Abstract
The cerebral cortex exhibits neural activity even in the absence of external stimuli. This self-sustained activity is characterized by irregular firing of individual neurons and population oscillations with a broad frequency range. Questions that arise in this context, are: What are the mechanisms responsible for the existence of neuronal spiking activity in the cortex without external input? Do these mechanisms depend on the structural organization of the cortical connections? Do they depend on intrinsic characteristics of the cortical neurons? To approach the answers to these questions, we have used computer simulations of cortical network models. Our networks have hierarchical modular architecture and are composed of combinations of neuron models that reproduce the firing behavior of the five main cortical electrophysiological cell classes: regular spiking (RS), chattering (CH), intrinsically bursting (IB), low threshold spiking (LTS), and fast spiking (FS). The population of excitatory neurons is built of RS cells (always present) and either CH or IB cells. Inhibitory neurons belong to the same class, either LTS or FS. Long-lived self-sustained activity states in our network simulations display irregular single neuron firing and oscillatory activity similar to experimentally measured ones. The duration of self-sustained activity strongly depends on the initial conditions, suggesting a transient chaotic regime. Extensive analysis of the self-sustained activity states showed that their lifetime expectancy increases with the number of network modules and is favored when the network is composed of excitatory neurons of the RS and CH classes combined with inhibitory neurons of the LTS class. These results indicate that the existence and properties of the self-sustained cortical activity states depend on both the topology of the network and the neuronal mixture that comprises the network.
Highlights
The same tendency, but with a weaker effect, was observed when the inhibitory neurons belonged to the fast spiking (FS) class: here at H = 2 and with 40% of CH neurons the distributions of activity lifetimes had medians that exceeded 1000 ms and some initial conditions resulted in sustained activity (SSA) states with lifetimes ∼104 ms
The architecture of the network is hierarchical and modular, which arguably (Wang et al, 2011; Samu et al, 2014) represents the generic topological organization of the cortex across many spatial scales, and the excitatory and inhibitory cells of our model belong to five distinct electrophysiological classes that can coexist in the same network (Nowak et al, 2003; Contreras, 2004)
To do so we performed an extensive computational study of our model by considering network architectures characterized by different combinations of hierarchical and modularity levels, mixture of excitatory-inhibitory neurons, strength of excitatory-inhibitory synapses and network size submitted to distinct initial conditions
Summary
The resting state of the brain, i.e., its state in the absence of sensory stimuli or behavioral tasks, shows sustained ongoing activity characterized by irregular neuronal firing and macroscopic ensemble oscillations covering a broad frequency range, from less than 1 Hz up to more than 100 Hz (Arieli et al, 1995; Bringuier et al, 1999; Tsodyks et al, 1999; Buzsáki and Draguhn, 2004; Fox and Raichle, 2007; Roopun et al, 2008; Shmuel and Leopold, 2008; Hahn et al, 2010). In the configuration with RS and CH excitatory neurons and LTS inhibitory neurons, hierarchical levels H = 1, 2 allowed the SSA lifetime to reach values ∼104 ms in the upper right corner of the diagram (see rows in Table 1 corresponding to LTS cases with H = 1, 2 and 20% or 40%CH) and a few thousand ms in the middle part of the diagram (not shown). The same tendency, but with a weaker effect, was observed when the inhibitory neurons belonged to the FS class (see Table 1 rows corresponding to FS cases with H = 1, 2 and 20% or 40%CH): here at H = 2 and with 40% of CH neurons the distributions of activity lifetimes had medians that exceeded 1000 ms and some initial conditions resulted in SSA states with lifetimes ∼104 ms
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