Controlling morpho-electrophysiological variability of neurons with detailed models

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While nowadays approaches for equilibrium free energy estimation are well established, nonequilibrium simulations represent both an appealing computational opportunity and a challenge. This kind of simulations allows for a trivially parallel scheme, but at ...

Metasurfaces, planar arrays of subwavelength resonators, have emerged as powerful tools for versatile light manipulation in compact formats across different spectral ranges. Among these, the mid-infrared (mid-IR) is uniquely characterized by its interactio ...

Wireless, miniaturised and distributed neural interfaces are emerging neurotechnologies. Although extensive research efforts contribute to their technological advancement, the need for real-time systems enabling simultaneous wireless information and power ...

Understanding cognitive processes in the brain demands sophisticated models capable of replicating neural dynamics at large scales. We present a physiologically inspired speech recognition architecture, compatible and scalable with deep learning frameworks ...

The development of novel strategies to augment motor training success is of great interest for healthy persons and neurological patients. A promising approach is the combination of training with transcranial electric stimulation. However, limited reproduci ...

BackgroundThe challenge of classifying cortical interneurons is yet to be solved. Data-driven classification into established morphological types may provide insight and practical value.ResultsWe trained models using 217 high-quality morphologies of rat so ...

This paper presents a remotely powered implantable heart monitoring system for freely moving animals. The system measures the blood pressure in the left ventricle of the heart and transmits the data to a database unit. The implanted unit is remotely powere ...

We advocate a compressed sensing strategy that consists of multiplying the signal of interest by a wide bandwidth modulation before projection onto randomly selected vectors of an orthonormal basis. Firstly, in a digital setting with random modulation, con ...

We study a kinetic mean-field equation for a system of particles with different sizes, in which particles are allowed to coagulate only if their sizes sum up to a prescribed time-dependent value. We prove well-posedness of this model, study the existence o ...

We review here the development of Hodgkin-Huxley (HH) type models of cerebral cortex and thalamic neurons for network simulations. The intrinsic electrophysiological properties of cortical neurons were analyzed from several preparations, and we selected th ...

Controlling morpho-electrophysiological variability of neurons with detailed models

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Nonequilibrium Binding Free Energy Simulations: Minimizing Dissipation

Design and Application of Functional Mid-IR Metasurfaces for Enhanced Light-Matter Interaction and Sensing

A Wearable Real-Time System for Simultaneous Wireless Power and Data Transmission to Cortical Visual Prosthesis

Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks

Cerebellar transcranial alternating current stimulation in the gamma range applied during the acquisition of a novel motor skill

Towards a supervised classification of neocortical interneuron morphologies

Remotely powered implantable heart monitoring system for freely moving animals

Universal and efficient compressed sensing by spread spectrum and application to realistic Fourier imaging techniques

On A Model For Mass Aggregation With Maximal Size

Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons