In experimental studies, electrical stimulation (ES) has been applied to induce neuronal activity or to disrupt pathological patterns. Nevertheless, the underlying mechanisms of these activity pattern transitions are not clear. To study these phenomena, we simulated a model of the hippocampal region CA1. The computational simulations using different amplitude levels and duration of ES revealed three states of neuronal excitability: burst-firing mode, depolarization block and spreading depression wave. We used the bifurcation theory to analyse the interference of ES in the cellular excitability and the neuronal dynamics. Understanding this process would help to improve the ES techniques to control some neurological disorders.

Here we propose and evaluate a new approach to analyse multichannel mesial temporal lobe epilepsy EEG data from eight patients through complex network and synchronization theories. The method employs a Granger causality test to infer the directed connectivity graphs and a wavelet transform based phase synchronization measure whose characteristics allow studying dynamical transitions during epileptic seizures. We present a new combined graph measure that quantifies the level of network hub formation, called network hub out-degree, which closely reflects the level of synchronization observed during the ictus.

This paper presents a unified mathematical derivation of the asymptotic behaviour of the three main forms of partial directed coherence (PDC). Numerical examples are used to contrast PDC, gPDC (generalized PDC) and iPDC (information PDC) as to meaning and applicability and, more importantly, to show their essential statistical equivalence insofar as connectivity inference is concerned.

We studied the influence of five biologic artifacts sources on quantitative EEG (blinking, forced eyes closure, forced jaw closure, tongue movements and pursuit eyes movements) through both visual and spectral analysis, with the purpose of verifying how do these artifacts can be seen in a cartographic way. We found that the spectrums potentials showed the same topographic display that was found through visual analysis. Visual analysis was superior than the quantitative evaluation to recognise the artifacts, as the former preserved the morphological display of the paroxysms. However it is important know how do the potentials are represented in quantitative maps, so that they can be identified as artifacts and not as pathologic EEG activity.

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Thalamic neurons have two firing modes: tonic and bursting. It was originally suggested that bursting occurs only during states such as slow-wave sleep, when little or no information is relayed by the thalamus. However, bursting occurs during wakefulness in the visual and somatosensory thalamus, and could theoretically influence sensory processing. Here we used chronically implanted electrodes to record from the ventroposterior medial thalamic nucleus (VPM) and primary somatosensory cortex (SI) of awake, freely moving rats during different behaviors. These behaviors included quiet immobility, exploratory whisking (large-amplitude whisker movements), and whisker twitching (small-amplitude, 7- to 12-Hz whisker movements). We demonstrated that thalamic bursting appeared during the oscillatory activity occurring before whisker twitching movements, and continued throughout the whisker twitching. Further, thalamic bursting occurred during whisker twitching substantially more often than during the other behaviors, and a neuron was most likely to respond to a stimulus if a burst occurred ≈120 ms before the stimulation. In addition, the amount of cortical area activated was similar to that during whisking. However, when SI was inactivated by muscimol infusion, whisker twitching was never observed. Finally, we used a statistical technique called partial directed coherence to identify the direction of influence of neural activity between VPM and SI, and observed that there was more directional coherence from SI to VPM during whisker twitching than during the other behaviors. Based on these findings, we propose that during whisker twitching, a descending signal from SI triggers thalamic bursting that primes the thalamocortical loop for enhanced signal detection during the whisker twitching behavior.

Modern methods in molecular biology, neuroanatomy, functional imaging, and monitoring electric signals from neuronal depolarization remains important when evaluating the functional aspects of both normal and pathological neural circuitry. Correlation methods ranks popular and are extensively used to analyze the functional interaction in the electroencephalogram (EEG), magnetoencephalogram, local field potentials, and recorded single- and multi-unit activity of many structures. A host of analytical techniques emerged, some employing information theoretic rationales by assessing mutual information or interdependence between signal pairs, while others are extensions of spectral analysis/coherence analysis. A large fraction of neuroscientists rely on the cross-correlation between the activities of pairs of neural structures to infer their functionality. The effective structural inference is possible, if simultaneous signals from many structures are jointly analyzed. To handle simultaneous structures, the recently introduced notion of partial directed coherence (PDC) is employed. This approach for simultaneous multichannel data analysis is based on Granger causality that employs multivariate auto-regressive (MAR) models for computational purposes. By analyzing linear toy models, PDC's superior performance over other commonly used methods specially cross-correlation and classical coherence, directed transfer function (DTF) analysis provides complementary information whose analysis is less clear than PDC's.

This paper discusses the employment of non-parametric non-linear prediction algorithms to investigate non-linear dynamics in the rhythmic brain activity of rats. Three algorithms (Sugihara-May Simplex, K-neighbour and Casdagli's) were tested yielding similar prediction results which--when subject to a suitable bootstrap based t-tests--revealed that the theta waves recorded in rat brains cannot have their intrinsic non-linearity dismissed at a significance of 0.05.

This paper illustrates the use of the recently introduced method of partial directed coherence in approaching how interactions among neural structures change over short time spans that characterize well defined behavioral states. Central to the method is its use of multivariate time series modelling in conjunction with the concept of Granger causality. Simulated neural network models were used to illustrate the technique's power and limitations when dealing with neural spiking data. This was followed by the analysis of multi-unit activity data illustrating dynamical change in the interaction of thalamo-cortical structures in a behaving rat.

The primate somatosensory cortex, which processes tactile stimuli, contains a topographic representation of the signals it receives, but the way in which such maps are maintained is poorly understood. Previous studies of cortical plasticity indicated that changes in cortical representation during learning arise largely as a result of hebbian synaptic change mechanisms. Here we show, using owl monkeys trained to respond to specific stimulus sequence events, that serial application of stimuli to the fingers results in changes to the neuronal response specificity and maps of the hand surfaces in the true primary somatosensory cortical field (S1 area 3b). In this representational remodelling stimuli applied asychronously to the fingers resulted in these fingers being integrated in their representation, whereas fingers to which stimuli were applied asynchronously were segregated in their representation. Ventroposterior thalamus response maps derived in these monkeys were not equivalently reorganized. This representational plasticity appears to be cortical in origin.

Electro-oscillographic recordings show that when rats wake up, behavioral manifestations such as head dorsal extension and snout and eye movements (which occur in this sequence), occasionally followed by brief ear and limb twitches, are preceded by and are simultaneous with theta waves (around 6.5 Hz in frequency) in neocortical areas 3 and 17 and in the hippocampus. Heart rate increases when the animal passes from synchronized sleep to relaxed wakefulness to exploratory behavior. During desynchronized sleep theta waves, similar to those found during alertness, usually precede and are simultaneous with rostrum and eye movements and brief ear and limb twitches. Heart rate also increases during dreaming activity. A high degree of coherence (near 1.0) was found among theta bursts in different hippocampal areas in both highly attentive alertness and dreaming. It is suggested that theta waves are related to attention as part of some kinds of behavior and of the process of dream shaping and expression, both characterized by consciousness.

The electrical activity of the posterior thalamic nuclear complex was studied in rats and related to the simultaneous hippocampal electro-oscillogram. Electrocorticographic tracings and spectral analysis showed that during attentive wakefulness the electro-oscillogram peaked at 8 Hz and in desynchronized sleep it oscillated at regular frequencies between 8 and 9 Hz. In quiet wakefulness, frequency was lower (around 6 Hz) and during synchronized sleep rhythmicity disappeared. The electrophysiological patterns during wakefulness and desynchronized sleep are proposed to be linked to the retrieval and combination of information for the generation of attention and dream content.