Neuroscience Principles Research Articles

Neuroscience of Adolescent Anorexia Nervosa: Implications for Family-Based Treatment (FBT).

Over the past 20 years significant progress has been made to elucidate some of the neurobiological underpinnings of the development and maintenance of anorexia nervosa and their possible implications for treatment. There is increasing evidence supporting the notion that anorexia nervosa shares neurobehavioral patterns with anxiety disorders and involves reward processing aberrations and habit formation. There is consensus for the need of early intervention to ameliorate the effects of starvation on the adolescent brain and the effects of illness duration on neurodevelopment. Family-based treatment (FBT) is the first line evidence-based treatment for adolescents with anorexia nervosa achieving sustainable full remission rates of over 40%. FBT has an agnostic treatment approach and its mechanisms of change have until now not been fully understood. To help fill this gap in theoretical understanding, this paper will provide a review of the treatment model of FBT through a neuroscientific lens. It argues that FBT is well designed to address the implications of current key findings of the neuroscience of anorexia nervosa and that it is also well aligned with the current understanding of neuroscience principles underpinning therapeutic change. The paper supports the perspective that FBT utilizes principles of parent facilitated exposure response prevention. It concludes that an integration of a neuroscience perspective to the provision of FBT will assist the clinician in their practice of FBT.

Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence.

Historically, neuroscience principles have heavily influenced artificial intelligence (AI), for example the influence of the perceptron model, essentially a simple model of a biological neuron, on artificial neural networks. More recently, notable recent AI advances, for example the growing popularity of reinforcement learning, often appear more aligned with cognitive neuroscience or psychology, focusing on function at a relatively abstract level. At the same time, neuroscience stands poised to enter a new era of large-scale high-resolution data and appears more focused on underlying neural mechanisms or architectures that can, at times, seem rather removed from functional descriptions. While this might seem to foretell a new generation of AI approaches arising from a deeper exploration of neuroscience specifically for AI, the most direct path for achieving this is unclear. Here we discuss cultural differences between the two fields, including divergent priorities that should be considered when leveraging modern-day neuroscience for AI. For example, the two fields feed two very different applications that at times require potentially conflicting perspectives. We highlight small but significant cultural shifts that we feel would greatly facilitate increased synergy between the two fields.

Neuroscience: alloy for early childhood education

It is intended to carry out a tour about the influence of neuroscience in early childhood education. It is important that all teachers, especially those working with infants, can know the fundamental principles of neuroscience and how the brain learns; thus have sufficient resources for decision making in school classrooms. This research paper attempts to make an introduction about the topic to be addressed and its focus on early childhood education.

Noise Helps Optimization Escape From Saddle Points in the Synaptic Plasticity.

Numerous experimental studies suggest that noise is inherent in the human brain. However, the functional importance of noise remains unknown. n particular, from a computational perspective, such stochasticity is potentially harmful to brain function. In machine learning, a large number of saddle points are surrounded by high error plateaus and give the illusion of the existence of local minimum. As a result, being trapped in the saddle points can dramatically impair learning and adding noise will attack such saddle point problems in high-dimensional optimization, especially under the strict saddle condition. Motivated by these arguments, we propose one biologically plausible noise structure and demonstrate that noise can efficiently improve the optimization performance of spiking neural networks based on stochastic gradient descent. The strict saddle condition for synaptic plasticity is deduced, and under such conditions, noise can help optimization escape from saddle points on high dimensional domains. The theoretical results explain the stochasticity of synapses and guide us on how to make use of noise. In addition, we provide biological interpretations of proposed noise structures from two points: one based on the free energy principle in neuroscience and another based on observations of in vivo experiments. Our simulation results manifest that in the learning and test phase, the accuracy of synaptic sampling with noise is almost 20% higher than that without noise for synthesis dataset, and the gain in accuracy with/without noise is at least 10% for the MNIST and CIFAR-10 dataset. Our study provides a new learning framework for the brain and sheds new light on deep noisy spiking neural networks.

Beyond Learning About the Brain: A Situated Approach to Training Teachers in Mind, Brain, and Education

ABSTRACTThe field of Mind, Brain, and Education (MBE) has debated the strategies and merit of training teachers in principles of neuroscience. A previous study argued for groups of teachers to be trained as “educational engineers” capable of translating the work of cognitive neuroscientists and education researchers into practical application. While several teacher education programs currently offer MBE courses, we offer a program description of a “situated learning” model of MBE that brings teachers to a unique pediatric hospital with a focus on neurodevelopmental disabilities. The aims of the program are to train educational engineers capable of improving special education services through applications of MBE. Teachers participating in this program learn about neurodevelopment, behavior, models of scientific knowledge acquisition, as well as applications of educational law, policy, leadership, and instruction. This unique program may offer a way to develop competent educational engineers capable of improving education for students with disabilities.

