Fernando H. Lopes da Silva

Neural mechanisms underlying brain waves: from neural membranes to networks

In this review, a number of experimental findings and theoretical concepts that have led to new insights into the mechanisms underlying brain waves are presented. At the cellular level, the new evidence that certain types of neuron have intrinsic oscillatory properties that may underlie rhythmic EEG activities is discussed. In particular, the question of whether spindle oscillations are autonomous or input-dependent is addressed. At the neural network level, the main circuits of the thalamus and cortex that are responsible for the occurrence and modulation of spindles and alpha activity are described. In addition, the properties of rhythmic activities outside the alpha band are considered, particularly in relation to the prominent beta activity of the visual cortex. At the theoretical level, the possibility that neural networks may behave as complex dynamic systems with the properties of deterministic chaos is discussed. Finally, the fact that brain rhythms may have functional implications for the working of neural networks is examined in relation to 2 cases: the possibility that oscillations may subserve a gating function, and that oscillations may play a role in the formation of assemblies of neurons that represent given stimulus patterns.

Chaos or noise in EEG signals; dependence on state and brain site ☆

EEG signals have been considered to result either from random processes or to be generated by non-linear dynamic systems exhibiting chaotic behaviour. In the latter case, the system may behave as a deterministic chaotic attractor. The complexity of the attractor can be characterized by the correlation dimension that can be computed from one signal generated by the system. A new procedure was developed and applied in order to test whether the correlation dimension, calculated from an EEG epoch, may correspond to a chaotic attractor or to a random process. This procedure was applied to EEG signals recorded from different sites of the limbic cortex of the rat during different states: wakeful rest, locomotion and in the course of an epileptic seizure induced by kindling. The signals recorded during the first two states had high dimensions and could not be distinguished from random noise. However, during an epileptic seizure the correlation dimension became low (between 2 and 4) indicating that in this state the networks behave as chaotic systems. A low correlation dimension appeared at different times and brain sites during an epileptic seizure. These results show that the computation of the correlation dimension may be useful in order to obtain insight into the dynamics of the propagation of an epileptic seizure in the brain.

Cortico-hippocampal communication by way of parallel parahippocampal-subicular pathways

The hippocampal memory system, consisting of the hippocampal formation and the adjacent parahippocampal region, is known to play an important role in learning and memory processes. In recent years, evidence from a variety of experimental approaches indicates that each of the constituting fields of the hippocampal memory system may serve functionally different, yet complementary roles. Understanding the anatomical organization of cortico‐parahippocampal‐hippocampal connectivity may lead to a further understanding of these potential functional differences. In the present paper we present the two main conclusions of experiments in which we studied the anatomical organization of the hippocampal memory system of the rat in detail, with a focus on the pivotal position of the entorhinal cortex. We first conclude that the simple traditional view of the entorhinal cortex as simply the input and output structure of the hippocampal formation needs to be modified. Second, our data indicate the existence of two parallel pathways through the hippocampal memory system, arising from the perirhinal and postrhinal cortex. These two parallel pathways may be involved in separately processing functionally different types of sensory information. This second proposition will be subsequently evaluated on the basis of series of electrophysiological studies we carried out in rats and some preliminary functional brain imaging studies in humans. Hippocampus 10:398–410, 2000

Potential new antiepileptogenic targets indicated by microarray analysis in a rat model for temporal lobe epilepsy.

To get insight into the mechanisms that may lead to progression of temporal lobe epilepsy, we investigated gene expression during epileptogenesis in the rat. RNA was obtained from three different brain regions [CA3, entorhinal cortex (EC), and cerebellum (CB)] at three different time points after electrically induced status epilepticus (SE): acute phase [group D (1 d)], latent period [group W (1 week)], and chronic epileptic period [group M (3–4 months)]. A group that was stimulated but that had not experienced SE and later epilepsy was also included (group nS). Gene expression analysis was performed using the Affymetrix Gene Chip System (RAE230A). We used GENMAPP and Gene Ontology to identify global biological trends in gene expression data. The immune response was the most prominent process changed during all three phases of epileptogenesis. Synaptic transmission was a downregulated process during the acute and latent phases. GABA receptor subunits involved in tonic inhibition were persistently downregulated. These changes were observed mostly in both CA3 and EC but not in CB. Rats that were stimulated but that did not develop spontaneous seizures later on had also some changes in gene expression, but this was not reflected in a significant change of a biological process. These data suggest that the targeting of specific genes that are involved in these biological processes may be a promising strategy to slow down or prevent the progression of epilepsy. Especially genes related to the immune response, such as complement factors, interleukins, and genes related to prostaglandin synthesis and coagulation pathway may be interesting targets.

