Datensatz

Zusammenfassung

Understanding the structure of multi-neuronal firing patterns has been a central quest and
major challenge for systems neuroscience. In particular, how do pairwise interactions between
neurons shape the firing patterns of neuronal ensembles in the cortex? To study this
question, we recorded simultaneously from multiple single neurons in the primary visual
cortex of an awake, behaving macaque using an array of chronically implanted tetrodes1. High
contrast flashed and moving bars were used for stimulation, while the monkey was required to
maintain fixation.
In a similar vein to recent studies of in vitro preparations2,3,5, we applied maximum entropy
analysis for the first time to the binary spiking patterns of populations of cortical neurons
recorded in vivo from the awake macaque. We employed the Dichotomized Gaussian
distribution, which can be seen as a close approximation to the pairwise maximum-entropy
model for binary data4. Surprisingly, we find that even pairs of neurons with nearby receptive
fields (receptive field center distance < 0.15°) have only weak correlations between their
binary responses computed in bins of 10 ms (median absolute correlation coefficient: 0.014,
0.010-0.019, 95 confidence intervals, N=95 pairs; positive correlations: 0.015, N=59;
negative correlations: -0.013, N=36). Accordingly, the distribution of spiking patterns of
groups of 10 neurons is described well with a model that assumes independence between
individual neurons (Jensen-Shannon-Divergence: 1.06×10-2 independent model, 0.96×10-2
approximate second-order maximum-entropy model4; H/H1=0.992). These results suggest that
the distribution of firing patterns of small cortical networks in the awake animal is
predominantly determined by the mean activity of the participating cells, not by their
interactions.
Meaningful computations, however, are performed by neuronal populations much larger than
10 neurons. Therefore, we investigated how weak pairwise correlations affect the firing
patterns of artificial populations4 of up to 1000 cells with the same correlation structure as
experimentally measured. We find that in neuronal ensembles of this size firing patterns with
many active or silent neurons occur considerably more often than expected from a fully
independent population (e.g. 130 or more out of 1000 neurons are active simultaneously
roughly every 300 ms in the correlated model and only once every 3-4 seconds in the
independent model). These results suggest that the firing patterns of cortical networks
comparable in size to several minicolumns exhibit a rich structure, even if most pairs appear
relatively independent when studying small subgroups thereof.