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Spatial Organization of Neuronal Population Responses in vivo: can you repeat that?

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Kerr,  JN
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Former Research Group Network Imaging, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Neural Population Imaging, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Kerr, J. (2007). Spatial Organization of Neuronal Population Responses in vivo: can you repeat that?. Talk presented at University of California: Redwood Center for Theoretical Neuroscience. Berkeley, CA, USA. 2007-10-31.


Cite as: https://hdl.handle.net/21.11116/0000-0004-4490-C
Abstract
Although individual pyramidal neurons of neocortex show sparse and variable responses to sensory stimuli in vivo, it has remained unclear how this variability extends to population responses on a trial-to-trial basis. Two-photon imaging allows the study of both form and function in populations of neurons, in vivo, while taking into account all the neurons within a local area, whether actively spiking or not. Here I will present data from ongoing studies in which we characterized single-neuron and neuronal population activity of layer 2/3 neurons located in identified columns in rat barrel cortex. First, optical detection of single action potentials from evoked calcium transients revealed low spontaneous firing rates, and variable response probabilities. Second, neuronal pairs showed correlations in both spontaneous and sensory-evoked activity that depended on the location of the neurons. Thus, even though neurons were not activated independently, precisely repeating spatial activation patterns were not observed. Instead, population responses showed large trial-to-trial variability. Nevertheless, the accuracy of decoding stimulus onset-times from local population activity increased with population size and depended on anatomical location. In conclusion, despite their sparseness and variability L2/3 population responses show a clear spatial organization on the columnar scale.