Upregulation of metabotropic glutamate receptor subtype mGluR3 and mGluR5 in reactive astrocytes in a rat model of mesial temporal lobe epilepsy

Reactive gliosis is a prominent morphological feature of mesial temporal lobe epilepsy. Because astrocytes express glutamate receptors, we examined changes in metabotropic glutamate receptor (mGluR) 2/3, mGluR5 and transforming growth factor (TGF)‐β in glial cells of the hippocampal regions in an experimental rat model of spontaneous seizures. Rats that exhibited behavioural status epilepticus (SE) directly after 1 h of electrical angular bundle stimulation, displayed chronic spontaneous seizures after a latent period of 1–2 weeks as observed using continuous electrographic monitoring. SE resulted in hypertrophy of astrocytes and microglia activation throughout the hippocampus as revealed by immunolabelling studies. A dramatic, seizure intensity‐dependent increase in vimentin immunoreactivity (a marker for reactive astrocytes) was revealed in CA3 and hilar regions where prominent neuronal loss occurs. Increased vimentin labelling was first apparent 24 h after onset of SE and persisted up to 3 months. mGluR2/3 and mGluR5 protein expression increased markedly in glial cells of CA3 and hilus by 1 week after SE, and persisted up to 3 months after SE. Double immunolabelling of brain sections with vimentin confirmed co‐localization with glial fibrillary acidic protein (GFAP), mGluR2/3 and mGluR5 in reactive astrocytes. TGF‐β, a cytokine implicated in mGluR3‐mediated neuroprotection, was also upregulated during the first 3 weeks after SE throughout the hippocampus. This study demonstrates seizure‐induced upregulation of two mGluR subtypes in reactive astrocytes, which − together with the increased production of TGF‐β − may represent a novel mechanism for modulation of glial function and for changes in glial‐neuronal communication in the course of epileptogenesis.

EEG and MEG: relevance to neuroscience.

To understand dynamic cognitive processes, the high time resolution of EEG/MEG is invaluable. EEG/MEG signals can play an important role in providing measures of functional and effective connectivity in the brain. After a brief description of the foundations and basic methodological aspects of EEG/MEG signals, the relevance of the signals to obtain novel insights into the neuronal mechanisms underlying cognitive processes is surveyed, with emphasis on neuronal oscillations (ultra-slow, theta, alpha, beta, gamma, and HFOs) and combinations of oscillations. Three main functional roles of brain oscillations are put in evidence: (1) coding specific information, (2) setting and modulating brain attentional states, and (3) assuring the communication between neuronal populations such that specific dynamic workspaces may be created. The latter form the material core of cognitive functions.To understand dynamic cognitive processes, the high time resolution of EEG/MEG is invaluable. EEG/MEG signals can play an important role in providing measures of functional and effective connectivity in the brain. After a brief description of the foundations and basic methodological aspects of EEG/MEG signals, the relevance of the signals to obtain novel insights into the neuronal mechanisms underlying cognitive processes is surveyed, with emphasis on neuronal oscillations (ultra-slow, theta, alpha, beta, gamma, and HFOs) and combinations of oscillations. Three main functional roles of brain oscillations are put in evidence: (1) coding specific information, (2) setting and modulating brain attentional states, and (3) assuring the communication between neuronal populations such that specific dynamic workspaces may be created. The latter form the material core of cognitive functions.

