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Abstract Comprehending digital content written in natural language online is vital for many aspects of life, including learning, professional tasks, and decision-making. However, facing comprehension difficulties can have negative consequences for learning outcomes, critical thinking skills, decision-making, error rate, and productivity. This paper introduces an innovative approach to predict comprehension difficulties at the local content level (e.g., paragraphs). Using affordable wearable devices, we acquire physiological responses non-intrusively from the autonomous nervous system, specifically pulse rate variability, and electrodermal activity. Additionally, we integrate data from a cost-effective eye-tracker. Our machine learning algorithms identify ’hotspots’ within the content and regions corresponding to a high cognitive load. These hotspots represent real-time predictors of comprehension difficulties. By integrating physiological data with contextual information (such as the levels of experience of individuals), our approach achieves an accuracy of 72.11% ± 2.21, a precision of 0.77, a recall of 0.70, and an f1 score of 0.73. This study opens possibilities for developing intelligent, cognitive-aware interfaces. Such interfaces can provide immediate contextual support, mitigating comprehension challenges within content. Whether through translation, content generation, or content summarization using available Large Language Models, this approach has the potential to enhance language comprehension.

Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer's cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer's cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.

Abstract Invasive brain recordings using many electrodes across a wide range of tasks provide a unique opportunity to study the role of oscillatory patterning and functional connectivity. We used large-scale recordings (stereo EEG) within and beyond the human hippocampus to investigate the role of distinct frequency oscillations during real-time execution of visual, attention and memory tasks in eight epileptic patients. We found that activity patterns in the hippocampus showed task and frequency dependent properties. Importantly, we found distinct connectivity signatures, in particular concerning parietal-hippocampal connectivity, thus revealing large scale synchronization of networks involved in memory tasks. Comparing the power per frequency band, across tasks and hippocampal regions (anterior/posterior) we confirmed a main effect of frequency band (p = 0.002). Gamma band activity was higher for visuo-spatial memory tasks in the anterior hippocampus. Further, we found that alpha and beta band activity in posterior hippocampus had larger modulation for high memory load visual tasks (p = 0.004). Three functional connectivity task related networks were identified: (dorsal) parietal-hippocampus (visual attention and memory), ventral stream- hippocampus and hippocampal-frontal connections (mainly tasks involving face recognition or object based search). These findings support the critical role of oscillatory patterning in the hippocampus during visual and memory tasks and suggests the presence of task related spectral and functional connectivity signatures. These results show that the use of large scale human intracranial recordings can validate the role of oscillatory and functional connectivity patterns across a broad range of cognitive domains.

Abstract Machado-Joseph disease (MJD) or Spinocerebellar ataxia type 3 (SCA3) is the most common form of dominant SCA worldwide. Magnetic Resonance Imaging (MRI) and Proton Magnetic Resonance Spectroscopy (1H-MRS) provide promising non-invasive diagnostic and follow-up tools, also serving to evaluate therapies efficacy. However, pre-clinical studies showing relationship between MRI-MRS based biomarkers and functional performance are missing, which hampers an efficient clinical translation of therapeutics. This study assessed motor behaviour, neurochemical profiles, and morphometry of the cerebellum of MJD transgenic mice and patients aiming at establishing magnetic-resonance-based biomarkers. 1H-MRS and structural MRI measurements of MJD transgenic mice were performed with a 9.4 Tesla scanner, correlated with motor performance on rotarod and compared with data collected from human patients. We found decreased cerebellar white and grey matter and enlargement of the fourth ventricle in both MJD mice and human patients as compared to controls. N-acetylaspartate (NAA), NAA + N-acetylaspartylglutamate (NAA + NAAG), Glutamate, and Taurine, were significantly decreased in MJD mouse cerebellum regardless of age, whereas myo-Inositol (Ins) was increased at early time-points. Lower neurochemical ratios levels (NAA/Ins and NAA/total Choline), previously correlated with worse clinical status in SCAs, were also observed in MJD mice cerebella. NAA, NAA + NAAG, Glutamate, and Taurine were also positively correlated with MJD mice motor performance. Importantly, these 1H-MRS results were largely analogous to those found for MJD in human studies and in our pilot data in human patients. We have established a magnetic resonance-based biomarker approach to monitor novel therapies in preclinical studies and human clinical trials.

