Human Cognitive Functions Research Articles

CRISPR-Mediated Genetic Interventions for Augmenting Human Cognition and Bodily Function: A Transhumanist Exploration and A Recent Gene Editting Tool: CyDENT

CRISPR-Mediated Genetic Interventions for Augmenting Human Cognition and Bodily Function: A Transhumanist Exploration and A Recent Gene Editting Tool: CyDENT

Hyperbaric intervention ameliorates the negative effects of long-term high-altitude exposure on cognitive control capacity.

Hypoxia due to reduced partial pressure of oxygen from high-altitude exposure affects the cognitive function of high-altitude migrants. Executive function is an important component of human cognitive function, characterized by high oxygen consumption during activity, and its level can be measured using cognitive control capacity (CCC). In addition, there is evidence for the potential value of hyperbaric oxygen (HBO) interventions in improving cognitive decline on the plateau. Therefore, the objective of this study was to investigate the effect of long-term high-altitude exposure on CCC in high-altitude newcomers and whether hyperbaric oxygen intervention has an ameliorative effect. This study measured the magnitude of participants' CCC using a Backward Masking Majority Function Task (MFT-M). Study 1 was a controlled study of different altitude conditions, with 64 participants in the high-altitude newcomer group and 64 participants in the low-altitude resident group, each completing the MFT-M task once. Study 2 was a controlled HBO intervention study in which newcomers who had lived at a high altitude for 2years were randomly divided into the HBO group (n = 28) and control group (n = 28). 15 times hyperbaric oxygen interventions were performed in the HBO group. Subjects in both groups completed the MFT-M task once before and once after the intervention. Study 1 showed that CCC was significantly higher in the low-altitude resident group than in the high-altitude newcomer group (p = 0.031). Study 2 showed that the CCC in the HBO group was significantly higher after 15 hyperbaric interventions than before (p = 0.005), while there was no significant difference in the control group (p = 0.972). The HBO group had significantly higher correct task rates than the control group after the intervention (p = 0.001). This study confirms that long-term high-altitude exposure leads to impairment of CCC in high-altitude newcomers and that hyperbaric oxygen intervention is effective in improving CCC.

Environmental pollutants PM2.5, PM10, carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) impair human cognitive functions.

Environmental pollution is an emerging global public health problem across the world and causes serious threats to ecosystems, human health, and the planet. This study is designed to explore the impact of environmental pollution particulate matter PM2.5, PM10, carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) on cognitive functions in students from schools located in or away from air-polluted areas. In this study, two schools were selected: one was located near a traffic-polluted area (school #1), and the second was in an area away from the traffic-polluted area (school #2). In this study, a total of 300 students were recruited: 150 (75 male and 75 female) students from school #1 located in a traffic-polluted area, and 150 students (75 male and 75 female) from school #2 located away from a traffic polluted area. The overall average age of students was 13.53±1.20 years. The students were selected based on age, gender, health status, height, weight, BMI, ethnicity, and homogenous socio-economic and educational status. The pollutants PM2.5, PM10, CO, NO2, O3, and SO2 were recorded in the surrounding environment. The overall mean concentration of environmental pollutants in school #1 was 35.00±0.65 and in school #2 was 29.95±0.32. The levels of airborne particles were measured, and the cognitive functions were recorded using the Cambridge Neuropsychological Test Automated Battery (CANTAB). The students performed the cognitive functions tasks, including the attention switching task (AST), choice reaction time (CRT), and motor screening task (MOT). The results revealed that the AST-Mean 928.34±182.23 vs. 483.79±146.73 (p=0.001), AST-mean congruent 889.12±197.12 vs. 473.30±120.11 (p=0.001), AST-mean in-congruent 988.98±201.27 vs. 483.87±144.57 (p=0.001), CRT-Mean 721.36±251.72 vs. 418.17±89.71 (p=0.001), and MOT-Mean 995.07±394.37 vs. 526.03±57.83 (p=0.001) were significantly delayed among the students who studied in school located in the traffic polluted area compared to students who studied in school which was located away from the traffic-polluted area. Environmental pollution was significantly higher in motor vehicle-congested areas. Cognitive functions were impaired among the students who were studying in a school located in a polluted area. The results further revealed that the students studying in schools located in environmentally polluted areas have attention, thinking, and decision-making abilities related to cognitive function impairment.

Unsupervised Joint Domain Adaptation for Decoding Brain Cognitive States From tfMRI Images.

