Journal of Neuroscience · 2000 · 570 citations · 53 references
Life SciencesNeuroscienceZoologyComputational NeuroscienceSensory NeuroscienceSensory PhysiologyAuditory NeurobiologyAuditory NeurophysiologyAuditory NeuroscienceAuditory PhysiologyAuditory SystemSensory System ModelingAuditory Signal ProcessingNeural Processing Of SoundNonlinear Receptive Field ModelsResponse PropertiesSpatiotemporal Receptive FieldsStimulus - Response ModelsWhite Noise
The spatial‑temporal receptive field (STRF) is a linear model traditionally estimated with reverse correlation using simple stimuli, but such stimuli often fail to activate high‑level auditory neurons that are tuned to natural sounds. The study aims to demonstrate that STRFs of avian auditory forebrain neurons can be accurately estimated from natural birdsong stimuli, overcoming the limitations of simple stimulus ensembles. They estimated STRFs by applying reverse‑correlation techniques to neural responses elicited by an ensemble of natural birdsongs. STRFs derived from natural birdsongs differ markedly from those obtained with random tone pips and predict neural responses more accurately, indicating that while the linear STRF model is incomplete for nonlinear auditory neurons, it remains a useful framework when estimated from relevant complex stimuli.
The stimulus–response function of many visual and auditory neurons has been described by a spatial-temporal receptive field (STRF), a linear model that for mathematical reasons has until recently been estimated with the reverse correlation method, using simple stimulus ensembles such as white noise. Such stimuli, however, often do not effectively activate high-level sensory neurons, which may be optimized to analyze natural sounds and images. We show that it is possible to overcome the simple-stimulus limitation and then use this approach to calculate the STRFs of avian auditory forebrain neurons from an ensemble of birdsongs. We find that in many cases the STRFs derived using natural sounds are strikingly different from the STRFs that we obtained using an ensemble of random tone pips. When we compare these two models by assessing their predictions of neural response to the actual data, we find that the STRFs obtained from natural sounds are superior. Our results show that the STRF model is an incomplete description of response properties of nonlinear auditory neurons, but that linear receptive fields are still useful models for understanding higher level sensory processing, as long as the STRFs are estimated from the responses to relevant complex stimuli.
53