How the optic nerve allocates space, energy capacity, and information

Mitochondrial retinopathies and optic neuropathies: The impact of retinal imaging on modern understanding of pathogenesis, diagnosis, and management

Advancements in ocular imaging have significantly broadened our comprehension of mitochondrial retinopathies and optic neuropathies by examining the structural and pathological aspects of the retina and optic nerve in these conditions. This article aims to review the prominent imaging characteristics associated with mitochondrial retinopathies and optic neuropathies, aiming to deepen our insight into their pathogenesis and clinical features. Preceding this exploration, the article provides a detailed overview of the crucial genetic and clinical features, which is essential for the proper interpretation of in vivo imaging. More importantly, we will provide a critical analysis on how these imaging modalities could serve as biomarkers for characterization and monitoring, as well as in guiding treatment decisions. However, these imaging methods have limitations, which will be discussed along with potential strategies to mitigate them. Lastly, the article will emphasize the potential advantages and future integration of imaging techniques in evaluating patients with mitochondrial eye disorders, considering the prospects of emerging gene therapies.

Why animals can outrun robots

Animals are much better at running than robots. The difference in performance arises in the important dimensions of agility, range, and robustness. To understand the underlying causes for this performance gap, we compare natural and artificial technologies in the five subsystems critical for running: power, frame, actuation, sensing, and control. With few exceptions, engineering technologies meet or exceed the performance of their biological counterparts. We conclude that biology's advantage over engineering arises from better integration of subsystems, and we identify four fundamental obstacles that roboticists must overcome. Toward this goal, we highlight promising research directions that have outsized potential to help future running robots achieve animal-level performance.

Probing brain tissue microstructure with MRI: principles, challenges, and the role of multidimensional diffusion-relaxation encoding

Diffusion MRI uses the random displacement of water molecules to sensitize the signal to brain microstructure and to properties such as the density and shape of cells. Microstructure modeling techniques aim to estimate these properties from acquired data by separating the signal between virtual tissue 'compartments' such as the intra-neurite and the extra-cellular space. A key challenge is that the diffusion MRI signal is relatively featureless compared with the complexity of brain tissue. Another challenge is that the tissue microstructure is wildly different within the gray and white matter of the brain. In this review, we use results from multidimensional diffusion encoding techniques to discuss these challenges and their tentative solutions. Multidimensional encoding increases the information content of the data by varying not only the b-value and the encoding direction but also additional experimental parameters such as the shape of the b-tensor and the echo time. Three main insights have emerged from such encoding. First, multidimensional data contradict common model assumptions on diffusion and T2 relaxation, and illustrates how the use of these assumptions cause erroneous interpretations in both healthy brain and pathology. Second, many model assumptions can be dispensed with if data are acquired with multidimensional encoding. The necessary data can be easily acquired in vivo using protocols optimized to minimize Cramér-Rao lower bounds. Third, microscopic diffusion anisotropy reflects the presence of axons but not dendrites. This insight stands in contrast to current 'neurite models' of brain tissue, which assume that axons in white matter and dendrites in gray matter feature highly similar diffusion. Nevertheless, as an axon-based contrast, microscopic anisotropy can differentiate gray and white matter when myelin alterations confound conventional MRI contrasts.

Mitophagy in Astrocytes Is Required for the Health of Optic Nerve

Mitochondrial dysfunction in astrocytes has been implicated in the development of various neurological disorders. Mitophagy, mitochondrial autophagy, is required for proper mitochondrial function by preventing the accumulation of damaged mitochondria. The importance of mitophagy, specifically in the astrocytes of the optic nerve (ON), has been little studied. We introduce an animal model in which two separate mutations act synergistically to produce severe ON degeneration. The first mutation is in Cryba1, which encodes βA3/A1-crystallin, a lens protein also expressed in astrocytes, where it regulates lysosomal pH. The second mutation is in Bckdk, which encodes branched-chain ketoacid dehydrogenase kinase, which is ubiquitously expressed in the mitochondrial matrix and involved in the catabolism of the branched-chain amino acids. BCKDK is essential for mitochondrial function and the amelioration of oxidative stress. Neither of the mutations in isolation has a significant effect on the ON, but animals homozygous for both mutations (DM) exhibit very serious ON degeneration. ON astrocytes from these double-mutant (DM) animals have lysosomal defects, including impaired mitophagy, and dysfunctional mitochondria. Urolithin A can rescue the mitophagy impairment in DM astrocytes and reduce ON degeneration. These data demonstrate that efficient mitophagy in astrocytes is required for ON health and functional integrity.

