Cognitive Tasks Research Articles

Cognitive and affective theory of mind in young and elderly patients with multiple sclerosis.

Theory of mind (ToM) deficits have been reported in persons with multiple sclerosis (pwMS). However, most studies have used pictures or written scenarios as stimuli without distinguishing between cognitive and affective ToM, and no studies have investigated older pwMS. We recruited 13 young healthy controls (HC), 14 young pwMS, 14 elderly HC and 15 elderly pwMS. ToM was measured using an adaptation of the Conversations and Insinuations task (Ouellet etal., J. Int. Neuropsychol. Soc., 16, 2010, 287). In this ecological video-based task, participants watch four 2-minute videos of social interactions, which are interrupted by multiple choice questions about either the emotional state (affective ToM) or the intention (cognitive ToM) of the characters. They also underwent a short neuropsychological battery including cognitive, executive and social cognition tasks and questionnaires. We observed a significant interaction between the ToM conditions and the groups regarding ToM performance. Elderly pwMS scored significantly lower than elderly HC and young pwMS in cognitive ToM, but not in affective ToM. They also showed the largest discrepancy between their cognitive and affective ToM. Young pwMS showed relatively preserved ToM in both conditions. Both cognitive and affective ToM correlated with global cognition and executive abilities, but not with social cognitive measures (emotion recognition, real-life empathy). This study suggests that decline in cognitive ToM might be accentuated by advancing age in pwMS. These impairments are most likely underlied by cognitive and executive difficulties, but not by core social cognitive impairments. Future studies should investigate the real-life impacts of ToM impairments in pwMS.

Cognitive and affective theory of mind in young and elderly patients with multiple sclerosis.

Theory of mind (ToM) deficits have been reported in persons with multiple sclerosis (pwMS). However, most studies have used pictures or written scenarios as stimuli without distinguishing between cognitive and affective ToM, and no studies have investigated older pwMS. We recruited 13 young healthy controls (HC), 14 young pwMS, 14 elderly HC and 15 elderly pwMS. ToM was measured using an adaptation of the Conversations and Insinuations task (Ouellet etal., J. Int. Neuropsychol. Soc., 16, 2010, 287). In this ecological video-based task, participants watch four 2-minute videos of social interactions, which are interrupted by multiple choice questions about either the emotional state (affective ToM) or the intention (cognitive ToM) of the characters. They also underwent a short neuropsychological battery including cognitive, executive and social cognition tasks and questionnaires. We observed a significant interaction between the ToM conditions and the groups regarding ToM performance. Elderly pwMS scored significantly lower than elderly HC and young pwMS in cognitive ToM, but not in affective ToM. They also showed the largest discrepancy between their cognitive and affective ToM. Young pwMS showed relatively preserved ToM in both conditions. Both cognitive and affective ToM correlated with global cognition and executive abilities, but not with social cognitive measures (emotion recognition, real-life empathy). This study suggests that decline in cognitive ToM might be accentuated by advancing age in pwMS. These impairments are most likely underlied by cognitive and executive difficulties, but not by core social cognitive impairments. Future studies should investigate the real-life impacts of ToM impairments in pwMS.

Association between caregiver and infant visual neurocognition

Previous work has shown that caregiver attention shapes visual cognition in infants through dyadic interactions. Is this association measurable when visual cognition is objectively measured in caregivers and infants using comparable experimental paradigms? In the current study, we presented infants (N = 86) and caregivers (N = 78) with age-specific variants of the same preferential looking visual cognition task to investigate whether caregiver visual cognition was associated with their infants’ visual cognition. In each trial of the task, two side-by-side flashing displays of coloured shapes were presented. On the ‘unchanging’ side, the colours of the shapes remained the same. On the ‘changing’ side, the colour of one shape changed after each flash. Load was varied by changing the number of shapes across trials (low, medium, and high loads). We extracted looking dynamics using video recordings and brain function using functional near-infrared spectroscopy as both infants and caregivers engaged with the task. Change preference (CP) score, which represented the amount of time spent looking at the changing side divided by the total looking duration, showed a load-dependent modulation for both infants and caregivers. Both groups showed the highest CP scores at the low load. Further, higher caregiver CP scores was associated with higher infant CP scores at the low load. Both infants and caregivers engaged canonical regions of the fronto-parietal network involved in visual cognition. Critically, higher caregiver CP scores were associated with greater activation in the left superior parietal lobule in younger infants, a region involved in allocating visuo-spatial attention and working memory maintenance. Further, there was spatial overlap between performance-dependent regions in the right parietal cortex in caregivers and younger infants. Our findings provide first evidence of a heritability-related visual neurocognitive association between caregivers and their children in the first year of life.