Recent advances in large model and neuroscience have enabled exploration of the mechanism of brain activity by using neuroimaging data. Brain decoding is one of the most promising researches to further understand the human cognitive function. However, current methods excessively depends on high-quality labeled data, which brings enormous expense of collection and annotation of neural images by experts. Besides, the performance of cross-individual decoding suffers from inconsistency in data distribution caused by individual variation and different collection equipments. To address mentioned above issues, a Join Domain Adapative Decoding (JDAD) framework is proposed for unsupervised decoding specific brain cognitive state related to behavioral task. Based on the volumetric feature extraction from task-based functional Magnetic Resonance Imaging (tfMRI) data, a novel objective loss function is designed by the combination of joint distribution regularizer, which aims to restrict the distance of both the conditional and marginal probability distribution of labeled and unlabeled samples. Experimental results on the public Human Connectome Project (HCP) S1200 dataset show that JDAD achieves superior performance than other prevalent methods, especially for fine-grained task with 11.5%-21.6% improvements of decoding accuracy. The learned 3D features are visualized by Grad-CAM to build a combination with brain functional regions, which provides a novel path to learn the function of brain cortex regions related to specific cognitive task in group level.

Artificial intelligence in ECG analysis - future or present?

This review discusses the significance of Electrocardiography (ECG) as a fundamental diagnostic tool for identifying electrical abnormalities in the heart. Despite its inception a century ago, ECG remains the gold standard for cardiovascular assessment. ECGs are routinely conducted in various healthcare settings, from family physician offices to emergency rooms, underscoring its ubiquitous clinical utility. However, misinterpretation of ECGs can lead to detrimental treatment decisions, emphasizing the critical need for accurate analysis. In recent years, artificial intelligence (AI) has emerged as a promising tool for ECG interpretation. AI models, designed to replicate human cognitive functions, undergo training with extensive datasets. While AI shows potential in improving ECG interpretation quality, it is not without limitations. Physician expertise remains indispensable in interpreting ECG findings accurately. Despite its potential, AI’s clinical application in ECG interpretation has yet to gain widespread approval. The paper emphasizes the importance of understanding the limitations and risks associated with AI implementation in cardiovascular diagnostics.

The Digital Age: Exploring the Intersection of AI/CI and Human Cognition and Social Interactions

Although solutions based on artificial and computational intelligence have made life easier, the fast development of technology also raises questions about near future and log term human cognition and social interaction. Through a survey of the literature and qualitative analysis, our work examined current research on how the AI/CI affects human cognitive functions and social interactions. We discuss how AI and CI are influencing e.g. how we humans gather information, build relationships, and communicate with others, with and without the new frontline technologies. Additionally, proposals for future advances are discussed along with the ethical and societal ramifications these technologies have, could and might bring into our lives. We think that by developing a deeper knowledge of how AI/CI affects human cognition and social interaction, new contributions are made to a positive conversation and encourage a responsible approach to incorporating new technologies into our daily lives.

Mental Deterioration in Eugene O'Neill's Plays The Emperor Jones and Desire Under the Elms: A Psychoanalytic Study

لقد حظيت محاولة فهم العقلية الإنسانية والوظائف المعرفية لدى الانسان باهتمام كبير من قبل الكاتب المسرحي الأمريكي يوجين أونيل (1888-1953) في نتاجاته الدرامية ، والتي حاول فيها ان يعكس خبراته وتجاربه الشخصية . والجدير بالذكر أن مسرحيات أونيل تعتمد على ما يصطلح عليه هو "الآمال اليائسة" أو "المخاوف الصغيرة التي لا شكل لها". وبناء على هذا هدفت هذه الدراسة إلى مناقشة وتحليل اثنتين من مسرحيات أونيل ؛ هما "الإمبراطور جونز" و"الرغبة تحت شجرة الدردار"، واللتين تم تحليلهما نقديا من خلال النظريات النفسية لمحاولة فهم طبيعة الاضطراب النفسي الذي يؤدي بدوره الى اختلال شخصية الفرد . حيث تم تحليل مسرحية "الامبراطور جونز" على وفق نظرية "كارل يونغ" حول اللاوعي الجمعي. وتم تحليل مسرحية "الرغبة تحت شجرة الدردار" من خلال نظرية "إريك فروم" حول عقدة التشبث بالأم.

