Axonal Conduction Speed Research Articles

Simulation-based inference of developmental EEG maturation with the spectral graph model

The spectral content of macroscopic neural activity evolves throughout development, yet how this maturation relates to underlying brain network formation and dynamics remains unknown. Here, we assess the developmental maturation of electroencephalogram spectra via Bayesian model inversion of the spectral graph model, a parsimonious whole-brain model of spatiospectral neural activity derived from linearized neural field models coupled by the structural connectome. Simulation-based inference was used to estimate age-varying spectral graph model parameter posterior distributions from electroencephalogram spectra spanning the developmental period. This model-fitting approach accurately captures observed developmental electroencephalogram spectral maturation via a neurobiologically consistent progression of key neural parameters: long-range coupling, axonal conduction speed, and excitatory:inhibitory balance. These results suggest that the spectral maturation of macroscopic neural activity observed during typical development is supported by age-dependent functional adaptations in localized neural dynamics and their long-range coupling across the macroscopic structural network.

Motor learning drives dynamic patterns of intermittent myelination on learning-activated axons.

Myelin plasticity occurs when newly formed and pre-existing oligodendrocytes remodel existing patterns of myelination. Myelin remodeling occurs in response to changes in neuronal activity and is required for learning and memory. However, the link between behavior-induced neuronal activity and circuit-specific changes in myelination remains unclear. Using longitudinal in vivo two-photon imaging and targeted labeling of learning-activated neurons in mice, we explore how the pattern of intermittent myelination is altered on individual cortical axons during learning of a dexterous reach task. We show that behavior-induced myelin plasticity is targeted to learning-activated axons and occurs in a staged response across cortical layers in the mouse primary motor cortex. During learning, myelin sheaths retract, which results in lengthening of nodes of Ranvier. Following motor learning, addition of newly formed myelin sheaths increases the number of continuous stretches of myelination. Computational modeling suggests that motor learning-induced myelin plasticity initially slows and subsequently increases axonal conduction speed. Finally, we show that both the magnitude and timing of nodal and myelin dynamics correlate with improvement of behavioral performance during motor learning. Thus, learning-induced and circuit-specific myelination changes may contribute to information encoding in neural circuits during motor learning.

Astrocyte Ca2+-evoked ATP release regulates myelinated axon excitability and conduction speed.