Effect of transcranial direct current stimulation with concurrent cognitive performance targeting posterior parietal cortex vs prefrontal cortex on working memory in schizophrenia: a randomized clinical trial

Working memory deficits are linked to irregularities in the dorsolateral prefrontal cortex (DLPFC) and the posterior parietal cortex (PPC) in schizophrenia, effective intervention strategies are lacking. We evaluated the differential efficacy and underlying neuromechanisms of targeting transcranial direct current stimulation (tDCS) at the DLPFC and the PPC with concurrent cognitive performance for working memory in schizophrenia. In a randomized and double-blind clinical trial, sixty clinically stable schizophrenic patients with below-average working memory were randomly assigned to active DLPFC, active PPC, and sham tDCS groups. Two sessions of tDCS during N-back task were delivered daily for five days. The primary outcome was changes in spatial span test scores from baseline to week 1. The secondary outcomes included changes in scores of color delay-estimation task, other cognitive tasks, and mismatch negativity (biomarker of N-methyl-d-aspartate receptor functioning). Compared with the active DLPFC group, the active PPC group demonstrated significantly greater improvement in spatial span test scores (p = 0.008, d = 0.94) and an augmentation in color delay-estimation task capacity at week 1; the latter sustained to week 2. Compared with the sham tDCS group, the active PPC group did not show a significant improvement in spatial span test scores at week 1 and 2; however, significant enhancement was observed in their color delay-estimation task capacity at week 2. Additionally, mismatch negativity amplitude was enhanced, and changes in theta band measures were positively correlated with working memory improvement in the active PPC group, while no such correlations were observed in the active DLPFC group or the sham tDCS group. Our results suggest that tDCS targeting the PPC relative to the DLPFC during concurrent cognitive performance may improve working memory in schizophrenia, meriting further investigation. The improvement in working memory appears to be linked to enhanced N-methyl-d-aspartate receptor functioning.

Effect of transcranial direct current stimulation with concurrent cognitive performance targeting posterior parietal cortex vs prefrontal cortex on working memory in schizophrenia: a randomized clinical trial

Working memory deficits are linked to irregularities in the dorsolateral prefrontal cortex (DLPFC) and the posterior parietal cortex (PPC) in schizophrenia, effective intervention strategies are lacking. We evaluated the differential efficacy and underlying neuromechanisms of targeting transcranial direct current stimulation (tDCS) at the DLPFC and the PPC with concurrent cognitive performance for working memory in schizophrenia. In a randomized and double-blind clinical trial, sixty clinically stable schizophrenic patients with below-average working memory were randomly assigned to active DLPFC, active PPC, and sham tDCS groups. Two sessions of tDCS during N-back task were delivered daily for five days. The primary outcome was changes in spatial span test scores from baseline to week 1. The secondary outcomes included changes in scores of color delay-estimation task, other cognitive tasks, and mismatch negativity (biomarker of N-methyl-d-aspartate receptor functioning). Compared with the active DLPFC group, the active PPC group demonstrated significantly greater improvement in spatial span test scores (p = 0.008, d = 0.94) and an augmentation in color delay-estimation task capacity at week 1; the latter sustained to week 2. Compared with the sham tDCS group, the active PPC group did not show a significant improvement in spatial span test scores at week 1 and 2; however, significant enhancement was observed in their color delay-estimation task capacity at week 2. Additionally, mismatch negativity amplitude was enhanced, and changes in theta band measures were positively correlated with working memory improvement in the active PPC group, while no such correlations were observed in the active DLPFC group or the sham tDCS group. Our results suggest that tDCS targeting the PPC relative to the DLPFC during concurrent cognitive performance may improve working memory in schizophrenia, meriting further investigation. The improvement in working memory appears to be linked to enhanced N-methyl-d-aspartate receptor functioning.

