Neuroscience Paradigms Research Articles

Perceptually-guided deep neural networks for ego-action prediction: Object grasping

We tackle the problem of predicting a grasping action in ego-centric video for the assistance to upper-limb amputees. Our work is based on paradigms of neuroscience that state that human gaze expresses intention and anticipates actions. In our scenario, human gaze fixations are recorded by a glass-worn eye-tracker and then used to predict the grasping actions. We have studied two aspects of the problem: which object from a given taxonomy will be grasped, and when is the moment to trigger the grasping action. To recognize objects, we using gaze to guide Convolutional Neural Networks (CNN) to focus on an object-to-grasp area. However, the acquired sequence of fixations is noisy due to saccades toward distractors and visual fatigue, and gaze is not always reliably directed toward the object-of-interest. To deal with this challenge, we use video-level annotations indicating the object to be grasped and a weak loss in Deep CNNs. To detect a moment when a person will take an object we take advantage of the predictive power of Long-Short Term Memory networks to analyze gaze and visual dynamics. Results show that our method achieves better performance than other approaches on a real-life dataset.

Brain Energy and Oxygen Metabolism: Emerging Role in Normal Function and Disease.

Dynamic metabolic changes occurring in neurons are critically important in directing brain plasticity and cognitive function. In other tissue types, disruptions to metabolism and the resultant changes in cellular oxidative state, such as increased reactive oxygen species (ROS) or induction of hypoxia, are associated with cellular stress. In the brain however, where drastic metabolic shifts occur to support physiological processes, subsequent changes to cellular oxidative state and induction of transcriptional sensors of oxidative stress likely play a significant role in regulating physiological neuronal function. Understanding the role of metabolism and metabolically-regulated genes in neuronal function will be critical in elucidating how cognitive functions are disrupted in pathological conditions where neuronal metabolism is affected. Here, we discuss known mechanisms regulating neuronal metabolism as well as the role of hypoxia and oxidative stress during normal and disrupted neuronal function. We also summarize recent studies implicating a role for metabolism in regulating neuronal plasticity as an emerging neuroscience paradigm.

Kuhnian revolutions in neuroscience: the role of tool development

The terms “paradigm” and “paradigm shift” originated in “The Structure of Scientific Revolutions” by Thomas Kuhn. A paradigm can be defined as the generally accepted concepts and practices of a field, and a paradigm shift its replacement in a scientific revolution. A paradigm shift results from a crisis caused by anomalies in a paradigm that reduce its usefulness to a field. Claims of paradigm shifts and revolutions are made frequently in the neurosciences. In this article I will consider neuroscience paradigms, and the claim that new tools and techniques rather than crises have driven paradigm shifts. I will argue that tool development has played a minor role in neuroscience revolutions.

Statistical power comparisons at 3T and 7T with a GO / NOGO task

The field of cognitive neuroscience is weighing evidence about whether to move from standard field strength to ultra-high field (UHF). The present study contributes to the evidence by comparing a cognitive neuroscience paradigm at 3 Tesla (3T) and 7 Tesla (7T). The goal was to test and demonstrate the practical effects of field strength on a standard GO/NOGO task using accessible preprocessing and analysis tools. Two independent matched healthy samples (N = 31 each) were analyzed at 3T and 7T. Results show gains at 7T in statistical strength, the detection of smaller effects and group-level power. With an increased availability of UHF scanners, these gains may be exploited by cognitive neuroscientists and other neuroimaging researchers to develop more efficient or comprehensive experimental designs and, given the same sample size, achieve greater statistical power at 7T.

Finding the needle in the haystack: systematic identification of psychobiotics.

The brain-gut-microbiota axis is increasingly viewed as a novel paradigm in neuroscience with the capacity to generate innovative therapies for patients with psychiatric illnesses. Psychobiotics, defined as live bacteria, which when ingested in adequate amounts, confer mental health benefits, are increasingly of interest, as preclinical trials continue to show promising results. Particularly in stress-related, anxiety and depressive disorders, there is potential for psychobiotics to deliver new therapies. The question of which microbes may prove to be the most promising psychobiotic in delivering such therapies at a clinical level is of great importance. Here we look at the characteristics of psychobiotics, in an attempt to present an outline from which the identification of potential new psychobiotics may be possible. LINKED ARTICLES: This article is part of a themed section on When Pharmacology Meets the Microbiome: New Targets for Therapeutics? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.24/issuetoc.

