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We present here an online platform for sharing resources underlying publications in neuroscience. It enables authors to easily upload and distribute digital resources, such as data, code, and notebooks, in a structured and systematic way. Interactivity is a prominent feature of the Live Papers, with features to download, visualise or simulate data, models and results presented in the corresponding publications. The resources are hosted on reliable data storage servers to ensure long term availability and easy accessibility. All data are managed via the EBRAINS Knowledge Graph, thereby helping maintain data provenance, and enabling tight integration with tools and services offered under the EBRAINS ecosystem., (© 2022. The Author(s).)

Sex differences exist in many neurological and psychiatric diseases, but these have not always been addressed adequately in research. In order to address this, it is necessary to consider how sex is incorporated into the design (e.g. using a balanced design) and into the analyses (e.g. using sex as a covariate) in the published literature. We surveyed papers published in 2009 and 2019 across six journals in neuroscience and psychiatry. In this sample, we find a 30% increase in the percentage of papers reporting studies that included both sexes in 2019 compared with 2009. Despite this increase, in 2019 only 19% of papers in the sample reported using an optimal design for discovery of possible sex differences, and only 5% of the papers reported studies that analysed sex as a discovery variable. We conclude that progress to date has not been sufficient to address the importance of sex differences in research for discovery and therapeutic potential for neurological and psychiatric disease., (© 2022. The Author(s).)

The International Conference on Cognitive Modeling brings together researchers from around the world whose main goal is to build computational systems that reflect the internal processes of the mind. In this issue, we present the four best representative papers on this work from our 18th meeting, ICCM 2020, which was also the first meeting to be held virtually. Two of these papers develop novel techniques for building larger and more complex models using Reinforcement Learning and Learning By Instruction, respectively. The other two show how cognitive models connect to neuroscience, drawing on details of the hippocampus and cerebellum to constrain and explain the cognitive processes involved in memory and conditioning., (© 2021 Cognitive Science Society LLC.)

The paper examines 1037 publications on bipolar disorder (BD) during the years 2000-19 from India, as listed in the Scopus database. India's publications constituted 2.27 % share of global output (45,624 publications) in the study period of 20 years. India does not figure in the top 10 countries in terms of research output on BD. The number of publications on BD from India increased from 13 in 2000 to 107 in 2019, registering 14.44 % annual average growth, higher than world's growth of 6.02 %. India's 10-year cumulative publications increased from 264 during 2000-09 to 773 during 2010-19, registering 192.8 % absolute growth, much higher than world cumulative growth of 63.27 %. India's publications on BD averaged citation impact per paper of 14.24, which decreased from 25.38 to 10.43 from 2000-09 to 2010-19. Maximum numbers of papers from India on BD were published by researchers from National Institute of Mental Health and Neurosciences, Bangalore (222 papers),Post Graduate Institute of Medical Education and Research, Chandigarh(118 papers), and AII India Institute of Medical Sciences, New Delhi (79 papers). Lady Harding Medical College, New Delhi (36.20 and 2.54), Schizophrenia Research Foundation, Chennai (27.45 and 1.93), and King George's Medical University, Lucknow (25.21 and 1.77) were the most significant organizations in terms of citation per paper and relative citation index. Maximum number of papers were published in Indian Journal of Psychiatry (101 papers), followed by Asian Journal of Psychiatry (88 papers) and Indian Journal of Psychology Medicine (34 papers)., (Copyright © 2020 Elsevier B.V. All rights reserved.)

To commemorate the 100th anniversary of the creation of the Instituto Cajal, we bring this thematic issue to honor Spanish neuroscience. The issue includes several papers written by scientists, most of them being direct descendants of those who lived on the front lines of the dawn of Spanish neuroscience. These pages reflect a summary of the main achievements of this unique group of neuroscientists, all of them belonging to the Cajal School. Finally, this school of scientists became the forerunner of the modern worldwide neuroscience. Anat Rec, 303:1179-1180, 2020. © 2020 American Association for Anatomy., (© 2020 American Association for Anatomy.)

