Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Stephen V David"'
Publikováno v:
eLife, Vol 12 (2024)
Categorical sensory representations are critical for many behaviors, including speech perception. In the auditory system, categorical information is thought to arise hierarchically, becoming increasingly prominent in higher-order cortical regions. Th
Externí odkaz:
https://doaj.org/article/ad01abdfb28d42bf843be58c3814df14
Autor:
Jacob R Pennington, Stephen V David
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 5, p e1011110 (2023)
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
Externí odkaz:
https://doaj.org/article/5554b8dbf50644c794bbb3958901ff47
Publikováno v:
PLoS Biology, Vol 20, Iss 9, p e3001771 (2022)
Despite increasing representation in graduate training programs, a disproportionate number of women leave academic research without obtaining an independent position that enables them to train the next generation of academic researchers. To understan
Externí odkaz:
https://doaj.org/article/d5d24593d01b4a9fafe378597b72e09d
Autor:
Charles R Heller, Stephen V David
Publikováno v:
PLoS ONE, Vol 17, Iss 7, p e0271136 (2022)
Rapidly developing technology for large scale neural recordings has allowed researchers to measure the activity of hundreds to thousands of neurons at single cell resolution in vivo. Neural decoding analyses are a widely used tool used for investigat
Externí odkaz:
https://doaj.org/article/d547c64071814360880dfe9948720636
Publikováno v:
PLoS Biology, Vol 19, Iss 6, p e3001299 (2021)
Early in auditory processing, neural responses faithfully reflect acoustic input. At higher stages of auditory processing, however, neurons become selective for particular call types, eventually leading to specialized regions of cortex that preferent
Externí odkaz:
https://doaj.org/article/df52a83284b2424abe3dbc4fc1bdeba7
Publikováno v:
eLife, Vol 10 (2021)
Both generalized arousal and engagement in a specific task influence sensory neural processing. To isolate effects of these state variables in the auditory system, we recorded single-unit activity from primary auditory cortex (A1) and inferior collic
Externí odkaz:
https://doaj.org/article/81c490fbaeda4c469b5272afeb880cb0
Publikováno v:
PLoS Computational Biology, Vol 15, Iss 10, p e1007430 (2019)
Perception of vocalizations and other behaviorally relevant sounds requires integrating acoustic information over hundreds of milliseconds. Sound-evoked activity in auditory cortex typically has much shorter latency, but the acoustic context, i.e., s
Externí odkaz:
https://doaj.org/article/63bd768daca8403281084b8a361a6d6a
Publikováno v:
PLoS Computational Biology, Vol 11, Iss 12, p e1004628 (2015)
Encoding properties of sensory neurons are commonly modeled using linear finite impulse response (FIR) filters. For the auditory system, the FIR filter is instantiated in the spectro-temporal receptive field (STRF), often in the framework of the gene
Externí odkaz:
https://doaj.org/article/e1a9453942604a76bb4bf0cf9804c91f
Publikováno v:
Frontiers in Neural Circuits, Vol 7 (2013)
The distributed nature of nervous systems makes it necessary to record from a large number of sites in order to break the neural code, whether single cell, local field potential (LFP), micro-electrocorticograms (μECoG), electroencephalographic (EEG)
Externí odkaz:
https://doaj.org/article/7b698495516b4466a8d886390c9b3c97
Autor:
Brian N Pasley, Stephen V David, Nima Mesgarani, Adeen Flinker, Shihab A Shamma, Nathan E Crone, Robert T Knight, Edward F Chang
Publikováno v:
PLoS Biology, Vol 10, Iss 1, p e1001251 (2012)
How the human auditory system extracts perceptually relevant acoustic features of speech is unknown. To address this question, we used intracranial recordings from nonprimary auditory cortex in the human superior temporal gyrus to determine what acou
Externí odkaz:
https://doaj.org/article/825de0b5af424181b4ccf7bb930283b0