Print Page SummaryIntroductionAstrocytes support neuronal function throughout the central nervous system. In the grey matter they regulate synapse number during development, remove synaptically-released neurotransmitters to terminate their action and prevent excitotoxicity, control the extracellular potassium concentration to prevent hyperexcitability, regulate blood flow to ensure an adequate energy supply, provide lactate to neurons for energy, and respond to rises of intracellular calcium concentration ([Ca2+]i) by releasing ATP and other gliotransmitters that act on neuronal receptors to modulate information processing. However, their role is unclear in the white matter, which transmits information rapidly between grey matter areas using axons wrapped with capacitance-reducing myelin, although they have been suggested to regulate myelination during development and during normal function.RationaleRecently it has been suggested that learning and memory may reflect, not only changes of synaptic function in the grey matter, but also changes of white matter function. In particular, neural circuit function might be regulated by changes in the conduction speed of myelinated axons that result in an altered arrival time of action potentials at a distant neuron. These speed changes might be brought about by alterations of the properties of the passively conducting myelinated internodes, or of the intervening excitable nodes of Ranvier where the action potential is generated. We applied immunohistochemistry to assess how astrocytes interact with myelinated axons, used neuronal stimulation and light evoked calcium uncaging in astrocytes to evoke Ca2+-dependent release of gliotransmitters, and employed electrophysiology and pharmacology to characterise how astrocyte-released substances might affect the axon initial segment (AIS) and nodes of Ranvier of myelinated neurons. Measurements of conduction velocity and computer modelling allowed us to interpret the results.ResultsAstrocytes closely approach the axons of myelinated neurons in layer V of the cerebral cortex. Uncaging Ca2+ within astrocytes, or stimulating spike trains in neurons, evoked a rise of astrocyte [Ca2+]i that triggered the release of ATP-containing vesicles from these cells. This evoked an inward current in the AIS and nodes of Ranvier of the pyramidal neurons. Pharmacology showed that this was mediated by the activation of Gs-linked adenosine A2a receptors, implying that the released ATP was converted to adenosine by extracellular enzymes. The A2a receptors raise the intracellular concentration of cyclic AMP, which activates HCN channels mediating the inward hyperpolarization-activated current Ih, and thus depolarizes the cell. In the AIS the activation of A2a receptors alters excitability and hence action potential generation, while in the nodes of Ranvier it decreases the conduction speed of the action potential along the axon.ConclusionAs in the grey matter, astrocyte [Ca2+]i regulates the release of ATP into the extracellular space in the white matter. After conversion to adenosine, this regulates the excitability and conduction speed of myelinated axons. The changes in excitability at the AIS will lead to changes in the relationship between the synaptic input and action potential output of the cell. The altered conduction speed of the myelinated axon may change neural circuit function by changing the action potential arrival time at the cell’s output synapses, thus altering the integration of signals in postsynaptic neurons. Variations in astrocyte-derived adenosine level can occur between wake and sleep states, and the extracellular adenosine concentration rises during energy deprivation conditions. These changes of adenosine level could thus control white matter information flow and neural circuit function.Astrocytes regulate myelinated axon excitability and conduction speed.For cortical neurons with myelinated axons crossing the corpus callosum (left), astrocytes regulate axon initial segment (AIS) excitability and axonal conduction speed (middle). Increases of astrocyte [Ca2+]i release ATP which, after conversion to adenosine (Ado) extracellularly, activates A2a receptors that raise the intracellular cyclic AMP concentration, and thus generate an inward current via HCN2 channels in the AIS and nodes of Ranvier (right). Created with BioRender.com.In the brain’s grey matter, astrocytes regulate synapse properties, but their role is unclear for the white matter where myelinated axons rapidly transmit information between grey matter areas. We found that, in rodents, neuronal activity raised [Ca2+]i in astrocyte processes located near action potential generating sites in the axon initial segment (AIS) and nodes of Ranvier of myelinated axons. This released ATP which was converted extracellularly to adenosine and thus, via A2a receptors, activated HCN2-containing cation channels that regulate two aspects of myelinated axon function: excitability of the AIS and speed of action potential propagation. Variations in astrocyte-derived adenosine level, between wake and sleep states or during energy deprivation, could thus control white matter information flow and neural circuit function.

Genetic Variation in CNS Myelination and Functional Brain Connectivity in Recombinant Inbred Mice

Myelination greatly increases the speed of action potential propagation of neurons, thereby enhancing the efficacy of inter-neuronal communication and hence, potentially, optimizing the brain’s signal processing capability. The impact of genetic variation on the extent of axonal myelination and its consequences for brain functioning remain to be determined. Here we investigated this question using a genetic reference panel (GRP) of mouse BXD recombinant inbred (RI) strains, which partly model genetic diversity as observed in human populations, and which show substantial genetic differences in a variety of behaviors, including learning, memory and anxiety. We found coherent differences in the expression of myelin genes in brain tissue of RI strains of the BXD panel, with the largest differences in the hippocampus. The parental C57BL/6J (C57) and DBA/2J (DBA) strains were on opposite ends of the expression spectrum, with C57 showing higher myelin transcript expression compared with DBA. Our experiments showed accompanying differences between C57 and DBA in myelin protein composition, total myelin content, and white matter conduction velocity. Finally, the hippocampal myelin gene expression of the BXD strains correlated significantly with behavioral traits involving anxiety and/or activity. Taken together, our data indicate that genetic variation in myelin gene expression translates to differences observed in myelination, axonal conduction speed, and possibly in anxiety/activity related behaviors.

Nodes of Ranvier during development and repair in the CNS.

Saltatory conduction of action potentials along myelinated axons depends on the nodes of Ranvier - small unmyelinated axonal domains where voltage-gated sodium channels are concentrated. Our knowledge of the complex molecular composition of these axonal domains continues to accumulate, although the mechanisms of nodal assembly, which have been elucidated in the PNS, remain only partially understood in the CNS. Besides the key role of the nodes in accelerating conduction, nodal variations are thought to allow the fine tuning of axonal conduction speed to meet information processing needs. In addition, through their multiple glial contacts, nodes seem to be important for neuron-glia interactions. As we highlight in this Review, the disorganization of axonal domains has been implicated in the pathophysiology of various neurological diseases. In multiple sclerosis, for example, nodal and perinodal disruption following demyelination, with subsequent changes in ion channel distribution, leads to altered axonal conduction and integrity. The nodal clusters regenerate concurrently with but also prior to remyelination, allowing the restoration of axonal conduction. In this article, we review current knowledge of the organization and function of nodes of Ranvier in the CNS. We go on to discuss dynamic changes in the nodes during demyelination and remyelination, highlighting the impact of these changes on neuronal physiology in health and disease as well as the associated therapeutic implications.

The roles of perineuronal nets and the perinodal extracellular matrix inneuronal function.

Perineuronal nets (PNNs) are extracellular matrix (ECM) chondroitin sulfate proteoglycan (CSPG)-containing structures that surround the soma and dendrites of various mammalian neuronal cell types. PNNs appear during development around the time that the critical periods for developmental plasticity end and are important for both their onset and closure. A similar structure - the perinodal ECM - surrounds the axonal nodes of Ranvier and appears as myelination is completed, acting as an ion-diffusion barrier that affects axonal conduction speed. Recent work has revealed the importance of PNNs in controlling plasticity in the CNS. Digestion, blocking or removal of PNNs influences functional recovery after a variety of CNS lesions. PNNs have further been shown to be involved in the regulation of memory and have been implicated in a number of psychiatric disorders.

Intravitreal AAV-Delivery of Genetically Encoded Sensors Enabling Simultaneous Two-Photon Imaging and Electrophysiology of Optic Nerve Axons.

Myelination of axons by oligodendrocytes is a key feature of the remarkably fast operating CNS. Oligodendrocytes not only tune axonal conduction speed but are also suggested to maintain long-term axonal integrity by providing metabolic support to the axons they ensheath. However, how myelinating oligodendrocytes impact axonal energy homeostasis remains poorly understood and difficult to investigate. Here, we provide a method of how to study electrically active myelinated axons expressing genetically encoded sensors by combining electrophysiology and two-photon imaging of acutely isolated optic nerves. We show that intravitreal adeno-associated viral (AAV) vector delivery is an efficient tool to achieve functional sensor expression in optic nerve axons, which is demonstrated by measuring axonal ATP dynamics following AAV-mediated sensor expression. This novel approach allows for fast expression of any optical sensor of interest to be studied in optic nerve axons without the need to go through the laborious process of producing new transgenic mouse lines. Viral-mediated biosensor expression in myelinated axons and the subsequent combination of nerve recordings and sensor imaging outlines a powerful method to investigate oligodendroglial support functions and to further interrogate cellular mechanisms governing axonal energy homeostasis under physiological and pathological conditions.

Node of Ranvier length as a potential regulator of myelinated axon conduction speed.

Myelination speeds conduction of the nerve impulse, enhancing cognitive power. Changes of white matter structure contribute to learning, and are often assumed to reflect an altered number of myelin wraps. We now show that, in rat optic nerve and cerebral cortical axons, the node of Ranvier length varies over a 4.4-fold and 8.7-fold range respectively and that variation of the node length is much less along axons than between axons. Modelling predicts that these node length differences will alter conduction speed by ~20%, similar to the changes produced by altering the number of myelin wraps or the internode length. For a given change of conduction speed, the membrane area change needed at the node is >270-fold less than that needed in the myelin sheath. Thus, axon-specific adjustment of node of Ranvier length is potentially an energy-efficient and rapid mechanism for tuning the arrival time of information in the CNS.

EEG functional connectivity, axon delays and white matter disease

ObjectiveBoth structural and functional brain connectivities are closely linked to white matter disease. We discuss several such links of potential interest to neurologists, neurosurgeons, radiologists, and non-clinical neuroscientists. MethodsTreatment of brains as genuine complex systems suggests major emphasis on the multi-scale nature of brain connectivity and dynamic behavior. Cross-scale interactions of local, regional, and global networks are apparently responsible for much of EEG’s oscillatory behaviors. Finite axon propagation speed, often assumed to be infinite in local network models, is central to our conceptual framework. ResultsMyelin controls axon speed, and the synchrony of impulse traffic between distant cortical regions appears to be critical for optimal mental performance and learning.Several experiments suggest that axon conduction speed is plastic, thereby altering the regional and global white matter connections that facilitate binding of remote local networks. ConclusionsCombined EEG and high resolution EEG can provide distinct multi-scale estimates of functional connectivity in both healthy and diseased brains with measures like frequency and phase spectra, covariance, and coherence. SignificanceWhite matter disease may profoundly disrupt normal EEG coherence patterns, but currently these kinds of studies are rare in scientific labs and essentially missing from clinical environments.

