Brain Systems Research Articles

Psychomotor reaction in adolescents with different levels of physical development

The work is aimed at studing dynamics of the latent time of motor reaction in conditions of noise interference in adolescents. The result of research of latent time of impellent reaction and force of nervous processes (under the tepping-test) at teenagers of 13-15 years with a certain level of physical development demonstrated that children with a high physical development level have low functional reserves brain programming systems. The influence of the processes underlying acceleration in terms of adaptive reactions of teenagers is showed by this way. The study of the motor reaction to a light stimulus was carried out using the latent time of simple motor reaction computer program developed in the laboratory. It was clear that the processes of acceleration affected the morph functional organization of regulatory brain systems, reducing their level of adaptability and operational reliability. Low indicators of adolescents’ strength of nervous processes, which were obtained during tapping testing, are the general modern trend towards a decrease in the level of their health. The data obtained can be used in the development of medical and pedagogical methods for correcting the functional state of the body of adolescents at the prenosological stage.

Jaak Panksepp’s primary emotions are associated with Diener’s global life satisfaction: How low arousal of the SADNESS/separation distress system could form the core of life satisfaction?

Abstract We compared Ed Diener’s Satisfaction With Life Scale (SWLS), which was designed as a purely cognitive measure of global life satisfaction, with the Affective Neuroscience Personality Scales 3.1, which provides self-report measures of Panksepp’s six primary emotions (excluding LUST), in two English-speaking samples: a main sample and a hold-out validation sample. Our data showed robust negative correlations between higher satisfaction with life and lower FEAR, lower SADNESS/Separation Distress, and positive associations (albeit less strong) between higher satisfaction with life and higher PLAY and SEEKING in both samples. The relationships between the SWLS and at least four of Panksepp’s primary emotions suggest Diener’s SWLS is not purely cognitive and includes a strong affective component. In addition, detailed analysis of the negative correlation between the SWLS and the ANPS 3.1 SADNESS scale provides insight into the importance of the low arousal end of the SADNESS/Separation Distress brain system and supports the idea of a continuum of psychological states from high SADNESS including loneliness and depression to low SADNESS psychological states characterized by social comfort, self-confidence, and social strength.

Multi-Scale FC-Based Multi-Order GCN: A Novel Model for Predicting Individual Behavior From fMRI.

Predicting individual behavior from brain imaging data using machine learning is a rapidly growing field in neuroscience. Functional connectivity (FC), which captures interactions between different brain regions, contains valuable information about the organization of the brain and is considered a crucial feature for modeling human behavior. Graph convolutional networks (GCN) have proven to be a powerful tool for extracting graph structure features and have shown promising results in various FC-based classification tasks, such as disease classification and prognosis prediction. Despite this success, few behavior prediction models currently exist based on GCN, and their performance is not satisfactory. To address this gap, a new model called the Multi-Scale FC-based Multi-Order GCN (MSFC-MO-GCN) was proposed in this paper. The model considers the hierarchical structure of the brain system and utilizes FCs inferred from multiple spatial scales as input to comprehensively characterize individual brain organization. To enhance the feature learning ability of GCN, a multi-order graph convolutional layer is incorporated, which uses multi-order neighbors to guide message passing and learns high-order graph information of nodal connections. Additionally, an inter-subject contrast constraint is designed to control the potential information redundancy of FCs among different spatial scales during the feature learning process. Experimental evaluation were conducted on the publicly available dataset from human connectome project. A total of 805 healthy subjects were included and 5 representative behavior metrics were used. The experimental results show that our proposed method outperforms the existing behavior prediction models in all behavior prediction tasks.

Two Independent Response Mechanisms to Auditory Stimuli Measured with Functional Near-Infrared Spectroscopy in Sleeping Infants.

