Normal and pathological oscillatory communication in the brain Jaeseung Jeong, Ph.D Department of Bio and Brain Engineering KAIST

Complex spatiotemporal dynamics in the Brain Now, let’s turn to the brain imaging tools. As you now, we have difficulties in studying living brain because of the skull, outside of the brain. However, there are several method to see the living brain, anatomical tools and functional tools. MRI is the popular method to see the anatomical aspect of the brain. CT also is. Tomographic scanning helps us to see the detailed brain structures. As to the functional imaging, PET and fMRI, electrophysiological and optical methods.

Brain oscillations The brain is constantly active, even during deep sleep. In the cerebral cortex, this spontaneous activity (activity that is not obviously driven by a sensory input or a motor command) often occurs as periodic, rhythmic discharges.

Main issues on Oscillations Recent improvements in the methods of studying long-range communication have allowed us to address several important questions: What are the common mechanisms that govern local and long-range communication and how do they relate to the structure of the brain? How does oscillatory synchronization subserve neural communication? What are the consequences of abnormal synchronization?

Brain is an information processor j threshold -> Spike i Spike reception: EPSP, summation of EPSPs Threshold Spike emission (Action potential) Spike reception: EPSP Brain is an information processor

LFP oscillations might be due to regularities in the firing of only a subset of neurons in a local area, as LFPs represent a spatial average.

As no behaviourally relevant task is performed independently by a single neuron, communication is of the utmost importance and, ultimately, optimal computational performance relies on optimal communication. Here we use a broad definition of neural communication, in which a neural element (a single neuron or a population of neurons) conveys certain aspects of its functional state to another neural element. Neural communication depends on the anatomical components that connect individual neurons (structure) and the process of transmitting information (function). Both aspects affect the overall performance of the system.

EEG recordings

Structurally, the most striking neuroanatomical feature of the brain is the abundant connectivity between neurons, which reflects the importance of neural communication. Functionally, oscillations are a prominent feature of neuronal activity and the synchronization of oscillations — which reflects the temporally precise interaction of neural activities — is a likely mechanism for neural communication.

Neuronal Oscillations infra-slow: 0.02-0.1 Hz, slow: 0.1-15 Hz (during slow-wave sleep or anesthesia) Slow oscillation (0.2-1 Hz), Delta (1-4 Hz), Spindle (7-15Hz), Theta (generated in the limbic system) fast: 20-60 Hz, ultra-fast: 100-600 Hz.

Fourier transformation of the EEG

Thalamocortical oscillations Oscillatory activity is an emerging property of the brain network, especially the thalamocortical system. The various oscillatory rhythms generated in the thalamocortical system are mediated by two types of mechanisms: Intrinsic mechanisms, which depend on the interplay between specific intrinsic currents. Extrinsic or network mechanisms, which require the interaction of excitatory and inhibitory neurons within a population. Intrinsic and network mechanisms can work alone (e.g., thalamic delta oscillations depend on the intrinsic properties of thalamic relay cells, cortical slow oscillation depends on network properties) or in combination (e.g., spindles depend on the interaction between thalamic relay and reticular neurons as well as on their intrinsic properties).

Infra-slow oscillation This type of oscillatory activity has a period within the range of tens of seconds to a minute. Very little is known about the underlying mechanisms of these oscillations but at least some of the factors responsible for their generation could depend on non-neuronal dynamics. Infra-slow activities likely have a cortical origin given that they can be recorded from small regions of neocortex devoid of their inputs by means of a surgical undercut. What is the functional role? Indirect evidence suggests that infra-slow oscillations synchronize faster activities, modulate cortical excitability, and contribute to the aggravation of epileptic activity during sleep.

Slow Oscillations Another form of rhythmic cortical activity that recently has been investigated extensively in vivo is the so-called "SLOW OSCILLATION." The slow oscillation is characterized by periods of sustained depolarization interweaved with periods of hyperpolarization and silence at a rate of between once every 10 seconds to approximately once per every 2 seconds. The depolarized state is associated with low frequency neuronal firing and is termed the UP state, while the hyperpolarized state is referred to as the DOWN state. The frequent transitions between the UP and DOWN state can make the membrane potential of the cortical neuron appear as a single channel recording, even though the slow oscillation is generated by the interaction of thousands of cells!