Complexity is the key element of software quality. This article investigates the problem of measuring code complexity and discusses the results of a controlled experiment to compare different views and methods to measure code complexity. Participants (27 programmers) were asked to read and (try to) understand a set of programs, while the complexity of such programs is assessed through different methods and perspectives: (a) classic code complexity metrics such as McCabe and Halstead metrics, (b) cognitive complexity metrics based on scored code constructs, (c) cognitive complexity metrics from state-of-the-art tools such as SonarQube, (d) human-centered metrics relying on the direct assessment of programmers’ behavioral features (e.g., reading time, and revisits) using eye tracking, and (e) cognitive load/mental effort assessed using electroencephalography (EEG). The human-centered perspective was complemented by the subjective evaluation of participants on the mental effort required to understand the programs using the NASA Task Load Index (TLX). Additionally, the evaluation of the code complexity is measured at both the program level and, whenever possible, at the very low level of code constructs/code regions, to identify the actual code elements and the code context that may trigger a complexity surge in the programmers’ perception of code comprehension difficulty. The programmers’ cognitive load measured using EEG was used as a reference to evaluate how the different metrics can express the (human) difficulty in comprehending the code. Extensive experimental results show that popular metrics such as V(g) and the complexity metric from SonarSource tools deviate considerably from the programmers’ perception of code complexity and often do not show the expected monotonic behavior. The article summarizes the findings in a set of guidelines to improve existing code complexity metrics, particularly state-of-the-art metrics such as cognitive complexity from SonarSource tools.

Deficits in mitochondrial function and redox deregulation have been attributed to Huntington's disease (HD), a genetic neurodegenerative disorder largely affecting the striatum. However, whether these changes occur in early stages of the disease and can be detected in vivo is still unclear. In the present study, we analysed changes in mitochondrial function and production of reactive oxygen species (ROS) at early stages and with disease progression. Studies were performed in vivo in human brain by PET using [64Cu]-ATSM and ex vivo in human skin fibroblasts of premanifest and prodromal (Pre-M) and manifest HD carriers. In vivo brain [64Cu]-ATSM PET in YAC128 transgenic mouse and striatal and cortical isolated mitochondria were assessed at presymptomatic (3 month-old, mo) and symptomatic (6–12 mo) stages. Pre-M HD carriers exhibited enhanced whole-brain (with exception of caudate) [64Cu]-ATSM labelling, correlating with CAG repeat number. Fibroblasts from Pre-M showed enhanced basal and maximal respiration, proton leak and increased hydrogen peroxide (H2O2) levels, later progressing in manifest HD. Mitochondria from fibroblasts of Pre-M HD carriers also showed reduced circularity, while higher number of mitochondrial DNA copies correlated with maximal respiratory capacity. In vivo animal PET analysis showed increased accumulation of [64Cu]-ATSM in YAC128 mouse striatum. YAC128 mouse (at 3 months) striatal isolated mitochondria exhibited a rise in basal and maximal mitochondrial respiration and in ATP production, and increased complex II and III activities. YAC128 mouse striatal mitochondria also showed enhanced mitochondrial H2O2 levels and circularity, revealed by brain ultrastructure analysis, and defects in Ca2+ handling, supporting increased striatal susceptibility. Data demonstrate both human and mouse mitochondrial overactivity and altered morphology at early HD stages, facilitating redox unbalance, the latter progressing with manifest disease.

ObjectivesWe aimed to investigate the antiepileptic effects of cathodal transcranial direct current stimulation (c-tDCS) and mechanisms of action based on its effects on the neurotransmitters responsible for the abnormal synchrony patterns seen in pharmacoresistant epilepsy. This is the first study to test the impact of neurostimulation on epileptiform interictal discharges (IEDs) and to measure brain metabolites in the epileptogenic zone (EZ) and control regions simultaneously in patients with pharmacoresistant epilepsy.MethodsThis is a hypothesis-driven pilot prospective single-blinded repeated measure design study in patients diagnosed with pharmacoresistant epilepsy of temporal lobe onset. We included seven patients who underwent two sessions of c-tDCS (sham followed by real). The real tDCS session was 20 min in duration and had a current intensity of 1.5 mA delivered via two surface electrodes that had dimensions of 3 × 4 cm. The cathode electrode was placed at FT7 in the center whereas the anode at Oz in the center. After each session, we performed electroencephalographic recording to count epileptiform IEDs over 30 min. We also performed magnetic resonance spectroscopy (MRS) to measure brain metabolite concentrations in the two areas of interest (EZ and occipital region), namely, gamma-aminobutyric acid (GABA), glutamate (Glx), and glutathione. We focused on a homogenous sample where the EZ and antiepileptic medications are shared among patients.ResultsReal tDCS decreased the number of epileptiform IEDs per min (from 9.46 ± 2.68 after sham tDCS to 5.37 ± 3.38 after real tDCS), p = 0.018, as compared to sham tDCS. GABA was decreased in the EZ after real c-tDCS stimulation as compared to sham tDCS (from 0.129 ± 0.019 to 0.096 ± 0.018, p = 0.02). The reduction in EZ GABA correlated with the reduction in the frequency of epileptiform IED per min (rho: 0.9, p = 0.003).ConclusionThese results provide a window into the antiepileptic mechanisms of action of tDCS, based on local and remote changes in GABA and neural oscillatory patterning responsible for the generation of interictal epileptiform discharges.