This study investigated the morphology of the functional near-infrared spectroscopy (fNIRS) response to speech sounds measured from 16 sleeping infants and how it changes with repeated stimulus presentation. We observed a positive peak followed by a wide negative trough, with the latter being most evident in early epochs. We argue that the overall response morphology captures the effects of two simultaneous, but independent, response mechanisms that are both activated at the stimulus onset: one being the obligatory response to a sound stimulus by the auditory system, and the other being a neural suppression effect induced by the arousal system. Because the two effects behave differently with repeated epochs, it is possible to mathematically separate them and use fNIRS to study factors that affect the development and activation of the arousal system in infants. The results also imply that standard fNIRS analysis techniques need to be adjusted to take into account the possibilities of multiple simultaneous brain systems being activated and that the response to a stimulus is not necessarily stationary.

Supplementary motor area is deactivated during mental rotation tasks with biomechanical constraints in fMRI.

Mental rotation (MR) tasks of body parts involve anatomically interconnected brain systems. The systems are implicated in sensorimotor information integration and activate cortical motor-related areas, corresponding to the execution of similar motor tasks. In this study, we aimed to investigate the effect of varying the angle in the hand MR task on cerebral activation of the motor-related areas. Twenty healthy right-handed participants were recruited. We investigated cerebral activation while each participant decided whether a hand-palm image, rotated by 0°, 90°, 180°, and 270°, was a right or left hand. A significant negative correlation between the angle and brain activity was observed in the right and left supplementary motor area (SMA) and right posterior anterior cingulate gyrus. The SMA was inactivated with 180°- or 270°-rotated images in the regions of interest analysis. 180°- and 270°-rotated palms would be biomechanically difficult to position; thus, SMA deactivation may be closely associated with biomechanical constraints. This study provided novel findings regarding the neurophysiological mechanisms of motor imagery and may be useful in developing treatment plans using MR tasks during patient rehabilitation.

Cerebral Cavernous Malformation (CCM)-like Vessel Lesion in the Aged ANKS1A-deficient Brain.

In this study, we show that ANKS1A is specifically expressed in the brain endothelial cells of adult mice. ANKS1A deficiency in adult mice does not affect the differentiation, growth, or patterning of the cerebrovascular system; however, its absence significantly impacts the cerebrovascular system of the aged brain. In aged ANKS1A knock-out (KO) brains, vessel lesions exhibiting cerebral cavernous malformations (CCMs) are observed. In addition, CCM-like lesions show localized peripheral blood leakage into the brain. The CCM-like lesions reveal immune cells infiltrating the parenchyma. The CCM-like lesions also contain significantly fewer astrocyte endfeets and tight junctions, indicating that the integrity of the BBB has been partially compromised. CCM-like lesions display increased fibronectin expression in blood vessels, which is also confirmed in cultured endothelial cells deficient for ANKS1A. Therefore, we hypothesize that ANKS1A may play a role in maintaining or stabilizing healthy blood vessels in the brain during aging.

Neurosarcoidosis: The Presentation, Diagnosis and Treatment Review of Two Cases.

Sarcoidosis is a chronic granulomatous disease of unknown cause characterized by the presence of non-caseating granulomas. The disease can affect any organ including the nervous system. Neurosarcoidosis occurs in about 5% patients with sarcoidosis. The clinical presentation of neurosarcoidosis is varied, and it can involve the brain, spinal cord and peripheral nervous system, separately or in different combinations. The diagnosis of neurosarcoidosis is challenging, as biopsies from the nervous system are not readily available. Anti-TNFα agents are becoming one of the cornerstone treatments for neurosarcoidosis. In this case-based review, we discuss two cases of neurosarcoidosis with different clinical presentations. The first patient presented with confusion, while the second presented with walking difficulty and neurogenic bladder. Both patients were treated with methylprednisolone pulse therapy with rapid, but non-complete, improvement. Therefore, infliximab was initiated in both cases with subsequent improvement in the clinical manifestations and imaging findings, emphasizing the effectiveness and safety of infliximab in cases of severe neurosarcoidosis. In conclusion, the goal of neurosarcoidosis management is to prevent organ system damage and minimize the toxic cumulative adverse effects of glucocorticoid use. In this case-based review we discuss the various presentations, the diagnosis and the treatment of neurosarcoidosis.

