Advances In Neuroscience Research Articles

TAPAS: An Open-Source Software Package for Translational Neuromodeling and Computational Psychiatry.

Psychiatry faces fundamental challenges with regard to mechanistically guided differential diagnosis, as well as prediction of clinical trajectories and treatment response of individual patients. This has motivated the genesis of two closely intertwined fields: (i) Translational Neuromodeling (TN), which develops “computational assays” for inferring patient-specific disease processes from neuroimaging, electrophysiological, and behavioral data; and (ii) Computational Psychiatry (CP), with the goal of incorporating computational assays into clinical decision making in everyday practice. In order to serve as objective and reliable tools for clinical routine, computational assays require end-to-end pipelines from raw data (input) to clinically useful information (output). While these are yet to be established in clinical practice, individual components of this general end-to-end pipeline are being developed and made openly available for community use. In this paper, we present the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) software package, an open-source collection of building blocks for computational assays in psychiatry. Collectively, the tools in TAPAS presently cover several important aspects of the desired end-to-end pipeline, including: (i) tailored experimental designs and optimization of measurement strategy prior to data acquisition, (ii) quality control during data acquisition, and (iii) artifact correction, statistical inference, and clinical application after data acquisition. Here, we review the different tools within TAPAS and illustrate how these may help provide a deeper understanding of neural and cognitive mechanisms of disease, with the ultimate goal of establishing automatized pipelines for predictions about individual patients. We hope that the openly available tools in TAPAS will contribute to the further development of TN/CP and facilitate the translation of advances in computational neuroscience into clinically relevant computational assays.

From marketing to neuromarketing: Ethical considerations

This paper discusses the emerging field of neuroethics – broadly speaking, the ethical and social issues raised by advances in neuroscience – in the context of neuromarketing. The paper explains how the field is strongly influenced by current events and cultural consciousness. The authors build on the opinions proposed by some scholars, highlighting key considerations, starting with respect for privacy, transparency and, most urgently, the need to place the consumer at the centre of any business strategy and any project development.

Racism in Pain Medicine: We Can and Should Do More

Racism in Pain Medicine: We Can and Should Do More

Sexual Dimorphism in Language, and the Gender Shift Hypothesis of Homosexuality.

Psychological sex differences have been studied scientifically for more than a century, yet linguists still debate about the existence, magnitude, and causes of such differences in language use. Advances in psychology and cognitive neuroscience have shown the importance of sex and sexual orientation for various psychobehavioural traits, but the extent to which such differences manifest in language use is largely unexplored. Using computerised text analysis (Linguistic Inquiry and Word Count: LIWC 2015), this study found substantial psycholinguistic sexual dimorphism in a large corpus of English-language novels (n = 304) by heterosexual authors. The psycholinguistic sex differences largely aligned with known psychological sex differences, such as empathising–systemising, people–things orientation, and men’s more pronounced spatial cognitive styles and abilities. Furthermore, consistent with predictions from cognitive neuroscience, novels (n = 158) by lesbian authors showed minor signs of psycholinguistic masculinisation, while novels (n = 167) by homosexual men had a female-typical psycholinguistic pattern, supporting the gender shift hypothesis of homosexuality. The findings on this large corpus of 66.9 million words indicate how psychological group differences based on sex and sexual orientation manifest in language use in two centuries of literary art.

Children ASD Evaluation Through Joint Analysis of EEG and Eye-Tracking Recordings With Graph Convolution Network.

Recent advances in neuroscience indicate that analysis of bio-signals such as rest state electroencephalogram (EEG) and eye-tracking data can provide more reliable evaluation of children autism spectrum disorder (ASD) than traditional methods of behavior measurement relying on scales do. However, the effectiveness of the new approaches still lags behind the increasing requirement in clinical or educational practices as the “bio-marker” information carried by the bio-signal of a single-modality is likely insufficient or distorted. This study proposes an approach to joint analysis of EEG and eye-tracking for children ASD evaluation. The approach focuses on deep fusion of the features in two modalities as no explicit correlations between the original bio-signals are available, which also limits the performance of existing methods along this direction. First, the synchronization measures, information entropy, and time-frequency features of the multi-channel EEG are derived. Then a random forest applies to the eye-tracking recordings of the same subjects to single out the most significant features. A graph convolutional network (GCN) model then naturally fuses the two group of features to differentiate the children with ASD from the typically developed (TD) subjects. Experiments have been carried out on the two types of the bio-signals collected from 42 children (21 ASD and 21 TD subjects, 3–6 years old). The results indicate that (1) the proposed approach can achieve an accuracy of 95% in ASD detection, and (2) strong correlations exist between the two bio-signals collected even asynchronously, in particular the EEG synchronization against the face related/joint attentions in terms of covariance.