The word "glia" was coined in the mid-19th century and defined as "the nerve glue". For decades, it was assumed to be a uniform matrix, until cell theorists raised the "neuron doctrine" which stipulated that nervous tissue was composed of individual cells. The term "astrocytes" was introduced in the late 19th century as a synonym for glial cells, but it was Santiago Ramón y Cajal who defined a "third element" distinct from glial cells (astrocytes) and neurons. It was not until 1919 when Pío del Río-Hortega, an alumnus of the Cajal School, introduced the modern terms we use today, and thoroughly described both "oligodendrocytes" and "microglia" to clearly distinguish them from astrocytes. In a series of four papers published that year in Spanish, Río-Hortega described the distribution and morphological phenotype of microglia. He also noted that these cells were the origin of the rod cells described earlier in pathologic tissue, and recognized that resting microglia transformed into an ameboid phenotype in different types of brain diseases and pathologies. He also noted the mesodermal origin of these cells and recognized their phagocytic capacity. We here provide the first English translation of these landmark series of papers, which paved the way for modern glial research. To heighten the value and accessibility of these classic papers and their original figures, an introduction to this critical period of neuroscience is provided, along with unpublished photographs. By adding comments to the translated text, we provide sufficient context so that contemporary scientists may fully appreciate it. GLIA 2016;64:1801-1840., (© 2016 Wiley Periodicals, Inc.)

Context: The highest cited papers published in a journal provide a snapshot of the clinical practice and research in that specialty and/or region., Aims: The aim of this study was to determine the highest cited papers published in Neurology India and analyze their attributes., Setting and Design: This study was a citation analysis of all papers published in Neurology India since online archiving commenced in 1993., Methods: All papers published in Neurology India between the years 1993-2014 were listed. The number of times each paper had been cited up till the time of performing this study was determined by performing a Google Scholar search. Published papers were then ranked on the basis of total times cited since publication and the annual citation rate. Statistical Techniques: Simple counts and percentages were used to report most results. The mean citations received by papers in various categories were compared using the Student's t-test or a one-way analysis of variance, as appropriate. All analyses were carried out on SAS University Edition (SAS/STAT®, SAS Institute Inc, NC, USA) and graphs were generated on MS Excel 2016., Results: The top papers on the total citations and annual citation rate rank lists pertained to basic neuroscience research. The highest cited paper overall had received 139 citations. About a quarter of the papers published had never been cited at all. The major themes represented were vascular diseases and infections., Conclusions: The highest cited papers reflect the diseases that are of major concern in India. Certain domains such as trauma, allied neurosciences, and basic neuroscience research were underrepresented.

When an academic paper is published in a journal that assigns a digital object identifier (DOI) to papers, this is a de facto fait accompli. Corrections or retractions are supposed to follow a specific protocol, especially in journals that claim to follow the Committee on Publication Ethics (COPE) guidelines. In this paper, we highlight a case of a new, fully open access neuroscience journal that claims to be COPE-compliant, yet has silently retracted two papers since all records, bibliometrics, and PDF files related to their existence have been deleted from the journal's website. Although this phenomenon does not seem to be common in the neurosciences, we consider that any opaque corrective measures in journals whose papers could be cited may negatively impact the wider neuroscience literature and community. Instead, we encourage transparency in retraction to promote truthfulness and trustworthiness., (© 2024 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

A fundamental goal of research in neuroscience is to uncover the causal structure of the brain. This focus on causation makes sense, because causal information can provide explanations of brain function and identify reliable targets with which to understand cognitive function and prevent or change neurological conditions and psychiatric disorders. In this research, one of the most frequently used causal concepts is 'mechanism' - this is seen in the literature and language of the field, in grant and funding inquiries that specify what research is supported, and in journal guidelines on which contributions are considered for publication. In these contexts, mechanisms are commonly tied to expressions of the main aims of the field and cited as the 'fundamental', 'foundational' and/or 'basic' unit for understanding the brain. Despite its common usage and perceived importance, mechanism is used in different ways that are rarely distinguished. Given that this concept is defined in different ways throughout the field - and that there is often no clarification of which definition is intended - there remains a marked ambiguity about the fundamental goals, orientation and principles of the field. Here we provide an overview of causation and mechanism from the perspectives of neuroscience and philosophy of science, in order to address these challenges., (© 2024. Springer Nature Limited.)