Explanatory models in neuroscience, Part 2: Functional intelligibility and the contravariance principle

Computational modeling plays an increasingly important role in neuroscience, highlighting the philosophical question of how computational models explain. In the particular case of neural network models, concerns have been raised about their intelligibility, and how these models relate (if at all) to what is found in the brain. We claim that what makes a system intelligible is an understanding of the dependencies between its behavior and the factors that are responsible for that behavior. In biology, many of these dependencies are naturally “top-down”, as ethological imperatives interact with evolutionary and developmental constraints under natural selection to produce systems with capabilities and behaviors appropriate to their evolutionary needs. We describe how the optimization techniques used to construct neural network models capture some key aspects of these dependencies, and thus help explain why brain systems are as they are — because when a challenging ecologically-relevant goal is shared by a neural network and the brain, it places constraints on the possible mechanisms exhibited in both kinds of systems. The presence and strength of these constraints explain why some outcomes are more likely than others. By combining two familiar modes of explanation — one based on bottom-up mechanistic description (whose relation to neural network models we address in a companion paper) and the other based on top-down constraints, these models have the potential to illuminate brain function.

BOLD Activation During the Application of MOXO-CPT in School Patients With and Without Attention Deficit Hyperactivity Disorder

Introduction: Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects 3% of children in the world. Objective: In this work, we seek to compare the different brain activations of pediatric patients with and without ADHD. Methods: A functional resonance examination with BOLD contrast was applied using the MOXO-CPT test (Continuous Performance test with single and double visual-auditory distractors). Results: Differences in BOLD activation were observed indicating that control children regularly presented negative BOLD activations that were not found in children with ADHD. Inhibitory activity in audiovisual association zones in control patients was greater than in patients with ADHD. The inhibition in the frontal and motor regions in the controls contrasted with the overactivation of the motor areas in patients with ADHD, this, together with the detection of cerebellar activation which attempted to modulate the responses of the different areas that lead to executive failure in patients with ADHD. Conclusions: In view of these results, it can be argued that the lack of inhibition of ADHD patients in their executive functions led to a disorganization of the different brain systems.

Individuals who see the good in the bad engage distinctive default network coordination during post-encoding rest.

Focusing on the upside of negative events often promotes resilience. Yet, the underlying mechanisms that allow some people to spontaneously see the good in the bad remain unclear. The broaden-and-build theory of positive emotion has long suggested that positive affect, including positivity in the face of negative events, is linked to idiosyncratic thought patterns (i.e., atypical cognitive responses). Yet, evidence in support of this view has been limited, in part, due to difficulty in measuring idiosyncratic cognitive processes as they unfold. To overcome this barrier, we applied Inter-Subject Representational Similarity Analysis to test whether and how idiosyncratic neural responding supports positive reactions to negative experience. We found that idiosyncratic functional connectivity patterns in the brain's default network while resting after a negative experience predicts more positive descriptions of the event. This effect persisted when controlling for connectivity 1) before and during the negative experience, 2) before, during, and after a neutral experience, and 3) between other relevant brain regions (i.e., the limbic system). The relationship between idiosyncratic default network responding and positive affect was largely driven by functional connectivity patterns between the ventromedial prefrontal cortex and the rest of the default network and occurred relatively quickly during rest. We identified post-encoding rest as a key moment and the default network as a key brain system in which idiosyncratic responses correspond with seeing the good in the bad.

Application of a new-type of defecator in the treatment of rectal fecal impaction