Occipital alpha-TMS causally modulates temporal order judgements: Evidence for discrete temporal windows in vision

Recent advances in neuroscience have challenged the view of conscious visual perception as a continuous process. Behavioral performance, reaction times and some visual illusions all undergo periodic fluctuations that can be traced back to oscillatory activity in the brain. These findings have given rise to the idea of a discrete sampling mechanism in the visual system. In this study we seek to investigate the causal relationship between occipital alpha oscillations and Temporal Order Judgements using neural entrainment via rhythmic TMS in 18 human subjects (9 females). We find that certain phases of the entrained oscillation facilitate temporal order perception of two visual stimuli, whereas others hinder it. Our findings support the idea that the visual system periodically compresses information into discrete packages within which temporal order information is lost. Significance statementNeural entrainment via TMS serves as a valuable tool to interfere with cortical rhythms and observe changes in perception. Here, using α-rhythmic TMS-pulses, we demonstrate the effect of the phase of entrained oscillations on performance in a temporal order judgment task. In extension of previous work, we 1. causally influenced brain rhythms far more directly using TMS, and 2. showed that previous results on discrete perception cannot simply be explained by rhythmic fluctuations in visibility. Our findings support the idea that the temporal organization of visual processing is discrete rather than continuous, and is causally modulated by cortical rhythms. To our knowledge, this is the first study providing causal evidence via TMS for an endogenous periodic modulation of time perception.

160 Applying the Free Energy Principle to Surgical Robotics

Abstract Introduction In an effort to build intelligent, autonomous systems, robotics has repeatedly used neuroscience as a source of inspiration for perception and control. This corresponds well with advances in neuroscience, particularly the free energy principle; a unified theory of the brain, integrating together notions of action, perception, and learning. Crucially for robotics, it provides a simple recipe to synthesise autonomous agents under the framework of active inference. Method We conducted a literature search assessing the practicality of autonomous agency within surgical robotics, and to understand the potential of applying the free energy principle to surgical robotics in a bid to optimise locomotion, spatial awareness, planning, and artificial curiosity. Results Numerous real-life examples demonstrate the feasibility of applying bayesian inference to humanoid robotics. Here we demonstrate a similar approach to adapting surgical robotics through the representation of sensory data through a probability density function over a group of unknown variables. In this manner, surgical robotics will be able to utilise sensory signals and can provide different weights to sensory cues, thereby efficiently integrating sensory input over space and time. Conclusions The free energy principle may be applied to surgical robotics to provide additional feedback, and control to improve patient prognosis.

The Hidden Brain: Uncovering Previously Overlooked Brain Regions by Employing Novel Preclinical Unbiased Network Approaches

A large focus of modern neuroscience has revolved around preselected brain regions of interest based on prior studies. While there are reasons to focus on brain regions implicated in prior work, the result has been a biased assessment of brain function. Thus, many brain regions that may prove crucial in a wide range of neurobiological problems, including neurodegenerative diseases and neuropsychiatric disorders, have been neglected. Advances in neuroimaging and computational neuroscience have made it possible to make unbiased assessments of whole-brain function and identify previously overlooked regions of the brain. This review will discuss the tools that have been developed to advance neuroscience and network-based computational approaches used to further analyze the interconnectivity of the brain. Furthermore, it will survey examples of neural network approaches that assess connectivity in clinical (i.e., human) and preclinical (i.e., animal model) studies and discuss how preclinical studies of neurodegenerative diseases and neuropsychiatric disorders can greatly benefit from the unbiased nature of whole-brain imaging and network neuroscience.

