Imaging neural activity in the ventral nerve cord of behaving adult Drosophila

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As the demand for high channel counts and high-resolution recordings of neural activity continues to grow, the increased power and data rate generated impose hard constraints on the telemetry capabilities of wireless implantable neural interfaces. To addre ...

Over the past decade, research has shown that the primary motor cortex (M1), the brain's main output for movement, also responds to rewards. These reward signals may shape motor output in its final stages, influencing movement invigoration and motor learni ...

The prefrontal cortex (PFC) is a brain region involved in higher-order cognitive processes such as attention, emotional regulation, and social behavior. However, the delineation of distinct subdivisions within the mouse PFC and their contributions to the b ...

The lumbosacral spinal cord contains neural circuits crucial for locomotion, organized into rostrocaudal levels with distinct somatosensory and motor neuron pools that project to and from the muscles of the lower limbs. However, the specific spinal levels ...

The study of brain disorders has long been central to both neurology and psychiatry, with these two disciplines evolving as distinct yet deeply interconnected fields. In fact, these specialties often share overlapping symptoms, neural pathways, and treatme ...

Restoring the ability to walk is a priority for individuals with neurological disorders or neurotraumatic injuries, given its significant impact on independence and quality of life. Multimodal closed-loop strategies that integrate robotic assistance and ne ...

Over the last two decades, Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) has been developed as a powerful MR imaging modality that allows estimating non-invasively the microscopic structure of biological tissues by exploiting the natural motion of ...

Scientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problems. Physics-based models rely on the physical understanding of the problem at ...

This thesis reports high energy-density electrostatic actuators for use in soft robotics. This thesis has two main parts: a) a detailed study of electro-adhesion using microfabricated electrodes, and b) a flexi-ble fiber-shaped linear motor. Electro-adhesi ...

A novel fast 3D-31P-B+1 mapping method called the frequency-selective Double-AngleMethod (fDAM) has been developed. This method integrates a 3D weighted stack of spiral gradient echo acquisitions with a frequency-selective pulse to efficiently map B+1 fiel ...

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, ...

Correlative light and electron microscopy (CLEM) combines light microscopy, for identifying a target via genetic labels, dyes, antibodies and morphological features, with electron microscopy, for analyzing high-resolution subcellular ultrastructures. Here, ...

Brain organoids enable the mechanistic study of human brain development and provide opportunities to explore self-organization in unconstrained developmental systems1, 2–3. Here we establish long-term, live light-sheet microscopy on unguided brain organoid ...

In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signa ...

Our sense of agency, the subjective experience of controlling our actions, is a crucial component of self-awareness and motor control. It is thought to originate from the comparison between intentions and actions across broad cortical networks. However, th ...

Electrical stimulation of the nervous system has emerged as a promising assistive technology in case of many injuries and illnesses across various parts of the nervous system. In particular, the invasive neuromodulation of the peripheral nervous system see ...

This thesis presents an extensive exploration of neuroelectronic interfaces, focusing on microfabrication, in silico modeling, and their applications in designing and fabricating devices for neural interfacing. The research encompasses both peripheral nerv ...

Literature on linear induction motors (LIMs) has proposed several approaches to model the behavior of such devices for different applications. In terms of accuracy and fidelity, field analysis-based models are the most relevant. Closed-form or numerical so ...

Objective: We predicted that accelerometry would be a viable alternative to electromyography (EMG) for assessing fundamental Transcranial Magnetic Stimulation (TMS) measurements (e.g. Resting Motor Threshold (RMT), recruitment curves, latencies). New Metho ...

The hands, our silent performers in daily life, face overwhelming challenges when neurological impairments disrupt the simple tasks that compose our daily symphony. This thesis unveils a comprehensive framework for the objective monitoring of upper-limb re ...

Imaging neural activity in the ventral nerve cord of behaving adult Drosophila

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A Reconfigurable High-Dynamic Range ∆Σ Front-End with Event-Based Decimation for Bandwidth-Efficient Implantable Neural Interfaces

Reward signals in the motor cortex: from biology to neurotechnology

Functional-based parcellation of the mouse prefrontal cortex for network perturbation analysis

Towards personalized mapping through lumbosacral spinal cord task fMRI

The Interdisciplinary Synergy Between Neurology and Psychiatry: Advancing Brain Health

Multimodal closed-loop strategies for gait recovery after spinal cord injury and stroke via the integration of robotics and neuromodulation

Simulation-based Microstructure Imaging: Towards Realistic White Matter Modeling using Monte Carlo Methods in DW-MRI

Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

High energy-density electrostatic actuators for soft robotics

Fast Quantification of Creatine Kinase Activity by Phosphorus Magnetic Resonance Fingerprinting

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Correlative light and electron microscopy for human brain and other biological models

Morphodynamics of human early brain organoid development

Fast adaptation to rule switching using neuronal surprise

Pre-movement sensorimotor oscillations shape the sense of agency by gating cortical connectivity

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Modeling, fabrication and validation of 3D neural interfaces for peripheral nerves and brain organoids

Pseudo-Three-Dimensional Analytical Model of Linear Induction Motors for High-Speed Applications

Accelerometry as a tool for measuring the effects of transcranial magnetic stimulation

Context-Aware Monitoring of Hand Motor Primitives in Daily Life Activities: A Pathway to Objectively Assess Rehabilitation of Patients with Upper-Limb Neurological Impairment