In vivo evidence of microstructural hypo-connectivity of brain white matter in 22q11.2 deletion syndrome

22q11.2 deletion syndrome, or 22q11.2DS, is a genetic syndrome associated with high rates of schizophrenia and autism spectrum disorders, in addition to widespread structural and functional abnormalities throughout the brain. Experimental animal models have identified neuronal connectivity deficits, e.g., decreased axonal length and complexity of axonal branching, as a primary mechanism underlying atypical brain development in 22q11.2DS. However, it is still unclear whether deficits in axonal morphology can also be observed in people with 22q11.2DS. Here, we provide an unparalleled in vivo characterization of white matter microstructure in participants with 22q11.2DS (12-15 years) and those undergoing typical development (8-18 years) using a customized magnetic resonance imaging scanner which is sensitive to axonal morphology. A rich array of diffusion MRI metrics are extracted to present microstructural profiles of typical and atypical white matter development, and provide new evidence of connectivity differences in individuals with 22q11.2DS. A recent, large-scale consortium study of 22q11.2DS identified higher diffusion anisotropy and reduced overall diffusion mobility of water as hallmark microstructural alterations of white matter in individuals across a wide age range (6-52 years). We observed similar findings across the white matter tracts included in this study, in addition to identifying deficits in axonal morphology. This, in combination with reduced tract volume measurements, supports the hypothesis that abnormal microstructural connectivity in 22q11.2DS may be mediated by densely packed axons with disproportionately small diameters. Our findings provide insight into the in vivo white matter phenotype of 22q11.2DS, and promote the continued investigation of shared features in neurodevelopmental and psychiatric disorders.

A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments

In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.

Retinal input integration in excitatory and inhibitory neurons in the mouse superior colliculus in vivo

The superior colliculus (SC) is a midbrain structure that receives inputs from retinal ganglion cells (RGCs). The SC contains one of the highest densities of inhibitory neurons in the brain but whether excitatory and inhibitory SC neurons differentially integrate retinal activity in vivo is still largely unknown. We recently established a recording approach to measure the activity of RGCs simultaneously with their postsynaptic SC targets in vivo, to study how SC neurons integrate RGC activity. Here, we employ this method to investigate the functional properties that govern retinocollicular signaling in a cell type-specific manner by identifying GABAergic SC neurons using optotagging in VGAT-ChR2 mice. Our results demonstrate that both excitatory and inhibitory SC neurons receive comparably strong RGC inputs and similar wiring rules apply for RGCs innervation of both SC cell types, unlike the cell type-specific connectivity in the thalamocortical system. Moreover, retinal activity contributed more to the spiking activity of postsynaptic excitatory compared to inhibitory SC neurons. This study deepens our understanding of cell type-specific retinocollicular functional connectivity and emphasizes that the two major brain areas for visual processing, the visual cortex and the SC, differently integrate sensory afferent inputs.

Transient and Sustained Ganglion Cell Light Responses Are Differentially Modulated by Intrinsically Produced Reactive Oxygen Species Acting upon Specific Voltage-Gated Na+ Channel Isoforms

Increasing spike rates drive greater neuronal energy demand. In turn, mitochondrial ATP production leads to the generation of reactive oxygen species (ROS) that can modulate ion channel gating. Does ROS production autoregulate the excitability of a neuron? We investigated the links between retinal ganglion cell (RGC) excitability and spike activity-driven ROS production in male and female mice. Changes to the light-evoked and current-evoked spike patterns of functionally identified αRGC subtypes, along with their NaV channel-gating properties, were recorded during experimentally induced decreases and increases of intracellular ROS. During periods of highest spike rates (e.g., following light onset in ON sustained RGCs and light offset in OFF sustained RGCs), these αRGC subtypes responded to reductions of ROS (induced by catalase or glutathione monoethyl ester) with higher spike rates. Increases in ROS (induced by mercaptosuccinate, antimycin-A, or H2O2) lowered spike rates. In ON and OFF transient RGCs, there were no changes in spike rate during ROS decreases but increased ROS increased spiking. This suggests that endogenous ROS are intrinsic neuromodulators in RGCs having high metabolic demands but not in RGCs with lower energy needs. We identified ROS-induced shifts in the voltage-dependent gating of specific isoforms of NaV channels that account for the modulation of ON and OFF sustained RGC spike frequency by ROS-mediated feedback. ROS-induced changes to NaV channel gating, affecting activation and inactivation kinetics, are consistent with the differing spike pattern alterations observed in RGC subtypes. Cell-autonomous generation of ROS during spiking contributes to tuning the spike patterns of RGCs.SIGNIFICANCE STATEMENT Energy production within retinal ganglion cells (RGCs) is accompanied by metabolic by-products harmful to cellular function. How these by-products modulate the excitability of RGCs bears heavily on visual function and the etiology of optic neuropathies. A novel hypothesis of how RGC metabolism can produce automodulation of electrical signaling was tested by identifying the characteristics and biophysical origins of changes to the excitability of RGCs caused by oxidizing by-products in the retina. This impacts our understanding of the pathophysiology of RGC dysfunction, supporting an emerging model in which increases in oxidizing chemical species during energy production, but not necessarily bioenergetic failure, lead to preferential degeneration of specific subtypes of RGCs, yielding loss of different aspects of visual capacity.

