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As epilepsy remains a refractory condition in about 30% of patients with complex partial seizures, electrical stimulation of the brain has recently shown potential for additive seizure control therapy. Previously, we applied noninvasive transcranial focal stimulation via novel tripolar concentric ring electrodes (TCREs) on the scalp of rats after inducing seizures with pentylenetetrazole (PTZ). We developed a close-loop system to detect seizures and automatically trigger the stimulation and evaluated its effect on the electrographic activity recorded by TCREs in rats. In our previous work the detectors of seizure onset were based on seizure-induced changes in signal power in the frequency range up to 100 Hz, while in this preliminary study we assess the feasibility of recording high frequency oscillations (HFOs) in the range up to 300 Hz noninvasively with scalp TCREs during PTZ-induced seizures. Grand average power spectral density estimate and generalized likelihood ratio tests were used to compare power of electrographic activity at different stages of seizure development in a group of rats (n= 8). The results suggest that TCREs have the ability to record HFOs from the scalp as well as that scalp-recorded HFOs can potentially be used as features for seizure onset detection.

Even though recent studies have suggested that seizures do not occur suddenly and that before a seizure there is a period with an increased probability of seizure occurrence, neurophysiological mechanisms of interictal and pre-seizure states are unknown. The ability of mathematical methods to provide much more sensitive tools for the detection of subtle changes in the electrical activity of the brain gives promise that electrophysiological markers of enhanced seizure susceptibility can be found even during interictal periods when EEG of epilepsy patients often looks 'normal'. Previously, we demonstrated in animals that hippocampal and neocortical gamma-band rhythms (30-100 Hz) intensify long before seizures caused by systemic infusion of kainic acid. Other studies in recent years have also drawn attention to the fast activity (>30 Hz) as a possible marker of epileptogenic tissue. The current study quantified gamma-band activity during interictal periods and seizures in intracranial EEG (iEEG) in 5 patients implanted with subdural grids/intracranial electrodes during their pre-surgical evaluation. In all our patients, we found distinctive (abnormal) bursts of gamma activity with a 3 to 100 fold increase in power at gamma frequencies with respect to selected by clinicians, quiescent, artifact-free, 7-20 min "normal" background (interictal) iEEG epochs 1 to 14 hours prior to seizures. Increases in gamma activity were largest in those channels which later displayed the most intensive electrographic seizure discharges. Moreover, location of gamma-band bursts correlated (with high specificity, 96.4% and sensitivity, 83.8%) with seizure onset zone (SOZ) determined by clinicians. Spatial localization of interictal gamma rhythms within SOZ suggests that the persistent presence of abnormally intensified gamma rhythms in the EEG may be an important tool for focus localization and possibly a determinant of epileptogenesis.

Epilepsy is a neurological disorder that affects approximately one percent of the world population. Anti-epileptic drugs are ineffective in 25~30% of cases. Electrical stimulation to control seizures may be an additive therapy. We applied noninvasive transcutaneous focal electrical stimulation (TFES) via concentric ring electrodes on the scalp of rats after inducing seizures with pentylenetetrazole. We found a significant increase in synchrony within the beta-gamma bands during seizures and that TFES significantly reduced the synchrony of the beta-gamma activity and increased synchrony in the delta band.

Near-infrared spectroscopy is a novel imaging technique potentially sensitive to both brain hemodynamics (slow signal) and neuronal activity (fast optical signal, FOS). The big challenge of measuring FOS noninvasively lies in the presumably low signal-to-noise ratio. Thus, detectability of the FOS has been controversially discussed. We present reliable detection of FOS from 11 individuals concurrently with electroencephalogram (EEG) during a Go-NoGo task. Probes were placed bilaterally over prefrontal cortex. Independent component analysis (ICA) was used for artifact removal. Correlation coefficient in the best correlated FOS-EEG ICA pairs was highly significant (p < 10(-8)), and event-related optical signal (EROS) was found in all subjects. Several EROS components were similar to the event-related potential (ERP) components. The most robust "optical N200" at t = 225 ms coincided with the N200 ERP; both signals showed significant difference between targets and nontargets, and their timing correlated with subject's reaction time. Correlation between FOS and EEG even in single trials provides further evidence that at least some FOS components "reflect" electrical brain processes directly. The data provide evidence for the early involvement of prefrontal cortex in rapid object recognition. EROS is highly localized and can provide cost-effective imaging tools for cortical mapping of cognitive processes.

