This lecture covers visualizing extracellular neurotransmitter dynamics
This lecture provides an introduction to the study of eye-tracking in humans.
The state of the field regarding the diagnosis and treatment of major depressive disorder (MDD) is discussed. Current challenges and opportunities facing the research and clinical communities are outlined, including appropriate quantitative and qualitative analyses of the heterogeneity of biological, social, and psychiatric factors which may contribute to MDD.
This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.
This lesson contains both a lecture and a tutorial component. The lecture (0:00-20:03 of YouTube video) discusses both the need for intersectional approaches in healthcare as well as the impact of neglecting intersectionality in patient populations. The lecture is followed by a practical tutorial in both Python and R on how to assess intersectional bias in datasets. Links to relevant code and data are found below.
This lesson delves into the opportunities and challenges of telepsychiatry. While novel digital approaches to clinical research and care have the potential to improve and accelerate patient outcomes, researchers and care providers must consider new population factors, such as digital disparity.
This lecture discusses what defines an integrative approach regarding research and methods, including various study designs and models which are appropriate choices when attempting to bridge data domains; a necessity when whole-person modelling.
This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.
This lesson aims to define computational neuroscience in general terms, while providing specific examples of highly successful computational neuroscience projects.
This lesson discusses both state-of-the-art detection and prevention schema in working with neurodegenerative diseases.
This lesson provides a basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.
This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.
This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.
This lesson gives an introduction to simple spiking neuron models.
This lesson provides an introduction to simple spiking neuron models.
This lesson gives an introductory presentation on how data science can help with scientific reproducibility.
The Virtual Brain (TVB) is an open-source, multi-scale, multi-modal brain simulation platform. In this lesson, you get introduced to brain simulation in general and to TVB in particular. This lesson also presents the newest approaches for clinical applications of TVB - that is, for stroke, epilepsy, brain tumors, and Alzheimer’s disease - and show how brain simulation can improve diagnostics, therapy, and understanding of neurological disease.
This lesson explains the mathematics of neural mass models and their integration to a coupled network. You will also learn about bifurcation analysis, an important technique in the understanding of non-linear systems and as a fundamental method in the design of brain simulations. Lastly, the application of the described mathematics is demonstrated in the exploration of brain stimulation regimes.
In this lesson, the simulation of a virtual epileptic patient is presented as an example of advanced brain simulation as a translational approach to deliver improved clinical results. You will learn about the fundamentals of epilepsy, as well as the concepts underlying epilepsy simulation. By using an iPython notebook, the detailed process of this approach is explained step by step. In the end, you are able to perform simple epilepsy simulations your own.
This lecture presents the Graphical (GUI) and Command Line (CLI) User Interface of TVB. Alongside with the speakers, explore and interact with all means necessary to generate, manipulate and visualize connectivity and network dynamics.