Semantic speech analysis using machine learning and deep learning techniques: a comprehensive review

Human cognitive functions such as perception, attention, learning, memory, reasoning, and problem-solving are all significantly influenced by emotion. Emotion has a particularly potent impact on attention, modifying its selectivity in particular and influencing behavior and action motivation. Artificial Emotional Intelligence (AEI) technologies enable computers to understand a user's emotional state and respond appropriately. These systems enable a realistic dialogue between people and machines. The current generation of adaptive user interference technologies is built on techniques from data analytics and machine learning (ML), namely deep learning (DL) artificial neural networks (ANN) from multimodal data, such as videos of facial expressions, stance, and gesture, voice, and bio-physiological data (such as eye movement, ECG, respiration, EEG, FMRT, EMG, eye tracking). In this study, we reviewed existing literature based on ML and data analytics techniques being used to detect emotions in speech. The efficacy of data analytics and ML techniques in this unique area of multimodal data processing and extracting emotions from speech. This study analyzes how emotional chatbots, facial expressions, images, and social media texts can be effective in detecting emotions. PRISMA methodology is used to review the existing survey. Support Vector Machines (SVM), Naïve Bayes (NB), Random Forests (RF), Recurrent Neural Networks (RNN), Logistic Regression (LR), etc., are commonly used ML techniques for emotion extraction purposes. This study provides a new taxonomy about the application of ML in SER. The result shows that Long-Short Term Memory (LSTM) and Convolutional Neural Networks (CNN) are found to be the most useful methodology for this purpose.

Semantic features of complex technosocial systems: On the taxonomy of artificial intelligence technological packages

Objectives. The aim ofthis work is to enhance the scientific and methodological apparatus of artificial intelligence (AI) sciences by enriching their conceptual framework. The current conceptual framework of AI sciences does not reflect the intricate nature of this technological and socioeconomic phenomenon as possessing the diverse range of capabilities and the interconnectedness that allows for the imitation of human cognitive functions and comparable results. The author of the article structures the concept of the technological package of AI, describing its system properties, connections and functional elements based on the various types of human cognitive and operational activities.Methods. The research is based on the concept (method) of technological packages—genetically and functionally connected sets of technologies with system properties.Results. For the first time in Russian and international practice, the basic (general) taxonomy of the AI technological package has been specified and structured. A taxonomy of the AI metatechnological package (a package of metatechnologies) has been proposed. General taxonomy can serve as a tool for improving strategies, methodological documents and state programs to define the development of AI systems at state or industry level.Conclusions. The suggested basic (general) taxonomy oftechnological package and taxonomy of metatechnologies package allows research to move away from the limited view of AI. It increases semantic and methodological clarity in relation to AI as a complex technosocial phenomenon and contributes to the harmonized integration of AI systems intо the sphere of socioeconomic activities of the state. It can thus serve as a foundation for further improvement of state economic and legal regulation of AI development.

Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice

Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brain’s computational capacities that subtend almost all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapt across evolution to accomplish increasingly complex functions? By applying a graph- and information-theory approach to assess information-related pathways in male mouse, macaque and human brains, we show a brain communication gap between selective information transmission in non-human mammals, where brain regions share information through single polysynaptic pathways, and parallel information transmission in humans, where regions share information through multiple parallel pathways. In humans, parallel transmission acts as a major connector between unimodal and transmodal systems. The layout of information-related pathways is unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides evidence that different communication patterns are tied to the evolution of mammalian brain networks.

Chronobiology of nutrition and cognitive function

AbstractCurrent literature on the association between nutrition and cognitive function has focused mainly on total daily dietary intake of nutrients, foods or dietary patterns, while there has been much less focus on the timing of intake, i.e. the distribution of intake throughout the day and/or during specific eating occasions. Meal timing interferes with the circadian clocks and it has been previously linked with several health outcomes, including obesity and glycemic control. At the same time, there are well established circadian rhythms in cognitive performance in humans, with worse performance in the early morning and late evening and best performance somewhere in the middle of the daytime.Literature of the chronobiology of nutrition (chrononutrition) in relation to cognitive function and decline is extremely limited and to a certain extend conflicting. For example, breakfast consumption has been associated with decreased odds of having Mild Cognitive Impairment (MCI) in some studies, while, according to other studies, individuals with Alzheimer’s Disease (AD) and MCI tend to prefer early (rather than late) day times for food intake. Overall, there is very little research on the effect on cognitive function of time of day or energy content or nutrient distribution of the consumed meals. Furthermore, even though certain biomarkers of neurodegeneration are known to exhibit circadian properties, their associations with aspects of chrononutrition have not been explored.In conclusion, there is growing interest in the field of chrononutrition, an emerging area of investigation that is revealing important insights into how the timing of meals and overall eating patterns can impact cognitive function in humans. Part of the reason that this field is still in its infancy is that not all methods of dietary assessment are suitable for such analyses: only the laborious and time‐consuming methods of 24h dietary recalls or food records, that collect information on the timing of each eating occasion, allow for the evaluation of intake (nutrient of foods) distribution during the day.Overall, much more investigational effort is needed to fully understand the mechanisms underlying potential associations of chrononutrition and cognition and to develop practical recommendations for maintaining cognitive health through dietary interventions.