Resilience of compound action potential peaks to high-frequency firing in the mouse optic nerve

Action potential conduction in axons triggers trans-membrane ion movements, where Na⁺ enters and K⁺ leaves axons, leading to disruptions in resting trans-membrane ion gradients that must be restored for optimal axon conduction, an energy dependent process. The higher the stimulus frequency, the greater the ion movements and the resulting energy demand. In the mouse optic nerve (MON), the stimulus evoked compound action potential (CAP) displays a triple peaked profile, consistent with subpopulations of axons classified by size producing the distinct peaks. The three CAP peaks show differential sensitivity to high-frequency firing, with the large axons, which contribute to the 1st peak, more resilient than the small axons, which produce the 3rd peak. Modeling studies predict frequency dependent intra-axonal Na⁺ accumulation at the nodes of Ranvier, sufficient to attenuate the triple peaked CAP. Short bursts of high-frequency stimulus evoke transient elevations in interstitial K⁺ ([K⁺ ]_o ), which peak at about 50 Hz. However, powerful astrocytic buffering limits the [K⁺ ]_o increase to levels insufficient to cause CAP attenuation. A post-stimulus [K⁺ ]_o undershoot below baseline coincides with a transient increase in the amplitudes of all three CAP peaks. The volume specific scaling relating energy expenditure to increasing axon size dictates that large axons are more resilient to high-frequency firing than small axons.

Activity-Dependent Fluctuations in Interstitial [K+]: Investigations Using Ion-Sensitive Microelectrodes

In the course of action potential firing, all axons and neurons release K⁺ from the intra- cellular compartment into the interstitial space to counteract the depolarizing effect of Na⁺ influx, which restores the resting membrane potential. This efflux of K⁺ from axons results in K⁺ accumulation in the interstitial space, causing depolarization of the K⁺ reversal potential (E_K), which can prevent subsequent action potentials. To ensure optimal neuronal function, the K⁺ is buffered by astrocytes, an energy-dependent process, which acts as a sink for interstitial K⁺, absorbing it at regions of high concentration and distributing it through the syncytium for release in distant regions. Pathological processes in which energy production is compromised, such as anoxia, ischemia, epilepsy and spreading depression, can lead to excessive interstitial K⁺ accumulation, disrupting sensitive trans-membrane ion gradients and attenuating neuronal activity. The changes that occur in interstitial [K⁺] resulting from both physiological and pathological processes can be monitored accurately in real time using K⁺-sensitive microelectrodes, an invaluable tool in electrophysiological studies.

Parvalbumin basket cell myelination accumulates axonal mitochondria to internodes

Parvalbumin-expressing (PV⁺) basket cells are fast-spiking inhibitory interneurons that exert critical control over local circuit activity and oscillations. PV⁺ axons are often myelinated, but the electrical and metabolic roles of interneuron myelination remain poorly understood. Here, we developed viral constructs allowing cell type-specific investigation of mitochondria with genetically encoded fluorescent probes. Single-cell reconstructions revealed that mitochondria selectively cluster to myelinated segments of PV⁺ basket cells, confirmed by analyses of a high-resolution electron microscopy dataset. In contrast to the increased mitochondrial densities in excitatory axons cuprizone-induced demyelination abolished mitochondrial clustering in PV⁺ axons. Furthermore, with genetic deletion of myelin basic protein the mitochondrial clustering was still observed at internodes wrapped by noncompacted myelin, indicating that compaction is dispensable. Finally, two-photon imaging of action potential-evoked calcium (Ca²⁺) responses showed that interneuron myelination attenuates both the cytosolic and mitochondrial Ca²⁺ transients. These findings suggest that oligodendrocyte ensheathment of PV⁺ axons assembles mitochondria to branch selectively fine-tune metabolic demands.

