Limits...
Estimating the amount of information conveyed by a population of neurons.

Crumiller M, Knight B, Yu Y, Kaplan E - Front Neurosci (2011)

Bottom Line: Recent technological advances have made the simultaneous recording of the activity of many neurons common.However, estimating the amount of information conveyed by the discharge of a neural population remains a significant challenge.Here we describe our recently published analysis method that assists in such estimates.

View Article: PubMed Central - PubMed

Affiliation: The Fishberg Department of Neuroscience and Friedman Brain Institute, The Mount Sinai School of Medicine New York, NY, USA.

ABSTRACT
Recent technological advances have made the simultaneous recording of the activity of many neurons common. However, estimating the amount of information conveyed by the discharge of a neural population remains a significant challenge. Here we describe our recently published analysis method that assists in such estimates. We describe the key concepts and assumptions on which the method is based, illustrate its use with data from both simulated and real neurons recorded from the lateral geniculate nucleus of a monkey, and show how it can be used to calculate redundancy and synergy among neuronal groups.

No MeSH data available.


The three steps that are required for calculating the information carried by a neural population: Fourier representation of each spike train; variance estimation, and entropy-information calculation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3139929&req=5

Figure 1: The three steps that are required for calculating the information carried by a neural population: Fourier representation of each spike train; variance estimation, and entropy-information calculation.

Mentions: The weighting coefficients of each sinusoid may be calculated for a large ensemble of signals, and may thus be characterized by a probability distribution. From this distribution one can calculate, using equation 1, the associated entropy. A signal representing a spike train may be expressed as a series of delta functions (smooth “spikes” of infinitesimal width, infinite height, and area 1), with each spike representing an action potential fired by the neuron at that moment in time. The Fourier coefficients of this resulting smooth function of time may be directly evaluated (Figure 1, top). This procedure may be applied to the laboratory data of the experiment discussed above, where spike trains driven by unique and repeat stimuli were interleaved. From the responses to each of the two kinds of stimuli we can estimate a multivariate probability distribution for the Fourier coefficients and, by Shannon's observation above, evaluate the signal information. Several further features simplify this approach.


Estimating the amount of information conveyed by a population of neurons.

Crumiller M, Knight B, Yu Y, Kaplan E - Front Neurosci (2011)

The three steps that are required for calculating the information carried by a neural population: Fourier representation of each spike train; variance estimation, and entropy-information calculation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3139929&req=5

Figure 1: The three steps that are required for calculating the information carried by a neural population: Fourier representation of each spike train; variance estimation, and entropy-information calculation.
Mentions: The weighting coefficients of each sinusoid may be calculated for a large ensemble of signals, and may thus be characterized by a probability distribution. From this distribution one can calculate, using equation 1, the associated entropy. A signal representing a spike train may be expressed as a series of delta functions (smooth “spikes” of infinitesimal width, infinite height, and area 1), with each spike representing an action potential fired by the neuron at that moment in time. The Fourier coefficients of this resulting smooth function of time may be directly evaluated (Figure 1, top). This procedure may be applied to the laboratory data of the experiment discussed above, where spike trains driven by unique and repeat stimuli were interleaved. From the responses to each of the two kinds of stimuli we can estimate a multivariate probability distribution for the Fourier coefficients and, by Shannon's observation above, evaluate the signal information. Several further features simplify this approach.

Bottom Line: Recent technological advances have made the simultaneous recording of the activity of many neurons common.However, estimating the amount of information conveyed by the discharge of a neural population remains a significant challenge.Here we describe our recently published analysis method that assists in such estimates.

View Article: PubMed Central - PubMed

Affiliation: The Fishberg Department of Neuroscience and Friedman Brain Institute, The Mount Sinai School of Medicine New York, NY, USA.

ABSTRACT
Recent technological advances have made the simultaneous recording of the activity of many neurons common. However, estimating the amount of information conveyed by the discharge of a neural population remains a significant challenge. Here we describe our recently published analysis method that assists in such estimates. We describe the key concepts and assumptions on which the method is based, illustrate its use with data from both simulated and real neurons recorded from the lateral geniculate nucleus of a monkey, and show how it can be used to calculate redundancy and synergy among neuronal groups.

No MeSH data available.