This title appears in the Scientific Report :
2017
Comparison of resting and movement state data from macaque monkey motor cortex
Comparison of resting and movement state data from macaque monkey motor cortex
Modeling studies of cortical network dynamics aim to include realistic assumptions on neuronal properties (Potjans & Diesmann 2014; Voges & Perrinet 2012). However, such models are typically bound to neglect functional aspects that relate to behavior. Rather, they describe the “ground” or “r...
Saved in:
Personal Name(s): | Dabrowska, Paulina (Corresponding author) |
---|---|
Voges, Nicole / von Papen, Michael / Riehle, Alexa / Brochier, Thomas / Grün, Sonja | |
Contributing Institute: |
Computational and Systems Neuroscience; INM-6 Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 |
Imprint: |
2017
|
Conference: | The 7th International Conference "Aspects of Neuroscience", Warsaw (Poland), 2017-11-24 - 2017-11-26 |
Document Type: |
Abstract |
Research Program: |
SMARTSTART Training Program in Computational Neuroscience Kausative Mechanismen mesoskopischer Aktivitätsmuster in der auditorischen Kategorien-Diskrimination Human Brain Project Specific Grant Agreement 1 Supercomputing and Modelling for the Human Brain Connectivity and Activity |
Publikationsportal JuSER |
Modeling studies of cortical network dynamics aim to include realistic assumptions on neuronal properties (Potjans & Diesmann 2014; Voges & Perrinet 2012). However, such models are typically bound to neglect functional aspects that relate to behavior. Rather, they describe the “ground” or “resting state” (Deco et al. 2011) of cortical networks. For model validation, i.e. a concrete comparison of experimental versus model data, we designed a resting state experiment. We recorded the spiking activity for 15 min from macaque monkey (pre)motor cortex during rest, i.e. without any task, using a chronically implanted 4x4 mm2 100 electrode Utah Array (Blackrock Microsystems). Based on a video recording of the monkey we differentiate between epochs of “resting” (RS) and of spontaneous movements (M). We subdivide the 147 simultaneously recorded single units into putative excitatory (EXC) and inhibitory (INH) neurons based on their spike width (Dehghani et al. 2016) and estimate their firing rates, local coefficients of variation, pairwise fine temporal correlations, and rate covariances. The distributions of the fine temporal correlations and the rate covariances are more broadly distributed during M compared to RS for each group of unit pairs and for INH-INH compared to EXC-EXC independently of behavioral state. INH units fire faster and more regularly compared to EXC in both states in which the distributions of population rate and local coefficient of variation are relatively similar. When focusing on the characteristics of the individual neurons, we find that several neurons increase their firing rates systematically when the monkey moves compared to rest, whereas others decrease or do not change their rates, an aspect that is not noticable when comparing the distributions for both states. Averaging cross-correlation histrograms of EXC-EXC and INH-INH pairs reveals an oscillation of about 17 Hz, which is especially pronounced in INH-INH pairs during rest. Similarly, preliminary LFP analysis shows increased power in the same freqency range (beta, 13-20 Hz), with different dominant frequencies in RS and M. In conclusion, firing patterns seem to be more structured in M than in RS, what is manifested in higher correlations and covariances and also lower coefficients of variation during M. |