Little is known about fine scale neural dynamics that accompany rapid shifts in spatial attention in freely behaving animals, primarily because reliable indicators of attention are lacking in standard model organisms engaged in natural tasks. The echolocating bat can serve to bridge this gap, as it exhibits robust dynamic behavioral indicators of overt spatial attention as it explores its environment. In particular, the bat actively shifts the aim of its sonar beam to inspect objects in different directions, akin to eye movements and foveation in humans and other visually dominant animals. Further, the bat adjusts the temporal features of sonar calls to attend to objects at different distances, yielding a metric of acoustic gaze along the range axis. Thus, an echolocating bat's call features not only convey the information it uses to probe its surroundings, but also provide fine scale metrics of auditory spatial attention in 3D natural tasks. These explicit metrics of overt spatial attention can be leveraged to uncover general principles of neural coding in the mammalian brain.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10269881 | PMC |
| http://dx.doi.org/10.12688/molpsychol.17488.1 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Cognitive component of auditory attention to natural speech events.
Front Hum Neurosci
January 2025
Center for Ear-EEG, Department of Electrical and Computer Engineering, Aarhus University, Aarhus, Denmark.
The recent progress in auditory attention decoding (AAD) methods is based on algorithms that find a relation between the audio envelope and the neurophysiological response. The most popular approach is based on the reconstruction of the audio envelope from electroencephalogram (EEG) signals. These methods are primarily based on the exogenous response driven by the physical characteristics of the stimuli.
View Article and Find Full Text PDFPEDRA-EFB0: colorectal cancer prognostication using deep learning with patch embeddings and dual residual attention.
Med Biol Eng Comput
January 2025
Radiol Dept, Jiangnan Univ, Affiliated Hosp, Wuxi, 214122, Jiangsu, People's Republic of China.
In computer-aided diagnosis systems, precise feature extraction from CT scans of colorectal cancer using deep learning is essential for effective prognosis. However, existing convolutional neural networks struggle to capture long-range dependencies and contextual information, resulting in incomplete CT feature extraction. To address this, the PEDRA-EFB0 architecture integrates patch embeddings and a dual residual attention mechanism for enhanced feature extraction and survival prediction in colorectal cancer CT scans.
View Article and Find Full Text PDFAn improved DeepLabv3 + railway track extraction algorithm based on densely connected and attention mechanisms.
Sci Rep
January 2025
School of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou, 412007, China.
The railway track extraction using unmanned aerial vehicle (UAV) aerial images suffers from issues such as low extraction accuracy and high time consumption. In response to these problems, this paper presents a lightweight algorithm DA-DeepLabv3 + based on densely connected and attention mechanisms. Firstly, the lightweight MobileNetV2 network is employed to replace the Xception feature extraction network, thereby reducing the number of model parameters.
View Article and Find Full Text PDFTriple-attentions based salient object detector for strip steel surface defects.
Sci Rep
January 2025
School of Computer and Information Technology, Xinyang Normal University, Xinyang, Henan Province, 464000, P. R. China.
Accurate detection of surface defects on strip steel is essential for ensuring strip steel product quality. Existing deep learning based detectors for strip steel surface defects typically strive to iteratively refine and integrate the coarse outputs of the backbone network, enhancing the models' ability to express defect characteristics. Attention mechanisms including spatial attention, channel attention and self-attention are among the most prevalent techniques for feature extraction and fusion.
View Article and Find Full Text PDFEvening Alpha-Lactalbumin Supplementation Alters Sleep Architecture and Reduces Morning Reaction Time in an Athletically Trained Population With Sleep Difficulties.
Int J Sport Nutr Exerc Metab
January 2025
Centre for Sport Research, Institute of Physical Activity and Nutrition, Deakin University, Geelong, Australia.
Evening consumption of a whey protein rich in the amino acid tryptophan, alpha-lactalbumin (ALAC), has previously shown to benefit sleep-particularly among poor sleepers. Given trained populations often experience sleep difficulty, this study investigated whether evening supplementation of ALAC would influence sleep outcomes, mood, and next-day cognitive performance within a trained population with sleep difficulties. Nineteen trained participants (females, n = 11) with sleep difficulties (Athlete Sleep Screening Questionnaire: 8.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!