Narrow Results

The theory of phase resetting can reveal important information about the dynamic behavior of a periodic system when a single brief stimulus is applied to that system at the appropriate time. Phase resetting studies have revealed the existence in some biological systems of a vulnerable stimulus window generating desynchronization and suppression of the activity. The objective of this study was to test the hypothesis that a "singular" stimulus could annihilate this activity. Perfusion with the high-K solution produced synchronous, quasi-periodic population bursts with inter-burst interval of ~0.8–1.5 seconds. A single 0.1 ms duration anodic pulse of programmable delay and magnitude was applied to the somatic layer of the CA3 pyramidal cells. Three types of phase-resetting behavior were observed: (1) Weak resetting with little or no effect on the timing of the subsequent burst, (2) Strong resetting where the applied current pulse delayed the next event by one time period, (3) Singular behavior where the applied pulse partially or completely suppressed the subsequent bursting. The singular stimulus parameter window, however, was very narrow making it difficult to generate the singular behavior reliably. Nevertheless, the results indicate that singularities exist for high potassium neural activity and that a well timed pulse applied with the right amplitude can suppress this activity. This study suggests that phase resetting of a population of neurons is possible for quasi-periodic interictal activity and similar techniques could be applied to the control of epileptic seizures.

Objective: In patients with Genetic Generalized Epilepsy (GGE), transcranial magnetic stimulation (TMS) can induce epileptiform discharges (EDs) of varying duration. We hypothesized that (a) the ED duration is determined by the dynamic states of critical network nodes (brain areas) at the early post-TMS period, and (b) brain connectivity changes before, during and after the ED, as well as within the ED. Methods: EEG recordings from two GGE patients were analyzed. For hypothesis (a), the characteristics of the brain dynamics at the early ED stage are measured with univariate and multivariate EEG measures and the dependence of the ED duration on these measures is evaluated. For hypothesis (b), effective connectivity measures are combined with network indices so as to quantify the brain network characteristics and identify changes in brain connectivity. Results: A number of measures combined with specific channels computed on the first EEG segment post-TMS correlate with the ED duration. In addition, brain connectivity is altered from pre-ED to ED and post-ED and statistically significant changes were also detected across stages within the ED. Conclusion: ED duration is not purely stochastic, but depends on the dynamics of the post-TMS brain state. The brain network dynamics is significantly altered in the course of EDs.

Generalized periodic discharges (GPD) are generalized waveforms that recur with a relatively uniform morphology and duration observed in EEG recordings of many types of metabolic encephalopathy, which are often referred to as epileptiform. In this paper, we try to link these spatiotemporal electrocortical activities and significant attributes of cortex based on Liley’s mean field model, and seek possible generation mechanisms of GPD rhythms from several factors. To these ends, the dynamical properties of simulated EEG consistent with neurophysiological features of human cortex are investigated, among which GPD patterns are our focus. Firstly, with different value sets of model parameters, we reproduce some typical simulation waveforms which are analogous to mammalian normal or abnormal brain activities detected by EEG. Or in other words, we put more emphasis on brain waveforms of GPD states, normal states, and low firing rate states in our numerical simulations, and mode transitions among different firing states are our main interests. Secondly, through analysis of maximum Lyapunov exponents and frequency spectrum, we give several mode transitions by varying synaptic connections between excitatory and inhibitory populations, which support the conjecture that selective changes of synaptic connections can trigger GPD states, such as in excitatory (AMPA receptors) and inhibitory neurotransmitters (GABA receptors). Thirdly, we stress the importance of time delay on neural population connections and find that they are free to transfer among different firing modes with appropriate time delays. Furthermore, considering the effects of external inputs to cerebral cortex, we verify that stimulation can lead to good controls on GPD patterns, including facilitation and elimination. Finally, we show that more dynamical rhythms can be produced when taking into account the cortico-cortical connections. These modeling results are expected to shed light into the pathophysiological mechanisms of GPD modes from a theoretical viewpoint.