Neural activity during inhibitory control predicts suicidal ideation with machine learning

Suicide is a leading cause of death in the US and worldwide. Current strategies for preventing suicide are often focused on the identification and treatment of risk factors, especially suicidal ideation (SI). Hence, developing data-driven biomarkers of SI may be key for suicide prevention and intervention. Prior attempts at biomarker-based prediction models for SI have primarily used expensive neuroimaging technologies, yet clinically scalable and affordable biomarkers remain elusive. Here, we investigated the classification of SI using machine learning (ML) on a dataset of 76 subjects with and without SI(+/−) (n = 38 each), who completed a neuro-cognitive assessment session synchronized with electroencephalography (EEG). SI+/− groups were matched for age, sex, and mental health symptoms of depression and anxiety. EEG was recorded at rest and while subjects engaged in four cognitive tasks of inhibitory control, interference processing, working memory, and emotion bias. We parsed EEG signals in physiologically relevant theta (4-8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) frequencies and performed cortical source imaging on the neural signals. These data served as SI predictors in ML models. The best ML model was obtained for beta band power during the inhibitory control (IC) task, demonstrating high sensitivity (89%), specificity (98%). Shapley explainer plots further showed top neural predictors as feedback-related power in the visual and posterior default mode networks and response-related power in the ventral attention, fronto-parietal, and sensory-motor networks. We further tested the external validity of the model in an independent clinically depressed sample (n = 35, 12 SI+) that engaged in an adaptive test version of the IC task, demonstrating 50% sensitivity and 61% specificity in this sample. Overall, the study suggests a promising, scalable EEG-based biomarker approach to predict SI that may serve as a target for risk identification and intervention.

A quantitative comparison of atlas parcellations on the human superior temporal sulcus

The superior temporal sulcus (STS) has a functional topography that has been difficult to characterize through traditional approaches. Automated atlas parcellations may be one solution while also being beneficial for both dimensional reduction and standardizing regions of interest, but they yield very different boundary definitions along the STS. Here we evaluate how well machine learning classifiers can correctly identify six social cognitive tasks from STS activation patterns dimensionally reduced using four popular atlases (Glasser et al., 2016; Gordon et al., 2016; Power et al., 2011 as projected onto the surface by Arslan et al., 2018; Schaefer et al., 2018). Functional data was summarized within each STS parcel in one of four ways, then subjected to leave-one-subject-out cross-validation SVM classification. We found that the classifiers could readily label conditions when data was parcellated using any of the four atlases, evidence that dimensional reduction to parcels did not compromise functional fingerprints. Mean activation for the social conditions was the most effective metric for classification in the right STS, whereas all the metrics classified equally well in the left STS. Interestingly, even atlases constructed from random parcellation schemes (null atlases) classified the conditions with high accuracy. We therefore conclude that the complex activation maps on the STS are readily differentiated at a coarse granular level, despite a strict topography having not yet been identified. Further work is required to identify what features have greatest potential to improve the utility of atlases in replacing functional localizers.

Effects of 12 weeks of head-down strong abdominal breathing on motor and cognitive performance during dual-tasking in patients with chronic obstructive pulmonary disease: Study protocol for a randomised controlled trial

ObjectiveHead-down training can affect behavioural and neurocognitive control while performing dual tasks (DT). Breathing training improves motor and cognitive performance in patients with chronic obstructive pulmonary disease (COPD). As a neurorehabilitation tool, functional near-infrared spectroscopy (fNIRS) has been demonstrated to be an effective method for detecting changes in brain activation during motor recovery, as well as monitoring patients' long-term progress during DT in motor and cognitive performance. However, no studies have examined the combined effect of head-down position and breathing exercises on motor and cognitive performance during DT. This study will employ a novel intervention involving head-down strong abdominal breathing training to investigate its effects on motor and cognitive performance during DT in patients with COPD aiming to inform future training modalities in the community and at home. MethodsWe will recruit participants from Anqing, China, through community announcements, bulletin board postings, WeChat, and offline visits and screen 72 patients with stable COPD, classified as Global Initiative for Chronic Obstructive Lung Disease (GOLD) I-II, by pulmonologists at the university hospital. All participants will be randomly assigned to the head-down strong abdominal breathing (tilt angle 0–30° on the inversion apparatus, respiratory rate 20–30 breaths/min), head-down training, and strong abdominal breathing training groups in a 1:1:1 ratio. The intervention will last 12 weeks, with sessions performed thrice weekly for 1 h. ResultsThe primary outcomes will be motor-cognitive DT time, dual-task effects, correct responses to cognitive tasks, and gait characteristics assessed at baseline, 6 and 12 weeks of intervention. The patient’s dorsolateral prefrontal cortex (PFC) will also be stimulated with fNIRS at wavelengths of 730 and 850 nm, with a sampling rate of 11 Hz, to record oxy-haemoglobin (oxy-Hb), deoxy-haemoglobin (deoxy-Hb), and total oxyhaemoglobin (total-Hb). Secondary outcomes will include pre- and post-intervention scales for dyspnoea, overall cognitive function, balance, and anxiety and depression. ConclusionAlterations in the PFC involved in attentional control, planning, and decision-making may partially explain cognitive and motor deficits (such as impaired balance and slower walking speed) in patients with COPD. This study may help to understand the effects of head-down strong abdominal breathing training on cognitive and motor performance under DT in patients with COPD and compare it with head-down training and breathing training alone. It may also help to determine whether it is a simple and effective form of exercise at home and in the community.