Efficient processing of natural scenes in visual cortex

Neural circuits in the periphery of the visual, auditory, and olfactory systems are believed to use limited resources efficiently to represent sensory information by adapting to the statistical structure of the natural environment. This "efficient coding" principle has been used to explain many aspects of early visual circuits including the distribution of photoreceptors, the mosaic geometry and center-surround structure of retinal receptive fields, the excess OFF pathways relative to ON pathways, saccade statistics, and the structure of simple cell receptive fields in V1. We know less about the extent to which such adaptations may occur in deeper areas of cortex beyond V1. We thus review recent developments showing that the perception of visual textures, which depends on processing in V2 and beyond in mammals, is adapted in rats and humans to the multi-point statistics of luminance in natural scenes. These results suggest that central circuits in the visual brain are adapted for seeing key aspects of natural scenes. We conclude by discussing how adaptation to natural temporal statistics may aid in learning and representing visual objects, and propose two challenges for the future: (1) explaining the distribution of shape sensitivity in the ventral visual stream from the statistics of object shape in natural images, and (2) explaining cell types of the vertebrate retina in terms of feature detectors that are adapted to the spatio-temporal structures of natural stimuli. We also discuss how new methods based on machine learning may complement the normative, principles-based approach to theoretical neuroscience.

Autophagic degradation of CNS myelin maintains axon integrity

(Macro)autophagy is a major lysosome-dependent degradation mechanism which engulfs, removes and recycles unwanted cytoplasmic material, including damaged organelles and toxic protein aggregates. Although a few studies implicate autophagy in CNS demyelinating pathologies, its role, particularly in mature oligodendrocytes and CNS myelin, remains poorly studied. Here, using both pharmacological and genetic inhibition of the autophagic machinery, we provide evidence that autophagy is an essential mechanism for oligodendrocyte maturation in vitro. Our study reveals that two core myelin proteins, namely proteolipid protein (PLP) and myelin basic protein (MBP) are incorporated into autophagosomes in oligodendrocytes, resulting in their degradation. Furthermore, we ablated atg5, a core gene of the autophagic machinery, specifically in myelinating glial cells in vivo by tamoxifen administration (plp-Cre ERT2 ; atg5 f/f ) and showed that myelin maintenance is perturbed, leading to PLP accumulation. Significant morphological defects in myelin membrane such as decompaction accompanied with increased axonal degeneration are observed. As a result, the mice exhibit behavioral deficits. In summary, our data highlight that the maintenance of adult myelin homeostasis in the CNS requires the involvement of a fully functional autophagic machinery.

Modeling Reactive Oxygen Species-Induced Axonal Loss in Leber Hereditary Optic Neuropathy

Leber hereditary optic neuropathy (LHON) is a rare syndrome that results in vision loss. A necessary but not sufficient condition for its onset is the existence of known mitochondrial DNA mutations that affect complex I biomolecular structure. Cybrids with LHON mutations generate higher rates of reactive oxygen species (ROS). This study models how ROS, particularly H₂O₂, could signal and execute the axonal degeneration process that underlies LHON. We modeled and explored several hypotheses regarding the influence of H₂O₂ on the dynamics of propagation of axonal degeneration in LHON. Zonal oxidative stress, corresponding to H₂O₂ gradients, correlated with the morphology of injury exhibited in the LHON pathology. If the axonal membrane is highly permeable to H₂O₂ and oxidative stress induces larger production of H₂O₂, small injuries could trigger cascading failures of neighboring axons. The cellular interdependence created by H₂O₂ diffusion, and the gradients created by tissue variations in H₂O₂ production and scavenging, result in injury patterns and surviving axonal loss distributions similar to LHON tissue samples. Specifically, axonal degeneration starts in the temporal optic nerve, where larger groups of small diameter fibers are located and propagates from that region. These findings correlate well with clinical observations of central loss of visual field, visual acuity, and color vision in LHON, and may serve as an in silico platform for modeling the mechanism of action for new therapeutics.