Mechanisms of physiological and epileptic HFO generation

High frequency oscillations (HFO) have a variety of characteristics: band-limited or broad-band, transient burst-like phenomenon or steady-state. HFOs may be encountered under physiological or under pathological conditions (pHFO). Here we review the underlying mechanisms of oscillations, at the level of cells and networks, investigated in a variety of experimental in vitro and in vivo models. Diverse mechanisms are described, from intrinsic membrane oscillations to network processes involving different types of synaptic interactions, gap junctions and ephaptic coupling. HFOs with similar frequency ranges can differ considerably in their physiological mechanisms. The fact that in most cases the combination of intrinsic neuronal membrane oscillations and synaptic circuits are necessary to sustain network oscillations is emphasized. Evidence for pathological HFOs, particularly fast ripples, in experimental models of epilepsy and in human epileptic patients is scrutinized. The underlying mechanisms of fast ripples are examined both in the light of animal observations, in vivo and in vitro, and in epileptic patients, with emphasis on single cell dynamics. Experimental observations and computational modeling have led to hypotheses for these mechanisms, several of which are considered here, namely the role of out-of-phase firing in neuronal clusters, the importance of strong excitatory AMPA-synaptic currents and recurrent inhibitory connectivity in combination with the fast time scales of IPSPs, ephaptic coupling and the contribution of interneuronal coupling through gap junctions. The statistical behaviour of fast ripple events can provide useful information on the underlying mechanism and can help to further improve classification of the diverse forms of HFOs.

Interdependence of EEG signals: linear vs. nonlinear associations and the significance of time delays and phase shifts.

SummaryTo investigate the degree of interdependence of EEG signals, we have to use signal analysis methods. Three of these are described and their performance is compared: the cross-correlation (coherence and phase), the average amount of mutual information (AAMI) or the normalized AAMI, also called transmission coefficient T, and the correlation ratio h2 that is a general measure of nonlinear fit between any two signals. The three methods were applied to simulated and real signals in order to put in evidence how nonlinear relationships may affect differently these three measures of association. The nature of the interdependence between EEG signals is not characterized only by the degree of association, but also by the corresponding phase relationship. A basic question is whether such a phase shift can be interpreted as a transmission delay. However, a fundamental problem is that a phase shift may be difficult to interpret in terms of a biophysical model. A procedure is described in order to solve this problem. This involves computing the phase spectrum between the pair of signals, estimating the gain of the corresponding linear transfer function and the associated minimum phase. By subtracting the minimum phase from the phase spectrum, a corrected phase function can be obtained. From the slope of this phase function, a transmission delay can be estimated. This procedure is illustrated by applications to simulated and real EEG signals. It is demonstrated that from phase shifts we may estimate transmission delays between at least certain classes of EEG signals. In this way we can asses, unambiguously, how the transmission of information between different brain sites develops.

Progression of temporal lobe epilepsy in the rat is associated with immunocytochemical changes in inhibitory interneurons in specific regions of the hippocampal formation

Immunocytochemical markers of specific rat hippocampal interneuron subpopulations, including the calcium binding proteins parvalbumin (PV), and calretinin (CR) were examined in relation to the evolution of spontaneous seizures after electrically induced status epilepticus (SE). PV/CR/NeuN immunoreactive neurons were counted in the hippocampal formation at different time intervals after SE and related to spontaneous hippocampal discharge activity. Decreased PV immunoreactivity was observed within 1 day after SE in the hilus, pre- and parasubiculum, and in the entorhinal cortex layers II and V/VI. In layer III, the density of detectable PV immunoreactive neurons did not decrease significantly, whereas the number of surrounding principal neurons was extensively decreased within a week in most post-SE rats, and after 3-4.5 months in all rats that had developed a progressive evolution of seizures. CR immunoreactive neuron number decreased in all hippocampal subregions except for the stratum lacunosum-moleculare and the EC layer II, in which the density did not decrease significantly. The apparent decrease in the number of PV and CR immunoreactive hilar neurons was correlated with the duration of the SE and was most extensive in rats with a progressive form of epilepsy. The loss of CR and PV expression or the loss of CR- and PV-containing neurons in specific regions of the hippocampal formation may play a role in the progressive nature of epilepsy possibly via increasing the entorhinal-hippocampal activity.

High frequency oscillations in the intact brain

High frequency oscillations (HFOs) constitute a novel trend in neurophysiology that is fascinating neuroscientists in general, and epileptologists in particular. But what are HFOs? What is the frequency range of HFOs? Are there different types of HFOs, physiological and pathological? How are HFOs generated? Can HFOs represent temporal codes for cognitive processes? These questions are pressing and this symposium volume attempts to give constructive answers. As a prelude to this exciting discussion, we summarize the physiological high frequency patterns in the intact brain, concentrating mainly on hippocampal patterns, where the mechanisms of high frequency oscillations are perhaps best understood.