Neocortical hyperexcitability in a genetic model of absence seizures and its reduction by levetiracetam

PURPOSE: To study the effect of the antiepileptic drug levetiracetam (LEV) on the patterns of intrinsic optical signals (IOSs) generated by slices of the somatosensory cortex obtained from 3- and 6-month-old WAG/Rij and age-matched, nonepileptic control (NEC) rats. METHODS: WAG/Rij and NEC animals were anesthetized with enfluorane and decapitated. Brains were quickly removed, and neocortical slices were cut coronally with a vibratome, transferred to a submerged tissue chamber, and superfused with oxygenated artificial cerebrospinal fluid (aCSF). Slices were illuminated with a dark-field condensor and examined with a x2.5 objective; images were processed with a real time digital video image-enhancement system. Images were acquired before (background) and during electrical stimulation with a temporal resolution of 10 images/s and were displayed in pseudocolors. Extracellular stimuli (200 micros; <4 V) were delivered through bipolar stainless steel electrodes placed in the white matter. RESULTS: IOSs recorded in NEC slices bathed in control aCSF became less intense and of reduced size with age (p < 0.05); this trend was not seen in WAG/Rij slices. Age-dependent decreases in IOS intensity and area size were also seen in NEC slices superfused with aCSF containing the convulsant 4-aminopyridine (4-AP, 5 microM); in contrast, significant increases in both parameters occurred with age in 4-AP-treated WAG/Rij slices (p < 0.05). Under any of these conditions, the IOS intensity and area size slices were larger in WAG/Rij than in NEC slices. LEV (50-500 microM) application to WAG/Rij slices caused dose-dependent IOS reductions that were evident both in control and in 4-AP-containing aCSF and were more pronounced in 6-month-old tissue. CONCLUSIONS: These data demonstrate age-dependent IOS modifications in NEC and WAG/Rij rat slices and identify a clear pattern of hyperexcitability that occurs in 6-month-old WAG/Rij neocortical tissue, an age when absence seizures occur in all animals. The ability of LEV to reduce these patterns of network hyperexcitability supports the potential use of this new antiepileptic drug in primary generalized epileptic disorders

Homeostatic Scaling of Excitability in Recurrent Neural Networks

Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which neurons reside. However, most neurons are embedded in recurrent networks, which require a delicate balance between excitation and inhibition to maintain network stability. This balance could be disrupted when neurons independently adjust their intrinsic excitability. Here, we study the functioning of activity-dependent homeostatic scaling of intrinsic excitability (HSE) in a recurrent neural network. Using both simulations of a recurrent network consisting of excitatory and inhibitory neurons that implement HSE, and a mean-field description of adapting excitatory and inhibitory populations, we show that the stability of such adapting networks critically depends on the relationship between the adaptation time scales of both neuron populations. In a stable adapting network, HSE can keep all neurons functioning within their dynamic range, while the network is undergoing several (patho)physiologically relevant types of plasticity, such as persistent changes in external drive, changes in connection strengths, or the loss of inhibitory cells from the network. However, HSE cannot prevent the unstable network dynamics that result when, due to such plasticity, recurrent excitation in the network becomes too strong compared to feedback inhibition. This suggests that keeping a neural network in a stable and functional state requires the coordination of distinct homeostatic mechanisms that operate not only by adjusting neural excitability, but also by controlling network connectivity

Impact of Dendritic Size and Dendritic Topology on Burst Firing in Pyramidal Cells

Neurons display a wide range of intrinsic firing patterns. A particularly relevant pattern for neuronal signaling and synaptic plasticity is burst firing, the generation of clusters of action potentials with short interspike intervals. Besides ion-channel composition, dendritic morphology appears to be an important factor modulating firing pattern. However, the underlying mechanisms are poorly understood, and the impact of morphology on burst firing remains insufficiently known. Dendritic morphology is not fixed but can undergo significant changes in many pathological conditions. Using computational models of neocortical pyramidal cells, we here show that not only the total length of the apical dendrite but also the topological structure of its branching pattern markedly influences inter- and intraburst spike intervals and even determines whether or not a cell exhibits burst firing. We found that there is only a range of dendritic sizes that supports burst firing, and that this range is modulated by dendritic topology. Either reducing or enlarging the dendritic tree, or merely modifying its topological structure without changing total dendritic length, can transform a cell's firing pattern from bursting to tonic firing. Interestingly, the results are largely independent of whether the cells are stimulated by current injection at the soma or by synapses distributed over the dendritic tree. By means of a novel measure called mean electrotonic path length, we show that the influence of dendritic morphology on burst firing is attributable to the effect both dendritic size and dendritic topology have, not on somatic input conductance, but on the average spatial extent of the dendritic tree and the spatiotemporal dynamics of the dendritic membrane potential. Our results suggest that alterations in size or topology of pyramidal cell morphology, such as observed in Alzheimer's disease, mental retardation, epilepsy, and chronic stress, could change neuronal burst firing and thus ultimately affect information processing and cognition