders, and genetic studies of anxiety-like behavior in rodent models. These studies are paving the way for a better understanding of the neurobiological mechanisms underlying anxiety disorders. Peer reviewed

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications.Evidence Level: 3Technical Efficacy: Stage 2

Abstract The goal of this study was to examine the relation between real-world socio-emotional measures and neural activation to parental criticism, a salient form of social threat for adolescents. This work could help us understand why heightened neural reactivity to social threat consistently emerges as a risk factor for internalizing psychopathology in youth. We predicted that youth with higher reactivity to parental criticism (vs neutral comments) in the subgenual anterior cingulate cortex (sgACC), amygdala and anterior insula would experience (i) less happiness in daily positive interpersonal situations and (ii) more sadness and anger in daily negative interpersonal situations. Participants (44 youth aged 11–16 years with a history of anxiety) completed a 10-day ecological momentary assessment protocol and a neuroimaging task in which they listened to audio clips of their parents’ criticism and neutral comments. Mixed-effects models tested associations between neural activation to critical (vs neutral) feedback and emotions in interpersonal situations. Youth who exhibited higher activation in the sgACC to parental criticism reported less happiness during daily positive interpersonal situations. No significant neural predictors of negative emotions (e.g. sadness and anger) emerged. These findings provide evidence of real-world correlates of neural reactivity to social threat that may have important clinical implications.

Most studies on EEG-based biometry recognition report results based on signal databases, with a limited number of recorded EEG sessions using the same single EEG recording for both training and testing a proposed model. However, the EEG signal is highly vulnerable to interferences, electrode placement, and temporary conditions, which can lead to overestimated assessments of the considered methods. Our study examined how different numbers of distinct recording sessions used as training sessions would affect EEG-based verification. We analyzed the original data from 29 participants with 20 distinct recorded sessions each, as well as 23 additional impostors with only one session each. We applied raw coefficients of power spectral density estimate, and the coefficients of power spectral density estimate converted to the decibel scale, as the input to a shallow neural network. Our study showed that the variance introduced by multiple recording sessions affects sensitivity. We also showed that increasing the number of sessions above eight did not improve the results under our conditions. For 15 training sessions, the achieved accuracy was 96.7 ± 4.2%, and for eight training sessions and 12 test sessions, it was 94.9 ± 4.6%. For 15 training sessions, the rate of successful impostor attacks over all attack attempts was 3.1 ± 2.2%, but this number was not significantly different from using six recording sessions for training. Our findings indicate the need to include data from multiple recording sessions in EEG-based recognition for training, and that increasing the number of test sessions did not significantly affect the obtained results. Although the presented results are for the resting-state, they may serve as a baseline for other paradigms.

AbstractThe proteomic profile of extracellular vesicles (EVs) from cerebrospinal fluid (CSF) can reveal novel biomarkers for diseases of the brain. Here, we validate an ultrafiltration combined with size-exclusion chromatography (UF-SEC) method for isolation of EVs from canine CSF and probe the effect of starting volume on the EV proteomics profile. First, we performed a literature review of CSF EV articles to define the current state of art, discovering a need for basic characterisation of CSF EVs. Secondly, we isolated EVs from CSF by UF-SEC and characterised the SEC fractions by protein amount, particle count, transmission electron microscopy, and immunoblotting. Data are presented as mean ± standard deviation. Using proteomics, SEC fractions 3–5 were compared and enrichment of EV markers in fraction 3 was detected, whereas fractions 4–5 contained more apolipoproteins. Lastly, we compared starting volumes of pooled CSF (6 ml, 3 ml, 1 ml, and 0.5 ml) to evaluate the effect on the proteomic profile. Even with a 0.5 ml starting volume, 743 ± 77 or 345 ± 88 proteins were identified depending on whether ‘matches between runs’ was active in MaxQuant. The results confirm that UF-SEC effectively isolates CSF EVs and that EV proteomic analysis can be performed from 0.5 ml of canine CSF.

This paper aims to describe the generations of particles and waves and describes the type of decisions they represent. This paper suggests that communication, decisions, certainty, and their variants are fundamental, and that universe as a whole is communicating the non-contradiction contradiction, or the contradictory non-contradiction, that which one cannot truly know, which is false. This paper introduces an equation for gravity and tries to explain what the result of a quantum gravitational system is. This paper uses physics to explain biology and uses biology to explain physics. This paper introduces a bio-space-time model representing the brains ability states, where space is recognition, time is perception, and spacetime is sense, and all together is communication. This paper was written under the implication that anything that describes everything is false.