Objective: This study aimed to investigate the viability and safety of a novel defecator in managing rectal fecal impaction. Methods: In a descriptive case series, this new defecator was administered to constipated individuals among the ages of 18 and 80 years who met the diagnostic criteria for rectal fecal impaction and were identified with acute rectal fecal impaction through CT scans. The contraindications for this defecator included: (1) Anal stenosis, acute intestinal obstruction, and intestinal perforation; (2) Concomitant rectal malignant tumors; (3) Coagulation dysfunction, low platelet counts, gastrointestinal bleeding, or other bleeding risks; (4) Patients with severe underlying conditions affecting the heart, brain, lungs, or other systems; (5) Individuals with mental health disorders. Based on these criteria, clinical data from 42 patients with rectal fecal impaction who underwent treatment with the new defecator at Deyang People's Hospital between July 2020 and April 2023 were retrospectively analyzed.The defecator comprises three components: a head, a spiral rod, and a handle, constructed from disposable stainless steel wire. The treatment procedure involves the following steps: The patient assumes a flexed, supine position on their left side with their buttocks slightly protruding from the bed's edge. A transparent sealing bag is affixed to the buttocks, centered around the anus. With gloved hands inserted through the bag's entrance, a cotton ball soaked in liquid paraffin lubricates the anal canal and the head of the defecator's spiral rod. The defecator is then slowly rotated and inserted into the anus, with careful attention to any changes in resistance. Once the spiral rod is fully inserted, the patient is instructed to inhale and defecate while the defecator is slowly withdrawn, carrying the dislodged fecal matter, and depositing it into the sealed bag. This operation is repeated 2 to 3 times, followed by the injection of either 100 ml of 36°C normal saline or 60 ml of liquid paraffin into the rectum. After a 5 to 8-minute wait, the patient assumes a squatting position to expel any remaining feces from the rectum. The study assessed the operation time, single treatment success rate, pain levels during treatment, and the occurrence of complications. Results: All 42 patients successfully underwent treatment with the new defecator device, achieving a single treatment success rate of 100%. The average operation time was 11.0 minutes (range: 9.0 to 13.3 minutes). During treatment, 20 cases (47.6%) reported moderate to severe anal pain, with 1 case (2.4%) experiencing anal fissure bleeding, and 6 cases (14.3%) reporting discomfort such as palpitations and sweating. No serious complications, including rectal perforation, were observed in any case. Conclusion: The new defecator device demonstrates ease of use and safety, making it a feasible option for treating acute rectal fecal impaction.

The burden of brain and central nervous system cancers in Asia from 1990 to 2019 and its predicted level in the next twenty-five years

BackgroundPrimary brain and central nervous system cancer (collectively called CNS cancers) cause a significant burden to society. The purpose of this study was to evaluate the trends in the burden of CNS cancers from 1990 to 2019 and to predict the incidence and mortality rates and the corresponding numbers for the next 25 years to help countries to understand the trends in its incidence and mortality, and to make better adjustments or formulation of policies and allocation of resources thereby reducing the burden of the disease.MethodsThe 2019 Global Burden of Disease Study provided incidence rates, death rates, and disability-adjusted life year (DALY) data in Asia from 1990 to 2019. To reflect the trends in the age-standardized incidence, mortality, and DALY rates, the estimated annual percentage change (EAPC) was determined. The Bayesian age-period cohort (BAPC) model was employed to predict the burden of CNS cancers in the next 25 years.ResultsThe incidence, death, and DALY rates of CNS cancers all increased from 1990 to 2019. The age-standardized incidence rate (ASIR) for CNS cancers increased from 9.89/100,000 in 1990 to 12.14/100,000 in 2019, with an EAPC of 0.69 (95% confidence interval (CI): 0.65, 0.73). The ASDR and the age-standardized DALY rate both decreased, with EAPCs of − 0.08 and − 0.52, respectively. Before 2005, the age-standardized DALY rate in East Asia was much greater in females than in males, while in Central Asia, the age-standardized death and DALY rates in males both increased sharply after 2000. In contrast to 1990, the caseload increased for the 55–70 years age group. The number of deaths decreased sharply among individuals aged younger than 20 years, especially in East Asia, accounting for only 5.41% of all deaths. The age group with the highest mortality rate was > 60 years, especially in Japan. The ASIR will continue to increase in Asia from 2020 to 2044, and the ASDR will gradually diminish. The incidence and number of deaths from CNS cancers in Asia are expected to increase over the next 25 years, especially among females.ConclusionsThe study identified an increasing trend in morbidity, mortality and disability-adjusted life-years (DALYs), with differences in age-standardized morbidity rates for different population groups. In addition, it is noteworthy that the burden of disease (as measured by disability-adjusted life-years (DALYs)) is higher among women in Central Asia compared with other regions. ASIR will continue to increase over the next 25 years, with the increase in female cases and mortality expected to be more pronounced. This may need to be further substantiated by additional research, on the basis of which health authorities and policymakers can better utilize limited resources and develop appropriate policies and preventive measures.

