Different Neuronal Recording Schemes

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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 ...

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, ...

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

In this thesis we will present two results on global existence for nonlinear dispersive equations with data at or below the scaling regularity. In chapter 1 we take a probabilistic perspective to study the energy-critical nonlinear Schrödinger equation in ...

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 ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

Masonry aggregates, which emerged as layouts of cities and villages became denser, make up historical centres all over the world. In these aggregates, neighbouring structures may share structural walls that are joined at the interfaces by mortar or interlo ...

Recordings of the physiological history of cells provide insights into biological processes, yet obtaining such recordings is a challenge. To address this, we introduce a method to record transient cellular events for later analysis. We designed proteins t ...

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 ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

This data package supports the publication 'Complexity of crack front geometry enhances toughness of brittle solids' by Xinyue Wei, Chenzhuo Li, Cían McCarthy, and John M. Kolinski Nature physics (2024) - https://doi.org/10.1038/s41567-024-02435-x DOI: 1 ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

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 ...

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in ne ...

Despite the widespread use of self-tracking technologies for promoting personal wellbeing, there is limited research on the monitoring of intimate data, particularly urine. To shed light on the design possibilities within this unexplored domain we designed ...

Numerous conductor designs for pulsed magnets based on High Temperature Superconductors (HTS), featuring stacks of tapes are currently being proposed. A major contribution to the AC losses is expected to be given by hysteresis losses. Several numerical mod ...

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 ...

Different Neuronal Recording Schemes

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

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

Data-driven statistical optimization of a groundwater monitoring network

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Probabilistic and Deterministic Wellposedness for Low Regularity Dispersive Equations

Subcortical correlates of consciousness with human single neuron recordings

Robust machine learning for neuroscientific inference

Orchestrating chromosome conformation capture analysis with Bioconductor

Seismic Testing of Adjacent Interacting Masonry Structures – Analysis of a Blind Prediction

Recording physiological history of cells with chemical labeling

Fast adaptation to rule switching using neuronal surprise

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Dataset for "Complexity of crack front geometry enhances toughness of brittle solids"

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

Designing for Intimate Wellbeing: Aidee, a Qualitative Approach To Urine Home Monitoring

Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

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