The influence of multiple cognitive workload levels of an exergame on dorsal attention network connectivity at the source level

This study investigates how adding a cognitive task on a balance board (exergame) affects connectivity in the dorsal attention network (DAN) during an exergame task. Healthy young adults performed a soccer ball-moving task by tilting a balance board with their feet while their brain activity was measured using electroencephalography (EEG). In this exergame, the speed of obstacles in front of the goal manipulated the cognitive workload. Higher speed means a higher cognitive workload. The study found significant changes in functional connectivity within DAN regions, specifically in the alpha band. During the shift from easy to medium cognitive task, we observed a significant increase in connectivity (p= 0.0436) between the right inferior temporal (ITG R) and the Left middle temporal (MTG L). During the transition from easy to hard cognitive tasks, strengthened interactions (p= 0.0324) between inferior temporal (ITG) and parsopercularis (pOPPER) were found. This suggests that the proposed balanceboard-based exergame enhances the functionality of specific brain regions, such as ITG and MTG regions, and improves connectivity in the frontal cortex. We also found a correlation between brain activity and performance data, highlighting that increased cognitive workload resulted in decreased performance and heightened frontal alpha activity. These findings align with research suggesting that adding cognitive games to physical activity-based tasks in rehabilitation programs can boost brain activity, resulting in improved decision-making and visual processing skills. This information can help clinicians tailor rehabilitation methods that target specific brain regions.

Contributions of brain regions to machine learning-based classifications of attention deficit hyperactivity disorder (ADHD) utilizing EEG signals

Objective The study presented focuses on the creation of a machine learning (ML) model that uses electrophysiological (EEG) data to identify kids with attention deficit hyperactivity disorder (ADHD) from healthy controls. The EEG signals are acquired during cognitive tasks to distinguish children with ADHD from their counterparts. Methodology The EEG data recorded in cognitive exercises was filtered using low pass Bessel filter and notch filters to remove artifacts, by the data set owners. To identify unique EEG patterns, we used many well-known classifiers, including Naïve Bayes (NB), Random Forest, Decision Tree (DT), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost and Linear Discriminant Analysis (LDA), to identify distinct EEG patterns. Input features comprised EEG data from nineteen channels, individually and in combination. Findings Study indicates that EEG-based categorization can differentiate between individuals with ADHD and healthy individuals with accuracy of 84%. The RF classifier achieved a maximum accuracy of 0.84 when particular region combinations were used. Evaluation of classification performance utilizing hemisphere-specific EEG data yielded promising outcomes, particularly in the right hemisphere channels. Novelty The study goes beyond traditional methodologies by investigating the effect of regional data on categorization results. The contributions of various brain regions to these classifications are being extensively researched. Understanding the role of different brain regions in ADHD can lead to better diagnosis and treatment options for individuals with ADHD. The study of categorization ability, utilizing EEG data specific to each hemisphere, particularly channels in the right hemisphere region, provides further granularity to the findings.

Contributions of brain regions to machine learning-based classifications of attention deficit hyperactivity disorder (ADHD) utilizing EEG signals