Characterizing neurocognitive late effects in childhood leukemia survivors using a combination of neuropsychological and cognitive neuroscience measures

ABSTRACTKnowledge about cognitive late effects in survivors of childhood acute lymphoblastic leukemia (ALL) is largely based on standardized neuropsychological measures and parent reports. To examine whether cognitive neuroscience paradigms provided additional insights into neurocognitive and behavioral late effects in ALL survivors, we assessed cognition and behavior using a selection of cognitive neuroscience tasks and standardized measures probing domains previously demonstrated to be affected by chemotherapy.130 ALL survivors and 158 control subjects, between 8 and 18 years old at time of testing, completed the n-back (working memory) and stop-signal (response inhibition) tasks. ALL survivors also completed standardized measures of intelligence (Wechsler Intelligence Scales [WISC-IV]), motor skills (Grooved Pegboard), math abilities (WIAT-III), and executive functions (Delis–Kaplan Executive Function System). Parents completed behavioral measures of executive functions (Behavior Rating Inventory of Executive Function [BRIEF]) and attention (Conners-3).ALL survivors exhibited deficiencies in working memory and response inhibition compared with controls. ALL survivors also exhibited deficits on WISC-IV working memory and processing speed, Grooved Pegboard, WIAT-III addition and subtraction fluency, and numerical operations, as well as DKEFS number-letter switching. Parent reports suggested more attention deficits (Conners-3) and behavioral difficulties (BRIEF) in ALL survivors compared with referenced norms. Low correspondence between standardized and experimental measures of working memory and response inhibition was noted.The use of cognitive neuroscience paradigms complements our understanding of the cognitive deficits evident after treatment of ALL. These measures could further delineate cognitive processes involved in neurocognitive late effects, providing opportunities to explore their underlying mechanisms.

Brain-Gut-Microbiota Axis and Mental Health.

The brain-gut-microbiota axis has been put forward as a new paradigm in neuroscience, which may be of relevance to mental illness. The mechanisms of signal transmission in the brain-gut-microbiota axis are complex and involve bidirectional communications that enable gut microbes to communicate with the brain and the brain to communicate with the microbes. This review assesses the potential usefulness and limitations of the paradigm. A selective literature review was conducted to evaluate the current knowledge in clinical and preclinical brain-gut-microbiota interactions as related to psychiatric disorders. Most published studies in the field are preclinical, and there is so far a lack of clinical studies. Preliminary studies in psychiatric populations support the view of a dysbiosis in some conditions, but studies are often small scale and marred by potential confounding variables. Preclinical studies support the view that psychobiotics ("bacteria which when ingested in adequate amounts have a positive mental health benefit") might be of use in treating some patients with mental health difficulties. To date, we have no well-conducted studies in clinical populations, although there are some studies in healthy volunteers. A cocktail of probiotics has been shown to alter brain activity as monitored by functional magnetic resonance imaging, and Bifidobacterium longum was reported to alter brain electrical activity. It has yet to be convincingly demonstrated that the exciting findings of psychobiotic efficacy demonstrated in preclinical models of psychiatric illness will translate to patients.

From Anomalies to Essential Scientific Revolution? Intrinsic Brain Activity in the Light of Kuhn's Philosophy of Science.