Phase-locked states in a spiking neural network model with a context-dependent connectivity

The investigation of nonlinear processes in brain systems based on the oscillatory-wave approach is currently one of the most consequential domains of researching signal generation and processing mechanisms in the brain. These investigations may offer insights into various phenomena, such as the mechanism of associative memory, based on network models of biologically relevant neurons. A neural network architecture is proposed in this paper to solve applied problems, such as signal filtering, processing, and recognition of information images. Mechanisms for incomplete fragments were implemented, enabling the extraction and complete restoration of objects from memory. Each neuron in this neural network comprises a Hodgkin–Huxley biophysical model with a Mainen modification, the dynamics of which most plausibly reproduce the processes in the neural cells of the brain. In the research on individual neurons, a constant external current with varying amplitudes was applied. The study determined the average periods of self-oscillations and identified parameter values for the Andronov–Hopf bifurcation. In particular, a stable limit cycle is created and destroyed depending on different scenarios when the bias current is increased or decreased. A stable limit cycle arises via the Andronov–Hopf bifurcation and is terminated via the saddle-node bifurcation on the cycle. The study identified parameter regions whereby two neurons with excitatory and inhibitory synaptic connections synchronize. The neurons were all in self-oscillating mode and exhibited a stable limit cycle in the phase space. A three-layer neural network was constructed, comprising of a reference neuron, sensory, control, and interneurons. The control and intermediate layer connections are arranged based on the Hebbian learning rule. Areas of excitation for various types of neurons were found. Experiments were conducted using the neural network architecture to distinguish binary information patterns encoded through signal phase. Excitatory and inhibitory synaptic connections were employed to encode the images stored in memory. The dynamic patterns are determined through the in-phase or anti-phase mode of phase locking, i.e., phase synchronization relative to the global rhythm. Before reaching the output layer of neurons, the signals are summed on the interneuron layer with the signal of the reference neuron, resulting in the filtering out of a certain information segment (in-phase or anti-phase). The network accurately recognized the patterns after parameter adjustments were made. Areas of neuron phase synchronization were discovered, enabling control of network activity modes. The confirmation of the viability of phase capture and pattern recognition modes using Hodgkin–Huxley–Mainen neurons was achieved. In total, as a result of the implementation of the spike neural network modeling project: 1) two-parameter diagrams of regions of neuronal excitation in various modes are calculated; 2) the effect of excitatory and inhibitory coupling in synaptic currents is used to represent the input signal; 3) an abstract mathematical algorithm for calculating the Hebbian matrix has been transferred to the implementation of synaptic currents between layers of neurons; 4) the effect of phase clusters is used to represent the output pattern; 5) the neurons’ topology in the visual-cerebral department served as a working model for recognizing graphic images through the Hopfield network on a spike neural network, using the Hebbian rule.

Prediction of Methyl Orange (MO) Toxicity and Minimizing Its Pollution in Aquatic Environment by Activated Carbon Adsorption

Minimizing environmental pollution is an essential work of the official and scientific communities around the world, especially in water systems. In water, soluble dye works as a blockage in photosynthesis process because of its toxicity. One of these highly applicable dyes in industry is Methyl Orange (MO), documented with more than 10% released to water. Here, a new Iraqi try of converting environmental and health problems to solutions with high quantification was as done by using face tissue (Kleenex) as a carbon source. Primary in Silico testing of this anionic dye (Methyl Orange) was done based on online website confirmed MO dye is unsafe in several toxicological determinations such as foetus health (during pregnancy). Also, it is permeable material to skin, Blood- Brain system (BBB), and Human Colon Carcinoma cell line (CaCO2) compatible with Human Intestinal absorption (74.166%). In experimental section, low quality of face tissue (Kleenex) was subject to a high acidic medium (concentrated sulphuric acid), followed by addition of sodium carbonate to .increase activation of based carbon material with more structural pores yielding high removal efficiency and adsorption capacity ranged (88-98)% and (88-98) mg/g respectively. Qualitative and quantitative evaluations were based upon choosing two wavelengths in ultraviolet (272 nm) and visible (464 nm) regions. In this work, two removal steps were performed with the same adsorbent companied by multiple UV-Vis spectroscopic evaluation of several tested sections. Reviewing of published papers in MO removal presents the extraordinary performance of this prepared material towards using it as an excellent adsorbent of toxic material in aqueous solution.