Objective The study presented focuses on the creation of a machine learning (ML) model that uses electrophysiological (EEG) data to identify kids with attention deficit hyperactivity disorder (ADHD) from healthy controls. The EEG signals are acquired during cognitive tasks to distinguish children with ADHD from their counterparts. Methodology The EEG data recorded in cognitive exercises was filtered using low pass Bessel filter and notch filters to remove artifacts, by the data set owners. To identify unique EEG patterns, we used many well-known classifiers, including Naïve Bayes (NB), Random Forest, Decision Tree (DT), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost and Linear Discriminant Analysis (LDA), to identify distinct EEG patterns. Input features comprised EEG data from nineteen channels, individually and in combination. Findings Study indicates that EEG-based categorization can differentiate between individuals with ADHD and healthy individuals with accuracy of 84%. The RF classifier achieved a maximum accuracy of 0.84 when particular region combinations were used. Evaluation of classification performance utilizing hemisphere-specific EEG data yielded promising outcomes, particularly in the right hemisphere channels. Novelty The study goes beyond traditional methodologies by investigating the effect of regional data on categorization results. The contributions of various brain regions to these classifications are being extensively researched. Understanding the role of different brain regions in ADHD can lead to better diagnosis and treatment options for individuals with ADHD. The study of categorization ability, utilizing EEG data specific to each hemisphere, particularly channels in the right hemisphere region, provides further granularity to the findings.

Parkinson’s-linked LRRK2-G2019S derails AMPAR trafficking, mobility, and composition in striatum with cell-type and subunit specificity

Parkinson's disease (PD) is a multifactorial disease that affects multiple brain systems and circuits. While defined by motor symptoms caused by degeneration of brainstem dopamine neurons, debilitating non-motor abnormalities in fronto-striatal-based cognitive function are common, appear early, and are initially independent of dopamine. Young adult mice expressing the PD-associated G2019S missense mutation in Lrrk2 also exhibit deficits in fronto-striatal-based cognitive tasks. In mice and humans, cognitive functions require dynamic adjustments in glutamatergic synapse strength through cell-surface trafficking of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid-type glutamate receptors (AMPARs), but it is unknown how LRRK2 mutation impacts dynamic features of AMPAR trafficking in striatal projection neurons (SPNs). Here, we used Lrrk2G2019S knockin mice to show that surface AMPAR subunit stoichiometry is altered biochemically and functionally in mutant SPNs in dorsomedial striatum to favor the incorporation of GluA1 over GluA2. GluA1-containing AMPARs were resistant to internalization from the cell surface, leaving an excessive accumulation of GluA1 on the surface within and outside synapses. This negatively impacted trafficking dynamics that normally support synapse strengthening, as GluA1-containing AMPARs failed to increase at synapses in response to a potentiating stimulus and showed significantly reduced surface mobility. Surface GluA2-containing AMPARs were expressed at normal levels in synapses, indicating subunit-selective impairment. Abnormal surface accumulation of GluA1 was independent of PKA activity and was limited to D1R SPNs. Since LRRK2 mutation is thought to be part of a common PD pathogenic pathway, our data suggest that sustained, striatal cell-type specific changes in AMPAR composition and trafficking contribute to cognitive or other impairments associated with PD.

Parkinson’s-linked LRRK2-G2019S derails AMPAR trafficking, mobility, and composition in striatum with cell-type and subunit specificity

Parkinson's disease (PD) is a multifactorial disease that affects multiple brain systems and circuits. While defined by motor symptoms caused by degeneration of brainstem dopamine neurons, debilitating non-motor abnormalities in fronto-striatal-based cognitive function are common, appear early, and are initially independent of dopamine. Young adult mice expressing the PD-associated G2019S missense mutation in Lrrk2 also exhibit deficits in fronto-striatal-based cognitive tasks. In mice and humans, cognitive functions require dynamic adjustments in glutamatergic synapse strength through cell-surface trafficking of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid-type glutamate receptors (AMPARs), but it is unknown how LRRK2 mutation impacts dynamic features of AMPAR trafficking in striatal projection neurons (SPNs). Here, we used Lrrk2G2019S knockin mice to show that surface AMPAR subunit stoichiometry is altered biochemically and functionally in mutant SPNs in dorsomedial striatum to favor the incorporation of GluA1 over GluA2. GluA1-containing AMPARs were resistant to internalization from the cell surface, leaving an excessive accumulation of GluA1 on the surface within and outside synapses. This negatively impacted trafficking dynamics that normally support synapse strengthening, as GluA1-containing AMPARs failed to increase at synapses in response to a potentiating stimulus and showed significantly reduced surface mobility. Surface GluA2-containing AMPARs were expressed at normal levels in synapses, indicating subunit-selective impairment. Abnormal surface accumulation of GluA1 was independent of PKA activity and was limited to D1R SPNs. Since LRRK2 mutation is thought to be part of a common PD pathogenic pathway, our data suggest that sustained, striatal cell-type specific changes in AMPAR composition and trafficking contribute to cognitive or other impairments associated with PD.

