Neural Switch Asymmetry in Feature-Based Auditory Attention Tasks

Feature-based Attention in Convolutional Neural Networks

Convolutional neural networks (CNNs) have proven effective for image processing tasks, such as object recognition and classification. Recently, CNNs have been enhanced with concepts of attention, similar to those found in biology. Much of this work on attention has focused on effective serial spatial processing. In this paper, I introduce a simple procedure for applying feature-based attention ...

When feature-based attention distorts neural representations.

Gender Differences in Auditory Perception and Computational Divided Attention Tasks

Women have been stereotyped as better multitaskers when compared to their male counterparts. The purpose of this study was to investigate whether there are differences in gender performance when performing cognitive combined tasks. Twenty-four graduate students (twelve females and twelve males) volunteered to participate in the study. The task required participants to indicate when they perceiv...

A Neural Oscillator Model of Auditory Attention

A model of auditory scene analysis is proposed, which incorporates an attentional mechanism and is implemented using a network of neural oscillators. The core of the model is a two-layer neural oscillator network which performs stream segregation and selection on the basis of oscillatory correlation. A stream is represented by a sychronised oscillator population, whereas different streams are r...

Visuo-Spatial Attention in ADHD Children: Investigating the Asymmetry

Objectives: The purpose of the present study was comparing visuo-spatial attention between children with Attention Deficit Hyperactivity Disorder-Inattentive (ADHD-I) type and normal children. Methods: In this cross-sectional study fifteen (7-10 years of age) children were classified with ADHD-I type and 15 normal children were matched for age, sex, and IQ. They were selected trough simple r...