Error-related electroencephalographic (EEG) signals have been widely studied concerning the human cognitive capability of differentiating between erroneous and correct actions. Midfrontal error-related negativity (ERN) and theta band oscillations are believed to underlie post-action error monitoring. However, it remains elusive how early monitoring activity is trackable and what are the pre-response brain mechanisms related to performance monitoring. Moreover, it is still unclear how task-specific parameters, such as cognitive demand or motor control, influence these processes. Here, we aimed to test pre- and post-error EEG patterns for different types of motor responses and investigate the neuronal mechanisms leading to erroneous actions. We implemented a go/no-go paradigm based on keypresses and saccades. Participants received an initial instruction about the direction of response to be given based on a facial cue and a subsequent one about the type of action to be performed based on an object cue. The paradigm was tested in 20 healthy volunteers combining EEG and eye tracking. We found significant differences in reaction time, number, and type of errors between the two actions. Saccadic responses reflected a higher number of premature responses and errors compared to the keypress ones. Nevertheless, both led to similar EEG patterns, supporting previous evidence for increased ERN amplitude and midfrontal theta power during error commission. Moreover, we found pre-error decreased theta activity independent of the type of action. Source analysis suggested different origin for such pre- and post-error neuronal patterns, matching the anterior insular cortex and the anterior cingulate cortex, respectively. This opposite pattern supports previous evidence of midfrontal theta not only as a neuronal marker of error commission but also as a predictor of action performance. Midfrontal theta, mostly associated with alert mechanisms triggering behavioral adjustments, also seems to reflect pre-response attentional mechanisms independently of the action to be performed. Our findings also add to the discussion regarding how salience network nodes interact during performance monitoring by suggesting that pre- and post-error patterns have different neuronal sources within this network.

Abstract Blood-brain barrier (BBB) disruption is a common feature in neurodegenerative diseases. However, BBB integrity has not been assessed in spinocerebellar ataxias (SCAs) such as Machado-Joseph disease/SCA type 3 (MJD/SCA3), a genetic disorder, triggered by polyglutamine-expanded ataxin-3. To investigate that, BBB integrity was evaluated in a transgenic mouse model of MJD and in human post-mortem brain tissues. Firstly, we investigated the BBB permeability in MJD mice by: i) assessing the extravasation of the Evans blue (EB) dye and blood-borne proteins (e.g fibrinogen) in the cerebellum by immunofluorescence, and ii) in vivo Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI). The presence of ataxin-3 aggregates in brain blood vessels and the levels of tight junction (TJ)-associated proteins were also explored by immunofluorescence and western blotting. Human brain samples were used to confirm BBB permeability by evaluating fibrinogen extravasation, co-localization of ataxin-3 aggregates with brain blood vessels and neuroinflammation. In the cerebellum of the mouse model of MJD, there was a 5-fold increase in EB accumulation when compared to age-matched controls. Moreover, vascular permeability displayed a 13-fold increase demonstrated by DCE-MRI. These results were validated by the 2-fold increase in fibrinogen extravasation in transgenic animals comparing to controls. Interestingly, mutant ataxin-3 aggregates were detected in cerebellar blood vessels of transgenic mice, accompanied by alterations of TJ-associated proteins in cerebellar endothelial cells, namely a 29% decrease in claudin-5 oligomers and a 10-fold increase in an occludin cleavage fragment. These results were validated in post-mortem brain samples from MJD patients as we detected fibrinogen extravasation across BBB, the presence of ataxin-3 aggregates in blood vessels and associated microgliosis. Altogether, our results prove BBB impairment in MJD/SCA3. These findings contribute for a better understanding of the disease mechanisms and opens the opportunity to treat MJD with medicinal products that in normal conditions would not cross the BBB.

