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Compositionality of arm movements can be realized by propagating synchrony.

Hanuschkin A, Herrmann JM, Morrison A, Diesmann M - J Comput Neurosci (2010)

Bottom Line: Here, we map the propagation of activity in a chain to a linearly evolving preferred velocity, which results in parabolic segments that fulfill the two-thirds power law.The model provides an explanation for the segmentation of the trajectory and the experimentally observed deviations of the trajectory from the parabolic shape at primitive transition sites.Furthermore, the model predicts low frequency oscillations (<10 Hz) of the motor cortex local field potential during ongoing movements and increasing firing rates of non-specific motor cortex neurons before movement onset.

View Article: PubMed Central - PubMed

Affiliation: Functional Neural Circuits Group, Faculty of Biology, Schänzlestrasse 1, 79104, Freiburg, Germany. hanuschkin@bccn.uni-freiburg.de

ABSTRACT
We present a biologically plausible spiking neuronal network model of free monkey scribbling that reproduces experimental findings on cortical activity and the properties of the scribbling trajectory. The model is based on the idea that synfire chains can encode movement primitives. Here, we map the propagation of activity in a chain to a linearly evolving preferred velocity, which results in parabolic segments that fulfill the two-thirds power law. Connections between chains that match the final velocity of one encoded primitive to the initial velocity of the next allow the composition of random sequences of primitives with smooth transitions. The model provides an explanation for the segmentation of the trajectory and the experimentally observed deviations of the trajectory from the parabolic shape at primitive transition sites. Furthermore, the model predicts low frequency oscillations (<10 Hz) of the motor cortex local field potential during ongoing movements and increasing firing rates of non-specific motor cortex neurons before movement onset.

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The effect of synfire chain switching realized by structured cross-inhibition on collective signals. (a) Spiking activity of a reduced network with synfire chain competition, connected as 1→2,7 and 2,7→1. Activity of 10% of the neurons is shown. (b) Firing rate (black), average membrane potential (red) and approximated LFP (blue; arbitrary units) calculated from activity in the reduced network. Arrows indicate signatures of synfire chain switching in the collective signals. (c, d) As in (a, b) but without synfire chain competition: connected as 1→2→7→1. Arrows indicate regimes in which cross-inhibition is absent (1) and present (2)
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Fig7: The effect of synfire chain switching realized by structured cross-inhibition on collective signals. (a) Spiking activity of a reduced network with synfire chain competition, connected as 1→2,7 and 2,7→1. Activity of 10% of the neurons is shown. (b) Firing rate (black), average membrane potential (red) and approximated LFP (blue; arbitrary units) calculated from activity in the reduced network. Arrows indicate signatures of synfire chain switching in the collective signals. (c, d) As in (a, b) but without synfire chain competition: connected as 1→2→7→1. Arrows indicate regimes in which cross-inhibition is absent (1) and present (2)

Mentions: The switching mechanism is demonstrated in Fig. 7(a), which shows the spiking activity of the minimal network with synfire chain competition. After each completion of chain 1, either chain 2 or chain 7 wins the competition; the activity in the other chain dies away. The average firing rate, mean potential and approximated LFP of the network are given in Fig. 7(b). The average firing rate increases whenever two chains are competing, returning to its initial value after the activity of the losing chain has died away. The time of cell assembly competition is also clearly visible in both LFP approximations. The average membrane potential shows a dip right after the increased local firing rate due to the neuron reset and refractory period during which the membrane potential is clamped to zero. The change in the signal given by the summed and smoothed absolute postsynaptic currents is particularly pronounced at the transition sites due to the contribution of the inhibitory PSCs, which are g times larger than the excitatory currents. Figure 7(c) shows the spiking activity for the corresponding network without synfire chain competition. The activity moves from one chain to the next in a deterministic fashion. Figure 7(d) shows the corresponding collective signals. The approximated LFP signal still exhibits step-like changes due to the increase of inhibitory activity when either chain 2 or 7 is active, however the transient increases of LFP signal and firing rate and transient decreases of membrane potential indicated by arrows in Fig. 7(b) are not observed in the reduced network without synfire chain competition. These results suggests that low frequency components of the LFP in experimental data could be indicators for cell assembly competition.Fig. 7


Compositionality of arm movements can be realized by propagating synchrony.

