Recent experimental evidence suggests that oscillatory activity plays a pivotal role in the
maintenance of information in working memory, both in rodents and humans. In particular …

Semantic memory is characterized by a hierarchical organization of concepts based on
shared properties. However, this aspect is insufficiently dealt with in recent …

Despite many deep learning models are proposed for content understanding or pattern
recognition of brain activities via EEGs, EEG-based object classification still demands efforts …

The present work investigates how complex semantics can be extracted from the statistics of
input features, using an attractor neural network. The study is focused on how feature …

This paper presents an ordered-patch-based image classification framework integrating the
image Grassmannian manifold to address handwritten digit recognition, face recognition …

In this paper, a new artificial neural network model is proposed for visual object recognition,
in which the bottom-up, sensory-driven pathway and top-down, expectation-driven pathway …

This work presents a connectionist model of the semantic-lexical system. Model assumes
that the lexical and semantic aspects of language are memorized in two distinct stores, and …

Inspired by the temporal correlation theory of brain functions, researchers have presented a
number of neural oscillator networks to implement visual scene segmentation problems …

A neural mass model for the memorization of sequences is presented. It exploits three layers
of cortical columns that generate a theta/gamma rhythm. The first layer implements an auto …

In a simple reaction time task in which auditory and visual stimuli are presented in random
sequence alone (A or V) or together (AV), there is a so-called reaction time (RT) cost on …