Error monitoring is the metacognitive process by which we are able to detect and signal our errors once a response has been made. Monitoring when the outcome of our actions deviates from the intended goal is crucial for behavior, learning, and the development of higher-order social skills. Here, we explored the neuronal substrates of error monitoring during the integration of facial expression cues using electroencephalography (EEG). Our goal was to investigate the signatures of error monitoring before and after a response execution dependent on the integration of facial cues. We followed the hypothesis of midfrontal theta as a robust neuronal marker of error monitoring since it has been consistently described as a mechanism to signal the need for cognitive control. Also, we hypothesized that EEG frequency-domain components might bring advantage to study error monitoring in complex scenarios as it carries information from locked and non-phase-locked signals. A challenging go/no-go saccadic paradigm was applied to elicit errors: integration of facial emotional signals and gaze direction was required to solve it. EEG data were acquired from twenty healthy participants and analyzed at the level of theta band activity during response preparation and execution. Although theta modulation has been consistently demonstrated during error monitoring, it is still unclear how early it starts to occur. We found theta power differences at midfrontal channels between correct and error trials. Theta was higher immediately after erroneous responses. Moreover, before response initiation we observed the opposite: lower theta preceding errors. These results suggest theta band activity not only as an index of error monitoring, which is needed to enhance cognitive control, but also as a requisite for success. This study adds to previous evidence for the role of theta band in error monitoring processes by revealing error-related patterns even before response execution in complex tasks, and using a paradigm requiring the integration of facial expression cues.

Introduction. To design more effective interventions, such as neurostimulation, for stroke rehabilitation, there is a need to understand early physiological changes that take place that may be relevant for clinical monitoring. We aimed to study changes in neurophysiology following recent ischemic stroke, both at rest and with motor planning and execution. Materials and Methods. We included 10 poststroke patients, between 7 and 10 days after stroke, and 20 age-matched controls to assess changes in cortical motor output via transcranial magnetic stimulation and in dynamics of oscillations, as recorded using electroencephalography (EEG). Results. We found significant differences in cortical oscillatory patterns comparing stroke patients with healthy participants, particularly in the beta rhythm during motor planning (p=0.011) and execution (p=0.004) of a complex movement with fingers from both hands simultaneously. Discussion. The stroke lesion induced a decrease in event-related desynchronization in patients, in comparison to controls, providing evidence for decreased disinhibition. Conclusions. After a stroke lesion, the dynamics of cortical oscillations is changed, with an increasing neural beta synchronization in the course of motor preparation and performance of complex bimanual finger tasks. The observed patterns may provide a potential functional measure that could be used to monitor and design interventional approaches in subacute stages.

Objectives: Transcranial magnetic stimulation, in particular continuous theta burst (cTBS), has been proposed for stroke rehabilitation, based on the concept that inhibition of the healthy hemisphere helps promote the recovery of the lesioned one. We aimed to study its effects on cortical excitability, oscillatory patterns, and motor function, the main aim being to identify potentially beneficial neurophysiological effects.Materials and Methods: We applied randomized real or placebo stimulation over the unaffected primary motor cortex of 10 subacute (7 ± 3 days) post-stroke patients. Neurophysiological measurements were performed using electroencephalography and electromyography. Motor function was assessed with the Wolf Motor Function Test. We performed a repeated measure study with the recordings taken pre-, post-cTBS, and at 3 months' follow-up.Results: We investigated changes in motor rhythms during arm elevation and thumb opposition tasks and found significant changes in beta power of the affected thumb's opposition, specifically after real cTBS. Our results are consistent with an excitatory response (increase in event-related desynchronization) in the sensorimotor cortical areas of the affected hemisphere, after stimulation. Neither peak-to-peak amplitude of motor-evoked potentials nor motor performance were significantly altered.Conclusions: Consistently with the theoretical prediction, this contralateral inhibitory stimulation paradigm changes neurophysiology, leading to a significant excitatory impact on the cortical oscillatory patterns of the contralateral hemisphere. These proof-of-concept results provide evidence for the potential role of continuous TBS in the neurorehabilitation of post-stroke patients. We suggest that these changes in ERS/ERD patterns should be further explored in future phase IIb/phase III clinical trials, in larger samples of poststroke patients.

Background: Several functional magnetic resonance imaging (fMRI) studies investigated the brain correlates of psychogenic erectile dysfunction (PED) and premature ejaculation (PE), representing the most common sexual dysfunctions in men. These studies allowed a wide set of brain regions in PED and PE patients when compared to healthy men. In the present meta-analysis, we aim at assessing the presence of homogeneity in the cerebral underpinnings of PED and PE. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and after the electronic search, duplicate removal and the application of pre-exclusion criteria, nine PED and ten PE studies were considered eligible with a Cohen’s k of 0.84 and 0.75, respectively. The effect sizes of the sociodemographic and psychological/urological dimensions were calculated. We extracted brain clusters from the retrieved studies, comparing patients and controls, and we calculated brain maps with Seed-Based D Mapping software. Results: We found a homogenous involvement of the frontal gyrus and insula in both dysfunctions, suggesting a common network. Conclusions: The anterior insula plays a key role in the processing of emotional features of stimuli, while the posterior insula in interoceptive information is relevant for sexual response. The prefrontal and inferior frontal cortices are important for sexual inhibition/disinhibition.