This document is an editorial summary of the top cited papers in the field of Systems Neuroscience in 2022. The top ten papers cover a range of topics including tinnitus, obesity, and neuromodulation. The papers come from authors all over the world, representing diverse perspectives. Some notable findings include the lack of therapeutic benefit of a specific stimulation modality for tinnitus, the potential improvement of tinnitus treatment through an enriched acoustic environment, the impact of psychological and sociodemographic factors on tinnitus-related distress, the potential benefits of aerobic exercise for individuals with mild cognitive impairment, the importance of considering insular epilepsy during surgical planning, the functional changes in brain activity induced by hypnosis, the effects of transcranial alternating current stimulation on motor cortex oscillation and inhibition, the effects of transcutaneous vagus nerve stimulation on autonomic responses, the neuroplastic capacity of different brain stimulation modalities, and the lack of association between obesity and executive functioning. These papers provide valuable insights into various aspects of Systems Neuroscience and are worth exploring for researchers and individuals interested in these topics. [Extracted from the article]

Background: Utilizing information technology (IT) systems, for example in form of computerized cognitive screening or exergame-based (also called active videogames) training, has gained growing interest for supporting healthy aging and to detect, prevent and treat neurocognitive disorders (NCD). To ameliorate the effectiveness of exergaming, the neurobiological mechanisms as well as the most effective components for exergame-based training remain to be established. At the same time, it is important to account for the end-users’ capabilities, preferences, and therapeutic needs during the design and development process to foster the usability and acceptance of the resulting program in clinical practice. This will positively influence adherence to the resulting exergame-based training program, which, in turn, favors more distinct training-related neurobiological effects.Objectives and Methods: This methodological paper describes the design and development process of novel exergame-based training concepts guided by a recently proposed methodological framework: The ‘Multidisciplinary Iterative Design of Exergames (MIDE): A Framework for Supporting the Design, Development, and Evaluation of Exergames for Health’ (Li et al., 2020).Case Study: A step-by-step application of the MIDE-framework as a specific guidance in an ongoing project aiming to design, develop, and evaluate an exergame-based training concept with the aim to halt and/or reduce cognitive decline and improve quality of life in older adults with mild neurocognitive disorder (mNCD) is illustrated.Discussion and Conclusion: The development of novel exergame-based training concepts is greatly facilitated when it is based on a theoretical framework (e.g., the MIDE-framework). Applying this framework resulted in a structured, iterative, and evidence-based approach that led to the identification of multiple key requirements for the exergame design as well as the training components that otherwise may have been overlooked or neglected. This is expected to foster the usability and acceptance of the resulting exergame intervention in “real life” settings. Therefore, it is strongly recommended to implement a theoretical framework (e.g., the MIDE-framework) for future research projects in line with well-known checklists to improve completeness of reporting and replicability when serious games for motor-cognitive rehabilitation purposes are to be developed.

Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake, behaving human brain. By tracking whole-brain signals across a diverse range of cognitive and behavioural states or mapping differences associated with specific traits or clinical conditions, fMRI has advanced our understanding of brain function and its links to both normal and atypical behaviour. Despite this headway, progress in human cognitive neuroscience that uses fMRI has been relatively isolated from rapid advances in other subdomains of neuroscience, which themselves are also somewhat siloed from one another. In this Perspective, we argue that fMRI is well-placed to integrate the diverse subfields of systems, cognitive, computational and clinical neuroscience. We first summarize the strengths and weaknesses of fMRI as an imaging tool, then highlight examples of studies that have successfully used fMRI in each subdomain of neuroscience. We then provide a roadmap for the future advances that will be needed to realize this integrative vision. In this way, we hope to demonstrate how fMRI can help usher in a new era of interdisciplinary coherence in neuroscience., (© 2023. Crown.)

Computational models in neuroscience usually take the form of systems of differential equations. The behaviour of such systems is the subject of dynamical systems theory. Dynamical systems theory provides a powerful mathematical toolbox for analysing neurobiological processes and has been a mainstay of computational neuroscience for decades. Recently, recurrent neural networks (RNNs) have become a popular machine learning tool for studying the non-linear dynamics of neural and behavioural processes by emulating an underlying system of differential equations. RNNs have been routinely trained on similar behavioural tasks to those used for animal subjects to generate hypotheses about the underlying computational mechanisms. By contrast, RNNs can also be trained on the measured physiological and behavioural data, thereby directly inheriting their temporal and geometrical properties. In this way they become a formal surrogate for the experimentally probed system that can be further analysed, perturbed and simulated. This powerful approach is called dynamical system reconstruction. In this Perspective, we focus on recent trends in artificial intelligence and machine learning in this exciting and rapidly expanding field, which may be less well known in neuroscience. We discuss formal prerequisites, different model architectures and training approaches for RNN-based dynamical system reconstructions, ways to evaluate and validate model performance, how to interpret trained models in a neuroscience context, and current challenges., (© 2023. Springer Nature Limited.)

Abstract: Clinical neurosciences, and psychiatry specifically, have been challenged by the lack of a comprehensive and practical framework that explains the core mechanistic processes of variable psychiatric presentations. Current conceptualization and classification of psychiatric presentations are primarily centered on a non-biologically based clinical descriptive approach. Despite various attempts, advances in neuroscience research have not led to an improved conceptualization or mechanistic classification of psychiatric disorders. This perspective article proposes a new-work-in-progress-framework for conceptualizing psychiatric presentations based on neural network components (NNC). This framework could guide the development of mechanistic disease classification, improve understanding of underpinning pathology, and provide specific intervention targets. This model also has the potential to dissolve artificial barriers between the fields of psychiatry and neurology., (Copyright © 2024 President and Fellows of Harvard College.)

This presentation to the ASE Annual Conference 2018 discussed how research in neuroscience can help in the learning of science both in the classroom and online.

In Keiser's words, "each work depicts, in a knowingly ridiculous manner, a natural philosopher digging into brain matter in the hope of exposing the mechanisms that make the mind tick" (pp. 143-144). Keiser's focus is not on how the nerves and various brain structures appear during a dissection, which is straightforward and verifiable. Locke did not partake in the kinds of fictions Willis, Cavendish, and others were promoting about the nerve spirits. [Extracted from the article]

The 22nd Workshop on Aggression was held in Limassol, the 2nd second largest urban area in Cyprus, in November 22-25, 2017, and was organized by the University of Cyprus. There were five keynote speakers, eight symposia, nine paper sessions and one poster session. In total, 78 high quality individual papers were presented, covering a broad area of research fields in accordance to the theme of the workshop. The thematic focus of the 22nd Workshop on Aggression 2017 was "Contemporary perspectives on aggressive behavior: Exploring trends across the lifespan". The conference aimed to present the latest research and stimulate interdisciplinary research mainly in the fields of: (1) conventional and cyber forms of aggression; (2) personality and environmental factors of aggression; (3) neuroscience and aggression; and (4) prevention and intervention programs of aggression.

Biomedical engineering (BME) is a multidisciplinary, constantly advancing field; as such, undergraduate programs in BME must continually adapt. Elective courses provide opportunities for students to select topic areas relevant to their interests or future careers. Specifically, laboratory courses allow experiential learning in specialized topics in a hands-on manner that is suitable and accessible to undergraduate students. In recent years, neural engineering has emerged as a research sub-specialty within BME, and students preparing to pursue careers in this field will require a broad range of fundamental and experiential training. We sought to demonstrate this possibility by implementing a neural tissue engineering module into an existing upper-level undergraduate biofabrication elective. Organoids, which are self-assembling aggregate cell culture models that mimic a tissue or organ in both function and structure, have been made more accessible by genetic tools and commercially available resources. These experimental tools can be incorporated into basic laboratory experiments to model neurological systems that are otherwise difficult to study. In this paper, we describe the execution of this new module in which teams followed an adapted protocol for producing human neural organoids and then designed and manufactured a 3D-printed 'solution' to a common problem in the fields of neural engineering and organoid research. Additionally, we include student feedback as well as advantages, disadvantages, and opportunities for improvement of this laboratory module in future implementations. Skills gained in this project-based setting could be beneficial in subsequent capstone design courses as well as translated into future courses or graduate research studies.

