It’s about time: Linking dynamical systems with human neuroimaging to understand the brain

Most human neuroscience research to date has focused on statistical approaches that describe stationary patterns of localized neural activity or blood flow. While these patterns are often interpreted in light of dynamic, information-processing concepts, the static, local and inferential nature of the statistical approach makes it challenging to directly link neuroimaging results to plausible underlying neural mechanisms. Here, we argue that dynamical systems theory provides the crucial mechanistic framework for characterizing both the brain’s time-varying quality and its partial stability in the face of perturbations, and hence, that this perspective can have a profound impact on the interpretation of human neuroimaging results and their relationship with behavior. After briefly reviewing some key terminology, we identify three key ways in which neuroimaging analyses can embrace a dynamical systems perspective: by shifting from a local to a more global perspective; by focusing on dynamics instead of static snapshots of neural activity; and by embracing modeling approaches that map neural dynamics using “forward” models. Through this approach, we envisage ample opportunities for neuroimaging researchers to enrich their understanding of the dynamic neural mechanisms that support a wide array of brain functions, both in health and in the setting of psychopathology.

Education 3.0

Bestselling organizational, behavioral, and academic authors such as Dan Pink, Peter Senge, John Medina, Clayton Christensen, and dozens more illustrate that despite research-based, proven actions regarding organizational, managerial, and strategic planning best practices as well as innovative thinking that is impactful or efficacious, organizations continue to employ behaviors that are dysfunctional, ineffective, and lead to poor outcomes. Some of these same authors amongst others point out that this is as true in higher education as any sector. But while other industries are primed for innovative solutioning to these issues, education employs systems and processes that prohibit transformation. Reaching Education 3.0, meaning to leverage the best learning practices through the confluence of neuroscience, research-based learning design, and educational technology, will require innovative strategies and practices. The question is whether colleges and universities can push through existing, dysfunctional infrastructure and move forward to help students learn, succeed, and thrive.

Blinding in tDCS Studies: Correct End-of-Study Guess Does Not Moderate the Effects on Associative and Working Memory

Transcranial direct current stimulation (tDCS) has become a valuable tool in cognitive neuroscience research as it enables causal inferences about neural underpinnings of cognition. However, studies using tDCS to modulate cognitive functions often yield inconsistent findings. Hence, there is an increasing interest in factors that may moderate the effects, one of which is the participants’ beliefs of the tDCS condition (i.e., real or sham) they received. Namely, whether participants’ correct guessing of sham condition may lead to false-positive tDCS effects. In this study, we aimed to explore if participants’ beliefs about received stimulation type (i.e., the success of blinding) impacted their task performance in tDCS experiments on associative (AM) and working memory (WM). We analyzed data from four within-subject, sham-controlled tDCS memory experiments (N = 83) to check if the correct end-of-study guess of sham condition moderated tDCS effects. We found no evidence that sham guessing moderated post-tDCS memory performance in experiments in which tDCS effects were observed as well as in experiments that showed null effects of tDCS. The results suggest that the correct sham guessing (i.e., placebo-like effect) is unlikely to influence the results in tDCS memory experiments. We discuss the results in light of the growing debate about the relevance and effectiveness of blinding in brain stimulation research.

Laboratoř neuropsychologie Neurologické kliniky 1. LF UK

The Laboratory of Neuropsychology (LN)—Jiří Diamant Neuropsychological Laboratory—is a generic base for research and teaching of clinical and experimental neuropsychology in close connection with clinical neuroscience research and postgraduate studies in neuroscience and medical psychology and psychopathology at the Department of Neurology. The LN provides medical services and participates in teaching and research as required by the Head of the Dept. of Neurology. The LN is a base for collaboration with external departments, especially in the areas of clinical and medical psychology, health psychology, brain imaging, neurosurgery, and psychopharmacology. The research program of the LN is mainly devoted to the neuropsychology of neurodegenerative diseases and the development of neuropsychological tools for the assessment of neuropsychiatric disorders.

Selfee: Self-supervised Features Extraction of animal behaviors

Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in the laboratories for behavior analysis. However, it has not been achieved to use a fully unsupervised method to extract comprehensive and discriminative features directly from raw behavior video frames for annotation and analysis purposes. Here, we report a self supervised feature extraction (Selfee) convolutional neural network with multiple downstream applications to process video frames of animal behavior in an end to end way. Visualization and classification of the extracted features (Meta representations) validate that Selfee processes animal behaviors in a comparable way of human understanding. We demonstrate that Meta representations can be efficiently used to detect anomalous behaviors that are indiscernible to human observation and hint in depth analysis. Furthermore, time series analyses of Meta representations reveal the temporal dynamics of animal behaviors. In conclusion, we present a self supervised learning approach to extract comprehensive and discriminative features directly from raw video recordings of animal behaviors and demonstrate its potential usage for various downstream applications.

The neurochemical pathology of schizophrenia: post-mortem studies from dopamine to parvalbumin

Research in Peter Riederer’s lab in Vienna in the late 1970’s came from a strong tradition in post-mortem neurochemical studies, at that time a relatively niche approach in neuroscience research. He was also early to recognise the value of post-mortem brain tissue in elucidating pharmacological mechanisms of neuropsychiatric treatments. I was fortunate to have Peter Riederer as a mentor in my early post-doctoral career; his generous support and the opportunities to use post-mortem brain tissue provided an invaluable grounding on which much of my future research was based. In this paper, I shall provide a brief overview of one trajectory of my research into the neurobiology of schizophrenia that started in the Riederer lab in Vienna investigating dopamine and the D2 receptor. Subsequent research to understand findings of increased dopamine resulted in the identification of reduced GABAergic innervation, culminating in the finding of a deficit in the parvalbumin-containing subtype of GABAergic neurons. Most recent work has been studying how changes in DNA methylation of the parvalbumin gene may relate to these findings in psychotic illness and its animal models.

Can Neuroscientists Test a New Physicalist Mind/Body View: DiCoToP (Diachronic Conjunctive Token Physicalism)?

Given that disparate mind/body views have interfered with interdisciplinary research in psychoanalysis and neuroscience, the mind/body problem itself is explored here. Adding a philosophy of mind framework, problems for both dualists and physicalists are presented, along with essential concepts including: independent mental causation, emergence, and multiple realization. To address some of these issues in a new light, this article advances an original mind/body account—Diachronic Conjunctive Token Physicalism (DiCoToP). Next, puzzles DiCoTop reveals, psychoanalytic problems it solves, and some empirical evidence accrued for views consistent with DiCoToP are presented. In closing, this piece challenges/appeals for neuroscience research to gain evidence for (or against) the DiCoToP view.