Chondroitin Sulphate Proteoglycan Axonal Coats in the Human Mediodorsal Thalamic Nucleus

Mounting evidence supports a key involvement of the chondroitin sulfate proteoglycans (CSPGs) NG2 and brevican (BCAN) in the regulation of axonal functions, including axon guidance, fasciculation, conductance, and myelination. Prior work suggested the possibility that these functions may, at least in part, be carried out by specialized CSPG structures surrounding axons, termed axonal coats. However, their existence remains controversial. We tested the hypothesis that NG2 and BCAN, known to be associated with oligodendrocyte precursor cells, form axonal coats enveloping myelinated axons in the human brain. In tissue blocks containing the mediodorsal thalamic nucleus (MD) from healthy donors (n = 5), we used dual immunofluorescence, confocal microscopy, and unbiased stereology to characterize BCAN and NG2 immunoreactive (IR) axonal coats and measure the percentage of myelinated axons associated with them. In a subset of donors (n = 3), we used electron microscopy to analyze the spatial relationship between axons and NG2- and BCAN-IR axonal coats within the human MD. Our results show that a substantial percentage (∼64%) of large and medium myelinated axons in the human MD are surrounded by NG2- and BCAN-IR axonal coats. Electron microscopy studies show NG2- and BCAN-IR axonal coats are interleaved with myelin sheets, with larger axons displaying greater association with axonal coats. These findings represent the first characterization of NG2 and BCAN axonal coats in the human brain. The large percentage of axons surrounded by CSPG coats, and the role of CSPGs in axonal guidance, fasciculation, conductance, and myelination suggest that these structures may contribute to several key axonal properties.

Efficient Temporal Coding in the Early Visual System: Existing Evidence and Future Directions

While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information should be stored, or encoded. Information theory provides a mathematical formalism that can be used to measure the efficiency and utility of different coding schemes for data transfer and storage. This theory shows that codes become efficient when they remove predictable, redundant spatial and temporal information. Efficient coding has been used to understand retinal computations and may also be relevant to understanding more complicated temporal processing in visual cortex. However, the literature on efficient coding in cortex is varied and can be confusing since the same terms are used to mean different things in different experimental and theoretical contexts. In this work, we attempt to provide a clear summary of the theoretical relationship between efficient coding and temporal prediction, and review evidence that efficient coding principles explain computations in the retina. We then apply the same framework to computations occurring in early visuocortical areas, arguing that data from rodents is largely consistent with the predictions of this model. Finally, we review and respond to criticisms of efficient coding and suggest ways that this theory might be used to design future experiments, with particular focus on understanding the extent to which neural circuits make predictions from efficient representations of environmental statistics.

Long-Term Changes in Axon Calibers after Injury: Observations on the Mouse Corticospinal Tract

White matter pathology is common across a wide spectrum of neurological diseases. Characterizing this pathology is important for both a mechanistic understanding of neurological diseases as well as for the development of neuroimaging biomarkers. Although axonal calibers can vary by orders of magnitude, they are tightly regulated and related to neuronal function, and changes in axon calibers have been reported in several diseases and their models. In this study, we utilize the impact acceleration model of traumatic brain injury (IA-TBI) to assess early and late changes in the axon diameter distribution (ADD) of the mouse corticospinal tract using Airyscan and electron microscopy. We find that axon calibers follow a lognormal distribution whose parameters significantly change after injury. While IA-TBI leads to 30% loss of corticospinal axons by day 7 with a bias for larger axons, at 21 days after injury we find a significant redistribution of axon frequencies that is driven by a reduction in large-caliber axons in the absence of detectable degeneration. We postulate that changes in ADD features may reflect a functional adaptation of injured neural systems. Moreover, we find that ADD features offer an accurate way to discriminate between injured and non-injured mice. Exploring injury-related ADD signatures by histology or new emerging neuroimaging modalities may offer a more nuanced and comprehensive way to characterize white matter pathology and may also have the potential to generate novel biomarkers of injury.