The Protective Role of L-carnitine on Psychosocial Stress-induced Changes in Gene Expression and Protein Levels of Matrix Metalloproteinases, Serum Corticosterone in a Rat Model.

Psychosocial stress (STS) is a common stress in modern societies. Chronic STS is associated with the impairment of a broad range of cognitive functions in humans and with prolonged abnormalities in memory. Matrix metalloproteinases (MMPs), a protein family of zinccontaining endopeptidases, are essential in neuro-inflammation and involved in neurodegenerative diseases. L-Car possessed neuroprotective, antioxidant, and anti-inflammatory properties and was shown to modulate MMPs. The current study aimed to examine the protective effect of L-Carnitine (L-CAR) on STSinduced changes in serum corticosterone levels, MMP-2, -9, and -12 protein and mRNA expression in the hippocampus as a possible mechanism for L-CAR protective effect on STS-induced memory impairment. The chronic STS and L-CAR (300 mg/kg/day, i.p) were simultaneously administered for 6 weeks to adult male Wistar rats. Serum corticosterone and protein levels of MMP-2, -9 and -12 were evaluated using ELISA. Real-Time PCR techniques were used to determine the mRNA levels of MMP-2, -9 and -12 in the hippocampus. The findings showed that serum corticosterone levels and MMP-2 and -9 protein levels were significantly increased (p<0.05) in the STS group compared to the control. Similarly, RT-PCR findings showed that the mRNA of those proteinases significantly increased (p<0.05) following the intruder method. On the other hand, the administration of L-CAR restored the alterations in corticosterone levels and MMPs gene and protein expression induced by chronic STS. STS induced elevations in corticosterone and MMP-2 and -9 levels in the hippocampus. L-CAR, on the other hand, exhibited protective effects against the STS-induced changes in MMP-2 and -9.

Prospects for gamification: analysis of students’ perception of the game’s image

Game is one of the most multifaceted phenomena in human life. It comes in many forms, uses a variety of capabilities, and can serve as a tool to achieve a variety of goals. Thus, the games can be used to solve problems in many areas: from pedagogy to business, from science to art. Each type of game requires players to have a certain level of proficiency in various skills. This contributes to the development of human cognitive and social functions and has certain characteristics. The popularity of gaming technologies in education continues to rise. The introduction of online formats has also contributed to the growth and use of interactive multimedia technologies. Gamification in education is an approach that uses game elements and mechanics to increase student motivation and engagement in learning. This scientific article reviews the concept of a game and analyzes the perception of the image of a game by students and schoolchildren in the context of learning. The study shows that gamification can significantly increase student engagement and motivation. This, in turn, has a positive impact on the quality of learning. The results of focus groups conducted using drawing techniques demonstrate that the image of the game is well perceived by schoolchildren and students and creates a favorable environment for active participation in the learning process. Based on this, the authors of the article propose to use gamification as an effective learning tool that helps increase motivation, self-organization and self-regulation of students. Analysis of the perception of the image of the game by students indicates the promise of using gamification in education. This approach can be an effective tool for the modern educational process, promoting the active involvement of students, increasing their motivation and achieving better educational results.

Exploring How do Expectations Influence Learning

Memory is a core component of human cognitive functioning and is vital for learning, decision-making, and quality of life. This paper reviews the correlation between setting expectations and aiding memory, focusing on the effects of constructing, capturing, and adjusting expectations during memory on memory performance. First, the paper describes the basic principles and processes of memory and clarifies the role of setting expectations in memory. Then, the critical role of setting expectations in memory is demonstrated. Finally, the role of expectations on memory interference, memory extraction, and memory retention is discussed, as well as directions for future research.

