Behaviorally Relevant Information Content in Interneuron Activity

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An important function of the neocortex is to compare sensory feedback stimuli with internal predictions of the outside world and evoke mismatch responses to deviations, thus allowing expectations to be updated. The mechanisms behind sensory feedback mismat ...

The rapid evolution of Machine Learning (ML) workloads, particularly Deep Neural Networks (DNNs) and Transformer-based models, has intensified demands on computing architectures, highlighting the limitations of traditional von Neumann systems due to the me ...

Metal ions are indispensable cofactors for many proteins and play crucial roles in numerous biological processes, yet the computational design of metalloproteins and the optimization of metal coordination sites poses significant challenges due to the comp ...

We investigate group fairness regularizers in federated learning, aiming to train a globally fair model in a distributed setting. Ensuring global fairness in distributed training presents unique challenges, as fairness regularizers typically involve probab ...

Background: Eating disorders (EDs) are serious psychiatric disorders characterized by impairments in neurocognition and altered brain structure. To date the majority of studies have investigated these in acutely ill or recovered individuals. Studying child ...

Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions ...

The brain and immune system communicate through complex bidirectional pathways, but the specificity by which the brain perceives or even remembers alterations in immune homeostasis is still poorly understood. Recent data revealed that immune-related inform ...

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, ...

We investigate the training dynamics of two-layer neural networks when learning multi-index target functions. We focus on multi-pass gradient descent (GD) that reuses the batches multiple times and show that it significantly changes the conclusion about wh ...

This dataset contains images (TIFF image data) of brain juvenile rats Wistar Han (P14) scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F5 ...

While classical in many theoretical settings-and in particular in statistical physics-inspired works-the assumption of Gaussian i.i.d. input data is often perceived as a strong limitation in the context of statistics and machine learning. In this study, we ...

Objective. Brain-Computer Interfaces targeting post-stroke recovery of the upper limb employ mainly electroencephalography to decode movement-related brain activation. Recently hybrid systems including muscular activity were introduced. We compared the mot ...

Although the spatial patterns of cultural ecosystem services (CES) are often considered in land use management, there is a noticeable disparity in research coverage compared to biophysical ecosystem services (BES). Moreover, there is a lack of research foc ...

The success of machine learning (ML) has been intimately linked with the availability of large amounts of data, typically collected from heterogeneous sources and processed on vast networks of computing devices (also called workers). Beyond accuracy, the u ...

Multi-object spectroscopic galaxy surveys typically make use of photometric and colour criteria to select their targets. That is not the case of Euclid, which will use the NISP slitless spectrograph to record spectra for every source over its field of view ...

Reinforcement learning (RL) with dense rewards and imitation learning (IL) with human-generated trajectories are the most widely used approaches for training modern embodied agents. RL requires extensive reward shaping and auxiliary losses and is often too ...

The spinal cord is an elongated nervous structure that together with the brain forms the central nervous system. It relays sensory and motor information between the brain and the body, thus controlling most somatic and autonomic body functions. In recent y ...

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

Over the last decades, implantable neural interfaces have been extensively explored and effectively deployed to address neurological and mental health disorders. The existing solutions present several limitations. Firstly, the physical size of the implanta ...

Intelligent Fault Diagnosis (IFD) based on deep learning has proven to be an effective and flexible solution, attracting extensive research. Deep neural networks can learn rich representations from vast amounts of representative labeled data for various ap ...

Behaviorally Relevant Information Content in Interneuron Activity

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Top-down modulation of sensory processing and mismatch in the mouse posterior parietal cortex

Stop Wasting your Cache! Bringing Machine Learning into Cache Computing

Engineering of stable and functional metalloproteins using evolutionary computation, deep learning and simulation

Global Group Fairness in Federated Learning via Function Tracking

Neurobiology and Cognition in Girls at High-risk of Eating Disorders: Exploring Imaging-derived Trait Markers

Ethological computational psychiatry: Challenges and opportunities

Investigations on the Ability of the Insular Cortex to Process Peripheral Immunosuppression

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

The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents

Nissl_5, Raw images for Machine learning for histological annotation and quantification of cortical layers

Gaussian universality of perceptrons with random labels

Brain and muscle derived features to discriminate simple hand motor tasks for a rehabilitative BCI: comparative study on healthy and post-stroke individuals

Integrating spatial patterns and driving factors of cultural ecosystem services into territorial spatial governance: A case study of the Horqin Sandy Land with multi-ethnic settlements

Brief Announcement: A Case for Byzantine Machine Learning

Euclid: Testing photometric selection of emission-line galaxy targets?

SPOC: Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World

Digital reconstruction of the mammalian spinal cord: from anatomical reference volume to cell type atlas of the mouse spinal cord

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Miniaturised, Wireless and Distributed Neural Interface Toward Cortical Visual Prosthesis

Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis