Neural Synchrony, Axonal Path Lengths, and General Anesthesia: A Hypothesis

Anesthetic action on the transmission delay between cortex and thalamus explains the beta-buzz observed under propofol anesthesia

In recent years, more and more surgeries under general anesthesia have been performed with the assistance of electroencephalogram (EEG) monitors. An increase in anesthetic concentration leads to characteristic changes in the power spectra of the EEG. Although tracking the anesthetic-induced changes in EEG rhythms can be employed to estimate the depth of anesthesia, their precise underlying mechanisms are still unknown. A prominent feature in the EEG of some patients is the emergence of a strong power peak in the β-frequency band, which moves to the α-frequency band while increasing the anesthetic concentration. This feature is called the beta-buzz. In the present study, we use a thalamo-cortical neural population feedback model to reproduce observed characteristic features in frontal EEG power obtained experimentally during propofol general anesthesia, such as this beta-buzz. First, we find that the spectral power peak in the α- and δ-frequency ranges depend on the decay rate constant of excitatory and inhibitory synapses, but the anesthetic action on synapses does not explain the beta-buzz. Moreover, considering the action of propofol on the transmission delay between cortex and thalamus, the model reveals that the beta-buzz may result from a prolongation of the transmission delay by increasing propofol concentration. A corresponding relationship between transmission delay and anesthetic blood concentration is derived. Finally, an analytical stability study demonstrates that increasing propofol concentration moves the systems resting state towards its stability threshold.

Early Cerebellar Network Shifting in Spinocerebellar Ataxia Type 6

Spinocerebellar ataxia 6 (SCA6), an autosomal dominant degenerative disease, is characterized by diplopia, gait ataxia, and incoordination due to severe progressive degeneration of Purkinje cells in the vestibulo- and spinocerebellum. Ocular motor deficits are common, including difficulty fixating on moving objects, nystagmus and disruption of smooth pursuit movements. In presymptomatic SCA6, there are alterations in saccades and smooth-pursuit movements. We sought to assess functional and structural changes in cerebellar connectivity associated with a visual task, hypothesizing that gradual changes would parallel disease progression. We acquired functional magnetic resonance imaging and diffusion tensor imaging data during a passive smooth-pursuit task in 14 SCA6 patients, representing a range of disease duration and severity, and performed a cross-sectional comparison of cerebellar networks compared with healthy controls. We identified a shift in activation from vermis in presymptomatic individuals to lateral cerebellum in moderate-to-severe cases. Concomitantly, effective connectivity between regions of cerebral cortex and cerebellum was at its highest in moderate cases, and disappeared in severe cases. Finally, we noted structural differences in the cerebral and cerebellar peduncles. These unique results, spanning both functional and structural domains, highlight widespread changes in SCA6 and compensatory mechanisms associated with cerebellar physiology that could be utilized in developing new therapies.

Cerebral mechanisms of general anesthesia

How does general anesthesia (GA) work? Anesthetics are pharmacological agents that target specific central nervous system receptors. Once they bind to their brain receptors, anesthetics modulate remote brain areas and end up interfering with global neuronal networks, leading to a controlled and reversible loss of consciousness. This remarkable manipulation of consciousness allows millions of people every year to undergo surgery safely most of the time. However, despite all the progress that has been made, we still lack a clear and comprehensive insight into the specific neurophysiological mechanisms of GA, from the molecular level to the global brain propagation. During the last decade, the exponential progress in neuroscience and neuro-imaging led to a significant step in the understanding of the neural correlates of consciousness, with direct consequences for clinical anesthesia. Far from shutting down all brain activity, anesthetics lead to a shift in the brain state to a distinct, highly specific and complex state, which is being increasingly characterized by modern neuro-imaging techniques. There are several clinical consequences and challenges that are arising from the current efforts to dissect GA mechanisms: the improvement of anesthetic depth monitoring, the characterization and avoidance of intra-operative awareness and post-anesthesia cognitive disorders, and the development of future generations of anesthetics.

Feedback of the amygdala globally modulates visual response of primary visual cortex in the cat

The amygdala is an important center for emotional behavior, and it influences other cortical regions. Long feedback projections from the amygdala to the primary visual cortex were recently reported in the cat and monkey, two animal models for vision research. However, the detailed functional roles of these extensive projections still remain largely unknown. In this study, intrinsic signal optical imaging was used to investigate the visually driven responses of the primary visual cortex of cats as focal drugs were injected into the basal nucleus of the amygdala. Both the visually evoked global signals and differential signals in the functional maps of the primary visual cortex were enhanced or reduced by glutamate-induced activation or GABA-induced deactivation of neurons in the amygdala, respectively. This modulation was found to be non-selective, consistent with the gain control mechanism-both the preferred orientation and its mapped orientation tuning width remained unchanged. The single unit recordings showed similar results supporting the above observations. These results suggest that the distal feedback signals of the amygdala enhance the primary sensory information processing in a non-selective, gain-control fashion. This provides direct neurophysiological evidence and insight for previous studies on emotional-cue related psychological studies.

The Mesoscopic Modeling of Burst Suppression during Anesthesia

The burst-suppression pattern is well recognized as a distinct feature of the mammalian electroencephalogram (EEG) waveform. Consisting of alternating periods of high amplitude oscillatory and isoelectric activity, it can be induced in health by deep anesthesia as well as being evoked by a range of pathophysiological processes that include coma and anoxia. While the electroencephalographic phenomenon and clinical implications of burst suppression have been studied extensively, the physiological mechanisms underlying its emergence remain unresolved and obscure. Because electroencephalographic bursting phenomenologically resembles the bursting observed in single neurons, it would be reasonable to assume that the theoretical insights developed to understand bursting at the cellular ("microscopic") level would enable insights into the dynamical genesis of bursting at the level of the whole brain ("macroscopic"). In general action potential bursting is the result of the interplay of two time scales: a fast time scale responsible for spiking, and a slow time scale that modulates such activity. We therefore hypothesize that such fast-slow systems dynamically underpin electroencephalographic bursting. Here we show that a well-known mean field dynamical model of the electroencephalogram, the Liley model, while unable to produce burst suppression unmodified, is able to give rise to a wide variety of burst-like activity by the addition of one or more slow systems modulating model parameters speculated to be major "targets" for anesthetic action. The development of a physiologically plausible theoretical framework to account for burst suppression will lead to a more complete physiological understanding of the EEG and the mechanisms that serve to modify ongoing brain activity necessary for purposeful behavior and consciousness.

Understanding the effects of anesthetic agents on the EEG through neural field theory

Anesthetic and analgesic agents act through a diverse range of pharmacological mechanisms. Existing empirical data clearly shows that such "microscopic" pharmacological diversity is reflected in their "macroscopic" effects on the human electroencephalogram (EEG). Based on a detailed mesoscopic neural field model we theoretically posit that anesthetic induced EEG activity is due to selective parametric changes in synaptic efficacy and dynamics. Specifically, on the basis of physiologically constrained modeling, it is speculated that the selective modification of inhibitory or excitatory synaptic activity may differentially effect the EEG spectrum. Such results emphasize the importance of neural field theories of brain electrical activity for elucidating the principles whereby pharmacological agents effect the EEG. Such insights will contribute to improved methods for monitoring depth of anesthesia using the EEG.

Axonal velocity distributions in neural field equations

By modelling the average activity of large neuronal populations, continuum mean field models (MFMs) have become an increasingly important theoretical tool for understanding the emergent activity of cortical tissue. In order to be computationally tractable, long-range propagation of activity in MFMs is often approximated with partial differential equations (PDEs). However, PDE approximations in current use correspond to underlying axonal velocity distributions incompatible with experimental measurements. In order to rectify this deficiency, we here introduce novel propagation PDEs that give rise to smooth unimodal distributions of axonal conduction velocities. We also argue that velocities estimated from fibre diameters in slice and from latency measurements, respectively, relate quite differently to such distributions, a significant point for any phenomenological description. Our PDEs are then successfully fit to fibre diameter data from human corpus callosum and rat subcortical white matter. This allows for the first time to simulate long-range conduction in the mammalian brain with realistic, convenient PDEs. Furthermore, the obtained results suggest that the propagation of activity in rat and human differs significantly beyond mere scaling. The dynamical consequences of our new formulation are investigated in the context of a well known neural field model. On the basis of Turing instability analyses, we conclude that pattern formation is more easily initiated using our more realistic propagator. By increasing characteristic conduction velocities, a smooth transition can occur from self-sustaining bulk oscillations to travelling waves of various wavelengths, which may influence axonal growth during development. Our analytic results are also corroborated numerically using simulations on a large spatial grid. Thus we provide here a comprehensive analysis of empirically constrained activity propagation in the context of MFMs, which will allow more realistic studies of mammalian brain activity in the future.

A multi-component model of the developing retinocollicular pathway incorporating axonal and synaptic growth

During development, neurons extend axons to different brain areas and produce stereotypical patterns of connections. The mechanisms underlying this process have been intensively studied in the visual system, where retinal neurons form retinotopic maps in the thalamus and superior colliculus. The mechanisms active in map formation include molecular guidance cues, trophic factor release, spontaneous neural activity, spike-timing dependent plasticity (STDP), synapse creation and retraction, and axon growth, branching and retraction. To investigate how these mechanisms interact, a multi-component model of the developing retinocollicular pathway was produced based on phenomenological approximations of each of these mechanisms. Core assumptions of the model were that the probabilities of axonal branching and synaptic growth are highest where the combined influences of chemoaffinity and trophic factor cues are highest, and that activity-dependent release of trophic factors acts to stabilize synapses. Based on these behaviors, model axons produced morphologically realistic growth patterns and projected to retinotopically correct locations in the colliculus. Findings of the model include that STDP, gradient detection by axonal growth cones and lateral connectivity among collicular neurons were not necessary for refinement, and that the instructive cues for axonal growth appear to be mediated first by molecular guidance and then by neural activity. Although complex, the model appears to be insensitive to variations in how the component developmental mechanisms are implemented. Activity, molecular guidance and the growth and retraction of axons and synapses are common features of neural development, and the findings of this study may have relevance beyond organization in the retinocollicular pathway.

Neural development is a process that involves a wide range of behaviors. As a result of these behaviors, neurons are able to extend axons to different brain areas and produce stereotypical patterns of innervation. One of the most commonly studied of these projections is in the visual system, where retinal axons project to multiple brain regions and produce retinotopic maps. This study examines the relative roles and interactions of different neural mechanisms in guiding axon growth and generating retinotopic order. We did this by producing a computational model of retinotopic development that represented many of the neural mechanisms thought to be involved, including axon and synapse growth, molecular guidance and synapse plasticity. Our results suggest that synaptic plasticity is realized by variation in the number of synapses between neurons, not through alteration of individual synaptic weights; that lateral connectivity between collicular neurons is not required for organization; and that axon arbor development does not require the gradient tracking abilities of growth cones. The mechanisms underlying neuronal development in the visual system are also observed in many other brain areas, so the findings here should apply more generally.

Dynamical relaying can yield zero time lag neuronal synchrony despite long conduction delays

Multielectrode recordings have revealed zero time lag synchronization among remote cerebral cortical areas. However, the axonal conduction delays among such distant regions can amount to several tens of milliseconds. It is still unclear which mechanism is giving rise to isochronous discharge of widely distributed neurons, despite such latencies. Here, we investigate the synchronization properties of a simple network motif and found that, even in the presence of large axonal conduction delays, distant neuronal populations self-organize into lag-free oscillations. According to our results, cortico-cortical association fibers and certain cortico-thalamo-cortical loops represent ideal circuits to circumvent the phase shifts and time lags associated with conduction delays.

Mechanism of spontaneous and self-sustained oscillations in networks connected through axo-axonal gap junctions

