2007, Number 2
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ABSTRACTNeuronal oscillations emerge as a consequence of the interaction of large groups of neurons, which can synchronize their activity to generate a rhythmic field behavior. They occur in different brain areas and have been associated to relevant physiological and pathological processes such as sensory processing, memory, epilepsy and consciousness.
Neuronal oscillations are mediated and shaped by i) the intrinsic properties of the cell membrane, ii) the architecture of synaptic connections between the neurons confined in a network, and iii) the dynamics of the synaptic currents. The firing properties of the neurons depend on the ionic channels that they possess but nonlinear interactions between different families of ionic currents, may produce small subthreshold membrane oscillations (SMOs).
Because the probability to generate an action potential rises during the depolarizing phase of the SMOs, this activity can regulate the neuron’s firing frequency. Consequently, SMOs influence the responsiveness of the neuron to synaptic inputs that occur at particular frequencies and which, finally, produce a broad range of brain rhythms. In addition to the intrinsic properties of the neuronal membrane, the firing frequency of single neurons depends on the synaptic inputs from other neurons within the network.
Indeed, neurons can produce responses in their neighbors by means of electrical and chemical synapses. In this sense, two or more neurons are in synchrony if each fires action potentials, within a small time window before or after the other. This could be explained if both neurons share the same synaptic input or if they interact with each other. Hence, network synchrony is reflected by the current flow between the extracellular and intracellular compartments which can be recorded as a field potential in the extracellular space.
Thus, this field potential reflects both synchronic subthreshold events and action potentials generated by the cells contained in the recorded field. Therefore, the electric potential produced by the synchronized activity of cortical neurons can be recorded over the scalp (the electroencephalogram or EEG). This activity is characterized by its morphology, its frequency and the experimental context in which it is recorded.
The cortical brain rhythms are classified in frequency bands, and they are associated with different brain states. They compete and interact with each other and can coexist in the same or in different structures. Because field oscillations can be spontaneously generated in vitro, their generating and sustaining mechanisms can be thoroughly studied. For instance, blockade of presynaptic or postsynaptic receptors is a common tool used to isolate the specific contributions of different synaptic components that generate the field oscillations.
We also discuss the role of short and long-term GABAergic plasticity and its involvement in neuronal oscillations and in the generation of hyper-synchronic rhythms that underlie epileptic discharges. Indeed, excitatory and inhibitory synaptic interactions regulate and sustain the firing synchrony in neural networks. For instance, diverse sets of GABAergic interneurons contribute with different firing frequencies that finally inhibit their postsynaptic targets: excitatory principal cells and other interneurons. In other words, inhibitory synapses, as a whole, generate different synchronic neuronal events and restrain the network excitability.
Hence, it is relevant to study which parameters do modify the GABAergic transmission. For instance, a feature of GABAergic synapses is that prolonged GABAA-R activation may lead to a switch from a hyperpolarizing to a depolarizing postsynaptic response.
This is partly due to a positive shift on the GABAA-R reversal potential (EGABA) because of a GABA-induced-chloride (Cl-) accumulation in the postsynaptic neurons.
Recent studies suggest that the activity-dependent EGABA shift may have important implications in the mechanisms involved in the generation of γ (~40 Hz) oscillations and seizure-like discharges.
The study of how intracellular Cl- dynamics shape network oscillations may bring insights into the mechanisms of physiological and pathological brain rhythms. Moreover, Cl- dynamics have also prominent functional implications during development.
Another relevant example of GABAergic plasticity is observed in the glutamatergic hippocampal granule cells (GCs). In response to an increment in network excitability, GCs are able to synthesize and release GABA for fast neurotransmission. Several experimental results have compellingly shown that GABAergic signaling from these cells activates presynaptic and postsynaptic GABAergic receptors.
Therefore, it is plausible that after seizures, the GCs could spontaneously release GABA that would, in turn, change the spontaneous field activity that naturally emerges from the postsynaptic targets that comprise the CA3 intrinsic network oscillator. And this is indeed the case. GABA released from CGs inhibits Β/γ oscillations (~20 Hz) in the CA3 area, where principal cells and interneurons are impinged by CGs. Thus, this mechanism could be used to limit network excitability after seizures. The emergence of the GABAergic phenotype in CGs could also be involved in the deleterious effects on learning and memory consolidation that have been observed after seizures. Finally, we briefly discuss the computational role that network oscillations may have to represent sensory information.
GOMEZ-LIRA G, TRILLO E, RAMIREZ M, ASAI M, SITGES M, GUTIERREZ R: The expression of GABA in mossy fiber synaptosomes coincides with the seizure-induced expression of GABAergic transmission in the mossy fiber sy21. GUTIERREZ R: Activity-dependent expression of simultaneous glutamatergic and GABAergic neurotransmission from the mossy fibers in vitro. J Neurophysiol, 87:2562-2570, 2002.