There is an increasing interest in the neural effects of psychoactive drugs, in particular tryptamine psychedelics, which has been incremented by the proposal that they have potential therapeutic benefits, based on their molecular mimicry of serotonin. It is widely believed that they act mainly through 5HT2A receptors but their effects on neural activation of distinct brain systems are not fully understood. We performed a quantitative meta-analysis of brain imaging studies to investigate the effects of substances within this class (e.g., LSD, Psilocybin, DMT, Ayahuasca) in the brain from a molecular and functional point of view. We investigated the question whether the changes in activation patterns and connectivity map into regions with larger 5HT1A/5HT2A receptor binding, as expected from indolaemine hallucinogens (in spite of the often reported emphasis only on 5HT2AR). We did indeed find that regions with changed connectivity and/or activation patterns match regions with high density of 5HT2A receptors, namely visual BA19, visual fusiform regions in BA37, dorsal anterior and posterior cingulate cortex, medial prefrontal cortex, and regions involved in theory of mind such as the surpramarginal gyrus, and temporal cortex (rich in 5HT1A receptors). However, we also found relevant patterns in other brain regions such as dorsolateral prefrontal cortex. Moreover, many of the above-mentioned regions also have a significant density of both 5HT1A/5HT2A receptors, and available PET studies on the effects of psychedelics on receptor occupancy are still quite scarce, precluding a metanalytic approach. Finally, we found a robust neuromodulatory effect in the right amygdala. In sum, the available evidence points towards strong neuromodulatory effects of tryptamine psychedelics in key brain regions involved in mental imagery, theory of mind and affective regulation, pointing to potential therapeutic applications of this class of substances.

Abstract Background It has been claimed that the retina can be used as a window to study brain disorders. However, concerning Alzheimer’s disease (AD), it still remains controversial whether changes occurring in the brain and retina are associated. We aim to understand when changes start appearing in the retina and brain, how changes progress, and if they are correlated. Methods We carried out a unique longitudinal study, at 4, 8, 12, and 16 months of age, in a triple transgenic mouse model of AD (3×Tg-AD), which mimics pathological and neurobehavioral features of AD, as we have already shown. Retinal structure and physiology were evaluated in vivo using optical coherence tomography and electroretinography. Brain visual cortex structure was evaluated in vivo using magnetic resonance imaging. Results The retinal thickness of 3×Tg-AD decreased, at all time points, except for the outer nuclear layer, where the opposite alteration was observed. Amplitudes in scotopic and photopic responses were increased throughout the study. Similarly, higher amplitude and lower phase values were observed in the photopic flicker response. No differences were found in the activity of retinal ganglion cells. Visual cortex gray matter volume was significantly reduced. Conclusions Our results show that this animal model shows similar neural changes in the retina and brain visual cortex, i.e., retinal and brain thinning. Moreover, since similar changes occur in the retina and brain visual cortex, these observations support the possibility of using the eye as an additional tool (noninvasive) for early AD diagnosis and therapeutic monitoring.

Social attention deficits represent a central impairment of patients suffering from autism spectrum disorder (ASD), but the nature of such deficits remains controversial. We compared visual attention regarding social (faces) vs. non-social stimuli (objects), in an ecological diagnostic context, in 46 children and adolescents divided in two groups: ASD (N = 23) and typical neurodevelopment (TD) (N = 23), matched for chronological age and intellectual performance. Eye-tracking measures of visual scanning, while exploring and describing scenes from three different tasks from the Autism Diagnostic Observation Schedule (ADOS), were analyzed: “Description of a Picture,” “Cartoons,” and “Telling a Story from a Book.” Our analyses revealed a three-way interaction between Group, Task, and Social vs. Object Stimuli. We found a striking main effect of group and a task dependence of attentional allocation: while the TD attended first and longer to faces, ASD participants became similar to TD when they were asked to look at pictures while telling a story. Our results suggest that social attention allocation is task dependent, raising the question whether spontaneous attention deficits can be rescued by guiding goal-directed actions.

