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Sensory neuroscience is a subfield of neuroscience which tries to understand the behaviour of neurons in sensory systems. Since the neural code is unknown, it is difficult to begin understanding the brain by looking at the behaviour of more abstract neurons. Since it is possible to experimentally control the stimulus a sensory system experiences, by recording responses from neurons while exposing sensory systems to stimuli it may be possible to gain insights into how the outside world is represented. Some scientists hope that knowing how information about the outside world is represented in the brain will be an important stepping stone in our understanding of how the brain as a whole functions.

Typical experiments

A typical experiment in sensory neuroscience involves the presentation of a stimulus to an experimental subject while the subject's brain is being monitored. This monitoring can be accomplished by noninvasive means such as functional magnetic resonance imaging (fMRI) or electroencephalography (EEG), or by more invasive means such as electrophysiology, the use of electrodes to capture the electrical activity of single neurons or groups of neurons.

Single neuron experiments

In most of the central nervous system, neurons communicate exclusively by sending each other action potentials, colloquially known as "spikes". It is therefore thought that all of the information a sensory neuron encodes about the outside world can be inferred by the pattern of its spikes. Current experimental techniques cannot measure individual spikes noninvasively, so electrodes must be used to reveal a neuron's spikes.

A typical single neuron experiment will consist of isolating a neuron (that is, navigating the neuron until the experimentor finds a neuron which spikes in response to the type of stimulus to be presented, and (optionally) determining that all of the spikes observed indeed come from a single neuron), then presenting a stimulus protocol. Because neural responses are inherently variable (that is, their spiking pattern may depend on more than just the stimulus which is presented, although not all of this variability may be true noise, since factors other than the presented stimulus may affect the sensory neuron under study), often the same stimulus protocol is repeated many times to get a feel for the variability a neuron may have. One common analysis technique is to study the neuron's average time-varrying firing rate, called its post stimulus time histogram or PSTH.

Receptive field estimation

One major goal of sensory neuroscience is to try to estimate the neuron's receptive field; that is, to try to determine which stimuli cause the neuron to fire in what ways. One common way to find the receptive field is to use linear regression to find which stimulus characteristics typically caused neurons to become excited or depressed. Since the receptive field of a sensory neuron can vary in time (i.e. latency between the stimulus and the effect it has on the neuron) and in some spatial dimension (literally space for vision and somatosensory cells, but other "spatial" dimensions such as the frequency of a sound for auditory neurons), the term spatio temporal receptive field or STRF is often used to describe these receptive fields.

Natural stimuli

One recent trend in sensory neuroscience has been the adoption of natural stimuli for the characterization of sensory neurons. There is good reason to believe that there has been evolutionary pressure on sensory systems to be able to represent natural stimuli well, so sensory systems may exhibit the most relevant behaviour in response to natural stimuli. The adpotion of natural stimuli in sensory neuroscience has been slowed by the fact that the mathematical descriptions of natural stimuli tend to be more complex than of simplified artificial stimuli such as simple tones or clicks in audition or line patterns in vision. Free software is now available to help neuroscientists interested in estimating receptive fields cope with the difficulty of using natural stimuli.

Sensory neuroscience is also used as a bottom-up approach to studying consciousness. For example, visual sense and representation has been studied by Crick and Koch (1998), and experiments have been suggested in order to test various hypotheses in this research stream.

See also


  • Crick and Kock (1998)Consciousness and Neuroscience. Cerebral Cortex, 8:97-107,

External links

  • [1] STRFPAK: free software (registration required) to help estimate receptive fields when natural stimuli are used.
  • [2] Cosyne: A major systems neuroscience meeting.
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