Electrical coupling of clusters of neurons via axo-axonal gap junctions is a candidate mechanism underlying the ultra-fast (> 100 Hz) oscillations recorded in various in vitro and in vivo normal and pathological conditions [Traub et al. (1999)Neuroscience, 92, 407-426]. The poor characterization of axo-axonal gap junctions, however, limits experimental verification of this mechanism. We simulated networks of prototype multi-compartmental neurons in order to identify the parameters constraining the production and frequency of ultra-fast oscillations. Weak axo-axonal coupling was found to synchronize networks preferentially at the gamma-range frequency (30-100 Hz). Networks with strong axo-axonal coupling were able to produce 200 Hz oscillations, a finding we extended with several new observations. Ultra-fast oscillations arose spontaneously during dendritic excitation, i.e. in the absence of extrinsic axonal background spikes, as the spike trigger zone concomitantly shifted from soma to axon. The all-or-none oscillations could be transitory or self-sustained, and lasted longer in larger networks. They occurred more likely during low to modest soma firing rates, as strong afterhyperpolarizing currents tended to impair them. The rate of the rhythm was independent of network size and of the level of excitation, but inversely proportional to the distance of the junctions from the soma. As a matter of fact, the resulting axonal firing rate was the highest one at which antidromic spikes would not collide with spikes reflected from the soma. Taken together, the observed model dynamics lends further credibility to axo-axonal coupling as a mechanism of ultra-fast oscillations.

Age-related changes in transient and oscillatory brain responses to auditory stimulation in healthy adults 19-45 years old

The capacity of the human cerebral cortex to track fast temporal changes in auditory stimuli is related to the development of language in children and to deficits in speech perception in the elderly. Although maturation of temporal processing in children and its deterioration in the elderly has been investigated previously, little is known about naturally occurring changes in auditory temporal processing between these limits. The present study examined age-related (19-45 years) changes in 3 electrophysiological measures of auditory processing: 1) the late transient auditory evoked potentials to tone onset, 2) the auditory steady-state response (ASSR) to a 40-Hz frequency-modulated tone, and 3) the envelope following response (EFR) to sweeps of amplitude-modulated white noise from 10 to 100 Hz. With increasing age, the latency of the auditory P1-N1 complex decreased, the oscillatory (ASSR) response became larger and more stable, and the resonant peak of the EFR increased from 38 Hz at 19 years to 46 Hz at 45 years. Source analysis localized these changes to the auditory regions of the temporal lobe. These results indicate persistent adaptation of cortical auditory processes into middle adulthood. We speculate that experience-driven myelination and/or refinement of inhibitory circuits may underlie these changes.

The importance of different timings of excitatory and inhibitory pathways in neural field models

In this paper, we consider a neural field model comprised of two distinct populations of neurons, excitatory and inhibitory, for which both the velocities of action potential propagation and the time courses of synaptic processing are different. Using recently-developed techniques, we construct the Evans function characterising the stability of both stationary and travelling wave solutions, under the assumption that the firing rate function is the Heaviside step. We find that these differences in timing for the two populations can cause instabilities of these solutions, leading to, for example, stationary breathers. We also analyse "anti-pulses", a novel type of pattern for which all but a small interval of the domain (in moving coordinates) is active. These results extend previous work on neural fields with space-dependent delays, and demonstrate the importance of considering the effects of the different time-courses of excitatory and inhibitory neural activity.

Operational principles of neurocognitive networks

Large-scale neural networks are thought to be an essential substrate for the implementation of cognitive function by the brain. If so, then a thorough understanding of cognition is not possible without knowledge of how the large-scale neural networks of cognition (neurocognitive networks) operate. Of necessity, such understanding requires insight into structural, functional, and dynamical aspects of network operation, the intimate interweaving of which may be responsible for the intricacies of cognition. Knowledge of anatomical structure is basic to understanding how neurocognitive networks operate. Phylogenetically and ontogenetically determined patterns of synaptic connectivity form a structural network of brain areas, allowing communication between widely distributed collections of areas. The function of neurocognitive networks depends on selective activation of anatomically linked cortical and subcortical areas in a wide variety of configurations. Large-scale functional networks provide the cooperative processing which gives expression to cognitive function. The dynamics of neurocognitive network function relates to the evolving patterns of interacting brain areas that express cognitive function in real time. This article considers the proposition that a basic similarity of the structural, functional, and dynamical features of all neurocognitive networks in the brain causes them to function according to common operational principles. The formation of neural context through the coordinated mutual constraint of multiple interacting cortical areas, is considered as a guiding principle underlying all cognitive functions. Increasing knowledge of the operational principles of neurocognitive networks is likely to promote the advancement of cognitive theories, and to seed strategies for the enhancement of cognitive abilities.