Brain Dynamics and Cognition Team, Lyon Neuroscience Research Center; CRNL, INSERM U1028, CNRS UMR5292, University of Lyon 1, Lyon, France,
Published: May 2015
AI Article Synopsis
Article Abstract
Attention improves the processing of specific information while other stimuli are disregarded. A good balance between bottom-up (attentional capture by unexpected salient stimuli) and top-down (selection of relevant information) mechanisms is crucial to be both task-efficient and aware of our environment. Only few studies have explored how an isolated unexpected task-irrelevant stimulus outside the attention focus can disturb the top-down attention mechanisms necessary to the good performance of the ongoing task, and how these top-down mechanisms can modulate the bottom-up mechanisms of attentional capture triggered by an unexpected event. We recorded scalp electroencephalography in 18 young adults performing a new paradigm measuring distractibility and assessing both bottom-up and top-down attention mechanisms, at the same time. Increasing task load in top-down attention was found to reduce early processing of the distracting sound, but not bottom-up attentional capture mechanisms nor the behavioral distraction cost in reaction time. Moreover, the impact of bottom-up attentional capture by distracting sounds on target processing was revealed as a delayed latency of the N100 sensory response to target sounds mirroring increased reaction times. These results provide crucial information into how bottom-up and top-down mechanisms dynamically interact and compete in the human brain, i.e. on the precarious balance between voluntary attention and distraction.
Lower-limb exoskeletons have become increasingly popular in rehabilitation to help patients with disabilities regain mobility and independence. Brain-computer interface (BCI) offers a natural control method for these exoskeletons, allowing users to operate them through their electroencephalogram (EEG) signals. However, the limited EEG decoding performance of the BCI system restricts its application for lower limb exoskeletons.
Background: Cognitive impairment, colloquially termed "brain fog", is one of the most prevalent manifestations of post-Covid syndrome and a major contributor to impaired daily function and reduced quality of life. However, despite the high numbers of affected individuals presenting to clinical services with cognitive impairment, little work has been undertaken to date on the suitability of current memory clinic tests for identifying the cognitive deficits in this new acquired cognitive disorder.The aim of this study was therefore to determine the performance of people with post-Covid syndrome presenting with cognitive impairment on the Addenbrooke's Cognitive Examination-III (ACE-III), a cognitive test used widely in memory clinics.
Tea leaf diseases are significant causes of reduced quality and yield in tea production. In the Yunnan region, where the climate is suitable for tea cultivation, tea leaf diseases are small, scattered, and vary in scale, making their detection challenging due to complex backgrounds and issues such as occlusion, overlap, and lighting variations. Existing object detection models often struggle to achieve high accuracy in detecting tea leaf diseases.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China.
Neural oscillations are fundamental for brain function and govern various cognitive processes. Recent functional magnetic resonance imaging advances offer the opportunity to study frequency-specific properties of blood-oxygen-level-dependent oscillations at multiple frequency bands. However, most have focused on spontaneous brain activity in the resting state, leaving a gap in direct evidence regarding the specific activations of cognitive tasks across different frequency bands.
Searching for a unique target is faster when its unique feature repeats than when it changes. The standard account for this priming-of-popout (PoP) phenomenon is that selecting a target increases the attentional priority of its features in subsequent searches. However, empirical tests of this priority account have yielded contradictory findings.