Objectives: Gamma oscillations (30-100 Hz gamma electroencephalographic (EEG) activity) correlate with high frequency synchronous rhythmic bursting in assemblies of cerebral neurons participating in aspects of consciousness. Previous studies in a kainic acid animal model of epilepsy revealed increased intensity of gamma rhythms in background EEG preceding epileptiform discharges, leading the authors to test for intensified gamma EEG in humans with epilepsy., Methods: 64 channel cortical EEG were recorded from 10 people with primary generalised epilepsy, 11 with partial epilepsy, and 20 controls during a quiescent mental state. Using standard methods of EEG analysis the strength of EEG rhythms (fast Fourier transformation) was quantified and the strengths of rhythms in the patient groups compared with with controls by unpaired t test at 1 Hz intervals from 1 Hz to 100 Hz., Results: In patients with generalised epilepsy, there was a threefold to sevenfold increase in power of gamma EEG between 30 Hz and 100 Hz (p<0.01). Analysis of three unmedicated patients with primary generalised epilepsies revealed an additional 10-fold narrow band increase of power around 35 Hz-40 Hz (p<0.0001). There were no corresponding changes in patients with partial epilepsy., Conclusions: Increased gamma EEG is probably a marker of the underlying ion channel or neurotransmitter receptor dysfunction in primary generalised epilepsies and may also be a pathophysiological prerequisite for the development of seizures. The finding provides a new diagnostic approach and also links the pathophysiology of generalised epilepsies to emerging concepts of neuronal correlates of consciousness.

Fast (beta-gamma band 20-100 Hz) rhythms of electrical activity of the brain have been suggested to play an important role in perception, cognition and consciousness providing temporal binding of neural activities and allowing the formation of mental representations. The recent advances in the concept of temporal binding and their relation to the theory of neural networks (connectionism) are reviewed here as well as some experimental results concerning the intensified gamma rhythms and epilepsy. The hippocampal-neocortical gamma rhythms are extremely intense and hypersynchronous at onset of the epileptiform discharges induced by systemic kainic acid in the rat. Those gamma rhythms are followed by a slow rhythm of epileptiform spikes/sharp waves or spike-wave complexes ('spike-wave' activity). During spike-wave activity, gamma synchronisation is significantly decreased. A novel unifying concept is proposed which relates the associative principle of neural networks to the mechanism of temporal binding at high frequencies. It suggests that for each memory stored in an associative network there is a corresponding quasi-stable state of synchronous oscillation at some frequency within the gamma band. It also suggests that excessive temporal binding ("over-binding") occurs at seizure onset when abnormally intensified and globally synchronous fast activity is often observed. "Over-binding" may cause the undesirable formation of false associations due to inadequate synaptic modifications. To prevent this process, spike-wave discharge develops as an extreme activation of the mechanism capable to desynchronise and eventually suppress fast activity and erase the spurious modes of activity associated with hypersynchronous gamma rhythms. Thus, spike-wave activity is suggested to be the "anti-binding" mechanism. This mechanism is also related to the spikes/sharp waves normally occurring in the brain mostly in sleep. It is qualitatively similar to the "unlearning" mechanism of Crick and Mitchison presumably associated with the PGO spikes of the REM sleep.

Desynchronous (low voltage fast activity), synchronous (high voltage slow waves) as well as convulsive brain activities were stimulated by a computer model of neuronal population. Network excitatory and inhibitory elements possessed fundamental dynamic properties of real neurones. Being independent both of the excitability of elements and of external influence efficacy, synchronous (desynchronous) network activity resulted from the increase (decrease) of the average power of "neuronal" interconnections which imitated mutual and recurrent excitation and inhibition. The inhibition efficacy being reduced as compared with excitation, synchronization of elements became intensified. As a consequence, the rhythmic activity amplitude increased and the appearance of self-sustained oscillations simulating convulsive activity was facilitated. The probable mechanism of EEG activation by virtue of the reduction of mutual and recurrent excitation and inhibition efficacy as well as the significance of inhibitory mechanism deficiency for epileptogenesis are discussed.

On the basis of neuronal network a linearized model of power spectrum of the network stable activity was calculated with the approximation of external input by "white" noise. The power spectrum function obtained was used for approximation of the power spectra of the rats motor cortex potentials by the least squares method. As a result the network parameters modelling excitatory and inhibitory cellular and synaptic mechanisms were calculated for two rat strains differing in seizure readiness. As a result of calculations genetically predisposed to seizures KM rats were assumed to differ from unpredisposed to seizures Wistar rats in the increase of efficacy of neuronal interactions (excitatory and inhibitory) as a consequence of the enhanced neuronal "reactivity".

The resting EEGs of several brain structures (motor and visual cortex, caudate nucleus and intralaminar thalamic nuclei) were submitted to spectral and coherence computer analyses in two rat strains. Genetically predisposed to convulsive state KM rats were shown to differ from nonpredisposed Wistar rats in EEG spectral properties. KM rats EEG pattern was characterized by increase of low frequencies (1-2 Hz) power and decrease of faster activity (5-12 Hz) power in cortical spectrograms as well as by decrease of caudate nucleus EEG absolute power. The coherence value between cortical or subcortical structures at below 4 Hz was intensified in KM rats. Reinforcement of cortical auto-oscillating properties manifested by ECoG synchronization in cortical-thalamic resonance interaction as well as weakening of striatal inhibitory system may constitute neurophysiological mechanisms of enhanced convulsive readiness. The probable role of mediator imbalance in these mechanisms is discussed.

Brain rhythmic activity model on the basis of space uniform neuronal network consisting of excitatory and inhibitory elements was examined. Network activity description by "lump approximation" was compared with simulation model computation. Lump approximation parameters dependence on the properties of neurons and synapses as well as conditions of the transition between network activity types which imitate desynchronous (low voltage fast activity) and synchronous (high voltage slow waves) brain activities were obtained.