Hanuschkin A, Herrmann JM, Morrison A, Diesmann M - J Comput Neurosci (2010)

The effect of synfire chain switching realized by structured cross-inhibition on collective signals. (a) Spiking activity of a reduced network with synfire chain competition, connected as 1→2,7 and 2,7→1. Activity of 10% of the neurons is shown. (b) Firing rate (black), average membrane potential (red) and approximated LFP (blue; arbitrary units) calculated from activity in the reduced network. Arrows indicate signatures of synfire chain switching in the collective signals. (c, d) As in (a, b) but without synfire chain competition: connected as 1→2→7→1. Arrows indicate regimes in which cross-inhibition is absent (1) and present (2)
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Related In: Results  -  Collection

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Fig7: The effect of synfire chain switching realized by structured cross-inhibition on collective signals. (a) Spiking activity of a reduced network with synfire chain competition, connected as 1→2,7 and 2,7→1. Activity of 10% of the neurons is shown. (b) Firing rate (black), average membrane potential (red) and approximated LFP (blue; arbitrary units) calculated from activity in the reduced network. Arrows indicate signatures of synfire chain switching in the collective signals. (c, d) As in (a, b) but without synfire chain competition: connected as 1→2→7→1. Arrows indicate regimes in which cross-inhibition is absent (1) and present (2)
Mentions: The switching mechanism is demonstrated in Fig. 7(a), which shows the spiking activity of the minimal network with synfire chain competition. After each completion of chain 1, either chain 2 or chain 7 wins the competition; the activity in the other chain dies away. The average firing rate, mean potential and approximated LFP of the network are given in Fig. 7(b). The average firing rate increases whenever two chains are competing, returning to its initial value after the activity of the losing chain has died away. The time of cell assembly competition is also clearly visible in both LFP approximations. The average membrane potential shows a dip right after the increased local firing rate due to the neuron reset and refractory period during which the membrane potential is clamped to zero. The change in the signal given by the summed and smoothed absolute postsynaptic currents is particularly pronounced at the transition sites due to the contribution of the inhibitory PSCs, which are g times larger than the excitatory currents. Figure 7(c) shows the spiking activity for the corresponding network without synfire chain competition. The activity moves from one chain to the next in a deterministic fashion. Figure 7(d) shows the corresponding collective signals. The approximated LFP signal still exhibits step-like changes due to the increase of inhibitory activity when either chain 2 or 7 is active, however the transient increases of LFP signal and firing rate and transient decreases of membrane potential indicated by arrows in Fig. 7(b) are not observed in the reduced network without synfire chain competition. These results suggests that low frequency components of the LFP in experimental data could be indicators for cell assembly competition.Fig. 7

Bottom Line: Here, we map the propagation of activity in a chain to a linearly evolving preferred velocity, which results in parabolic segments that fulfill the two-thirds power law.The model provides an explanation for the segmentation of the trajectory and the experimentally observed deviations of the trajectory from the parabolic shape at primitive transition sites.Furthermore, the model predicts low frequency oscillations (<10 Hz) of the motor cortex local field potential during ongoing movements and increasing firing rates of non-specific motor cortex neurons before movement onset.

View Article: PubMed Central - PubMed

Affiliation: Functional Neural Circuits Group, Faculty of Biology, Schänzlestrasse 1, 79104, Freiburg, Germany. hanuschkin@bccn.uni-freiburg.de

ABSTRACT
We present a biologically plausible spiking neuronal network model of free monkey scribbling that reproduces experimental findings on cortical activity and the properties of the scribbling trajectory. The model is based on the idea that synfire chains can encode movement primitives. Here, we map the propagation of activity in a chain to a linearly evolving preferred velocity, which results in parabolic segments that fulfill the two-thirds power law. Connections between chains that match the final velocity of one encoded primitive to the initial velocity of the next allow the composition of random sequences of primitives with smooth transitions. The model provides an explanation for the segmentation of the trajectory and the experimentally observed deviations of the trajectory from the parabolic shape at primitive transition sites. Furthermore, the model predicts low frequency oscillations (<10 Hz) of the motor cortex local field potential during ongoing movements and increasing firing rates of non-specific motor cortex neurons before movement onset.

Show MeSH