Timescales and the large-scale organization of cortical dynamics
In the first part of this talk I will present results from a model of 29 interacting areas in the macaque cortex. We built this model by combining quantitative data on long-range projections between cortical areas with an estimate of the strength of excitatory connections within an area. These anatomical constraints naturally give rise to a hierarchy of timescales in network activity: early sensory areas respond in a moment-to-moment fashion, allowing them to track a changing environment, while cognitive areas show long timescales, potentially providing the substrate for information integration and flexible decision-making. We characterize the dependence of this hierarchy on local and long-range anatomical properties and show the existence of multiple dynamical hierarchies subserved by the same anatomical structure. The model thus demonstrates how variations in anatomical properties across the cortex can produce dynamical and functional specialization in timescales of response.
I will then describe a network model for the temporal structure of human ECoG dynamics. We find the power spectra of ECoG recordings are well-described by the output of a randomly-connected linear dynamical network with net excitatory interactions between nodes. The architecture predicts that slow fluctuations show long-range spatial correlations and that decorrelation of inputs to a network could account for observed changes in ECoG power spectra upon task initiation. It also predicts that networks with strongly local connectivity should produce power spectra that show "1/f" behavior at low-frequencies. This analysis provides mechanistic insight into emergent network dynamics, links observed changes in power spectra to particular reconfigurations of the network and could help characterize differences between cortical regions, states and subjects.
In the first part of this talk I will present results from a model of 29 interacting areas in the macaque cortex. We built this model by combining quantitative data on long-range projections between cortical areas with an estimate of the strength of excitatory connections within an area. These anatomical constraints naturally give rise to a hierarchy of timescales in network activity: early sensory areas respond in a moment-to-moment fashion, allowing them to track a changing environment, while cognitive areas show long timescales, potentially providing the substrate for information integration and flexible decision-making. We characterize the dependence of this hierarchy on local and long-range anatomical properties and show the existence of multiple dynamical hierarchies subserved by the same anatomical structure. The model thus demonstrates how variations in anatomical properties across the cortex can produce dynamical and functional specialization in timescales of response.
I will then describe a network model for the temporal structure of human ECoG dynamics. We find the power spectra of ECoG recordings are well-described by the output of a randomly-connected linear dynamical network with net excitatory interactions between nodes. The architecture predicts that slow fluctuations show long-range spatial correlations and that decorrelation of inputs to a network could account for observed changes in ECoG power spectra upon task initiation. It also predicts that networks with strongly local connectivity should produce power spectra that show "1/f" behavior at low-frequencies. This analysis provides mechanistic insight into emergent network dynamics, links observed changes in power spectra to particular reconfigurations of the network and could help characterize differences between cortical regions, states and subjects.
No comments:
Post a Comment
Note: Only a member of this blog may post a comment.