Slow oscillations During slow-wave sleep and some types of anesthesia the dominant activity pattern is slow oscillation, with frequency 0.3 - 1 Hz. The following observations point to an intracortical origin for this rhythm: a. It survives extensive thalamic lesions in vivo and exists in cortical in vitro preparations. It is absent in the thalamus of decorticated cats.

The slow oscillation is generated in the Cerebral Cortex, since removal of the thalamus does not block the slow oscillation and isolation of slabs of cortex retain this activity. McCormick et al. demonstrated the slow oscillation in cortical slices maintained in vitro.

Beta oscillations Beta oscillation is the oscillation with frequency range above 12 Hz. Low amplitude beta with multiple and varying frequencies is often associated with active, busy or anxious thinking and active concentration. Rhythmic beta with a dominant set of frequencies is associated with various pathologies and drug effects, especially benzodiazepines.

Fast oscillations Fast oscillations could be divided on fast (beta and gamma) and ultra-fast (>100 Hz, ripples). Fast oscillations have been implicated in cognitive processes. They also form a prominent part of sleep EEG signals, when intracortical electrodes are used. They also occur in association with seizures. Ultrafast oscillations could be found during sharp waves and sleep. The ripples are prominent in the onset of seizures.

Two major categories of fast oscillations (Homogeneous) Those which occur in a homogeneous collection of neurons, all of the same type, for example CA1 pyramidal neurons. (Heterogeneous) Those which require synaptic interactions between two or more populations of neurons, for example CA1 pyramidal neurons together with fast-spiking CA1 interneurons.

Gamma oscillations Gamma oscillation is the rhythmic activity with the frequency range approximately 26–100 Hz. Gamma rhythms may be involved in higher mental activity, including perception, problem solving, fear, and consciousness.

Persistent gamma in hippocampus and entorhinal cortex This type of gamma is notable for the sparse firing of pyramidal cell somata, despite the prominent presence of IPSPs in pyramidal cells, and the dependence of the oscillation on synaptic inhibition. Additionally, phasic EPSPs and gap junctions are also required; the experimental evidence suggests that axonal electrical coupling between pyramidal cells is an absolute requirement, while interneuronal electrical coupling plays a modulatory role. Persistent gamma is usually induced by bath application of an appropriate drug, such as kainate or carbachol, and can last for hours.

Persistent gamma in Hippocampus Power spectra of the field oscillation reveal both a gamma peak, and also a faster, but non-harmonic, peak at >70 Hz. Remarkably, the pyramidal cell axonal plexus, in the hippocampal CA1 region, when it is surgically separated from pyramidal cell somata, generates a continuous very fast oscillation, rather than gamma. It is thought that the mechanism for this continuous very fast oscillation is similar to the mechanism for the first type of "homogeneous" fast oscillation described above. It is apparent that very fast oscillations (>70 Hz) and persistent gamma oscillations are intimately related.

Functional role of fast oscillations for perception and behavior Cognitive functions like perception, attention, memory or language are based on highly parallel and distributed information processing by the brain. One of the major unresolved questions is how information can be integrated and how coherent representational states can be established in the distributed neuronal systems subserving these functions. It has been suggested that this so-called 'binding problem' may be solved in the temporal domain. The hypothesis is that synchronization of neuronal discharges can serve for the integration of distributed neurons into cell assemblies and that this process may underlie the selection of perceptually and behaviourally relevant information.

Functional role of fast oscillations for perception and behavior Moreover, it has been suggested that fast oscillations at frequencies in the so-called gamma range (> 30 Hz) may help to entrain spatially separate neurons into synchrony and thus may indirectly promote the dynamic binding of neuronal populations. In accordance with these predictions, states characterized by synchronized gamma activity have been shown to be associated with functions like processing of coherent stimuli, perceptual discrimination, focused attention, short-term memory, or sensorimotor integration. Typically, the observed magnitude of gamma activity is positively correlated with increased 'processing load' and thus with the level of vigilance and attention, as well as with the difficulty or integrative nature of the processing.

The antennal lobe receives input from olfactory receptor neurons; it then transforms and reformats this input for transfer through projection neurons to the mushroom body, which is responsible for memory encoding and retrieval, and to the lateral horn. In turn, inhibitory interneurons in the lateral horn project to the mushroom body.

Odours elicit global oscillatory activity of 20–30 Hz in the antennal lobe network (which is composed of local and projection neurons), and this, in turn, is reflected in the local field potentials (LFPs) of the antennal lobe, mushroom body and lateral horn. The action potentials of projection neurons are PHASE-LOCKED to the LFP oscillations in a neuron-, odour- and time-specific manner, such that the antennal lobe output is an evolving 20–30 Hz sequence of synchronized projection neuron spikes.

