Uniting functional network topology and oscillations in the fronto-parietal single unit network of behaving primates

Abstract

The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks.DOI: http://dx.doi.org/10.7554/eLife.15719.001

Dynamical networks: finding, measuring, and tracking neural population activity using network science

“…Such multi-scale structure is potentially a consequence of the order-of-magnitude distribution in firing rates (Dann et al, 2016;Wohrer et al, 2013), for which more work is needed on suitable measures of interaction. It may also indicate that some neurons are members of more than one ensemble, which are active at different times during the recording.…”

“…The existing toolbox of network science gives us a plethora of options for quantifying the structure of a dynamical network. We may simply quantify its degree and strength distributions ( Figure 1C), revealing dominant neurons (Dann, Michaels, Schaffelhofer, & Scherberger, 2016;Nigam et al, 2016). We can assess the local clustering of the dynamical network, the proportion of a neuron's linked neighbours that are also strongly linked to each other (Watts & Strogatz, 1998; Figure 1D), revealing the locking of dynamics among neurons (Bettencourt et al, 2007;Sadovsky & MacLean, 2013).…”

“…Consequently, there is not a consistent set of modules across time-scales ( Figure 3I). Such multiscale structure is potentially a consequence of the order-of-magnitude distribution in firing rates (Dann et al, 2016;Wohrer et al, 2013), for which more work is needed on suitable measures of interaction. Clearly, such multi-scale structure means that tracking changes in the structure of population activity should be done at a range of time-scales, and comparisons made based on similar time-scales.…”

Neural dynamics of variable grasp movement preparation in the macaque fronto-parietal network

“…Basic experimental methods have been described previously (Michaels et al, 2015;Dann et al, 2016). We trained monkeys to perform a delayed grasping task.…”

“…Afterwards, the signal was low-pass filtered with a non-causal Butterworth filter (5000 Hz; 4 th order). To eliminate movement noise (i.e., common component induced by reference and ground), PCA artifact cancellation was applied for all electrodes of each array (Musial et al, 2002;Dann et al, 2016). In order to ensure that no individual channels were eliminated, PCA dimensions with any coefficient greater than 0.36 (with respect to normalized data) were retained.…”