Aerobic Glycolysis: A DeOxymoron of (Neuro)Biology

The term ‘aerobic glycolysis’ has been in use ever since Warburg conducted his research on cancer cells’ proliferation and discovered that cells use glycolysis to produce adenosine triphosphate (ATP) rather than the more efficient oxidative phosphorylation (oxphos) pathway, despite an abundance of oxygen. When measurements of glucose and oxygen utilization by activated neural tissue indicated that glucose was consumed without an accompanied oxygen consumption, the investigators who performed those measurements also termed their discovery ‘aerobic glycolysis’. Red blood cells do not contain mitochondria and, therefore, produce their energy needs via glycolysis alone. Other processes within the central nervous system (CNS) and additional organs and tissues (heart, muscle, and so on), such as ion pumps, are also known to utilize glycolysis only for the production of ATP necessary to support their function. Unfortunately, the phenomenon of ‘aerobic glycolysis’ is an enigma wherever it is encountered, thus several hypotheses have been produced in attempts to explain it; that is, whether it occurs in cancer cells, in activated neural tissue, or during postprandial or exercise metabolism. Here, it is argued that, where the phenomenon in neural tissue is concerned, the prefix ‘aerobic’ in the term ‘aerobic glycolysis’ should be removed. Data collected over the past three decades indicate that L-lactate, the end product of the glycolytic pathway, plays an essential role in brain energy metabolism, justifying the elimination of the prefix ‘aerobic’. Similar justification is probably appropriate for other tissues as well.

Novel Cognitive Functions Arise at the Convergence of Macroscale Gradients

Functions in higher-order brain regions are the source of extensive debate. Although past trends have been to describe the brain-especially posterior cortical areas-in terms of a set of functional modules, a new emerging paradigm focuses on the integration of proximal functions. In this review, we synthesize emerging evidence that a variety of novel functions in the higher-order brain regions are due to convergence: convergence of macroscale gradients brings feature-rich representations into close proximity, presenting an opportunity for novel functions to arise. Using the TPJ as an example, we demonstrate that convergence is enabled via three properties of the brain: (1) hierarchical organization, (2) abstraction, and (3) equidistance. As gradients travel from primary sensory cortices to higher-order brain regions, information becomes abstracted and hierarchical, and eventually, gradients meet at a point maximally and equally distant from their sensory origins. This convergence, which produces multifaceted combinations, such as mentalizing another person's thought or projecting into a future space, parallels evolutionary and developmental characteristics in such regions, resulting in new cognitive and affective faculties.

The Role of Mitochondria in Optic Atrophy With Autosomal Inheritance

Optic atrophy (OA) with autosomal inheritance is a form of optic neuropathy characterized by the progressive and irreversible loss of vision. In some cases, this is accompanied by additional, typically neurological, extra-ocular symptoms. Underlying the loss of vision is the specific degeneration of the retinal ganglion cells (RGCs) which form the optic nerve. Whilst autosomal OA is genetically heterogenous, all currently identified causative genes appear to be associated with mitochondrial organization and function. However, it is unclear why RGCs are particularly vulnerable to mitochondrial aberration. Despite the relatively high prevalence of this disorder, there are currently no approved treatments. Combined with the lack of knowledge concerning the mechanisms through which aberrant mitochondrial function leads to RGC death, there remains a clear need for further research to identify the underlying mechanisms and develop treatments for this condition. This review summarizes the genes known to be causative of autosomal OA and the mitochondrial dysfunction caused by pathogenic mutations. Furthermore, we discuss the suitability of available in vivo models for autosomal OA with regards to both treatment development and furthering the understanding of autosomal OA pathology.

Presynaptic stochasticity improves energy efficiency and helps alleviate the stability-plasticity dilemma

When an action potential arrives at a synapse there is a large probability that no neurotransmitter is released. Surprisingly, simple computational models suggest that these synaptic failures enable information processing at lower metabolic costs. However, these models only consider information transmission at single synapses ignoring the remainder of the neural network as well as its overall computational goal. Here, we investigate how synaptic failures affect the energy efficiency of models of entire neural networks that solve a goal-driven task. We find that presynaptic stochasticity and plasticity improve energy efficiency and show that the network allocates most energy to a sparse subset of important synapses. We demonstrate that stabilising these synapses helps to alleviate the stability-plasticity dilemma, thus connecting a presynaptic notion of importance to a computational role in lifelong learning. Overall, our findings present a set of hypotheses for how presynaptic plasticity and stochasticity contribute to sparsity, energy efficiency and improved trade-offs in the stability-plasticity dilemma.