A measure of reliability convergence to select and optimize cognitive tasks for individual differences research

Surging interest in individual differences has faced setbacks in light of recent replication crises in psychology, for example in brain-wide association studies exploring brain-behavior correlations. A crucial component of replicability for individual differences studies, which is often assumed but not directly tested, is the reliability of the measures we use. Here, we evaluate the reliability of different cognitive tasks on a dataset with over 250 participants, who each completed a multi-day task battery. We show how reliability improves as a function of number of trials, and describe the convergence of the reliability curves for the different tasks, allowing us to score tasks according to their suitability for studies of individual differences. We further show the effect on reliability of measuring over multiple time points, with tasks assessing different cognitive domains being differentially affected. Data collected over more than one session may be required to achieve trait-like stability.

Gait Analysis and Magnetic Resonance Imaging Characteristics in Patients with Isolated Rapid Eye Movement Sleep Behavior Disorder.

Isolated rapid eye movement sleep behavioral disorder (iRBD) can precede neurodegenerative diseases. There is an urgent need for biomarkers to aid early intervention and neuroprotection. The aim is to assess quantitative motor, cognitive, and brain magnetic resonance imaging (MRI) characteristics in iRBD patients. Thirty-eight polysomnography-confirmed iRBD patients and 28 age- and sex-matched healthy controls underwent clinical, cognitive, and motor functional evaluations, along with brain MRI. Motor tasks included nine-hole peg test, five-times-sit-to-stand test, timed-up-and-go test, and 4-meter walking test with and without cognitive dual task. Quantitative spatiotemporal gait parameters were obtained using an optoelectronic system. Brain MRI analysis included functional connectivity (FC) of the main resting-state networks, gray matter (GM) volume using voxel-based morphometry, cortical thickness, and deep GM and brainstem volumes using FMRIB's Integrated Registration and Segmentation Tool and FreeSurfer. iRBD patients relative to healthy subjects exhibited a poorer performance during the nine-hole peg test and five-times-sit-to-stand test, and greater asymmetry of arm-swing amplitude and stride length variability during dual-task gait. Dual task significantly worsened the walking performance of iRBD patients more than healthy controls. iRBD patients exhibited nonmotor symptoms, and memory, abstract reasoning, and visuospatial deficits. iRBD patients exhibited decreased FC of pallidum and putamen within the basal ganglia network and occipital and temporal areas within the visuo-associative network, and a reduced volume of the supramarginal gyrus. Brain functional alterations correlated with gait changes. Subtle motor and nonmotor alterations were identified in iRBD patients, alongside brain structural and functional MRI changes. These findings may represent early signs of neurodegeneration and contribute to the development of predictive models for progression to parkinsonism. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Individual differences in sociocognitive traits in semi-free-ranging rhesus monkeys (Macaca mulatta).

Characterizing individual differences in cognition is crucial for understanding the evolution of cognition as well as to test the biological consequences of different cognitive traits. Here, we harnessed the strengths of a uniquely large, naturally-living primate population at the Cayo Santiago Biological Field Station to characterized individual differences in rhesus monkey performance across two social cognitive tasks. A total of n = 204 semi-free-ranging adult rhesus monkeys participated in a data collection procedure, where we aimed to test individuals on both tasks at two time-points that were one year apart. In the socioemotional responses task, we assessed monkeys' attention to conspecific photographs with neutral versus negative emotional expressions. We found that monkeys showed overall declines in interest in conspecific photographs with age, but relative increases in attention to threat stimuli specifically, and further that these responses exhibited long-term stability across repeated testing. In the gaze following task we assessed monkeys' propensity to co-orient with an experimenter. Here, we found no evidence for age-related change in responses, and responses showed only limited repeatability over time. Finally, we found some evidence for common individual variation for performance across the tasks: monkeys that showed greater interest in conspecific photographs were more likely to follow a human's gaze. These results show how studies of comparative cognitive development and aging can provide insights into the evolution of cognition, and identify core primate social cognitive traits that may be related across and within individuals.

A Hardware–Software Complex for Diagnostics of a Human Being’s Psychophysiological State during the Solution of Cognitive Tasks

A Hardware–Software Complex for Diagnostics of a Human Being’s Psychophysiological State during the Solution of Cognitive Tasks

Polycomb repressive complex 2 is critical for mouse cortical glutamatergic neuron development.

