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Multimodal Fusion of Muscle and Brain Signals for a Hybrid-BCI

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Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies

Auke Ijspeert

Animal locomotion is the result of complex and multi-layered interactions between the nervous system, the musculo-skeletal system and the environment. Decoding the underlying mechanisms requires an integrative approach. Comparative experimental biology has ...

Company Biologists Ltd2023

Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive

Auke Ijspeert, Milad Shafiee Ashtiani, Guillaume Denis Antoine Bellegarda

Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Computational models of CPGs have been widely used for investigating the spinal co ...

IEEE2023

Robust gamma-aminobutyric acid and energy metabolism measurements by proton and phosphorus magnetic resonance spectroscopy and fingerprinting

Songi Lim

Magnetic resonance spectroscopy (MRS) is the only technique that can detect endogenous metabolites directly and non-invasively in vivo. It allows to identify different metabolites and analyze the dynamic neurochemical processes in the brain, skeletal muscl ...

EPFL2023

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Sahand Jamal Rahi, Ariane Andrée Marie Delrocq

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Nature Publishing Group2023

Brain Fingerprinting Using Fmri Spectral Signatures On High-Resolution Cortical Graphs

Dimitri Nestor Alice Van De Ville, Hamid Behjat, Maria Giulia Preti, Stefano Moia

Resting-state fMRI has proven to entail subject-specific signatures that can serve as a fingerprint to identify individuals. Conventional methods are based on building a connectivity matrix based on correlation between the average time course of pairs of b ...

IEEE2023

New insights into rodent brain microstructure and metabolism in hepatic encephalopathy

Jessie Julie Mosso

Type C hepatic encephalopathy (HE) is a severe neuropsychiatric complication of chronic liver disease, for which the prognosis is poor in the absence of liver transplantation. Cirrhosis in type C HE leads to a toxic accumulation of ammonia in the blood, wh ...

EPFL2023

Revealing the complexity of ultra-soft hydrogel re-swelling inside the brain

Stéphanie Lacour, Michael Shur, John Martin Kolinski, Outman Akouissi, Olivier Didier Christian Rizzo

The brain is an ultra-soft viscoelastic matrix. Sub-kPa hydrogels match the brain's mechanical properties but are challenging to manipulate in an implantable format. We propose a simple fabrication and processing sequence, consisting of de-hydration, patte ...

2023

A parcellation scheme of mouse isocortex based on reversals in connectivity gradients

Michael Reimann

The brain is composed of several anatomically clearly separated structures. This parcellation is often extended into the isocortex, based on anatomical, physiological or functional differences. Here, we derive a parcellation scheme based purely on the spat ...

2023

Brain mitochondrial diversity and network organization predict anxiety-like behavior in male mice

Maria del Carmen Sandi Perez

The brain and behavior are under energetic constraints, limited by mitochondrial energy transformation capacity. However, the mitochondria-behavior relationship has not been systematically studied at a brain-wide scale. Here we examined the association bet ...

Nature Research2023

Walking naturally after spinal cord injury using a brain-spine interface

Léonie Asboth, Salif Axel Komi, Grégoire Courtine, Robin Jonathan Demesmaeker, Jocelyne Bloch, Sergio Daniel Hernandez, Henri Charles Alexandre Lorach, Edeny Baaklini, Jimmy James Ravier, Carmina Andrea Galvez Solano, Cathal John Harte, Grégory Didier Dumont, Thibault Jean Etienne Collin, Icare Sakr, Nadine Intering

A spinal cord injury interrupts the communication between the brain and the region of the spinal cord that produces walking, leading to paralysis(1,2). Here, we restored this communication with a digital bridge between the brain and spinal cord that enable ...

NATURE PORTFOLIO2023

Neuromodulation/neurostimulation system for mitigating locomotor deficits of parkinson's disease, spinal cord injury (sci), stroke and/or other neurological disorders

Tomislav Milekovic, Léonie Asboth, Grégoire Courtine, Eduardo Martin Moraud, Robin Jonathan Demesmaeker, Newton Cho, Jocelyne Bloch, Jordan Squair

The present invention relates to a combined neuromodulation and/or neurostimulation system (10) for mitigating locomotor deficits of/or neuronal disorders, especially Parkinson's disease, said system (10) comprising: - at least one Deep Brain Stimulation ( ...

2023

Noninvasive theta-burst stimulation of the human striatum enhances striatal activity and motor skill learning

Elena Beanato, Pablo Maceira Elvira, Esra Neufeld, Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Chang-Hyun Park, Traian Popa, Pierre Theopistos Vassiliadis, Pauline Menoud, Fabienne Windel

The stimulation of deep brain structures has thus far only been possible with invasive methods. Transcranial electrical temporal interference stimulation (tTIS) is a novel, noninvasive technology that might overcome this limitation. The initial proof-of-co ...

Nature Portfolio2023

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Meritxell Bach Cuadra, Rizhong Lin

Diffusion Magnetic Resonance Imaging (dMRI) is a powerful non-invasive method for studying white matter tracts of the brain. However, accurate microstructure estimation with fiber orientation distribution (FOD) using existing computational methods requires ...

Springer2023

Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals

Aude Billard, José del Rocio Millán Ruiz, Fumiaki Iwane

During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin. This comfort margin varie ...

Nature Portfolio2023