Capacity Scaling of Cognitive Networks: Beyond Interference-Limited Communication

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Over the course of a lifetime, the human brain acquires an astonishing amount of semantic knowledge and autobiographical memories, often with an imprinting strong enough to allow detailed information to be recalled many years after the initial learning exp ...

Deep learning has achieved remarkable success in various challenging tasks such as generating images from natural language or engaging in lengthy conversations with humans. The success in practice stems from the ability to successfully train massive neural ...

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 ...

Training accurate and robust machine learning models requires a large amount of data that is usually scattered across data silos. Sharing, transferring, and centralizing the data from silos, however, is difficult due to current privacy regulations (e.g., H ...

Neural networks provide an attractive framework to monitor the water table level and the volume of stored water in porous media from seismic data in an automated, fast and cost-efficient manner. In this work, a subsurface reservoir is modeled as a coupled ...

One challenge in designing RF wireless bioelectronic devices is the impact of the interaction between electromagnetic waves and host body tissues on far-field wireless performance. In this paper, we investigate a peculiar phenomenon of implantable RF wirel ...

Deep neural networks trained on physical losses are emerging as promising surrogates for nonlinear numerical solvers. These tools can predict solutions to Maxwell's equations and compute gradients of output fields with respect to the material and geometric ...

Prism adaptation (PA) is a useful method to investigate short-term sensorimotor plasticity. Following active exposure to prisms, individuals show consistent after-effects, probing that they have adapted to the perturbation. Whether after-effects are transf ...

Objectives: Bipolar disorder (BD) is a severe, chronic, affective disorder characterized by recurrent switching between mood states, psychomotor and cognitive symptoms, which can linger in euthymic states as residual symptoms. Hippocampal alterations may p ...

Multiple lines of evidence across human functional, lesion, and animal data point to a cerebellar role, in particular of crus I, crus II, and lobule VIIB, in cognitive function. However, a mapping of distinct facets of cognitive function to cerebellar stru ...

How the 'what', 'where', and 'when' of past experiences are stored in episodic memories and retrieved for suitable decisions remains unclear. In an effort to address these questions, the authors present computational models of neural networks that behave l ...

Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which ev ...

The choice of the shape parameter highly effects the behaviour of radial basis function (RBF) approximations, as it needs to be selected to balance between the ill-conditioning of the interpolation matrix and high accuracy. In this paper, we demonstrate ho ...

The concept of novelty is central to questions of creativity, innovation, and discovery. Despite the prominence in scientific inquiry and everyday discourse, there is a chronic ambiguity over its meaning and a surprising variety of empirical measures, whic ...

Motivated by the need for a better understanding of post-stroke recovery and new biomarkers to improve stroke patient stratification and outcomes, this thesis investigated structure-function coupling and its role in post-stroke recovery. Furthermore, in or ...

For decades, the mammalian hippocampus has been the focus of cellular, anatomical, behavioral, and computational studies aimed at understanding the fundamental mechanisms underlying cognition. Long recognized as the brain's seat for learning and memory, a ...

Novel usages of brain stimulation combined with artificially intelligent (AI) systems promise to address a large range of diseases. These new conjoined technologies, such as brain-computer interfaces (BCI), are increasingly used in experimental and clinica ...

Oxytocin (OT) is a key modulator of human social cognition, popular in behavioral neuroscience. To adequately design and interpret intranasal OT (IN-OT) research, it is crucial to know for how long it affects human brain function once administered. However ...

This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

The viable and safe application of wireless power transfer for powering bioelectronic implants requires understanding the wave propagation in heterogeneous and dispersive media, the electromagnetic exposure assessment, and the optimum design of the system ...

Capacity Scaling of Cognitive Networks: Beyond Interference-Limited Communication

Chattez avec Graph Search

A theory of memory consolidation and synaptic pruning in cortical circuits

A Theory of Finite-Width Neural Networks: Generalization, Scaling Laws, and the Loss Landscape

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

Privacy-preserving federated neural network training and inference

Monitoring of water table level and volume of water in a porous storage by seismic data

Radiation Patterns of RF Wireless Devices Implanted in Small Animals: Unexpected Deformations Due to Body Resonance

Predicting nonlinear optical scattering with physics-driven neural networks

Inter-Task Transfer of Prism Adaptation through Motor Imagery

Dynamic functional hippocampal markers of residual depressive symptoms in euthymic bipolar disorder

The Cerebellum and Cognitive Function: Anatomical Evidence from a Transdiagnostic Sample

Computational models of episodic-like memory in food-caching birds

The EEG multiverse of schizophrenia

A new variable shape parameter strategy for RBF approximation using neural networks

Nothing New Under the Sun: Novelty Constructs and Measures in Social Studies

Determining patterns of post-stroke motor recovery through longitudinal multimodal MRI: A step towards patient stratification

Sharpening the blades of the dentate gyrus: how adult-born neurons differentially modulate diverse aspects of hippocampal learning and memory

How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?

Temporal dynamics of intranasal oxytocin in human brain electrophysiology

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

Theoretical Efficiency and Dosimetry of Buffered On-body Transmitter Antennas for Wireless Powering of In-body Devices