Neuroanatomy is a notoriously challenging subject for medical students to learn. Due to the coronavirus disease-19 (COVID-19) pandemic, anatomical education transitioned to an online format. We assessed student performance in, and attitudes toward, an online neuroanatomy assessment compared to an in-person equivalent, as a marker of the efficacy of remote neuroanatomy education. Participants in the National Undergraduate Neuroanatomy Competition (NUNC) 2021 undertook two online examinations: a neuroanatomically themed multiple-choice question paper and anatomy spotter. Students completed pre- and post-examination questionnaires to gauge their attitudes toward the online competition and prior experience of online anatomical teaching/assessment. To evaluate performance, we compared scores of students who sat the online (2021) and in-person (2017) examinations, using 12 identical neuroradiology questions present in both years. Forty-six percent of NUNC 2021 participants had taken an online anatomy examination in the previous 12 months, but this did not impact examination performance significantly (p > 0.05). There was no significant difference in examination scores between in-person and online examinations using the 12 neuroradiology questions (p = 0.69). Fifty percent of participants found the online format less enjoyable, with 63% citing significantly fewer networking opportunities. The online competition was less stressful for 55% of participants. This study provides some evidence to suggest that student performance is not affected when undertaking online examinations and proposes that online neuroanatomy teaching methods, particularly for neuroradiology, may be equally as effective as in-person approaches within this context. Participants perceived online examinations as less stressful but raised concerns surrounding the networking potential and enjoyment of online events.

The quality of the relationship between caregiver and child has long-term effects on the cognitive and socio-emotional development of children. A process involved in human parenting is the bio-behavioural synchrony that occurs between the partners in the relationship during interaction. Through interaction, bio-behavioural synchronicity allows the adaptation of the physiological systems of the parent to those of the child and promotes the positive development and modelling of the child's social brain. The role of bio-behavioural synchrony in building social bonds could be investigated using functional near-infrared spectroscopy (fNIRS). In this paper we have (a) highlighted the importance of the quality of the caregiver-child relationship for the child's cognitive and socio-emotional development, as well as the relevance of infantile stimuli in the activation of parenting behaviour; (b) discussed the tools used in the study of the neurophysiological substrates of the parental response; (c) proposed fNIRS as a particularly suitable tool for the study of parental responses; and (d) underlined the need for a multi-systemic psychobiological approach to understand the mechanisms that regulate caregiver-child interactions and their bio-behavioural synchrony. We propose to adopt a multi-system psychobiological approach to the study of parental behaviour and social interaction., (© 2022 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

This document is an editorial that discusses the concept of electromagnetic (EM) field theories of consciousness. It highlights the growing interest in this type of solution for understanding consciousness and its philosophical and physical aspects. The document also includes summaries of various research papers on EM field theories of consciousness, which explore the role of EM fields in understanding consciousness and propose different frameworks and theories to explain its mechanisms. The papers discuss topics such as brain activity, EM field oscillations, qualia, and the boundary problem in consciousness studies. Overall, these papers contribute to the ongoing exploration of EM field theories of consciousness and offer potential avenues for further research. [Extracted from the article]

The Neurosequential Model in Education (NME) is described as a developmentally sensitive and biologically respectful approach to development and learning. This paper postulates that the NME shares many commonalities with the Montessori Method in that it, too, is developmentally sensitive and adheres to biologically respectful concepts. This paper compares some of the core principles and recommended practices of the NME with those in the Montessori Method and argues that they are consistent in many ways. The paper also examines Dr. Montessori's unique use of "sensitive periods" in development for educational purposes, in particular her use of the sensitive periods for movement, the social aspects of life, and the sensitive period for order respectively. It argues that in doing this, she was actively promoting an approach to human development and education that appears to correlate with what Dr. Bruce Perry calls a developmentally sensitive and biologically respectful approach to learning. The goal of this study is to show the science behind why many of Dr. Montessori's original practices worked and had such a positive effect on children. This knowledge should empower Montessori educators and give them the confidence to promote authentic Montessori practices in the knowledge that they are in line with current neuroscientific theories that have been shown to be beneficial to children.

