Advanced age is commonly associated with progressive cochlear pathology and central auditory deficits, collectively known as presbycusis. The present study examined central correlates of presbycusis by measuring response properties of primary auditory cortex (AI) layer V neurons in the Fischer Brown Norway rat model. Layer V neurons represent the major output of AI to other cortical and subcortical regions (primarily the inferior colliculus). In vivo single-unit extracellular recordings were obtained from 114 neurons in aged animals (29-33 mo) and compared with 105 layer V neurons in young-adult rats (4-6 mo). Three consecutive repetitions of a pure-tone receptive field map were run for each neuron. Age was associated with fewer neurons exhibiting classic V/U-shaped receptive fields and a greater percentage of neurons with more Complex receptive fields. Receptive fields from neurons in aged rats were also less reliable on successive repetitions of the same stimulus set. Aging was also associated with less firing during the stimulus in V/U-shaped receptive field neurons and more firing during the stimulus in Complex neurons, which were generally associated with inhibited firing in young controls. Finally, neurons in aged rats with Complex receptive fields were more easily driven by current pulses delivered to the soma. Collectively, these findings provide support for the notion that age is associated with diminished signal-to-noise coding by AI layer V neurons and are consistent with other research suggesting that GABAergic neurotransmission in AI may be compromised by aging.
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http://dx.doi.org/10.1152/jn.00362.2005 | DOI Listing |
Front Comput Neurosci
December 2024
Sussex AI, School of Engineering and Informatics, University of Sussex, Brighton, United Kingdom.
We present a Spiking Neural Network (SNN) model that incorporates learnable synaptic delays through two approaches: per-synapse delay learning via Dilated Convolutions with Learnable Spacings (DCLS) and a dynamic pruning strategy that also serves as a form of delay learning. In the latter approach, the network dynamically selects and prunes connections, optimizing the delays in sparse connectivity settings. We evaluate both approaches on the Raw Heidelberg Digits keyword spotting benchmark using Backpropagation Through Time with surrogate gradients.
View Article and Find Full Text PDFSci Rep
January 2025
School of Computer and Control Engineering, Qiqihar University, Qiqihar, 161003, China.
In semantic segmentation research, spatial information and receptive fields are essential. However, currently, most algorithms focus on acquiring semantic information and lose a significant amount of spatial information, leading to a significant decrease in accuracy despite improving real-time inference speed. This paper proposes a new method to address this issue.
View Article and Find Full Text PDFNeural Netw
December 2024
Institute of Automation, Chinese Academy of Sciences, MAIS, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 101408, China.
In the rapidly evolving field of deep learning, Convolutional Neural Networks (CNNs) retain their unique strengths and applicability in processing grid-structured data such as images, despite the surge of Transformer architectures. This paper explores alternatives to the standard convolution, with the objective of augmenting its feature extraction prowess while maintaining a similar parameter count. We propose innovative solutions targeting depthwise separable convolution and standard convolution, culminating in our Multi-scale Progressive Inference Convolution (MPIC).
View Article and Find Full Text PDFPLoS One
January 2025
Julius Kühn-Institut (JKI), Federal Research Centre for Cultivated Plants, Institute for Epidemiology and Pathogen Diagnostics, Rodent Research, Muenster, Germany.
Small rodents can cause problems on farms such as infrastructure damage, crop losses or pathogen transfer. The latter threatens humans and livestock alike. Frequent contacts between wild rodents and livestock favour pathogen transfer and it is therefore important to understand the movement patterns of small mammals in order to develop strategies to prevent damage and health issues.
View Article and Find Full Text PDFJ Vis
January 2025
Department of Psychology, University of Washington, Seattle, WA, USA.
The population receptive field (pRF) method, which measures the region in visual space that elicits a blood-oxygen-level-dependent (BOLD) signal in a voxel in retinotopic cortex, is a powerful tool for investigating the functional organization of human visual cortex with fMRI (Dumoulin & Wandell, 2008). However, recent work has shown that pRF estimates for early retinotopic visual areas can be biased and unreliable, especially for voxels representing the fovea. Here, we show that a log-bar stimulus that is logarithmically warped along the eccentricity dimension produces more reliable estimates of pRF size and location than the traditional moving bar stimulus.
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