Naturalistic stimuli increase the rate and efficiency of information transmission by primary auditory afferents

By F. Rieke, D. Bodnar, William Bialek. 1995

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Citations in the corpus

Density Modeling of Images using a Generalized Normalization Transformation (2015, background): “…achieve desired statistical properties at the output is central to theories of efﬁcient sensory coding in neurobiology (Barlow, 1961; Ruderman, 1994; Rieke et al., 1995; Bell & Sejnowski, 1997; Schwartz & Simoncelli, 2001), and also lends itself naturally to the design of cascaded representations…”
Efficient coding of natural sounds (2002, background): “In the auditory system, it has been shown that auditory nerves encode naturalistic stimuli with greater efficiency than white noise [10].”
Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli (2001, background): “For example, neurons in the early auditory system of frogs are more efficient at encoding sounds with natural power spectra ( Rieke et al 1995 ).”
Reconstructing Speech from Human Auditory Cortex (2012, background): “[41] reconstructed the sound pressure waveform using neural responses from the bullfrog auditory periphery, where neural responses phase-lock to fluctuations in the raw stimulus waveform [2].”
Natural image statistics and neural representation. (2001, methodology): “In using natural sounds as experimental stimui, Rieke et al (1995) have shown that neurons at early stages of the frog auditory system are adapted specifically to encode the structure in the natural vocalizations of the animal.”
Sequential and efficient neural-population coding of complex task information (2019, unknown): “We did not observe that individual neurons have statistically independent responses (Figures S5G–S5L), so in a strict sense our findings differ from being a fully efficient code, as well as the individual-neuron focus of a large body of related work (Atick and Redlich, 1992; Baddeley et al., 1997; D”
Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions (2002, background): “…and audition, a growing number of experiments are examining the responses of sensory neurons to natural stimuli (Creutzfeldt & Northdurft, 1978; Rieke et al., 1995; Baddeley et al., 1997; Stanley et al., 1999; Theunissen et al., 2000; Vinje & Gallant, 2000; Lewen et al., 2001; Sen et al.,…”
Neural processing of amplitude-modulated sounds. (2004, result): “Similar results have been seen in the frog (232).”
Attentional Selection in a Cocktail Party Environment Can Be Decoded from Single-Trial EEG. (2015, methodology): “…studies have used recorded cortical population data to estimate the input stimulus using a mapping approach in the reverse direction (i.e., from the neural data back to the stimulus) (Rieke et al. 1995; Stanley et al. 1999; Mesgarani et al. 2009; Pasley et al. 2012; Zion Golumbic et al. 2013).”
Mapping Information Flow in Sensorimotor Networks (2006, methodology): “These include modelling frameworks for effective information transmission [37,38], efficient and sparse coding [5,6,39], visual attention [40], extraction of behaviorally relevant stimulus properties [41], and information processing in sensorimotor systems [42,43].”
Tuning for spectro-temporal modulations as a mechanism for auditory discrimination of natural sounds (2005, unknown): “Preserving the natural distribution of envelope amplitud”
The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli (2016, methodology): “The stimulus reconstruction method has previously been used to study both the visual and auditory system in various animal models (Bialek et al., 1991; Rieke et al., 1995; Stanley et al., 1999).”
Neural processing of natural sounds (2014, methodology): “In contrast, the behavioral relevance of the neuroethological approach was clearly less problematic and results showing that behaviorally relevant stimuli yield the largest neural responses [7](or the most informative [9,10]) gave support for evolutionary arguments and ultimate explanations; in othe”
Cellular-resolution population imaging reveals robust sparse coding in the Drosophila Mushroom Body (2011, background): “There are examples in the auditory and visual systems where neurons transmit more information about stimuli with natural statistics than artificial stimuli (Rieke et al., 1995; Machens et al., 2001; Yu et al., 2005; Garcia-Lazaro et al., 2006).”