The ability to perceive and feel another person' pain as if it were one's own pain, e.g., pain empathy, is related to brain activity in the “pain-matrix” network. A non-core region of this network in Dorsolateral Prefrontal Cortex (DLPFC) has been suggested as a modulator of the attentional-cognitive dimensions of pain processing in the context of pain empathy. We conducted a neurofeedback experiment using real-time functional magnetic resonance imaging (rt-fMRI-NF) to investigate the association between activity in the left DLPFC (our neurofeedback target area) and the perspective assumed by the participant (“first-person”/“Self” or “third-person”/“Other” perspective of a pain-inducing stimulus), based on a customized pain empathy task. Our main goals were to assess the participants' ability to volitionally modulate activity in their own DLPFC through an imagery task of pain empathy and to investigate into which extent this ability depends on feedback. Our results demonstrate participants' ability to significantly modulate brain activity of the neurofeedback target area for the “first-person”/”Self” and “third-person”/”Other” perspectives. Results of both perspectives show that the participants were able to modulate (with statistical significance) the activity already in the first run of the session, in spite of being naïve to the task and even in the absence of feedback information. Moreover, they improved modulation throughout the session, particularly in the “Self” perspective. These results provide new insights on the role of DLPFC in pain and pain empathy mechanisms and validate the proposed protocol, paving the way for future interventional studies in clinical populations with empathic deficits.

Positron emission tomography (PET) neuroimaging with the Pittsburgh Compound_B (PiB) is widely used to assess amyloid plaque burden. Standard quantification approaches normalize PiB-PET by mean cerebellar gray matter uptake. Previous studies suggested similar pons and white-matter uptake in Alzheimer's disease (AD) and healthy controls (HC), but lack exhaustive comparison of normalization across the three regions, with data-driven diagnostic classification.We aimed to compare the impact of distinct reference regions in normalization, measured by data-driven statistical analysis, and correlation with cerebrospinal fluid (CSF) amyloid β (Aβ) species concentrations.243 individuals with clinical diagnosis of AD, HC, mild cognitive impairment (MCI) and other dementias, from the Biomarkers for Alzheimer's/Parkinson's Disease (BIOMARKAPD) initiative were included. PiB-PET images and CSF concentrations of Aβ38, Aβ40 and Aβ42 were submitted to classification using support vector machines. Voxel-wise group differences and correlations between normalized PiB-PET images and CSF Aβ concentrations were calculated.Normalization by cerebellar gray matter and pons yielded identical classification accuracy of AD (accuracy-96%, sensitivity-96%, specificity-95%), and significantly higher than Aβ concentrations (best accuracy 91%). Normalization by the white-matter showed decreased extent of statistically significant multivoxel patterns and was the only method not outperforming CSF biomarkers, suggesting statistical inferiority. Aβ38 and Aβ40 correlated negatively with PiB-PET images normalized by the white-matter, corroborating previous observations of correlations with non-AD-specific subcortical changes in white-matter. In general, when using the pons as reference region, higher voxel-wise group differences and stronger correlation with Aβ42, the Aβ42/Aβ40 or Aβ42/Aβ38 ratios were found compared to normalization based on cerebellar gray matter.

Abstract Microvascular dysfunction has been suggested to trigger adipose tissue dysfunction in obesity. This study investigates the hypothesis that glycation impairs microvascular architecture and expandability with an impact on insulin signalling. Animal models supplemented with methylglyoxal (MG), maintained with a high-fat diet (HFD) or both (HFDMG) were studied for periepididymal adipose (pEAT) tissue hypoxia and local and systemic insulin resistance. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used to quantify blood flow in vivo, showing MG-induced reduction of pEAT blood flow. Increased adipocyte size and leptin secretion were observed only in rats feeding the high-fat diet, without the development of hypoxia. In turn, hypoxia was only observed when MG was combined (HFDMG group), being associated with impaired activation of the insulin receptor (Tyr1163), glucose intolerance and systemic and muscle insulin resistance. Accordingly, the adipose tissue angiogenic assay has shown decreased capillarization after dose-dependent MG exposure and glyoxalase-1 inhibition. Thus, glycation impairs adipose tissue capillarization and blood flow, hampering its expandability during a high-fat diet challenge and leading to hypoxia and insulin resistance. Such events have systemic repercussions in glucose metabolism and may lead to the onset of unhealthy obesity and progression to type 2 diabetes.

An emergent research area in software engineering and software reliability is the use of wearable biosensors to monitor the cognitive state of software developers during software development tasks. The goal is to gather physiologic manifestations that can be linked to error-prone scenarios related to programmers’ cognitive states. In this paper we investigate whether electroencephalography (EEG) can be applied to accurately identify programmers’ cognitive load associated with the comprehension of code with different complexity levels. Therefore, a controlled experiment involving 26 programmers was carried. We found that features related to Theta, Alpha, and Beta brain waves have the highest discriminative power, allowing the identification of code lines and demanding higher mental effort. The EEG results reveal evidence of mental effort saturation as code complexity increases. Conversely, the classic software complexity metrics do not accurately represent the mental effort involved in code comprehension. Finally, EEG is proposed as a reference, in particular, the combination of EEG with eye tracking information allows for an accurate identification of code lines that correspond to peaks of cognitive load, providing a reference to help in the future evaluation of the space and time accuracy of programmers’ cognitive state monitored using wearable devices compatible with software development activities.