Evaluating functional brain organization in individuals and identifying contributions to network overlap

Abstract Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting-state networks can be derived using high-quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that overlap between 2-network pairs is indicative of coupling. These results suggest that regions of network overlap concurrently process information from both contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.

Complexity and 1/f slope jointly reflect brain states

Characterization of brain states is essential for understanding its functioning in the absence of external stimuli. Brain states differ on their balance between excitation and inhibition, and on the diversity of their activity patterns. These can be respectively indexed by 1/f slope and Lempel–Ziv complexity (LZc). However, whether and how these two brain state properties relate remain elusive. Here we analyzed the relation between 1/f slope and LZc with two in-silico approaches and in both rat EEG and monkey ECoG data. We contrasted resting state with propofol anesthesia, which directly modulates the excitation-inhibition balance. We found convergent results among simulated and empirical data, showing a strong, inverse and non trivial monotonic relation between 1/f slope and complexity, consistent at both ECoG and EEG scales. We hypothesize that differentially entropic regimes could underlie the link between the excitation-inhibition balance and the vastness of the repertoire of brain systems.

The neural circuits and molecular mechanisms underlying fear dysregulation in posttraumatic stress disorder.

Post-traumatic stress disorder (PTSD) is a stress-associated complex and debilitating psychiatric disorder due to an imbalance of neurotransmitters in response to traumatic events or fear. PTSD is characterized by re-experiencing, avoidance behavior, hyperarousal, negative emotions, insomnia, personality changes, and memory problems following exposure to severe trauma. However, the biological mechanisms and symptomatology underlying this disorder are still largely unknown or poorly understood. Considerable evidence shows that PTSD results from a dysfunction in highly conserved brain systems involved in regulating stress, anxiety, fear, and reward circuitry. This review provides a contemporary update about PTSD, including new data from the clinical and preclinical literature on stress, PTSD, and fear memory consolidation and extinction processes. First, we present an overview of well-established laboratory models of PTSD and discuss their clinical translational value for finding various treatments for PTSD. We then highlight the research progress on the neural circuits of fear and extinction-related behavior, including the prefrontal cortex, hippocampus, and amygdala. We further describe different molecular mechanisms, including GABAergic, glutamatergic, cholinergic, and neurotropic signaling, responsible for the structural and functional changes during fear acquisition and fear extinction processes in PTSD.

Neurobiological basis of reinforcement-based decision making in adults with ADHD treated with lisdexamfetamine dimesylate: Preliminary findings and implications for mechanisms influencing clinical improvement

