Pathological Effect of Homeostatic Synaptic Scaling on Network Dynamics in Diseases of the Cortex

Abstract

Slow periodic EEG discharges are common in CNS disorders. The pathophysiology of this aberrant rhythmic activity is poorly understood. We used a computational model of a neocortical network with a dynamic homeostatic scaling rule to show that loss of input (partial deafferentation) can trigger network reorganization that results in pathological periodic discharges. The decrease in average firing rate in the network by deafferentation was compensated by homeostatic synaptic scaling of recurrent excitation among pyramidal cells. Synaptic scaling succeeded in recovering the network target firing rate for all degrees of deafferentation (fraction of deafferented cells), but there was a critical degree of deafferentation for pathological network reorganization. For deafferentation degrees below this value, homeostatic upregulation of recurrent excitation had minimal effect on the macroscopic network dynamics. For deafferentation above this threshold, however, a slow periodic oscillation appeared, patterns of activity were less sparse, and bursting occurred in individual neurons. Also, comparison of spike-triggered afferent and recurrent excitatory conductances revealed that information transmission was strongly impaired. These results suggest that homeostatic plasticity can lead to secondary functional impairment in case of cortical disorders associated with cell loss.

Embedding Multiple Trajectories in Simulated Recurrent Neural Networks in a Self-Organizing Manner

“…In the present study the duration of a trial was 250 ms, and in between trials all state variables were considered to have decayed back to their initial values. This scheme for trial-based learning dynamics was used since the time scale of homeostatic plasticity and neural activation is not agreed upon (Buonomano, 2005;Fröhlich et al, 2008).…”

“…One synaptic learning rule that would appear to be well suited to guide network dynamics to stable dynamical regimes is synaptic scaling (van Rossum et al, 2000). However, it has been previously shown that, when recurrent networks are driven by transient synaptic activity, synaptic scaling is inherently unstable (Buonomano, 2005), and can underlie repeating pathological burst discharges (Houweling et al, 2005;Fröhlich et al, 2008). Additionally, a number of experimental studies have shown that while synapses may be up or downregulated in a homeostatic manner, this form of plasticity does not always obey synaptic scaling (Thiagarajan et al, 2005(Thiagarajan et al, , 2007Goel and Lee, 2007).…”

Spike-Time Precision and Network Synchrony Are Controlled by the Homeostatic Regulation of the D-Type Potassium Current

“…Homeostatic plasticity has previously been implicated in the restoration of rhythmic network activity in invertebrates (Turrigiano et al, 1994) and the spinal cord (Galante et al, 2001). Studies using in vivo sensory deprivation (Maffei and Turrigiano, 2008), organotypic slice culture (Buckby et al, 2006;Karmarkar and Buonomano, 2006;Kim and Tsien, 2008), and computational modeling (Frohlich et al, 2008) have begun to explore the network effects of homeostasis. Here we show that the presence of an ionic conductance cannot only control the precision of the generation of an AP at the scale of single principal neurons but can also determine network synchrony, endowing voltagedependent ion channels with increasing functional significance.…”

Adaptation to prolonged neuromodulation in cortical cultures: an invariable return to network synchrony

“…These network-wide bursts are less frequent and more stereotyped as compared to those observed in the intact brain, which might be expected given the smaller size and lower connection density of these networks as well as the lack of reentrant pathways [21,[39][40][41]). Moreover, it has been suggested that the degree of synchrony in these and other in vitro preparations is exacerbated by various homeostatic responses to deafferentation, resulting in activity forms that share some similarities with seizure-related paroxysmal activity (as indicated by in vivo deafferentation studies [42,43]). Yet, while the forms of synchrony observed in vitro differ in many respects from those associated with low arousal levels in the intact brain, their underlying biophysical mechanisms share important similarities.…”