Bioelectronics for Millimeter-Sized Model Organisms.

Advances in microfabrication technologies and biomaterials have enabled a growing class of electronic devices that can stimulate and record bioelectronic signals. Many of these devices have been developed for humans or vertebrate animals, where miniaturization allows for implantation within the body. There are, however, another class of bioelectronic interfaces that exploit microfabrication and nanoelectronics to record signals from tiny, millimeter-sized organisms. In these cases, rather than implanting a device inside an animal, animals themselves are loaded in large numbers into bioelectronic devices for neural circuit and behavioral interrogation. These scalable interfaces provide platforms to develop new therapeutics as well as better understand basic principles of bioelectronic communication, neuroscience, and behavior. Here we review recent progress in these bioelectronic technologies and describe how they can complement on-chip optical, mechanical, and chemical interrogation methods to achieve high-throughput, multimodal studies of millimeter-sized small animals.

Studying convergent evolution to relate genotype to behavioral phenotype.

Neuroscience has a long, rich history in embracing unusual animals for research. Over the past several decades, there has been a technology-driven bottleneck in the species used for neuroscience research. However, an oncoming wave of technologies applicable to many animals hold promise for enabling researchers to address challenging scientific questions that cannot be solved using traditional laboratory animals. Here, we discuss how leveraging the convergent evolution of physiological or behavioral phenotypes can empower research mapping genotype to phenotype interactions. We present two case studies using electric fish and poison frogs and discuss how comparative work can teach us about evolutionary constraint and flexibility at various levels of biological organization. We also offer advice on the potential and pitfalls of establishing novel model systems in neuroscience research. Finally, we end with a discussion on the use of charismatic animals in neuroscience research and their utility in public outreach. Overall, we argue that convergent evolution frameworks can help identify generalizable principles of neuroscience.

A Computational Intelligence Paradigm with Human Computer Interface Learning

The cognitive Science is the leading technology which works on the principle of Neuroscience. Human Computer Interface is a challenging approach in neurosciences, which is the leading method to handle the brain activities to control external communications with the electronic devices for physically challenged human beings. The various HCI applications are developed with this advance technology. This helps in various patients which are physically challenged or facing the lock in syndrome, a condition where limbs are not functioning to full extent. Therefore, this paper is the review paper to the various EEG signal classification techniques using different taxonomy with techniques like linear, nonlinear, stableubstable, static-discriminant to design various HCI applications.

Bridge to neuroscience workshop: An effective educational tool to introduce principles of neuroscience to Hispanics students.

Neuroscience as a discipline is rarely covered in educational institutions in Puerto Rico. In an effort to overcome this deficit we developed the Bridge to Neuroscience Workshop (BNW), a full-day hands-on workshop in neuroscience education. BNW was conceived as an auxiliary component of a parent recruitment program called Bridge to the PhD in Neuroscience Program (BPNP). The objectives of BNW are to identify promising students for BPNP, and to increase awareness of neuroscience as a discipline and a career option. BNW introduces basic concepts in neuroscience using a variety of educational techniques, including mini-lectures, interactive discussions, case studies, experimentation, and a sheep brain dissection. Since its inception in 2011 BNW has undergone a series of transformations that continue to improve upon an already successful and influential educational program for underrepresented minorities. As of Fall 2018, we have presented 21 workshops, impacting 200 high school and 424 undergraduate students. BNW has been offered at University of Puerto Rico (UPR)-Arecibo, UPR-Cayey, UPR-Humacao, Pontificia Universidad Católica de Ponce, and Universidad Interamericana de Puerto Rico-Arecibo. A pre-and post evaluation was given to evaluate material comprehension and thus measure effectiveness of our one-day interactive workshop. Our results suggest that both high school and undergraduate students have little prior knowledge of neuroscience, and that participation in BNW improves not only understanding, but also enthusiasm for the discipline. Currently, our assessment has only been able to evaluate short-term effects (e.g. comprehension and learning). Therefore, our current focus is developing methods capable of determining how participation in BNW impacts future academic and career decisions.