A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks

Dissipative accounts of structure formation show that the self-organisation of complex structures is thermodynamically favoured, whenever these structures dissipate free energy that could not be accessed otherwise. These structures therefore open transition channels for the state of the universe to move from a frustrated, metastable state to another metastable state of higher entropy. However, these accounts apply as well to relatively simple, dissipative systems, such as convection cells, hurricanes, candle flames, lightning strikes, or mechanical cracks, as they do to complex biological systems. Conversely, interesting computational properties-that characterize complex biological systems, such as efficient, predictive representations of environmental dynamics-can be linked to the thermodynamic efficiency of underlying physical processes. However, the potential mechanisms that underwrite the selection of dissipative structures with thermodynamically efficient subprocesses is not completely understood. We address these mechanisms by explaining how bifurcation-based, work-harvesting processes-required to sustain complex dissipative structures-might be driven towards thermodynamic efficiency. We first demonstrate a simple mechanism that leads to self-selection of efficient dissipative structures in a stochastic chemical reaction network, when the dissipated driving chemical potential difference is decreased. We then discuss how such a drive can emerge naturally in a hierarchy of self-similar dissipative structures, each feeding on the dissipative structures of a previous level, when moving away from the initial, driving disequilibrium.

Dominant optic atrophy: Culprit mitochondria in the optic nerve

Dominant optic atrophy (DOA) is an inherited mitochondrial disease leading to specific degeneration of retinal ganglion cells (RGCs), thus compromising transmission of visual information from the retina to the brain. Usually, DOA starts during childhood and evolves to poor vision or legal blindness, affecting the central vision, whilst sparing the peripheral visual field. In 20% of cases, DOA presents as syndromic disorder, with secondary symptoms affecting neuronal and muscular functions. Twenty years ago, we demonstrated that heterozygous mutations in OPA1 are the most frequent molecular cause of DOA. Since then, variants in additional genes, whose functions in many instances converge with those of OPA1, have been identified by next generation sequencing. OPA1 encodes a dynamin-related GTPase imported into mitochondria and located to the inner membrane and intermembrane space. The many OPA1 isoforms, resulting from alternative splicing of three exons, form complex homopolymers that structure mitochondrial cristae, and contribute to fusion of the outer membrane, thus shaping the whole mitochondrial network. Moreover, OPA1 is required for oxidative phosphorylation, maintenance of mitochondrial genome, calcium homeostasis and regulation of apoptosis, thus making OPA1 the Swiss army-knife of mitochondria. Understanding DOA pathophysiology requires the understanding of RGC peculiarities with respect to OPA1 functions. Besides the tremendous energy requirements of RGCs to relay visual information from the eye to the brain, these neurons present unique features related to their differential environments in the retina, and to the anatomical transition occurring at the lamina cribrosa, which parallel major adaptations of mitochondrial physiology and shape, in the pre- and post-laminar segments of the optic nerve. Three DOA mouse models, with different Opa1 mutations, have been generated to study intrinsic mechanisms responsible for RGC degeneration, and these have further revealed secondary symptoms related to mitochondrial dysfunctions, mirroring the more severe syndromic phenotypes seen in a subgroup of patients. Metabolomics analyses of cells, mouse organs and patient plasma mutated for OPA1 revealed new unexpected pathophysiological mechanisms related to mitochondrial dysfunction, and biomarkers correlated quantitatively to the severity of the disease. Here, we review and synthesize these data, and propose different approaches for embracing possible therapies to fulfil the unmet clinical needs of this disease, and provide hope to affected DOA patients.

The axonal radial contractility: Structural basis underlying a new form of neural plasticity

Axons are the longest cellular structure reaching over a meter in the case of human motor axons. They have a relatively small diameter and contain several cytoskeletal elements that mediate both material and information exchange within neurons. Recently, a novel type of axonal plasticity, termed axonal radial contractility, has been unveiled. It is represented by dynamic and transient diameter changes of the axon shaft to accommodate the passages of large organelles. Mechanisms underpinning this plasticity are not fully understood. Here, we first summarised recent evidence of the functional relevance for axon radial contractility, then discussed the underlying structural basis, reviewing nanoscopic evidence of the subtle changes. Two models are proposed to explain how actomyosin rings are organised. Possible roles of non-muscle myosin II (NM-II) in axon degeneration are discussed. Finally, we discuss the concept of periodic functional nanodomains, which could sense extracellular cues and coordinate the axonal responses. Also see the video abstract here: https://youtu.be/ojCnrJ8RCRc.