The first step toward a modern understanding of fMRI resting brain activity was made by Bharat Biswal in 1995. This surprising, and at first rejected, discovery is now associated with many resting state networks, notably the famous default mode network (DMN). Resting state activity and DMN significantly reassessed our traditional beliefs and conventions about the functioning of the brain. For the majority of the twentieth century, neuroscientists assumed that the brain is mainly the “reactive engine” to the environment operating mostly through stimulation. This “reactive convention” was very influential and convenient for the goals of twentieth century neuroscience–non-invasive functional localization based on stimulation. Largely unchallenged, “reactive convention” determined the direction of scientific research for a long time and became the “reactive paradigm” of the twentieth century. Resting state activity brought knowledge that was quite different of the “reactive paradigm.” Current research of the DMN, probably the best known resting state network, leads to entirely new observations and conclusions, which were not achievable from the perspective of the “reactive paradigm.” This shift from reactive activity to resting state activity of the brain is accompanied by an important question: “Can resting state activity be considered a scientific revolution and the new paradigm of neuroscience, or is it only significant for one branch of neuroscience, such as fMRI?”

Alignment in social interactions

According to the prevailing paradigm in social-cognitive neuroscience, the mental states of individuals become shared when they adapt to each other in the pursuit of a shared goal. We challenge this view by proposing an alternative approach to the cognitive foundations of social interactions. The central claim of this paper is that social cognition concerns the graded and dynamic process of alignment of individual minds, even in the absence of a shared goal. When individuals reciprocally exchange information about each other's minds processes of alignment unfold over time and across space, creating a social interaction. Not all cases of joint action involve such reciprocal exchange of information. To understand the nature of social interactions, then, we propose that attention should be focused on the manner in which people align words and thoughts, bodily postures and movements, in order to take one another into account and to make full use of socially relevant information.

Translating neuroscience, psychology and education: An abstracted conceptual framework for the learning sciences

Educators strive to understand and apply knowledge gained through scientific endeavours. Yet, within the various sciences of learning, particularly within educational neuroscience, there have been instances of seemingly contradictory or incompatible research findings and theories. We argue that this situation arises through confusion between levels of analysis applicable to various disciplines. In this article, we propose a conceptual framework for the science of learning which integrates sociological, psychological, biological and neurological perspectives of learning. This framework seeks to recognise the distinction between learning—essentially a complex neurological phenomenon—and education, an even more complex sociocultural phenomenon. As such, the framework allows a coherent perspective to emerge that can help resolve a number of key issues. Specifically, we argue that its adoption will (a) provide the science of learning with a foundation to assist in the development of a translational paradigm for neuroscience, psychology and education professionals, (b) enable neuromyths to be more easily identified and (c) help prevent unhelpful debates in the future.

The Predictive Processing Paradigm Has Roots in Kant.

Predictive processing (PP) is a paradigm in computational and cognitive neuroscience that has recently attracted significant attention across domains, including psychology, robotics, artificial intelligence and philosophy. It is often regarded as a fresh and possibly revolutionary paradigm shift, yet a handful of authors have remarked that aspects of PP seem reminiscent of the work of 18th century philosopher Immanuel Kant. To date there have not been any substantive discussions of how exactly PP links back to Kant. In this article, I argue that several core aspects of PP were anticipated by Kant (1996/1787) in his works on perception and cognition. Themes from Kant active in PP include: (1) the emphasis on “top-down” generation of percepts; (2) the role of “hyperpriors”; (3) the general function of “generative models”; (4) the process of “analysis-by-synthesis”; and (5) the crucial role of imagination in perception. In addition to these, I also point out that PP echoes Kant’s general project in that it aims to explain how minds track causal structure in the world using only sensory data, and that it uses a reverse-engineer or “top-down” method of analysis. I then locate a possible source of Kant’s influence on PP by tracing the paradigm back to Hermann von Helmholtz, who saw himself as providing a scientific implementation of Kant’s conclusions. I conclude by arguing that PP should not be regarded as a new paradigm, but is more appropriately understood as the latest incarnation of an approach to perception and cognition initiated by Kant and refined by Helmholtz.

