Receptive fields

The receptive field of an individual sensory neuron is the particular region of the sensory space (e.g., the body surface, or the visual field) in which a stimulus will modify the firing of that neuron. This region can be a hair in the cochlea or a piece of skin, retina, tongue or other part of an animal's body. Additionally, it can be the space surrounding an animal, such as an area of auditory space that is fixed in a reference system based on the ears but that moves with the animal as it moves (the space inside the ears), or in a fixed location in space that is largely independent of the animal's location (place cells). Receptive fields have been identified for neurons of the auditory system, the somatosensory system, and the visual system.

The term receptive field was first used by Sherrington (1906) to describe the area of skin from which a scratch reflex could be elicited in a dog. According to Alonso and Chen (2008) it was Hartline (1938) who applied the term to single neurons, in this case from the retina of a frog.

The concept of receptive fields can be extended further up the nervous system; if many sensory receptors all form synapses with a single cell further up, they collectively form the receptive field of that cell. For example, the receptive field of a ganglion cell in the retina of the eye is composed of input from all of the photoreceptors which synapse with it, and a group of ganglion cells in turn forms the receptive field for a cell in the brain. This process is called convergence.

The auditory system processes the temporal and spectral (i.e. frequency) characteristics of sound waves, so the receptive fields of neurons in the auditory system are modeled as spectro-temporal patterns that cause the firing rate of the neuron to modulate with the auditory stimulus. Auditory receptive fields are often modeled as spectro-temporal receptive fields (STRFs), which are the specific pattern in the auditory domain that causes modulation of the firing rate of a neuron. Linear STRFs are created by first calculating a spectrogram of the acoustic stimulus, which determines the how the spectral density of the acoustic stimulus changes over time, often using the Short-time Fourier transform (STFT). Firing rate is modeled over time for the neuron, possibly using a peristimulus time histogram if combining over multiple repetitions of the acoustic stimulus. Then, linear regression is used to predict the firing rate of that neuron as a weighted sum of the spectrogram. The weights learned by the linear model are the STRF, and represent the specific acoustic pattern that causes modulation in the firing rate of the neuron. STRFs can also be understood as the transfer function that maps an acoustic stimulus input to a firing rate response output.

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