Inhibitory interneurons provide an important mechanism for synchronization of the LFP oscillations of remote neural populations. According to the network model of Bibbig and co-workers, synchronization can be mediated by a pair of action potentials per oscillation cycle (long-interval doublets): The first spike of the doublet originates from excitatory input from local principal cells; the second is caused by excitation from distant principal cells. The timing between the doublets in a given cycle provides the feedback required to synchronize the oscillations of distant networks.

Functional consequences of oscillatory driving input to the motoneurons that relate to breathing have also been shown in rats in vitro. First, similar to the effect of correlated presynaptic inputs on other neurons, the timing of action potentials in motor neurons is crucially affected by oscillatory modulations of input. Motor neuron spike trains are much less variable and more consistent during oscillatory input. Second, increased synchronization in the oscillatory input increases the gain — that is, an increase in the number of action potentials that are elicited by a given input58 augments the force output in a computer simulation of a motor neuron pool. Third, synchronization increases the robustness of the input–output relationship for motor neurons against changes in neurotransmitter level. Finally, recent studies indicate that oscillatory communication subserves gating of information processing and modulates the effects of spike trains, and so shows a strong dependence on the behavioural state11,

Three lines of evidence provide experimental support for extending the concept of gamma-band synchronization as a mechanism for binding: First, there is new experimental evidence that beta oscillations are important in long-range synchronization, which is further supported by computational modelling. Second, the importance of desynchronization, or, more specifically, the spatiotemporal balance of synchronization and desynchronization, is increasingly being recognized. Third, there is new evidence that specific synchronization patterns are directly related to behaviour.

The synchronization index (SI), which quantifies phase synchronization, shown for five successive stimuli. The x-axis specifies time after presentation of the first target. Each point represents the mean SI in a 60-ms-window centred at 260 ms after the respective stimulus. Values at 260 ms quantify the network synchronization to the first target (T1), whereas values at 114 ms represent the network synchronization that corresponds to the distractor preceding the first target. The blue line represents the response seen when both targets were correctly reported and the red line the response seen when the second target was missed.

The spatial distribution of coherence with the left primary motor cortex (M1) as a reference region. Only areas with p<0.05 (corrected, one-sample t-test) are shown. Note that the left thalamus and right cerebellum are projected to the left surface for easier visualization. The dominant coupling direction (mean directionality index) is indicated by arrows.

Line thickness indicates the degree of coherence (left) and Granger causality (right) found between recording sites (labelled 1–6) when a monkey performs a contraction task. Granger causality quantifies the directionality of information flow. Only significant interactions are shown. As, arcuate sulcus; Cs, central sulcus; IPs, intraparietal sulcus; Ls, lateral sulcus; STs, superior temporal sulcus.

The striatum receives most of the input from the cerebral cortex; in this sense, it is the doorway to the basal ganglia. The GPi and SNr are the output nuclei of the basal ganglia and send the main inhibitory output from the basal ganglia back to the thalamus. The striatum sends its output to the GPi/SNr through a direct dopamine D1-receptor-mediated pathway and through an indirect dopamine D2-receptor-mediated pathway involving the GPe and STN. The direct pathway is thought to facilitate movement, whereas the indirect pathway is thought to suppress movement. There is a delicate balance between these two pathways that is partly maintained by dopamine release from the SNc to the striatum. Dopamine release inhibits the indirect pathway by stimulating dopamine D2 receptors and excites the direct pathway by stimulating the dopamine D1 receptors.

Maps of spatially normalized cerebro-muscular and cerebro-cerebral coherence averaged across 4 patients with right-sided rest tremor. Cerebro-muscular coherence at double tremor frequency occurs in the contralateral primary motor cortex (b). Cerebro-cerebral coherence was computed with the reference region in the primary motor cortex and averaged for all patients. Areas of consistent coherence are the lateral (a) and medial (c) premotor areas, secondary somatosensory cortex (a), posterior parietal cortex (a) as well as the thalamus/basal ganglia (d) contralateral to the tremor hand and the cerebellum (e) ipsilateral to the tremor hand. Note that because of the large distance to the magnetoencephalogram (MEG) sensors, localization in both subcortical areas is not as precise as at the cortical level.