Control modeling toward understanding articulatory disfluency in autism spectrum disorder

Speech control models founded on principles of neuroscience have potential to create powerful clinical tools for personalized medicine and for understanding behavior. We explore two prominent speech control models: Directions into Velocities of Articulators (DIVA) (Guenther, 2006) and Task Dynamics (TD) (Saltzman, 1991) toward an understanding of speech disfluency of autism spectrum disorder (ASD). To introduce perturbations into both systems in the common framework of (Parrrell, 2018), we translate the TD model into MATLAB Simulink. For word stimuli, we compare both models’ acoustic outputs, under the hypothesis that speech impediments in ASD arise from overreliance on delayed sensory feedback (Lin, 2015). For DIVA, the output from a 50ms auditory feedback delay contain increased formant production errors and formant oscillations at about 10Hz, sometimes observed in disfluent ASD cases, but also seen in stuttering (Civier, 2010). The same delay introduced in the proprioceptive and tactile feedback in TD takes 5x the time to settle at the target, creating about 20Hz oscillations in TD articulators. Though neither fully capturing disfluency in ASD, together these models lay the groundwork for a more complete neurocomputational speech control model that can be used to longitudinally track and potentially guide ASD speech therapy.

Learning to synchronize: How biological agents can couple neural task modules for dealing with the stability-plasticity dilemma.

We provide a novel computational framework on how biological and artificial agents can learn to flexibly couple and decouple neural task modules for cognitive processing. In this way, they can address the stability-plasticity dilemma. For this purpose, we combine two prominent computational neuroscience principles, namely Binding by Synchrony and Reinforcement Learning. The model learns to synchronize task-relevant modules, while also learning to desynchronize currently task-irrelevant modules. As a result, old (but currently task-irrelevant) information is protected from overwriting (stability) while new information can be learned quickly in currently task-relevant modules (plasticity). We combine learning to synchronize with task modules that learn via one of several classical learning algorithms (Rescorla-Wagner, backpropagation, Boltzmann machines). The resulting combined model is tested on a reversal learning paradigm where it must learn to switch between three different task rules. We demonstrate that our combined model has significant computational advantages over the original network without synchrony, in terms of both stability and plasticity. Importantly, the resulting models’ processing dynamics are also consistent with empirical data and provide empirically testable hypotheses for future MEG/EEG studies.

Ecological cocktail party listening reveals the utility of extended high-frequency hearing

A fundamental principle of neuroscience is that each species' and individual's sensory systems are tailored to meet the demands placed upon them by their environments and experiences. What has driven the upper limit of the human frequency range of hearing? The traditional view is that sensitivity to the highest frequencies (i.e., beyond 8 kHz) facilitates localization of sounds in the environment. However, this has yet to be demonstrated for naturally occurring non-speech sounds. An alternative view is that, for social species such as humans, the biological relevance of conspecific vocalizations has driven the development and retention of auditory system features. Here, we provide evidence for the latter theory. We evaluated the contribution of extended high-frequency (EHF) hearing to common ecological speech perception tasks. We found that restricting access to EHFs reduced listeners' discrimination of talker head orientation by approximately 34%. Furthermore, access to EHFs significantly improved speech recognition under listening conditions in which the target talker's head was facing the listener while co-located background talkers faced away from the listener. Our findings raise the possibility that sensitivity to the highest audio frequencies fosters communication and socialization of the human species. These findings suggest that loss of sensitivity to the highest frequencies may lead to deficits in speech perception. Such EHF hearing loss typically goes undiagnosed, but is widespread among the middle-aged population.

Neural Foundations of Ayres Sensory Integration®.

Sensory integration, now trademarked as Ayres Sensory Integration® or ASI, is based on principles of neuroscience and provides a framework for understanding the contributions of the sensory and motor foundations of human behavior. The theory and practice of ASI continues to evolve as greater understanding of the neurobiology of human behavior emerges. In this paper we examine core constructs of ASI identified in the seminal work of Dr. Jean Ayres, and present current neuroscience research that underlies the main patterns of sensory integration function and dysfunction. We consider how current research verifies and clarifies Ayres’ propositions by describing functions of the vestibular, proprioceptive, and tactile sensory systems, and exploring their relationships to ocular, postural, bilateral integration, praxis, and sensory modulation. We close by proposing neuroplasticity as the mechanisms underlying change as a result of ASI intervention.

