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Human-like environment recognition by musculoskeletal humanoids is important for task realization in real complex environments and for use as dummies for test subjects. Humans integrate various sensory information to perceive their…

Information encoding in the nervous system is supported through the precise spike-timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains unclear. Here we…

Neural and Evolutionary Computing · Computer Science 2015-12-01 Brian Gardner , Ioana Sporea , André Grüning

During voiced speech, the human vocal folds interact with the vocal tract acoustics. The resulting glottal source-resonator coupling has been observed using mathematical and physical models as well as in in vivo phonation. We propose a…

Fluid Dynamics · Physics 2017-03-16 Atte Aalto , Tiina Murtola , Jarmo Malinen , Daniel Aalto , Martti Vainio

In this paper we present a novel approach to automatically infer parameters of spiking neural networks. Neurons are modelled as timed automata waiting for inputs on a number of different channels (synapses), for a given amount of time (the…

Neurons and Cognition · Quantitative Biology 2018-08-07 Elisabetta De Maria , Cinzia Di Giusto , Laetitia Laversa

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A…

Neurons and Cognition · Quantitative Biology 2015-06-19 Sadra Sadeh , Stefan Rotter

Sparse sequences of neural spikes are posited to underlie aspects of working memory, motor production, and learning. Discovering these sequences in an unsupervised manner is a longstanding problem in statistical neuroscience. Promising…

Machine Learning · Statistics 2020-10-13 Alex H. Williams , Anthony Degleris , Yixin Wang , Scott W. Linderman

Tremendous progress has been made in sequential processing with the recent advances in recurrent neural networks. However, recurrent architectures face the challenge of exploding/vanishing gradients during training, and require significant…

Neural and Evolutionary Computing · Computer Science 2021-10-13 Bing Han , Cheng Wang , Kaushik Roy

Speaker counting is the task of estimating the number of people that are simultaneously speaking in an audio recording. For several audio processing tasks such as speaker diarization, separation, localization and tracking, knowing the…

Sound · Computer Science 2021-01-07 Pierre-Amaury Grumiaux , Srdan Kitic , Laurent Girin , Alexandre Guérin

Human cognition emerges from coordinated spiking dynamics in distributed neural circuits, where information is encoded via both firing rates and precise spike timing determined by brain rhythms. Inspired by this notion, we propose a…

Neurons and Cognition · Quantitative Biology 2026-05-05 Tingting Dan , Guorong Wu

Sequences of neuronal activation have long been implicated in a variety of brain functions. In particular, these sequences have been tied to memory formation and spatial navigation in the hippocampus, a region of mammalian brains.…

Neurons and Cognition · Quantitative Biology 2016-03-10 Zachary Roth

Neural networks have emerged as a tool for solving differential equations in many branches of engineering and science. But their progress in frequency domain acoustics is limited by the vanishing gradient problem that occurs at higher…

Computational Engineering, Finance, and Science · Computer Science 2024-05-09 D. Veerababu , Prasanta K. Ghosh

Temporal processing is fundamental for both biological and artificial intelligence systems, as it enables the comprehension of dynamic environments and facilitates timely responses. Spiking Neural Networks (SNNs) excel in handling such data…

Neural and Evolutionary Computing · Computer Science 2025-02-14 Chenxiang Ma , Xinyi Chen , Yanchen Li , Qu Yang , Yujie Wu , Guoqi Li , Gang Pan , Huajin Tang , Kay Chen Tan , Jibin Wu

Neuromorphic computing targets energy-efficient event-driven information processing by placing artificial spiking-neurons at its core. Artificial neuron devices and circuits have multiple operating modes and produce region-dependent…

Applied Physics · Physics 2026-01-06 Zhiwei Li , Shi-Li Zhang , Chenyu Wen

The acoustic cues used by humans and other animals to localise sounds are subtle, and change during and after development. This means that we need to constantly relearn or recalibrate the auditory spatial map throughout our lifetimes. This…

Neural and Evolutionary Computing · Computer Science 2025-04-18 Yang Chu , Wayne Luk , Dan Goodman

Human brain neuron activities are incredibly significant nowadays. Neuronal behavior is assessed by analyzing signal data such as electroencephalography (EEG), which can offer scientists valuable information about diseases and…

While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates.…

Neurons and Cognition · Quantitative Biology 2015-07-17 Michael A. Schwemmer , Adrienne L. Fairhall , Sophie Denéve , Eric T. Shea-Brown

Biologically inspired auditory models play an important role in developing effective audio representations that can be tightly integrated into speech and audio processing systems. Current computational models of the cochlea are typically…

Audio and Speech Processing · Electrical Eng. & Systems 2021-08-16 T. Dang , V. Sethu , E. Ambikairajah , J. Epps , H. Li

Computational models of cortical activity provide insight into the mechanisms of higher-order processing in the human brain including planning, perception and the control of movement. Activity in the cortex is ongoing even in the absence of…

Neurons and Cognition · Quantitative Biology 2023-07-07 Lysea Haggie , Thor Besier , Angus McMorland

In this correspondence information theoretical tools are used to investigate the statistical properties of modeled cochlear nucleus globular bushy cell spike trains. The firing patterns are obtained from a simulation software that generates…

Neurons and Cognition · Quantitative Biology 2012-04-25 Andrea Grigorescu , Marek Rudnicki , Michael Isik , Werner Hemmert , Stefano Rini

We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of continuous data. Although the stimulus can be considered as a…

Neurons and Cognition · Quantitative Biology 2017-09-28 R. Ozgur Doruk , Kechen Zhang