High-frequency activity (HFA) is believed to subserve a functional role in cognition, but these patterns are often not accessible to scalp EEG recordings. Intracranial studies provide a unique opportunity to link the all-encompassing range of high-frequency patterns with holistic perception. We tested whether the functional topography of HFAs (up to 250Hz) is related to perceptual decision-making. Human intracortical data were recorded (6 subjects; >250channels) during an ambiguous object-recognition task. We found a spatial topography of HFAs reflecting processing anterior dorsal and ventral streams, linked to decision independently of the type of processed object/stimulus category. Three distinct regional fingerprints could be identified, with lower gamma frequency patterns (

The relation of gamma-band synchrony to holistic perception in which concerns the effects of sensory processing, high level perceptual gestalt formation, motor planning and response is still controversial. To provide a more direct link to emergent perceptual states we have used holistic EEG/ERP paradigms where the moment of perceptual "discovery" of a global pattern was variable. Using a rapid visual presentation of short-lived Mooney objects we found an increase of gamma-band activity locked to perceptual events. Additional experiments using dynamic Mooney stimuli showed that gamma activity increases well before the report of an emergent holistic percept. To confirm these findings in a data driven manner we have further used a support vector machine classification approach to distinguish between perceptual vs. non perceptual states, based on time-frequency features. Sensitivity, specificity and accuracy were all above 95%. Modulations in the 30-75 Hz range were larger for perception states. Interestingly, phase synchrony was larger for perception states for high frequency bands. By focusing on global gestalt mechanisms instead of local processing we conclude that gamma-band activity and synchrony provide a signature of holistic perceptual states of variable onset, which are separable from sensory and motor processing.

Being social animals, rats exhibit a range of social behaviors that help them build social bonds and maintain group cohesion. Behavior is influenced by multiple factors, including stress exposure, and the expression of the impact of stress on both social and non-social behaviors may also be aected by the living conditions of rats. In this study, we explored the physiological and behavioral eects of chronic unpredictable stress on group-housed rats in the PhenoWorld (PhW), a socially and physically enriched environment closer to real-life conditions. Two independent experiments were performed: one in the control condition (PhW control, n = 8) and one in the stress condition (PhW stress, n = 8). Control animals remained undisturbed except for cage cleaning and daily handling procedures. Stress group animals were all exposed to chronic unpredictable stress. Data confirm that stress exposure triggers anxiety-like behavior in the PhW. In terms of home-cage behaviors, we found that stress aects social behaviors (by decreased playing and increased huddling behaviors) and non-social behaviors (as shown by the decrease in rearing and walking behaviors). These results are of relevance to expand our knowledge on the influence of stress on social and non-social behaviors, which are of importance to understand better species-typical behaviors. [ABSTRACT FROM AUTHOR]

In this study, we present iMind, a novel prototype tool designed to predict individuals’ comprehension difficulties with online content at local levels, such as paragraphs or multiple lines. iMind seamlessly captures the physiological responses of the Autonomic Nervous System (ANS) using commercially available wearable sensors (wristbands) in conjunction with a desktop eye-tracker to identify potentially difficult content sections. The machine learning model of iMind successfully predicts comprehension difficulties in English content at local levels, achieving a mean accuracy of 0.70 (±0.02), a precision mean of 0.70 (±0.03), a mean recall of 0.75 (±0.03), and an F1 score mean of 0.72 (±0.02). Furthermore, this document introduces a comprehensive risk analysis model that not only explains the predictions of iMind but also quantifies the risk scores associated with specific sections of content deemed difficult to comprehend. This integration enhances the interpretability of iMind’s outcomes, providing clearer insights into which content sections may require further simplification or support for improved comprehension.