Learning to extract robust handcrafted features with a single observation via evolutionary neurogenesis

Recent advances in neuroscience demonstrate that neurogenesis in the human brain results in the born of new neurons, which evolve and replace mature neurons over time. This procedure causes a gradual reduction in the number of neurons, resulting in the human brain’s fast learning and thinking abilities. This paper models brain’s neurogenesis procedure by combining evolutionary algorithms with the Convolutional Neural Network (CNN) framework. This paper shows the promising effect of evolutionary neurogenesis by analyzing its performance for solving the challenging problem of handcrafted feature extraction, which is the primary requirement of all intelligent machines. The proposed approach benefits from the knowledge of a pre-trained CNN that contains mature neurons to evolve a newborn convolutional neuron, via Particle Swarm Optimization (PSO), to detect corners robustly. The proposed approach requires only a single training data to train a robust interest point detection model, and can be trained in about 20 min on CPU, which is significantly faster than other learning-based approaches. Besides, the results demonstrate that the proposed corner detection module outperforms existing techniques, in terms of robustness in various conditions, for approximately 20 percent. The proposed learning strategy can be generalized to solve other problems as well.

Historical reflection on Taijin-kyōfushō during COVID-19: a global phenomenon of social anxiety?

Although fear and anxiety have gradually become a shared experience in the time of COVID-19, few studies have examined its content from historical, cultural, and phenomenological perspectives concerning the self-awareness and alterity. We discuss the development of the ubiquitous nature of Taijin-kyōfushō (TKS), a subtype of social anxiety disorder (SAD) originated and considered culturally-bound in the 1930s Japan involving fear of offending or displeasing other people. Considering the historical processes of disease classification, advances in cognitive neurosciences, and the need to better understand the content of suffering, psychiatric nosology for SAD still appears controversial and requires further investigations.

Enhancing the developing brain: tensions between parent, child, and state in the United States.

ABSTRACTRecent technological advances in neuroscience offer a novel way for parents to nurture their children: altering brain activation to improve cognitive functions. Parental use and state regulation of cognitive enhancement will inevitably cause tensions between parent, child, and state. These tensions stem from three different but fundamentally related causes, namely minors’ incompetency in making decisions about their own welfare, parental autonomy to make decisions about the upbringing of their minor children, and the state’s interests in protecting minors’ well-being. However, these tensions are not without precedents. The courts have frequently struggled to set the boundary of parental autonomy and to balance parents’ rights, children’s interests, and state’s interests, and have accumulated extensive precedents in various contexts. This article reviews previous US court decisions in select contexts analogous to cognitive enhancement—medical intervention, education, and mandatory vaccination—and analyzes their implications for the use of cognitive enhancement on minors. This article will provide a useful guide for policy makers and researchers to identify and analyze issues regarding cognitive enhancement and to develop sound policies to ensure responsible use of this novel technology.

Vitamins and Cognition: A Nutrigenomics Perspective

The rise in the prevalence of neurodegenerative and neurodevelopmental cognitive disorders combined with a lack of efficient therapeutic strategies has necessitated the need to develop alternate approaches. Dietary supplements are now being considered as a complementary and alternative medicine for cognitive impairments. Considerable evidence suggests the role of vitamins in modulating the genetic and epigenetic factors implicated in neuropsychiatric, neurodevelopmental and neurodegenerative disorders. In this review, we provide an overview of the implications of nutrigenomics with reference to vitamins that are suggested to boost cognitive functions (nootropic vitamins). Several vitamins have been found to possess antioxidant and anti-inflammatory properties which make them potential candidates in preventing or delaying age-related neurodegeneration and cognitive decline. Well-designed longitudinal studies are essential to examine the association between vitamins and cognitive functions. Future studies linking nutrition with advances in neuroscience, genomics and epigenomics would provide novel approaches to managing cognitive disorders.