BackgroundADHD is often described as a disorder of altered reward sensitivity, yet few studies have examined the extent to which: (i) treatments for ADHD impact reward-related mechanisms; and (ii) changes in the reward system are associated with clinical improvement. This study addresses these issues - examining the extent to which clinical improvement following lisdexamfetamine (LDX) treatment is associated with changes in brain reward system activation. MethodsTwenty adults (M = 11, 55%, F = 9, 45%), ages 19–52 (M = 33.9, SD = 10.0) with ADHD participated in a randomized cross-over study with lisdexamfetamine (LDX) and placebo (PB). Changes in brain activation were assessed during functional magnetic resonance (fMRI) scans: after receiving 3–5 weeks of treatment with LDX and 3–5 weeks of no drug/PB. fMRI contrasts were derived from the passive-avoidance (PA) learning task, which assessed reward-related learning using computational variables. We analyzed the following conditions: the Choice-Phase, modulated by the expected value (EV; i.e., object-choose and object-reject), and the Feedback-Phase, modulated by the prediction error (PE; i.e., reward and punish). Clinical symptom severity was assessed via interview with the ADHD-Rating Scale (ADHD-RS-IV). To address the primary objective, we performed group-level mass-univariate regression analyses between LDX and PB of percent change of the ADHD-RS total scores and the four contrast images under the Choice- and Feedback-conditions. Significance was set at a whole-brain voxel-wise threshold of p < 0.05 with family-wise error (FWE) correction and an extent (cluster) threshold of 50 contiguous voxels. ResultsImprovement in ADHD symptoms with LDX was accompanied by significantly increased activation in a series of brain regions previously implicated in reinforcement processing in the choice and feedback conditions (e.g., left caudate and putamen, right orbitofrontal cortex, left middle frontal, superior frontal, and precentral gyri). ConclusionsThese findings, while preliminary, are the first to show that ADHD symptom improvement with stimulant treatment is associated with increased responsiveness of brain systems engaged in reward processing. Results support the hypothesis that LDX treatment may restore balance to dysfunction (e.g., hypoactivation) within the brain reward circuitry in adults with ADHD.Trial RegistrationClinicaltrials.gov Identifier: NCT01924429.

Brain connectivity and academic skills in English learners.

English learners (ELs) are a rapidly growing population in schools in the United States with limited experience and proficiency in English. To better understand the path for EL's academic success in school, it is important to understand how EL's brain systems are used for academic learning in English. We studied, in a cohort of Hispanic middle-schoolers (n = 45, 22F) with limited English proficiency and a wide range of reading and math abilities, brain network properties related to academic abilities. We applied a method for localizing brain regions of interest (ROIs) that are group-constrained, yet individually specific, to test how resting state functional connectivity between regions that are important for academic learning (reading, math, and cognitive control regions) are related to academic abilities. ROIs were selected from task localizers probing reading and math skills in the same participants. We found that connectivity across all ROIs, as well as connectivity of just the cognitive control ROIs, were positively related to measures of reading skills but not math skills. This work suggests that cognitive control brain systems have a central role for reading in ELs. Our results also indicate that an individualized approach for localizing brain function may clarify brain-behavior relationships.

Optimizing the Local Charge of Graphene via Iron Doping to Promote the Adsorption of Formaldehyde Molecules—A Density Functional Theory Study

Formaldehyde is a colorless, pungent, and highly volatile toxic gas known for its detrimental effects on the brain, respiratory, and nervous systems. The adsorption method emerges as an effective approach for detecting and mitigating formaldehyde gas, with the adsorption material serving as its core component. Graphene, a two-dimensional nanomaterial with remarkable properties, exhibits enhanced adsorption capabilities when subjected to metal doping, which alters its local geometric and charge characteristics. In this investigation, theoretical first-principles density functional technology was employed to optimize the efficiency of Fe-doped graphene in formaldehyde adsorption. The calculated adsorption bond length and energy were used to determine the type of adsorption. Then, the calculated Bader charge, density of states (partial density of states), and differential valence charge density distribution were used to analyze the electron transfer process before and after adsorption. Finally, the theoretical optical properties analysis result was applied to analyze the potential of Fe-doped graphene for formaldehyde detection. The findings indicated that Fe-doped graphene constitutes a viable and stable doping structure, accompanied by a notable shift in valence charge distribution around the doped iron atom. This altered charge distribution facilitated the chemical adsorption process, leading to reduced adsorption spacing and increased adsorption energy. Throughout the chemical adsorption process, there was evident charge transfer between carbon (formaldehyde) and iron atoms, as well as between oxygen (formaldehyde) and iron atoms. The formation of adsorption bonds primarily involved the p-orbital electrons of carbon and oxygen atoms, along with the p- and d-orbital electrons of iron atoms. Ultimately, the Fe-doped graphene material exhibited promising applications in the realm of formaldehyde molecular detection, marked by significant theoretical disparities in optical properties before and after the adsorption process.