Neurons versus Networks: The Interplay between Individual Neurons and Neural Networks in Cognitive Functions

The main paradigm of cognitive neuroscience is the connectionist concept postulating that the higher nervous activity is performed through interactions of neurons forming complex networks, whereas the function of individual neurons is restricted to generating electrical potentials and transmitting signals to other cells. In this article, I describe the observations from three fields—neurolinguistics, physiology of memory, and sensory perception—that can hardly be explained within the constraints of a purely connectionist concept. Rather, these examples suggest that cognitive functions are determined by specific properties of individual neurons and, therefore, are likely to be accomplished primarily at the intracellular level. This view is supported by the recent discovery that the brain’s ability to create abstract concepts of particular individuals, animals, or places is performed by neurons (“concept cells”) sparsely distributed in the medial temporal lobe.

Correlative Light Electron Microscopy: Connecting Synaptic Structure and Function.

Many core paradigms of contemporary neuroscience are based on information obtained by electron or light microscopy. Intriguingly, these two imaging techniques are often viewed as complementary, yet separate entities. Recent technological advancements in microscopy techniques, labeling tools, and fixation or preparation procedures have fueled the development of a series of hybrid approaches that allow correlating functional fluorescence microscopy data and ultrastructural information from electron micrographs from a singular biological event. As correlative light electron microscopy (CLEM) approaches become increasingly accessible, long-standing neurobiological questions regarding structure-function relation are being revisited. In this review, we will survey what developments in electron and light microscopy have spurred the advent of correlative approaches, highlight the most relevant CLEM techniques that are currently available, and discuss its potential and limitations with respect to neuronal and synapse-specific applications.

Brain plasticity and rehabilitation by using Near-Infrared Spectroscopy

The present review elucidated the use of optical imaging technique (Near-Infrared Spectroscopy, NIRS) to better explain the brain plasticity for learning mechanisms, rehabilitation and post-traumatic brain recovery. Some recent applications were discussed, with specific focus on the usability of integrated measures (such as electroencephalography, EEG-NIRS; Transcranial Magnet Stimulation, TMS-NIRS) to study plasticity and its dynamic effects. NIRS-Neurofeedback and NIRS-BCI (Brain Computer Interface) were also explored as possible tools to produce a specific long-lasting learning in relationship with a specific cognitive domain. Finally a proficient domain where NIRS was found to be useful to test neuroplasticity is the interpersonal brain-tobrain coupling, termed “hyperscanning”, a new emerging paradigm in neuroscience which measures brain activity from two or more people simultaneously.

Intelligence vs. Artificial Intelligence: The King Is Naked

The sociological dimension of Artificial Intelligence (AI), and automation, is placed in the path traced by the man-machine integration process, started in the eighteenth century by the Industrial Revolution that assumes its current connotation after World War II. The use of the term intelligence, which appears in the expression Artificial Intelligence, is shown to be improper and misleading, and the expression itself should be replaced, eventually, by Artificial Simulation of the Savant Syndrome. By adopting a theoretical perspective, namely Endo-Dynamo-Tensive Model [Messori 2012B], it is traced the mapping of human’s neurological (neuro-dynamics) and psychological (psycho-dynamics) dimension, and is provided the coordinates to be followed in the phenomenological qualification and definition of the psychic-mental-cognitive function intelligence. The neuro-dynamics of the Nervous System (NS), is taken into account by adopting the theoretical, interpretative and investigative perspective indicated by the particular line of research developed in the context of Quantum Field Theory (QFT) and QED (Quantum Electrodynamic Field Theory), that describes the water of which all living systems are composed, i.e. biological water, as water in a coherent oscillatory phase or state other than that of common water, named super-coherent oscillatory state. By introducing the possible functional role exerted within brain activity by glial cells, cerebrospinal fluid, intra- and extra-cellular fluid is outlined the overcoming of the classical neuroscience paradigm, based on the vision of brain activity as ruled by networks of neurons interconnected by synapses. The body-mind hard problem is taken into account and a solution is advanced. The psycho-dynamics of the humans mind territory is taken into account according to the four poles of mental functions introduced by C.G. Jung in his Psychological Types (1921), where he introduces a hierarchy of mental functions in two mental bipolar dimensions (dichotomies). These are sensing (attentiveness by means of the sense organs) coupled to intuition (awareness in unconscious way or being aware of unconscious contents) and thinking (function of intellectual cognition; the forming of logical conclusions) coupled to feeling (function of subjective estimation). At the conclusion of this work, it is provided the phenomenological definition of intelligence that does not contemplate the possibility to apply to neuroscience, and to natural and human sciences in general, the paradigm that inspires the research on AI, i.e. computational model and Information Theory.