Role of local network oscillations in resting-state functional connectivity

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain.

Effects of the anesthetic agent propofol on neural populations.

The neuronal mechanisms of general anesthesia are still poorly understood. Besides several characteristic features of anesthesia observed in experiments, a prominent effect is the bi-phasic change of power in the observed electroencephalogram (EEG), i.e. the initial increase and subsequent decrease of the EEG-power in several frequency bands while increasing the concentration of the anaesthetic agent. The present work aims to derive analytical conditions for this bi-phasic spectral behavior by the study of a neural population model. This model describes mathematically the effective membrane potential and involves excitatory and inhibitory synapses, excitatory and inhibitory cells, nonlocal spatial interactions and a finite axonal conduction speed. The work derives conditions for synaptic time constants based on experimental results and gives conditions on the resting state stability. Further the power spectrum of Local Field Potentials and EEG generated by the neural activity is derived analytically and allow for the detailed study of bi-spectral power changes. We find bi-phasic power changes both in monostable and bistable system regime, affirming the omnipresence of bi-spectral power changes in anesthesia. Further the work gives conditions for the strong increase of power in the δ-frequency band for large propofol concentrations as observed in experiments.

Dopaminergic modulation of neurosecretory cells in the crayfish.

The main aims of this paper are (a) to locate possible dopaminergic neurons in the eyestalk with anti-tyrosine hydroxylase antibodies, (b) to search for the presence of dopamine (DA) in the nervous structures of the eyestalk, (c) to explore its release, and (d) to test the effect of DA on neurosecretory cells in the eyestalk. Experiments were performed in adult crayfishes Procambarus clarkii, in isolated optic peduncle. Immunocytochemistry was made with the antibody against its precursor synthesizing enzyme tyrosine-hydroxylase. The content and release studies of DA were made using high performance liquid chromatography (HPLC). Extracellular and intracellular recordings were conducted with conventional recording techniques. A large number (approximately 2000) of immunopositive somata of different sizes and shapes were identified in various regions of the eyestalk. The majority of somata are of the smallest size (5-25 microm diameter). DA content in the eyestalk was 5.6 +/- 0.1 pmol per structure; the greatest content is in the MT (over 60%). A basal level release of DA was observed. Incubation of eyestalks in solution containing a high K+ concentration increased the DA release (79%). Two effects of DA on the excitability of X-organ neurons were observed; an excitatory effect on neurons of approximately 25 microm somata diameter and another inhibitory effect in the group of approximately 35-microm somata diameter neurons. The excitation occurs with a depolarization and decrement of membrane conductance in the cell soma while the inhibition occurs with a hyperpolarization and increment of membrane conductance in soma. We concluded the following: (1) Dopamine is present in each optic ganglia of the crayfish eyestalk. (2) There is a basal release of DA from the isolated eyestalk. (3) DA release is enhanced threefold by eyestalk incubation in 40 mM [K+] solution. (4) DA selectively excites a population of neurons with low-speed conduction axons, and small somata in the X-organ-sinus gland system, while inhibiting another population characterized by higher axonal conduction speed and large somata. (5) These observations support a role for DA as a neurotransmitter or neuromodulator in the X-organ neurons of the crayfish eyestalk.

Power-law for axon diameters at branch point

BackgroundAxon calibers vary widely among different animals, neuron classes, and even within the same neuron. What determines the diameter of axon branches?ResultsWe pursue the hypothesis that the axon caliber has evolved to minimize signal propagation delays, while keeping arbor volume to a minimum. For a general cost function, we show that the optimal diameters of mother and daughter branches at a bifurcation satisfy a power law. The derivation relies on the fact that the axon conduction speed scales as a power of axon diameter. Although available data are consistent with the law, there is a large spread in the data. Future experimental tests will determine whether this spread is due to biological variability or measurement error.ConclusionsMinimization of arbor volume and signal propagation delay may have been an important factor in the evolution of the brain.