Details

Autor(en) / Beteiligte

• Heitmann, Stewart
• Boonstra, Tjeerd
• Breakspear, Michael
• Miller, Kai

Titel

A dendritic mechanism for decoding traveling waves: principles and applications to motor cortex

Ist Teil von

• PLoS computational biology, 2013-10, Vol.9 (10), p.e1003260-e1003260

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2013

Link zum Volltext

Quelle

Elektronische Zeitschriftenbibliothek

Beschreibungen/Notizen

• Traveling waves of neuronal oscillations have been observed in many cortical regions, including the motor and sensory cortex. Such waves are often modulated in a task-dependent fashion although their precise functional role remains a matter of debate. Here we conjecture that the cortex can utilize the direction and wavelength of traveling waves to encode information. We present a novel neural mechanism by which such information may be decoded by the spatial arrangement of receptors within the dendritic receptor field. In particular, we show how the density distributions of excitatory and inhibitory receptors can combine to act as a spatial filter of wave patterns. The proposed dendritic mechanism ensures that the neuron selectively responds to specific wave patterns, thus constituting a neural basis of pattern decoding. We validate this proposal in the descending motor system, where we model the large receptor fields of the pyramidal tract neurons - the principle outputs of the motor cortex - decoding motor commands encoded in the direction of traveling wave patterns in motor cortex. We use an existing model of field oscillations in motor cortex to investigate how the topology of the pyramidal cell receptor field acts to tune the cells responses to specific oscillatory wave patterns, even when those patterns are highly degraded. The model replicates key findings of the descending motor system during simple motor tasks, including variable interspike intervals and weak corticospinal coherence. By additionally showing how the nature of the wave patterns can be controlled by modulating the topology of local intra-cortical connections, we hence propose a novel integrated neuronal model of encoding and decoding motor commands.