Association of bone turnover markers and cognitive function in Chinese chronic schizophrenia patients with or without vitamin D insufficiency

BackgroundIncreasing evidence shows that bone turnover markers (BTMs) and vitamin D can affect human cognitive function. However, there are few studies that have investigated the association between BTMs and cognitive function in chronic schizophrenia patients. The aim of this study was to investigate the relationship between BTMs and cognitive function in chronic schizophrenia patients with or without vitamin D insufficiency (VDI).MethodsIn all, 118 chronic schizophrenia patients were enrolled in this cross-sectional study. Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was applied to evaluate the cognitive function of the subjects. Blood analysis included bone turnover markers, vitamin D levels, and glycolipid levels.ResultsRelative to 72 vitamin D-sufficient (VDS) patients, 46 VDI patients had higher bone resorption markers levels and lower bone formation markers levels. Regression analysis showed that, in the total sample, CTX and language function exhibited independent positive correlation (p = 0.027, R2 change = 0.042), and in the VDS group, procollagen type I N-terminal propeptide (PINP) was independently negatively correlated with language function (p = 0.031, R2 change = 0.065), while the positive correlation between osteopontin (OPN) and delayed memory remained in the VDI group (p = 0.036, R2 change = 0.083).ConclusionOur study showed an association between the levels of BTMs and cognitive function among chronic schizophrenia patients. This correlation may have different mechanisms of action at different vitamin D levels.

Protocol of the Budapest sleep, experiences, and traits study: An accessible resource for understanding associations between daily experiences, individual differences, and objectively measured sleep.

Sleep is both a neurophysiological state and a biologically necessary behavior that performs a variety of indispensable roles for human health, development, and cognitive functioning. Despite this, comparatively little is known about the relationships between daily experiences and sleep features. Importantly, these relationships are bidirectional in nature, may be differently associated with subjectively and objectively assessed sleep, and may also be modulated by individual differences To address this challenge, we created the Budapest Sleep, Experiences, and Traits Study (BSETS), a multidisciplinary observational sleep study utilizing novel remote EEG devices. BSETS was designed to establish a dataset for future use in investigating the relationships between sleep features and daily experiences. In this paper we describe the protocol of the currently ongoing BSETS, which examines a community-dwelling sample of over 250 healthy participants who are studied in a naturalistic setting using a large questionnaire assessing psychological, demographic, and anthropometric information, as well as evening/morning diaries of sleep and daily experiences, and mobile EEG recordings over a period of 7 days. This dataset will become an accessible resource to the wider scientific community and can be utilized to investigate the complex multidirectional relationships between objectively and subjectively measured sleep, daily experiences, and individual differences, bestowing it with significant value for sleep researchers as well as practitioners working in clinical settings with patients suffering from disordered sleep.

Treadmill exercise prevents the hyperexcitability of pyramidal neurons in medial entorhinal cortex in the 3xTg-AD mouse model of Alzheimer's disease

Neuronal hyperactivity is a key abnormality in early stage Alzheimer's disease (AD). Medial entorhinal cortex (mEC) plays a vital role in memory function and is affected early in AD. Growing evidence indicates benefits of regular exercise on memory and cognitive function in humans with AD, although, the underlying mechanisms are not clear. Therefore, this study was designed to test the effects of 16 weeks treadmill exercise on spatial learning memory and the underlying cellular mechanisms in 6-month-old 3xTg-AD mice. Whole-cell patch clamp was used to examine neuronal intrinsic excitability, spontaneous excitatory postsynaptic currents (sEPSCs) and spontaneous inhibitory postsynaptic currents (sIPSCs) of mEC layer II/III pyramidal neurons in the following groups: wild type (WT + sham), 3xTg-AD (AD+sham), WT receiving exercise (WT + Ex), and AD receiving exercise (AD+Ex). We found that at a behavioral level, treadmill exercise decreased working memory errors in radial arm maze (RAM) test in 6-month-old AD mice. At a cellular level, we found that treadmill exercise prevented the abnormal increase in mEC pyramidal neuron input resistance and action potential firing in 6-month-old 3xTg-AD mice compared with WT + sham and AD+Ex mice; further, sEPSC amplitude and frequency were normal in AD+Ex but overactive in AD+sham; additionally, GABAergic inhibition was normal in AD+Ex mice but reduced in AD+sham. In conclusion, our results indicate that treadmill exercise improves spatial learning memory and prevents network hyperexcitability in mEC by reducing pyramidal neuronal intrinsic excitability and normalizing excitatory and inhibitory synaptic transmission in 3xTg-AD mice.

Structural Fingerprinting of the Frontal Aslant Tract: Predicting Cognitive Control Capacity and Obsessive-Compulsive Symptoms.