(Invited) Ferroelectric Devices for Alternative, Non-Von Neumann Computing

In the post-Moore era of electronics, significant interests are developing around new models of computation that overcome the bottlenecks of traditional von Neumann architectures, and draw features from the neuro-scientific principles of biological brains. In physically implementing those alternative kernels, emerging nanoelectronic materials and devices show great promise in terms of power efficiency and compactness due to their interesting features (such as hysteresis, non-volatility, plasticity, stochasticity, polymorphism)--features that are not readily available in CMOS platforms. The ferroelectric field-effect transistor (FeFET) is such an emerging device where a ferroelectric oxide is introduced into the gate oxide stack of a field-effect transistor. In this talk, we will present how the FeFET technology could be utilized for implementing non-von Neumann computing systems such as coupled neuro-oscillatory networks and spiking neural networks. The talks will include recent experimental results in tandem with theoretical calculations and simulations.

Mind in the brain - creation of the greatest virtual world

Human mind is a functional capability of the brain, by which information about sensory-motor contacts made through the nervous system are perceived and interpreted by the mind. While the detection and interpretations are subjective and experiential, they are based purely on a cascade of neurocognitive processes that unfold in the brain in response to external events or sequential changes detected over time and space. Experiential or subjective interpretations are generally based on the selected choices, and often depend on the cognitive judgments made by the individual. The cognitive judgments mold the drive present in the individual and it is experienced as positive or negative emotions by the individual. Drive is the fuel or energy present in the system for all responses and actions related to "seeking", and they are automatically initiated when the drive reaches a Critical Level of Potentiation. It is possible for an individual to become aware of the presence of the drive as well as the process of initiation of actions in the attempt to satisfying the drive. Scientific observations of the changes that occur in the physical and social environment, which are normally detected by the sensory-motor systems, are repeatable and explain the time-space sequential relationships that exist in the physical universe. The major role of the mind is the experiential detection and interpretations of the sensory-motor events, which are experienced and expressed by the mental processes related to detection and expression. Subjective interpretations are generally based on personal experiences, which are highly suggestable and as per the needs experienced at personal and group levels by the individual minds. Individuals create goals and purposes for all actions, and in the process, the new functional systems of the mind are also created according to neuroscientific principles. The physical world shaped by the humans using science and technology for superior facilities are distinctly different from the functional world created for personal satisfaction, happiness, and as per their belief systems. One of the basic cognitive functions of human mind is to find meaningful associations among the elements within the universe in order to achieve the self-defined purposes of life in various ways. Mind is indeed the greatest natural apparatus, naturally evolved in the human brain and could develop signal generation and higher-order processing abilities. Ability to sequentially relate multi-modal signals across time and space, which help to make sensory-motor contacts with the inside and outside worlds, gives rise to cognitive functioning. Such processing in the brain produces concepts, thoughts, and communications, which may be essential for creating descriptive accounts of effective functioning in the living world. These cognitive functions helped to mold the motivational and emotional processes leading to advancements in civilization and culture. While scientific thinking considering relationships across space and time helped creation of new physical realities of innovations and technologies, functional systems help achieve higher levels of mental and social functioning

International Neuroinformatics Coordinating Facility Review Criteria for Endorsement of Standards and Best Practices v. 1.0

The International Neuroinformatics Coordinating Facility (INCF) is a standards organization for open and FAIR neuroscience that develops, evaluates, and endorses standards and best practices that embrace the principles of Open, FAIR, and Citable neuroscience. The purpose of this document is to describe the criteria used in INCF's formal procedure for evaluating and endorsing community standards and best practices.

Selected Principles of Pankseppian Affective Neuroscience.

In the early nineties of the twentieth century Jaak Panksepp coined the term “Affective Neuroscience” (AN) today being accepted as a unique research area in cross-species brain science. By means of (i) electrical stimulation, (ii) pharmacological challenges, and (iii) brain lesions of vertebrate brains (mostly mammalian), Panksepp carved out seven primary emotional systems called SEEKING, CARE, PLAY, and LUST on the positive side, whereas FEAR, SADNESS, and ANGER belong to the negative affects. Abundant research into human clinical applications has supported the hypothesis that imbalances in these ancient primary emotional systems are strongly linked to psychiatric disorders such as depression. The present paper gives a concise overview of Panksepp's main ideas. It gives an historical overview of the development of Panksepp's AN thinking. It touches not only areas of neuroscience, but also shows how AN has been applied to other research fields such as personality psychology. Finally, the present work gives a brief overview of the main ideas of AN.

Toward Functional Restoration of the Central Nervous System: A Review of Translational Neuroscience Principles.

