Academic Articles & Research Papers

On the character of consciousness

The human brain is a particularly demanding system to infer its nature from observations. Thus, there is on one hand plenty of room for theorizing and on the other hand a pressing need for a rigorous theory. We apply statistical mechanics o...

How structure determines correlations in neuronal networks.

Networks are becoming a ubiquitous metaphor for the understanding of complex biological systems, spanning the range between molecular signalling pathways, neural networks in the brain, and interacting species in a food web. In many models, ...

A role for neural modeling in the study of brain disorders: Comment on From intracerebral EEG signals to brain connectivity: identification of epileptogenic networks in partial epilepsy by F. Wendling et al.

The Handbook of brain theory and neural networks

From the Publisher: Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields ...

Overview of Artificial Neural Networks

The artificial neural network (ANN), or simply neural network, is a machine learning method evolved from the idea of simulating the human brain. The data explosion in modem drug discovery research requires sophisticated analysis methods to ...

Invariant representation of physical stability in the human brain

Successful engagement with the world requires the ability to predict what will happen next. Here, we investigate how the brain makes a fundamental prediction about the physical world: whether the situation in front of us is stable, and henc...

Neural Networks in Chemistry

Abstract The capabilities of the human brain have always fascinated scientists and led them to investigate its inner workings. Over the past 50 years a number of models have been developed which have attempted to replicate the brain's vario...

Brain tumor grading based on Neural Networks and Convolutional Neural Networks

This paper studies brain tumor grading using multiphase MRI images and compares the results with various configurations of deep learning structure and baseline Neural Networks. The MRI images are used directly into the learning machine, wit...

Memristor-based neural networks

The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent p...

Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks

Forming transformation-tolerant object representations is critical to high-level primate vision. Despite its significance, many details of tolerance in the human brain remain unknown. Likewise, despite the ability of convolutional neural ne...

Neural Networks and Brain Function

The aim of this book is to describe the types of computation that can be performed by biologically plausible neural networks, and to show how these may be implemented in different systems in the brain. The book is structured in three sectio...

Connectomic insights into the impact of 1p/19q co-deletion in dominant hemisphere insular glioma patients

ObjectivesThis study aimed to elucidate the influences of 1p/19q co-deletion on structural connectivity alterations in patients with dominant hemisphere insular diffuse gliomas.MethodsWe incorporated 32 cases of left insular gliomas and 20 ...

A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks

Modular organization is an emergent property of brain networks, responsible for shaping communication processes and underpinning brain functioning. Moreover, brain networks are intrinsically multilayer since their attributes can vary across...

ACTIVATION FUNCTIONS IN NEURAL NETWORKS

Artificial Neural Networks are inspired from the human brain and the network of neurons present in the brain.The information is processed and passed on from one neuron to another through neuro synaptic junctions.Similarly, in artificial neu...

An Introduction to Neural Networks

An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain funct...

Childhood Trauma and APOEε4 Are Associated With Patterns of Developmental Frontal Alpha Connectivity, Posttraumatic Stress, and Alcohol-Related Outcomes.

CL-BPUWM: continuous learning with Bayesian parameter updating and weight memory

Abstract Catastrophic forgetting in neural networks is a common problem, in which neural networks lose information from previous tasks after training on new tasks. Although adopting a regularization method that preferentially retains the pa...

Deep Learning

This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising....

The impact of robot-assisted frameless brain biopsy on performance differences between junior and senior neurosurgeons.

Hierarchical Multimodal Sleep Staging with Optimized EEG, EOG, and PPG Features for Wearable Applications

Automatic sleep staging is fundamental for diagnosing sleep disorders and enabling long-term sleep monitoring with wearable devices. Although Deep Learning has significantly improved classification performance, balancing accuracy with compu...