Carnegie Mellon University researchers have discovered that the diversity in how neurons respond to incoming stimuli, formerly ignored by neuroscientists, is actually critical to overall brain function and to how neurons process complex stimuli and code information.

“I think neuroscientists have, at an intuitive level, recognized the variability between neurons, but we swept it under the rug because we didn’t consider that diversity could be a feature. Rather, we looked at it as a fundamental reflection of the imprecision of biology,” said Nathan N. Urban, professor and head of CMU’s Department of Biological Sciences. “We wanted to reconsider that notion. Perhaps this diversity is important — maybe it serves some function.”

The diversity of neuron cells within each type

Estimates say that the human brain alone has about 100 billion neurons, which can be broken down into a number of different types. While members of the same type of brain cells look structurally alike, and contribute to completing the same overall task, each individual neuron in a group of cells fires in response to subtle differences in the incoming stimulus in different ways (such as different firing rates and interspike intervals). Typically, neuroscientists assume they can ignore these differences, and average out the data to obtain their results, assuming that the variability is a “bug of biology.”

Urban and postdoctoral student Krishnan Padmanabhan, both researchers in CMU’s Department of Biological Sciences and the joint CMU/University of Pittsburgh Center for the Neural Basis of Cognition, decided to test this assumption, using single neurons’ responses to a complex stimulus. By placing an electrical probe into individual excitatory neurons called mitral cells (in the mouse olfactory bulb) and exposing them to a complex computer-controlled noise stimulus, the researchers were able to determine how each individual cell responded.

Doubling the information in the brain

They found that out of the dozens of neurons they tested, no two had the exact same response. While the researchers believed that these results were striking on their own, it led them to wonder whether or not the neurons were giving a messy version of a single response, or if they were each providing different pieces of information about the stimulus.

To test this latter hypothesis, the CMU researchers used “spike-triggered averaging,” which allowed them to determine what feature of the stimulus causes each neuron to respond. They found that some responded to rapid changes in the stimulus and others to slower changes; still other neurons responded when the input signal changed in a regular or rhythmic way. The researchers then computed the information contained in the outputs of highly diverse sets of neurons and compared it to that of groups of more-similar neurons. They found that the heterogeneous groups of neurons transmitted twice as much information as the homogeneous group.

The researchers next want to discover how diversity is achieved. Neurons of a given type are typically born at the same stage of development, with many of them coming from the same progenitor cell. Urban hopes to discover how neurons diversify during development, what proteins are involved, and if any type of training or exposure enhances diversity.

The researchers also believe neuronal diversity also could play a role in neurological disorders like epilepsy, Parkinson’s disease and schizophrenia. In these conditions, there is a disruption in the synchrony and rhythmicity of neuronal firing. In the case of epilepsy and Parkinson’s, groups of neurons fire simultaneously, causing seizures or tremors. In schizophrenia, some neurons have a reduced ability to coordinate firing in certain situations, such as during attention tasks. Changes in the diversity of neuronal populations may alter the ease with which neurons enter into these rhythmic firing patterns.

Reference (available for free download): “Intrinsic biophysical diversity decorrelates neuronal firing while increasing information content,” Krishnan Padmanabhan & Nathaniel N. Urban, Nature Neuroscience (2010) doi:10.1038/nn.2630, 29 August 2010

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