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One of the most important goals in neuroscience research has always been to understand how animals control their behavior. However, the long focus on the role of brain neurons in behavioral control might be missing the full story. In fact, brain-wide fluct ...
Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentia ...
How does reliable computation emerge from networks of noisy neurons? While individual neurons are intrinsically noisy, the collective dynamics of populations of neurons taken as a whole can be almost deterministic, supporting the hypothesis that, in the br ...
In this paper we present the Open Software Services for Classrooms and Research (OSSCAR) platform. OSSCAR provides an open collaborative environment to develop and access educational resources in the form of web applications, for which various deployment m ...
Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity patterns are propagating bursts of place-cell activities called hippocampal rep ...
Surrogate deep neural networks (DNNs) can significantly speed up the engineering design process by providing a quick prediction that emulates simulated data. Many previous works have considered improving the accuracy of such models by introducing additiona ...
A painful episode can lead to a life-long increase in an individual's experience of pain. Fearful anticipation of imminent pain could play a role in this phenomenon, but the neurobiological underpinnings are unclear because fear can both suppress and enhan ...
Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...
Recent successes in deep learning for vision and natural language processing are attributed to larger models but come with energy consumption and scalability issues. Current training of digital deep-learning models primarily relies on backpropagation that ...
For the prediction of landslide-generated waves, previous studies have developed numerous empirical equations to express the maximums of wave characteristics as functions of slide parameters upon impact. In this study, we built the temporal relationship be ...