White matter of the human brain is influenced by common genetic variations and shaped by neural activity-dependent experiences. Variations in microstructure of cerebral white matter across individuals and even across fiber tracts might underlie differences in cognitive capacity and vulnerabilities to mental disorders. The frontoparietal and cingulo-opercular networks of the brain constitute the central system supporting cognitive functions, and functional connectivity of these networks has been used to distinguish individuals known as "functional fingerprinting." The frontal aslant tract (FAT) that passes through the two networks has been implicated in executive functions. However, whether FAT can be used as a "structural fingerprint" to distinguish individuals and predict an individual's cognitive function and dysfunction is unknown. Here we investigated the fingerprinting property of FAT microstructural profiles using three independent diffusion MRI datasets with repeated scans on human participants including both females and males. We found that diffusion and geometric profiles of FAT can be used to distinguish individuals with a high accuracy. Next, we demonstrated that fractional anisotropy in different FAT segments predicted distinct cognitive functions, including working memory, inhibitory control, and relational reasoning. Finally, we assessed the contribution of altered FAT microstructural profiles to cognitive dysfunction in unmedicated patients with obsessive-compulsive disorders. We found that the altered microstructure in FAT was associated with the severity of obsessive-compulsive symptoms. Collectively, our findings suggest that the microstructural profiles of FAT can identify individuals with a high accuracy and may serve as an imaging marker for predicting an individual's cognitive capacity and disease severity.SIGNIFICANCE STATEMENT The frontoparietal network and cingulo-opercular network of the brain constitute a dual-network architecture for human cognitive functions, and functional connectivity of these two networks can be used as a "functional fingerprint" to distinguish individuals. However, the structural underpinnings of these networks subserving individual heterogeneities in their functional connectivity and cognitive ability remain unknown. We show here that the frontal aslant tract (FAT) that passes through the two networks distinguishes individuals with a high accuracy. Further, we demonstrate that the diffusion profiles of FAT predict distinct cognitive functions in healthy subjects and are associated with the clinical symptoms in patients with obsessive-compulsive disorders. Our findings suggest that the FAT may serve as a unique structural fingerprint underlying individual cognitive capability.

Shared and divergent principles of synaptic transmission between cortical excitatory neurons in rodent and human brain.

Information transfer between principal neurons in neocortex occurs through (glutamatergic) synaptic transmission. In this focussed review, we provide a detailed overview on the strength of synaptic neurotransmission between pairs of excitatory neurons in human and laboratory animals with a specific focus on data obtained using patch clamp electrophysiology. We reach two major conclusions: (1) the synaptic strength, measured as unitary excitatory postsynaptic potential (or uEPSP), is remarkably consistent across species, cortical regions, layers and/or cell-types (median 0.5 mV, interquartile range 0.4-1.0 mV) with most variability associated with the cell-type specific connection studied (min 0.1-max 1.4 mV), (2) synaptic function cannot be generalized across human and rodent, which we exemplify by discussing the differences in anatomical and functional properties of pyramidal-to-pyramidal connections within human and rodent cortical layers 2 and 3. With only a handful of studies available on synaptic transmission in human, it is obvious that much remains unknown to date. Uncovering the shared and divergent principles of synaptic transmission across species however, will almost certainly be a pivotal step toward understanding human cognitive ability and brain function in health and disease.

Comparative single-cell transcriptomic analysis of primate brains highlights human-specific regulatory evolution.

Enhanced cognitive function in humans is hypothesized to result from cortical expansion and increased cellular diversity. However, the mechanisms that drive these phenotypic innovations remain poorly understood, in part because of the lack of high-quality cellular resolution data in human and non-human primates. Here, we take advantage of single-cell expression data from the middle temporal gyrus of five primates (human, chimp, gorilla, macaque and marmoset) to identify 57 homologous cell types and generate cell type-specific gene co-expression networks for comparative analysis. Although orthologue expression patterns are generally well conserved, we find 24% of genes with extensive differences between human and non-human primates (3,383 out of 14,131), which are also associated with multiple brain disorders. To assess the functional significance of gene expression differences in an evolutionary context, we evaluate changes in network connectivity across meta-analytic co-expression networks from 19 animals. We find that a subset of these genes has deeply conserved co-expression across all non-human animals, and strongly divergent co-expression relationships in humans (139 out of 3,383, <1% of primate orthologues). Genes with human-specific cellular expression and co-expression profiles (such as NHEJ1, GTF2H2, C2 and BBS5) typically evolve under relaxed selective constraints and may drive rapid evolutionary change in brain function.