Modelling the spatiotemporal dynamics in the activity of neural populations while also enabling their flexible inference is hindered by the complexity and noisiness of neural observations. Here we show that the lower-dimensional nonlinear latent factors and latent structures can be computationally modelled in a manner that allows for flexible inference causally, non-causally and in the presence of missing neural observations. To enable flexible inference, we developed a neural network that separates the model into jointly trained manifold and dynamic latent factors such that nonlinearity is captured through the manifold factors and the dynamics can be modelled in tractable linear form on this nonlinear manifold. We show that the model, which we named 'DFINE' (for 'dynamical flexible inference for nonlinear embeddings') achieves flexible inference in simulations of nonlinear dynamics and across neural datasets representing a diversity of brain regions and behaviours. Compared with earlier neural-network models, DFINE enables flexible inference, better predicts neural activity and behaviour, and better captures the latent neural manifold structure. DFINE may advance the development of neurotechnology and investigations in neuroscience., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

I present a computational-level model of language production in terms of a combination of information theory and control theory in which words are chosen incrementally in order to maximize communicative value subject to an information-theoretic capacity constraint. The theory generally predicts a tradeoff between ease of production and communicative accuracy. I apply the theory to two cases of apparent availability effects in language production, in which words are selected on the basis of their accessibility to a speaker who has not yet perfectly planned the rest of the utterance. Using corpus data on English relative clause complementizer dropping and experimental data on Mandarin noun classifier choice, I show that the theory reproduces the observed phenomena, providing an alternative account to Uniform Information Density and a promising general model of language production which is tightly linked to emerging theories in computational neuroscience., (© 2023 The Authors. Topics in Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society.)

Background: The insula is one of the most researched brain regions with many highly cited papers. However, unlike the literature of other fields, there is currently no study that has identified the 100 most cited papers within the literature of the insula. The aim of the current study was to fill in the knowledge gap by determining which publications concerning the insula have been cited most often, who contributed to them, and what topics they were dealing with.Methods: The Web of Science online database was searched to identify the 100 most cited publications mentioning the insular cortex in their titles, abstracts or keywords. To systematically exclude irrelevant publications, the search strategy was finalized as: TS = (insula OR insular OR “island of Reil”) NOT TS = (“insular biogeography” OR “insular mammal*” OR “*insular lymphatic*”) NOT WC = (“Geochemistry and Geophysics” OR “Ecology”). The identified publications were sorted in descending order of citation count. The 100 most cited publications concerning the insula of the brain were identified and their bibliometric data was extracted and assessed. The VOSviewer software was used with default parameters to generate a bubble map that analyzes and visualizes the words/phrases used in the titles and abstracts of the publications.Results: There were 67 articles on experiments/lab studies and 33 meta-analyses/reviews but no opinion or methods paper. They had an average of 943.4 citations (or 62.9 citations per year), 93.5 references and 13.4 pages. There were 35 papers published in open access. USA was the major contributing country. The most top-ranked publications were concerning emotion, salience and pain.Conclusion: Two-thirds of the publications concerned the normal brain function/mechanism (n = 67), whereas 20 publications concerned disease/therapeutic intervention and another 13 concerned normal anatomy. For the 67 original articles, 57 used human subjects whereas 10 used animal models. MRI was the commonest modality (n = 37), followed by PET (n = 16). Nine articles investigated by histology, two by multiple modalities and three by other modality.

