12 papers · ranked by Valyu relevance
Takumi Ando
Image recognition models have evolved tremendously. Despite the progress for general images, histopathological images are not easy targets. One of the reasons is that histopathological images can be 100000-200000px in height and width which are often too large for a deep neural network model to handle directly because…
Wai Hoh Tang, Shao Ren Sim, Daniel Ying Kia Aik, Ashwin Venkata Subba Nelanuthala + 3 more
Imaging Fluorescence Correlation Spectroscopy (Imaging FCS) is a powerful tool to extract information on molecular mobilities, actions and interactions in live cells, tissues and organisms. Nevertheless, several limitations restrict its applicability. First, FCS is data hungry, requiring 50,000 frames at 1 ms time…
Zihui Yan, Guanjin Qu, Xin Chen, Gang Zheng + 1 more
DNA-based data storage is a promising solution to the challenges of large-scale data storage. However, the low throughput of the mainstream inkjet-based DNA synthesis method has hindered its widespread adoption. In contrast, high-throughput electrochemical synthesis provides higher throughput but with more nucleotide…
Jing-Yi Li, Yuhao Tan, Zheng-Yang Wen, Yu-Jian Kang + 2 more
Deep neural networks equipped with convolutional neural layers have been widely used in omics data analysis. Though highly efficient in data-oriented feature detection, the classical convolutional layer is designed with inter-positional independent filters, hardly modeling inter-positional correlations in various…
Xin Li
In this paper, we revisit the problem of computational modeling of simple and complex cells for an over-parameterized and direct-fit model of visual perception. Unlike conventional wisdom, we highlight the difference in parallel and sequential binding mechanisms between simple and complex cells. A new proposal for…
Jacob R. Pennington, Stephen V. David
Convolutional neural networks (CNNs) can provide powerful and flexible models of neural sensory processing. However, the utility of CNNs in studying the auditory system has been limited by their requirement for large datasets and the complex response properties of single auditory neurons. To address these limitations…
Siwei Wang, Benjamin Hoshal, Elizabeth A de Laittre, Olivier Marre + 2 more
Much of sensory neuroscience focuses on presenting stimuli that are chosen by the experimenter because they are parametric and easy to sample and are thought to be behaviorally relevant to the organism. However, it is not generally known what these relevant features are in complex, natural scenes. This work focuses on…
Lorenzo Tiberi, Haim Sompolinsky
In everyday vision, animals routinely extract from the same visual stimulus both object identity and continuous identity-independent variables such as position and size. It has been shown that linear decoding performance of both kinds of information increases along the ventral stream, suggesting that inferior temporal…
Andrea Navas-Olive, Rodrigo Amaducci, Teresa Jurado-Parras, Enrique R Sebastian + 1 more
Local field potential (LFP) deflections and oscillations define hippocampal sharp-wave ripples (SWR), one of the most synchronous events of the brain. SWR reflect firing and synaptic current sequences emerging from cognitively relevant neuronal ensembles. Current spectral methods fail to capture their mechanistic…
Karim G. Habashy, Benjamin D. Evans, Dan F. M. Goodman, Jeffrey S. Bowers
The genomic mechanisms that efficiently encode the initial architecture and synaptic connectivity of neural circuits remain poorly understood. We hypothesise that two primary mechanisms — spatial encoding and factorisation — enable a limited genome to initialise networks of billions of neurons. Spatial encoding, a form…
James A. Gornet, Matt Thomson
Humans construct internal cognitive maps of their environment directly from sensory inputs without access to a system of explicit coordinates or distance measurements. While machine learning algorithms like SLAM utilize specialized inference procedures to identify visual features and construct spatial maps from visual…
Franklin Leong, Babak Rahmani, Demetri Psaltis, Christophe Moser + 1 more
A fundamental challenge in neuroengineering is determining a proper input to a sensory system that yields the desired functional output. In neuroprosthetics, this process is known as sensory encoding, and it holds a crucial role in prosthetic devices restoring sensory perception in individuals with disabilities. For…