Membrane activity detection in cultured cells using phase-sensitive plasmonics

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Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...

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 ...

Subcortical brain structures such as the basal ganglia or the thalamus are involved in regulating motor and cognitive behavior. However, their contribution to perceptual consciousness is still unclear, due to the inherent difficulties of recording subcorti ...

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

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 ...

This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

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, ...

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

Plasmonic photochemistry has a large potential to replace energy-intensive chemical processes with low-temperature, low-pressure light-driven chemical reactions. Plasmonic nanostructures have emerged as promising photocatalysts with exceptional and tunable ...

The reported rate of the occurrence of unilateral spatial neglect (USN) is highly variable likely due to the lack of validity and low sensitivity of classical tools used to assess it. Virtual reality (VR) assessments try to overcome these limitations by pr ...

A spinal cord injury (SCI) triggers a cascade of molecular and cellular responses involving inflammatory cell infiltration and cytokine release, apoptosis, demyelination, excitotoxicity, ischemia, and the formation of a fibrotic scar surrounded by an astro ...

Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...

The present invention concerns a bodily implantable or probe device and microelectrode fabrication method comprising providing at least one silicon substrate including an electronic device or unit; providing, on a first side of the silicon substrate, at le ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

Topographical disorientation refers to the selective inability to orient oneself in familiar surroundings. However, to date its neural correlates remain poorly understood. Here we use quantitative lesion analysis and a lesion network mapping approach in or ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

Neuroprostheses have been used clinically for decades, to help restore or preserve brain functions, when pharmaceutical treatments are inefficient. Although great progress in the field has been made over the years to interface with the nervous system, surf ...

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 ...

Membrane activity detection in cultured cells using phase-sensitive plasmonics

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Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Fast adaptation to rule switching using neuronal surprise

Subcortical correlates of consciousness with human single neuron recordings

Driving and suppressing the human language network using large language models

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

Small-scale robotic devices for medical interventions in the brain

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

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Plasmonic Nanostructures for Photocatalysis: Material, Photonic and Electronic Effects

An immersive virtual reality tool for assessing left and right unilateral spatial neglect

Multimodal transcriptomic atlases of mouse spinal cord injury

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

Bodily implant microelectrode and bodily implant microelectrode fabrication method

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Unveiling the complexity of learning and decision-making

The neural correlates of topographical disorientation-a lesion analysis study

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Unraveling behavior and cortical signals to guide the development of soft neuroprostheses for auditory restoration and spreading depolarization

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