Neural processing of natural sounds
FE Theunissen, JE Elie - Nature Reviews Neuroscience, 2014 - nature.com
We might be forced to listen to a high-frequency tone at our audiologist's office or we might
enjoy falling asleep with a white-noise machine, but the sounds that really matter to us are …
enjoy falling asleep with a white-noise machine, but the sounds that really matter to us are …
Encoding and decoding models in cognitive electrophysiology
Cognitive neuroscience has seen rapid growth in the size and complexity of data recorded
from the human brain as well as in the computational tools available to analyze this data …
from the human brain as well as in the computational tools available to analyze this data …
Continuous online sequence learning with an unsupervised neural network model
The ability to recognize and predict temporal sequences of sensory inputs is vital for survival
in natural environments. Based on many known properties of cortical neurons, hierarchical …
in natural environments. Based on many known properties of cortical neurons, hierarchical …
Neural system identification for large populations separating “what” and “where”
Neuroscientists classify neurons into different types that perform similar computations at
different locations in the visual field. Traditional methods for neural system identification do …
different locations in the visual field. Traditional methods for neural system identification do …
Estimating and interpreting nonlinear receptive field of sensory neural responses with deep neural network models
Our understanding of nonlinear stimulus transformations by neural circuits is hindered by the
lack of comprehensive yet interpretable computational modeling frameworks. Here, we …
lack of comprehensive yet interpretable computational modeling frameworks. Here, we …
Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization
Neurons in sensory systems often pool inputs over arrays of presynaptic cells, giving rise to
functional subunits inside a neuron's receptive field. The organization of these subunits …
functional subunits inside a neuron's receptive field. The organization of these subunits …
Global and multiplexed dendritic computations under in vivo-like conditions
Dendrites integrate inputs nonlinearly, but it is unclear how these nonlinearities contribute to
the overall input-output transformation of single neurons. We developed statistically …
the overall input-output transformation of single neurons. We developed statistically …
Capturing the dynamical repertoire of single neurons with generalized linear models
A key problem in computational neuroscience is to find simple, tractable models that are
nevertheless flexible enough to capture the response properties of real neurons. Here we …
nevertheless flexible enough to capture the response properties of real neurons. Here we …
Learning divisive normalization in primary visual cortex
Divisive normalization (DN) is a prominent computational building block in the brain that has
been proposed as a canonical cortical operation. Numerous experimental studies have …
been proposed as a canonical cortical operation. Numerous experimental studies have …
Analysis of neuronal spike trains, deconstructed
As information flows through the brain, neuronal firing progresses from encoding the world
as sensed by the animal to driving the motor output of subsequent behavior. One of the more …
as sensed by the animal to driving the motor output of subsequent behavior. One of the more …