Interictal fast oscillations between 100 and 500 Hz have been reported in signals recorded from implanted microelectrodes in epileptic patients and experimental rat models. Oscillations between 250 and 500 Hz, or fast ripples (FR), appeared related to the epileptic focus whereas ripples (80^200 Hz) were not. We report high-frequency oscillations recorded with intracranial macroelectrodes in seven patients with refractory focal epilepsy during slow-wave sleep.We characterize the relation of fast oscillations to the seizure focus and quantify their concordance with epileptiform transients, with which they are strongly associated. The patients were selected because interictal spikes were found within and outside the seizure onset zone.Visual inspection was used to identify and classify the ripples and FRs according to their relation to epileptiform spikes. Continuoustime wavelet analysis was used to compute their power. Ripples were present in all patients while FRs where found in five of the seven patients. Most ripples and FRs occurred at the same time as epileptiform transients. The rate of occurrence of ripples was higher within the seizure onset zone than outside in four of seven patients. The rate of FRs was much higher within the seizure onset zone than outside in four of the five patients with FRs (in these four patients, FRs were almost inexistent outside the seizure onset zone). The power of ripples and FRs tended to be higher in the electrodes where their rate was also higher. These results indicate that FRs were more restricted to the electrodes located within the seizure onset zone, especially to the hippocampus,

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of stratum lacunosum-moleculare in rat hippocampus contributes to associative LTP at a phase offset in stratum radiatum. J Neurophysiol 92: 1615–1624, 2004. First published May 5, 2004; 10.1152/jn.00848.2003. Computational modeling demonstrates that encoding and context-dependent retrieval of memories in region CA1 of the hippocampus will be most effective when the phase of strongest entorhinal input (to stratum lacunosum-moleculare) is offset from the phase of maximal induction of long-term potentiation at Schaffer collateral synapses (in s. radiatum). This would allow entorhinal input to play a role in both retrieval and encoding without engaging long-term potentiation (LTP) during retrieval. Experiments in brain slice preparations of the hippocampal formation tested the relationship between rhythmic input to s. lacunosum-moleculare and the time of maximal LTP induction at Schaffer collateral synapses in s. radiatum. Analysis of the data demonstrates a statistically significant difference in the induction of LTP for different time intervals between the end of each four-pulse train in s. lacunosum-moleculare and the single pulse s. radiatum stimulation. The time of maximal LTP induction was found to be �30 ms after the end of lacunosum-moleculare stimulation, consistent with the requirements of the model.

The idea that sleep might be involved in brain plasticity has been investigated for many years through a large number of animal and human studies, but evidence remains fragmentary. Large amounts of sleep in early life suggest that sleep may play a role in brain maturation. In particular, the influence of sleep in developing the visual system has been highlighted. The current data suggest that both Rapid Eye Movement (REM) and non-REM sleep states would be important for brain development. Such findings stress the need for optimal paediatric sleep management. In the adult brain, the role of sleep in learning and memory is emphasized by studies at behavioural, systems, cellular and molecular levels. First, sleep amounts are reported to increase following a learning task and sleep deprivation impairs task acquisition and consolidation. At the systems level, neurophysiological studies suggest possible mechanisms for the consolidation of memory traces. These imply both thalamocortical and hippocampo-neocortical networks. Similarly, neuroimaging techniques demonstrated the experiencedependent changes in cerebral activity during sleep. Finally, recent works show the modulation during sleep of cerebral protein synthesis and expression of genes involved in neuronal plasticity.

Frequency-dependent signal transmission and modulation by neuromodulators

ABSTRACT: Neuronal population oscillations at a variety of frequen-cies can be readily seen in electroencephalographic (EEG) as well as local field potential recordings in many different species. Although these brain rhythms have been studied for many years, the methods for identi-fying discrete oscillatory epochs are still widely variable across studies. The ‘‘better oscillation detection’ ’ (BOSC) method applies standardized criteria to detect runs of ‘‘true’ ’ oscillatory activity and rejects transient events that do not reflect actual rhythms. It does so by estimating the background spectrum of the actual signal to derive detection criteria that include both power and duration thresholds. This method has not yet been applied to nonhuman data. Here, we test the BOSC method on two important rat hippocampal oscillatory signals, the theta rhythm and slow oscillation (SO), two large amplitude and mutually exclusive states. The BOSC method detected both the relatively sustained theta rhythm and the relatively transient SO apparent under urethane anesthesia and was relatively resilient to spectral features that changed across states, complementing previous findings for human EEG. Detection of oscilla-tory activity using the BOSC method (but not more traditional Fourier transform-based power analysis) corresponded well with human expert ratings. Moreover, for near-continuous theta, BOSC proved useful for detecting discrete disruptions that were associated with sudden and large amplitude phase shifts of the ongoing rhythm. Thus, the BOSC method accurately extracts oscillatory and nonoscillatory episodes from field potential recordings and produces systematic, objective, and con-sistent results—not only across frequencies, brain regions, tasks, and waking states, as shown previously, but also across species and for both sustained and transient rhythms. Thus, the BOSC method will facilitate more direct comparisons of oscillatory brain activity across all types of experimental paradigms. VC 2011 Wiley Periodicals, Inc. KEY WORDS: theta; slow oscillation; urethane anesthesia; brain state; spectral analysis

Modulation of hippocampal sharp wave-ripple activity in vitro.

Abstract: Spectral decomposition, to this day, still remains the main analytical paradigm for the analysis of EEG oscillations. However, conventional spectral analysis assesses the mean characteristics of the EEG power spectra averaged out over extended periods of time and/or broad frequency bands, thus resulting in a “static ” picture which cannot reflect adequately the underlying neurodynamic. A relatively new promising area in the study of EEG is based on reducing the signal to elementary short-term spectra of various types in accordance with the number of types of EEG stationary segments instead of using averaged power spectrum for the whole EEG. It is suggested that the various perceptual and cognitive operations associated with a mental or behavioural condition constitute a single distinguishable neurophysiological state with a distinct and reliable spectral pattern. In this case, one type of short-term spectral pattern may be considered as a single event in EEG phenomenology. To support this assumption the following issues are considered in detail: (a) the relations between local EEG short-term spectral pattern of particular type and the actual state of the neurons in underlying network and a volume conduction; (b) relationship between morphology of EEG short-term spectral pattern and the state of the underlying neurodynamical system i.e. neuronal assembly; (c) relation of different spectral pattern components to a distinct physiological mechanism; (d) relation of different spectral pattern components to different functional significance; (e) developmental changes of spectral pattern components; (f) heredity of the variance in the individual spectral pattern and its components; (g) intra-individual stability of the sets of EEG short-term spectral patterns and their percent ratio; (h)