Editorial: Decision-making experiments under a philosophical analysis: human choice as a challenge for neuroscience.

Editorial: Decision-making experiments under a philosophical analysis: human choice as a challenge for neuroscience.

From the neuron doctrine to neural networks.

For over a century, the neuron doctrine--which states that the neuron is the structural and functional unit of the nervous system--has provided a conceptual foundation for neuroscience. This viewpoint reflects its origins in a time when the use of single-neuron anatomical and physiological techniques was prominent. However, newer multineuronal recording methods have revealed that ensembles of neurons, rather than individual cells, can form physiological units and generate emergent functional properties and states. As a new paradigm for neuroscience, neural network models have the potential to incorporate knowledge acquired with single-neuron approaches to help us understand how emergent functional states generate behaviour, cognition and mental disease.

Emergence, Adaptation, and Relational Improvisation: Commentary on Terry Marks-Tarlow’s “From Emergency to Emergence: The Deep Structure of Play in Psychotherapy”

Dr. Marks-Tarlow’s paper provides a valuable examination of play processes in psychotherapy, using the novel synthesis of psychoevolutionary and nonlinear dynamical perspectives. The author’s sophisticated blend of psychobiological and intersubjective accounts is of great clinical value, illustrating the need for a rapprochement between affective neuroscience, intersubjectivity, and complexity paradigms. Comparisons are made to the Dynamical Systems Therapy 10 (DST) model (Shapiro, this issue), which similarly aims to integrate psychobiological and intersubjective accounts of psychopathology with internal representations.

Towards oscillations-based simulation of social systems: a neurodynamic approach

This multidisciplinary work presents synopsis of theories in the search for common field-like fundamental principles of self-organisation and communication existing on quantum, cellular, and even social levels. Based on these fundamental principles, we formulate conceptually novel social neuroscience paradigm (OSIMAS), which envisages social systems emerging from the coherent neurodynamical processes taking place in the individual mind-fields. In this way, societies are understood as global processes emerging from the superposition of the conscious and subconscious mind-fields of individual members of society. For the experimental validation of the biologically inspired OSIMAS paradigm, we have designed a framework of EEG-based experiments. Initial baseline individual tests of spectral cross-correlations of EEG-recorded brainwave patterns for some mental states have been provided in this paper. Preliminary experimental results do not refute the main OSIMAS postulates. This paper also provides some insights for the construction of OSIMAS-based simulation models.

Big data, open science and the brain: lessons learned from genomics.

The BRAIN Initiative aims to break new ground in the scale and speed of data collection in neuroscience, requiring tools to handle data in the magnitude of yottabytes (1024). The scale, investment and organization of it are being compared to the Human Genome Project (HGP), which has exemplified “big science” for biology. In line with the trend towards Big Data in genomic research, the promise of the BRAIN Initiative, as well as the European Human Brain Project, rests on the possibility to amass vast quantities of data to model the complex interactions between the brain and behavior and inform the diagnosis and prevention of neurological disorders and psychiatric disease. Advocates of this “data driven” paradigm in neuroscience argue that harnessing the large quantities of data generated across laboratories worldwide has numerous methodological, ethical and economic advantages, but it requires the neuroscience community to adopt a culture of data sharing and open access to benefit from them. In this article, we examine the rationale for data sharing among advocates and briefly exemplify these in terms of new “open neuroscience” projects. Then, drawing on the frequently invoked model of data sharing in genomics, we go on to demonstrate the complexities of data sharing, shedding light on the sociological and ethical challenges within the realms of institutions, researchers and participants, namely dilemmas around public/private interests in data, (lack of) motivation to share in the academic community, and potential loss of participant anonymity. Our paper serves to highlight some foreseeable tensions around data sharing relevant to the emergent “open neuroscience” movement.