Consciousness as a domain of extraterritoriality

ABSTRACT Traditional understandings of extraterritoriality have overlooked human consciousness as an intimate province of territorial governance. Whereas traditional approaches to extraterritoriality often adopt a modernist understanding of territory, this article expands on the concept by referring to extraterritoriality as the process and practice of discovering, reifying and intervening in new domains of territorial governance. Insofar as territorial practices adapt in accordance with emergent knowledges and technologies, the realm of human consciousness appeared as an object of governmental interest during the mid-twentieth century alongside advances in neuroscience and psychopharmacology. Through the subsequent illegalisation of psychedelic plants and fungi, in combination with the hegemonic norms established through disciplinary institutions, the full spectrum of human consciousness has since become territorialised as a new domain of governmental intervention and management. As such, this article argues that the regulation of cognition enforced through drug prohibitions and sanctions enfold human consciousness as an extended domain of extraterritoriality.

Today’s psychiatric neuroscience advances were science fiction during my residency

Today’s psychiatric neuroscience advances were science fiction during my residency

Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies.

The development and application of quantitative systems pharmacology models in neuroscience have been modest relative to other fields, such as oncology and immunology, which may reflect the complexity of the brain. Technological and methodological advancements have enhanced the quantitative understanding of brain physiology and pathophysiology and the effects of pharmacological interventions. To maximize the knowledge gained from these novel data types, pharmacometrics modelers may need to expand their toolbox to include additional mathematical and statistical frameworks. A session was held at the 10th annual American Conference on Pharmacometrics (ACoP10) to highlight several recent advancements in quantitative and systems neuroscience. In this mini‐review, we provide a brief overview of technological and methodological advancements in the neuroscience therapeutic area that were discussed during the session and how these can be leveraged with quantitative systems pharmacology modeling to enhance our understanding of neurological diseases. Microphysiological systems using human induced pluripotent stem cells (IPSCs), digital biomarkers, and large‐scale imaging offer more clinically relevant experimental datasets, enhanced granularity, and a plethora of data to potentially improve the preclinical‐to‐clinical translation of therapeutics. Network neuroscience methodologies combined with quantitative systems models of neurodegenerative disease could help bridge the gap between cellular and molecular alterations and clinical end points through the integration of information on neural connectomics. Additional topics, such as the neuroimmune system, microbiome, single‐cell transcriptomic technologies, and digital device biomarkers, are discussed in brief.

Synchronization of interacted spiking neuronal networks with inhibitory coupling

• The synchronization index (SI) in two large interacted via inhibitory coupling networks oscillates periodically in time; the time intervals of high SI alternates with the time intervals of low SI. • The synchronization indexes in these networks exhibit either inphase or antiphase synchronization depending on the inhibitory coupling strength between them. We suppose that the underlying mechanism behind the antiphase dynamics lies in the cognitive resource redistribution between neuronal ensembles in the brain. • Excitatory coupling between the neurons inside the network affects the synchronization index. To maintain the neural network in the regimes of inphase or antiphase SI oscillations, we should keep a balance between excitatory and inhibitory connections. It suggests that the excitatory and the inhibitory currents should compensate each other. In other words, when one of them increases, the other must be increased too, and vice versa. • The coupling inside the input small network affects antiphase synchronization between two large networks. However, the scenario from positive and negative correlation and back between the large networks are only determined by inhibitory coupling between them. The development of mathematical models to describe neuronal interaction processes in the brain is a challenging task of nonlinear dynamics. Recent advances in biochemistry and neuroscience allow better understanding of biological mechanisms underlying the neuron functioning and synaptic connections between neurons. Moreover, significant progress in brain imaging sheds light on the structure of the brain network and certain aspects of neuronal dynamics. However, dynamical mechanisms leading to synchronization between different brain areas still remain unknown and require further investigation. To shed light on this issue, we consider two small-world networks of Hodgkin-Huxley neurons interacting via inhibitory coupling. We found that synchronization indices (SI) in both networks oscillate periodically in time, so that time intervals of high SI alternate with time intervals of low SI. Depending on the coupling strength, the two coupled networks can be in the regime of either in-phase or anti-phase synchronization. We suppose that the inherent mechanism behind such a behavior lies in the cognitive resource redistribution between neuronal ensembles of the brain.