This document, published in Science Advances, discusses the challenges of multidisciplinary research in the field of neuroscience. The author emphasizes the importance of drawing on various disciplines to understand the mind and brain. However, the review process can be challenging due to different norms, philosophies, and standards of assessment in different fields. The author suggests tools such as cross-review and involving authors in the editorial process to address these challenges. The document also highlights the importance of collaboration across disciplines in advancing neuroscience knowledge. [Extracted from the article]

Advances in neuro-technology provide new insights into how individual students learn in educational contexts. However, applying it poses challenges for teachers in natural settings. This paper presents an example of the use and applicability of eye-tracking technology in Higher Education. We worked with a sample of 20 students from three universities (Burgos and Valladolid in Spain and Miño in Portugal). The objectives were: (1) to determine whether there were significant differences in indicators of cognitive effort (FC, FD, SC, PD, VC) found with eye-tracking technology between students with and without prior knowledge; (2) to determine whether there were clusters of learning behavior patterns among students; and (3) to analyze differences in the visualization of behavior patterns. A quasi-experimental design without a control group and a descriptive design were used. The results indicated significant differences in learning outcomes between students with and without prior knowledge. In addition, two clusters were found in indicators of cognitive effort. Finally, a comparative analysis of learning behavior patterns between students in cluster 1 vs. cluster 2 was performed. Eye-tracking technology makes it possible to record large data about the learning process. However, using it in natural educational settings currently requires teachers to have technological and data mining skills.

Background: From time to time, neuroimaging research findings receive press coverage and attention by the general public. Scientific articles therefore should be written in a readable manner to facilitate knowledge translation and dissemination. However, no published readability report on neuroimaging articles like those published in education, medical and marketing journals is available. As a start, this study therefore aimed to evaluate the readability of the most-cited neuroimaging articles.Methods: The 100 most-cited articles in neuroimaging identified in a recent study by Kim et al. (2016) were evaluated. Headings, mathematical equations, tables, figures, footnotes, appendices, and reference lists were trimmed from the articles. The rest was processed for number of characters, words and sentences. Five readability indices that indicate the school grade appropriate for that reading difficulty (Automated Readability Index, Coleman-Liau Index, Flesch-Kincaid Grade Level, Gunning Fog index and Simple Measure of Gobbledygook index) were computed. An average reading grade level (AGL) was calculated by taking the mean of these five indices. The Flesch Reading Ease (FRE) score was also computed. The readability of the trimmed abstracts and full texts was evaluated against number of authors, country of corresponding author, total citation count, normalized citation count, article type, publication year, impact factor of the year published and type of journal.Results: Mean AGL ± standard deviation (SD) of the trimmed abstracts and full texts were 17.15 ± 2.81 (college graduate level) and 14.22 ± 1.66 (college level) respectively. Mean FRE score ± SD of the abstracts and full texts were 15.70 ± 14.11 (college graduate level) and 32.11 ± 8.56 (college level) respectively. Both items indicated that the full texts were significantly more readable than the abstracts (p < 0.001). Abstract readability was not associated with any factors under investigation. ANCOVAs showed that review/meta-analysis (mean AGL ± SD: 16.0 ± 1.4) and higher impact factor significantly associated with lower readability of the trimmed full texts surveyed.Conclusion: Concerning the 100 most-cited articles in neuroimaging, the full text appears to be more readable than the abstracts. Experimental articles and methodology papers were more readable than reviews/meta-analyses. Articles published in journals with higher impact factors were less readable.

Neuroscience research has entered a phase of key discoveries in the realm of neurogenomics owing to strong financial and intellectual support for resource building and tool development. The previous challenge of tissue heterogeneity has been met with the application of techniques that can profile individual cells at scale. Moreover, the ability to perturb genes, gene regulatory elements and neuronal activity in a cell-type-specific manner has been integrated with gene expression studies to uncover the functional underpinnings of the genome at a systems level. Although these insights have necessarily been grounded in model systems, we now have the opportunity to apply these approaches in humans and in human tissue, thanks to advances in human genetics, brain imaging and tissue collection. We acknowledge that there will probably always be limits to the extent to which we can apply the genomic tools developed in model systems to human neuroscience; however, as we describe in this Perspective, the neuroscience field is now primed with an optimal foundation for tackling this ambitious challenge. The application of systems-level network analyses to these datasets will facilitate a deeper appreciation of human neurogenomics that cannot otherwise be achieved from directly observable phenomena., (© 2023. Springer Nature Limited.)