The Polycomb Repressive Complex 2 (PRC2) regulates corticogenesis, yet the consequences of mutations to this epigenetic modifier in the mature brain are poorly defined. Importantly, PRC2 core genes are haploinsufficient and causative of several human neurodevelopmental disorders. To address the role of PRC2 in mature cortical structure and function, we conditionally deleted the PRC2 gene Eed from the developing mouse dorsal telencephalon. Adult homozygotes displayed smaller forebrain structures. Single-nucleus transcriptomics revealed that glutamatergic neurons were particularly affected, exhibiting dysregulated gene expression profiles, accompanied by aberrations in neuronal morphology and connectivity. Remarkably, homozygous mice performed well on challenging cognitive tasks. In contrast, while heterozygous mice did not exhibit clear anatomical or behavioral differences, they displayed dysregulation of neuronal genes and altered neuronal morphology that was strikingly different from homozygous phenotypes. Collectively, these data reveal how alterations to PRC2 function shape the mature brain and reveal a dose-specific role for PRC2 in determining glutamatergic neuron identity.

Neurovascular coupling, functional connectivity, and cerebrovascular endothelial extracellular vesicles as biomarkers of mild cognitive impairment.

Mild cognitive impairment (MCI) is a prodromal stage of dementia. Understanding the mechanistic changes from healthy aging to MCI is critical for comprehending disease progression and enabling preventative intervention. Patients with MCI and age-matched controls (CN) were administered cognitive tasks during functional near-infrared spectroscopy (fNIRS) recording, and changes in plasma levels of extracellular vesicles (EVs) were assessed using small-particle flow cytometry. Neurovascular coupling (NVC) and functional connectivity (FC) were decreased in MCI compared to CN, prominently in the left-dorsolateral prefrontal cortex (LDLPFC). We observed an increased ratio of cerebrovascular endothelial EVs (CEEVs) to total endothelial EVs in patients with MCI compared to CN, correlating with structural MRI small vessel ischemic damage in MCI. LDLPFC NVC, CEEV ratio, and LDLPFC FC had the highest feature importance in the random Forest group classification. NVC, CEEVs, and FC predict MCI diagnosis, indicating their potential as markers for MCI cerebrovascular pathology. Neurovascular coupling (NVC) is impaired in mild cognitive impairment (MCI). Functional connectivity (FC) compensation mechanism is lost in MCI. Cerebrovascular endothelial extracellular vesicles (CEEVs) are increased in MCI. CEEV load strongly associates with cerebral small vessel ischemic lesions in MCI. NVC, CEEVs, and FC predict MCI diagnosis over demographic and comorbidity factors.

Mentalizing impairments and hypermentalizing bias in individuals with first-episode schizophrenia-spectrum disorder and at-risk mental state: the differential roles of neurocognition and social anxiety.

Mentalizing, or theory of mind (ToM), impairments and self-referential hypermentalizing bias are well-evident in schizophrenia. However, findings compared to individuals with at-risk mental states (ARMS) are inconsistent, and investigations into the relationship between social cognitive impairments and social anxiety in the two populations are scarce. This study aimed to examine and compare these deficits in first-episode schizophrenia-spectrum disorder (FES) and ARMS, and to explore potential specific associations with neurocognition and symptomatology. Forty patients with FES, 40 individuals with ARMS, and 40 healthy controls (HC) completed clinical assessments, a battery of neurocognitive tasks, and three social cognitive tasks. The comic strip and hinting tasks were used to measure non-verbal and verbal mentalizing abilities, and the gaze perception task was employed to assess self-referential hypermentalizing bias. FES and ARMS showed comparable mentalizing impairments and self-referential hypermentalizing bias compared to HC. However, only ambiguous self-referential gaze perception (SRGP) bias remained significantly different between three groups after controlling for covariates. Findings suggested that self-referential hypermentalizing bias could be a specific deficit and may be considered a potential behavioral indicator in early-stage and prodromal psychosis. Moreover, working memory and social anxiety were related to the social cognitive impairments in ARMS, whereas higher-order executive functions and positive symptoms were associated with the impairments in FES. The current study indicates the presence of stage-specific mechanisms of mentalizing impairments and self-referential hypermentalizing bias, providing insights into the importance of personalized interventions to improve specific neurocognitive domains, social cognition, and clinical outcomes for FES and ARMS.