Subcellular specificity of cannabinoid effects in striatonigral circuits

Recent advances in neuroscience have positioned brain circuits as key units in controlling behavior, implying that their positive or negative modulation necessarily leads to specific behavioral outcomes. However, emerging evidence suggests that the activation or inhibition of specific brain circuits can actually produce multimodal behavioral outcomes. This study shows that activation of a receptor at different subcellular locations in the same neuronal circuit can determine distinct behaviors. Pharmacological activation of type 1 cannabinoid (CB1) receptors in the striatonigral circuit elicits both antinociception and catalepsy in mice. The decrease in nociception depends on the activation of plasma membrane-residing CB1 receptors (pmCB1), leading to the inhibition of cytosolic PKA activity and substance P release. By contrast, mitochondrial-associated CB1 receptors (mtCB1) located at the same terminals mediate cannabinoid-induced catalepsy through the decrease in intra-mitochondrial PKA-dependent cellular respiration and synaptic transmission. Thus, subcellular-specific CB1 receptor signaling within striatonigral circuits determines multimodal control of behavior.

Nanoscale imaging of the functional anatomy of the brain

Abstract Progress in microscopy technology has a long history of triggering major advances in neuroscience. Super-resolution microscopy (SRM), famous for shattering the diffraction barrier of light microscopy, is no exception. SRM gives access to anatomical designs and dynamics of nanostructures, which are impossible to resolve using conventional light microscopy, from the elaborate anatomy of neurons and glial cells, to the organelles and molecules inside of them. In this review, we will mainly focus on a particular SRM technique (STED microscopy), and explain a series of technical developments we have made over the years to make it practical and viable in the field of neuroscience. We will also highlight several neurobiological findings on the dynamic structure-function relationship of neurons and glia cells, which illustrate the value of live-cell STED microscopy, especially when combined with other modern approaches to investigate the nanoscale behavior of brain cells.

Venus and Mars: The Importance of Sex In Late-Life Neuropsychiatric Disorders

Sex has increasingly become recognized as an important biological variable in brain disorders. Differences in the risk for both cognitive and emotional disorders by sex and gender are an increasing area of investigation. While women are at higher risk for depression and Alzheimer's disease, the causes of these differences are poorly understood and the implications for therapy not exploited in a systematic way. Advances in clinical and translational neuroscience have begun to reveal potential reasons for these sex differences. Differences in how men and women process emotional information and react to psychological and psychosocial stress as well as the unique hormone environment of women versus men have identified potential causative factors in the preponderance of mood disorders in women. New advances in brain imaging and analysis have revealed novel sex-related differences in structural network connectivity that affects the spread of abnormal proteins, which may help to explain sex-related differences in neurodegenerative disease. Hormonal changes that occur at menopause and beyond may have significant implications for how neurotransmitter system activity changes with normal and pathologic aging and may help to explain why women may be at higher risk for developing Alzheimer's disease. This session will explore advances in our understanding of sex differences in late life neuropsychiatric disorders including depression and neurodegenerative disease. For example, research has identified specific circuits in the brain that are sensitive to sex hormones and are involved in the processing of negative emotional information and in modulating response to psychological stress. These circuits react differentially to the presence of sex hormones and change following menopause and aging. These results may help explain sex differences in mood disorders and changes in sex ratios with normal aging. New research has identified sex-related differences in the spread of tau protein in the brains of patients with normal aging, with women showing more advanced spread and greater structural network connectivity. Whether this sex difference extends to early syndromes such as subjective cognitive decline is under investigation. Women may differ from men in the earliest expression of self-perceived cognitive symptoms due to changes at menopause. The role of gonadal steroids and other individual difference factors like lifetime hormone exposure as well mood and lifetime stress have the potential to modulate these relationships. Discussion will center on how this research may point the way towards sex-specific treatments, prevention strategies, and specific therapies.

Is mind–body dualism compatible with modern psychiatry?

SUMMARYMind–body dualism is often considered to be incompatible with modern psychiatry for two reasons. First, it is claimed that dualism is falsified by recent advances in neuroscience. Second, dualism is thought to lead to an unhelpful attitude towards patients and their illnesses. I reflect on and challenge both lines of thought and argue that there is no inherent conflict between dualism and psychiatry.