Assessing comprehension difficulties requires the ability to assess cognitive load. Changes in cognitive load induced by comprehension difficulties could be detected with an adequate time resolution using different biofeedback measures (e.g., changes in the pupil diameter). However, identifying the Spatio-temporal sources of content comprehension difficulties (i.e., when, and where exactly the difficulty occurs in content regions) with a fine granularity is a big challenge that has not been explicitly addressed in the state-of-the-art. This paper proposes and evaluates an innovative approach named Intelligent BiofeedbackAugmented Content Comprehension (TellBack) to explicitly address this challenge. The goal is to autonomously identify regions of digital content that cause user's comprehension difficulty, opening the possibility to provide real-time comprehension support to users. TellBack is based on assessing the cognitive load associated with content comprehension through non-intrusive cheap biofeedback devices that acquire measures such as pupil response or Heart Rate Variability (HRV). To identify when exactly the difficulty in comprehension occurs, physiological manifestations of the Autonomic Nervous System (ANS) such as the pupil diameter variability and the modulation of HRV are exploited, whereas the fine spatial resolution (i.e., the region of content where the user is looking at) is provided by eye-tracking. The evaluation results of this approach show an accuracy of 83.00% ± 0.75 in classifying regions of content as difficult or not difficult using Support Vector Machine (SVM), and precision, recall, and micro F1-score of 0.89, 0.79, and 0.83, respectively. Results obtained with 4 other classifiers, namely Random Forest, k-nearest neighbor, Decision Tree, and Gaussian Naive Bayes, showed a slightly lower precision. TellBack outperforms the state-of-the-art in precision & recall by 23% and 17% respectively.

The neural correlates of software programming skills have been the target of an increasing number of studies in the past few years. Those studies focused on error-monitoring during software code inspection. Others have studied task-related cognitive load as measured by distinct neurophysiological measures. Most studies addressed only syntax errors (shallow level of code monitoring). However, a recent functional MRI (fMRI) study suggested a pivotal role of the insula during error-monitoring when challenging deep-level analysis of code inspection was required. This raised the hypothesis that the insula is causally involved in deep error-monitoring. To confirm this hypothesis, we carried out a new fMRI study where participants performed a deep source-code comprehension task that included error-monitoring to detect bugs in the code. The generality of our paradigm was enhanced by comparison with a variety of tasks related to text reading and bugless source-code understanding. Healthy adult programmers (N = 21) participated in this 3T fMRI experiment. The activation maps evoked by error-related events confirmed significant activations in the insula [p(Bonferroni) < 0.05]. Importantly, a posterior-to-anterior causality shift was observed concerning the role of the insula: in the absence of error, causal directions were mainly bottom-up, whereas, in their presence, the strong causal top-down effects from frontal regions, in particular, the anterior cingulate cortex was observed.

Software programming is a modern activity that poses strong challenges to the human brain. The neural mechanisms that support this novel cognitive faculty are still unknown. On the other hand, reading and calculation abilities represent slightly less recent human activities, in which neural correlates are relatively well understood. We hypothesize that calculus and reading brain networks provide joint underpinnings with distinctly weighted contributions which concern programming tasks, in particular concerning error identification. Based on a meta-analysis of the core regions involved in both reading and math and recent experimental evidence on the neural basis of programming tasks, we provide a theoretical account that integrates the role of these networks in program understanding. In this connectivity-based framework, error-monitoring processing regions in the frontal cortex influence the insula, which is a pivotal hub within the salience network, leading into efficient causal modulation of parietal networks involved in reading and mathematical operations. The core role of the anterior insula and anterior midcingulate cortex is illuminated by their relation to performance in error processing and novelty. The larger similarity that we observed between the networks underlying calculus and programming skills does not exclude a more limited but clear overlap with the reading network, albeit with differences in hemispheric lateralization when compared with prose reading. Future work should further elucidate whether other features of computer program understanding also use distinct weights of phylogenetically “older systems” for this recent human activity, based on the adjusting influence of fronto-insular networks. By unraveling the neural correlates of program understanding and bug detection, this work provides a framework to understand error monitoring in this novel complex faculty.

Being social animals, rats exhibit a range of social behaviors that help them build social bonds and maintain group cohesion. Behavior is influenced by multiple factors, including stress exposure, and the expression of the impact of stress on both social and non-social behaviors may also be affected by the living conditions of rats. In this study, we explored the physiological and behavioral effects of chronic unpredictable stress on group-housed rats in the PhenoWorld (PhW), a socially and physically enriched environment closer to real-life conditions. Two independent experiments were performed: one in the control condition (PhW control, n = 8) and one in the stress condition (PhW stress, n = 8). Control animals remained undisturbed except for cage cleaning and daily handling procedures. Stress group animals were all exposed to chronic unpredictable stress. Data confirm that stress exposure triggers anxiety-like behavior in the PhW. In terms of home-cage behaviors, we found that stress affects social behaviors (by decreased playing and increased huddling behaviors) and non-social behaviors (as shown by the decrease in rearing and walking behaviors). These results are of relevance to expand our knowledge on the influence of stress on social and non-social behaviors, which are of importance to understand better species-typical behaviors.