Injury to the central nervous system (CNS) can leave patients with devastating neurological deficits that may permanently impair independence and diminish quality of life. Recent insights into how the CNS responds to injury and reacts to critically timed interventions are being translated into clinical applications that have the capacity to drastically improve outcomes for patients suffering from permanent neurological deficits due to spinal cord injury, stroke, or other CNS disorders. The translation of such knowledge into practical and impactful treatments involves the strategic collaboration between neurosurgeons, clinicians, therapists, scientists, and industry. Therefore, a common understanding of key neuroscientific principles is crucial. Conceptually, current approaches to CNS revitalization can be divided by scale into macroscopic (systems-circuitry) and microscopic (cellular-molecular). Here we review both emerging and well-established tenets that are being utilized to enhance CNS recovery on both levels, and we explore the role of neurosurgeons in developing therapies moving forward. Key principles include plasticity-driven functional recovery, cellular signaling mechanisms in axonal sprouting, critical timing for recovery after injury, and mechanisms of action underlying cellular replacement strategies. We then discuss integrative approaches aimed at synergizing interventions across scales, and we make recommendations for the basis of future clinical trial design. Ultimately, we argue that strategic modulation of microscopic cellular behavior within a macroscopic framework of functional circuitry re-establishment should provide the foundation for most neural restoration strategies, and the early involvement of neurosurgeons in the process will be crucial to successful clinical translation.

Mind in the Brain – Creation of the Greatest Virtual World

Human mind is a functional capability of the brain, by which information about sensory-motor contacts made through the nervous system are perceived and interpreted by the mind. While the detection and interpretations are subjective and experiential, they are based purely on a cascade of neurocognitive processes that unfold in the brain in response to external events or sequential changes detected over time and space. Experiential or subjective interpretations are generally based on the selected choices, and often depends on the cognitive judgments made by the individual. The cognitive judgments mold the drive present in the individual and it is experienced as positive or negative emotions by the individual. Drive is the fuel or energy present in the system for all responses and actions related to “seeking”, and they are automatically initiated when the drive reaches a Critical Level of Potentiation (Mukundan et al. 1). It is possible for an individual to become aware of the presence of the drive as well as the process of initiation of actions in the attempt to satisfying the drive. Scientific observations of the changes that occur in the physical and social environment, which are normally detected by the sensory-motor systems are repeatable and explain the time-space sequential relationships that exist in the physical universe. The major role of the mind is the experiential detection and interpretations of the sensory-motor events, which are experienced and expressed by the mental processes related to detection and expression. Subjective interpretations are generally based on personal experiences, which are highly suggestable and as per the needs experienced at personal and group levels by the individual minds. Individuals create goals and purposes for all actions, and in the process, the new functional systems of the mind are also created according to neuroscientific principles. The physical world shaped by man scientifically for superior facilities are distinctly different from the functional world created for personal satisfaction, happiness, and as per their belief systems. Cognitively human mind may consider it necessary to find meaningful associations among the elements within the universe, and specifically for the purpose of life. Mind is indeed the greatest natural apparatus, naturally evolved in the human brain and could develop signal generation and processing abilities. Ability to sequentially relate signals across time and space became scientific processing, whereas simultaneous processing of signals helped create additional systems with purposeful functioning of the parts. Such processing using signals helped to create concepts, and find meaningful relationships of signals across time and space. Scientific thinking facilitated creation of new physical realities, whereas considering relationships across space and time helped creation of functional systems, meaningful only when simultaneous relationships could be established.

Virtual Reality as a Vehicle to Empower Motor-Cognitive Neurorehabilitation.

In this paper, we advocate the combination of four key ingredients that we believe are necessary to design long-lasting effective treatments for neurorehabilitation: (i) motor-cognitive training, (ii) evidence-based neuroscience principles, in particular those related to body perception, (iii) motivational games, and (iv) empowerment techniques. Then, we propose virtual reality (VR) as the appropriate medium to encompass all the requirements mentioned above. VR is arguably one of the most suitable technologies for neurorehabilitation able to integrate evidence-based neurorehabilitation techniques and neuroscience principles into motivating training approaches that promote self-management by empowering patients to own their recovery process. We discuss the advantages and challenges of such an approach on several exemplary applications and outline directions for future developments. We strongly believe that the combination of positive psychology and positive technology mediated by VR-based interventions can heavily impact the rehabilitation outcomes of motor-cognitive functions along all the stages of the rehabilitation path.