Natural environment statistics in the upper and lower visual field are reflected in mouse retinal specializations

Pressures for survival make sensory circuits adapted to a species' natural habitat and its behavioral challenges. Thus, to advance our understanding of the visual system, it is essential to consider an animal's specific visual environment by capturing natural scenes, characterizing their statistical regularities, and using them to probe visual computations. Mice, a prominent visual system model, have salient visual specializations, being dichromatic with enhanced sensitivity to green and UV in the dorsal and ventral retina, respectively. However, the characteristics of their visual environment that likely have driven these adaptations are rarely considered. Here, we built a UV-green-sensitive camera to record footage from mouse habitats. This footage is publicly available as a resource for mouse vision research. We found chromatic contrast to greatly diverge in the upper, but not the lower, visual field. Moreover, training a convolutional autoencoder on upper, but not lower, visual field scenes was sufficient for the emergence of color-opponent filters, suggesting that this environmental difference might have driven superior chromatic opponency in the ventral mouse retina, supporting color discrimination in the upper visual field. Furthermore, the upper visual field was biased toward dark UV contrasts, paralleled by more light-offset-sensitive ganglion cells in the ventral retina. Finally, footage recorded at twilight suggests that UV promotes aerial predator detection. Our findings support that natural scene statistics shaped early visual processing in evolution.

Diversity-enabled sweet spots in layered architectures and speed-accuracy trade-offs in sensorimotor control

Nervous systems sense, communicate, compute, and actuate movement using distributed components with severe trade-offs in speed, accuracy, sparsity, noise, and saturation. Nevertheless, brains achieve remarkably fast, accurate, and robust control performance due to a highly effective layered control architecture. Here, we introduce a driving task to study how a mountain biker mitigates the immediate disturbance of trail bumps and responds to changes in trail direction. We manipulated the time delays and accuracy of the control input from the wheel as a surrogate for manipulating the characteristics of neurons in the control loop. The observed speed-accuracy trade-offs motivated a theoretical framework consisting of two layers of control loops-a fast, but inaccurate, reflexive layer that corrects for bumps and a slow, but accurate, planning layer that computes the trajectory to follow-each with components having diverse speeds and accuracies within each physical level, such as nerve bundles containing axons with a wide range of sizes. Our model explains why the errors from two control loops are additive and shows how the errors in each control loop can be decomposed into the errors caused by the limited speeds and accuracies of the components. These results demonstrate that an appropriate diversity in the properties of neurons across layers helps to create "diversity-enabled sweet spots," so that both fast and accurate control is achieved using slow or inaccurate components.

Local Accumulation of Axonal Mitochondria in the Optic Nerve Glial Lamina Precedes Myelination

Mitochondria are essential for neurons and must be optimally distributed along their axon to fulfill local functions. A high density of mitochondria has been observed in retinal ganglion cell (RGC) axons of an unmyelinated region of the optic nerve, called the glial lamina (GL) in mouse (lamina cribrosa in human). In glaucoma, the world's leading cause of irreversible blindness, the GL is the epicenter of RGC degeneration and is connected to mitochondrial dysfunction. It is generally accepted that the local accumulation of mitochondria in the GL is established due to the higher energy requirement of unmyelinated axons. Here we revisit the connection between mitochondrial positioning and myelin in RGC axons. We show that the high density of mitochondria in the GL is restricted to larger axons and is established before myelination. Thus, contrary to a longstanding belief in the field, the myelination pattern is not responsible for the establishment of the local accumulation of mitochondria in GL axons. Our findings open new research avenues likely critical to understanding the pathophysiology of glaucoma.

Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number

Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. Taking a particular energy-efficient viewpoint, we define neural computation and make use of an energy-constrained computational function. This function can be optimized over a variable that is proportional to the number of synapses per neuron. This function also implies a specific distinction between adenosine triphosphate (ATP)-consuming processes, especially computation per se vs. the communication processes of action potentials and transmitter release. Thus, to apply this mathematical function requires an energy audit with a particular partitioning of energy consumption that differs from earlier work. The audit points out that, rather than the oft-quoted 20 W of glucose available to the human brain, the fraction partitioned to cortical computation is only 0.1 W of ATP [L. Sokoloff, Handb. Physiol. Sect. I Neurophysiol. 3, 1843-1864 (1960)] and [J. Sawada, D. S. Modha, "Synapse: Scalable energy-efficient neurosynaptic computing" in Application of Concurrency to System Design (ACSD) (2013), pp. 14-15]. On the other hand, long-distance communication costs are 35-fold greater, 3.5 W. Other findings include 1) a [Formula: see text]-fold discrepancy between biological and lowest possible values of a neuron's computational efficiency and 2) two predictions of N, the number of synaptic transmissions needed to fire a neuron (2,500 vs. 2,000).

The variability of MR axon radii estimates in the human white matter

The noninvasive quantification of axonal morphology is an exciting avenue for gaining understanding of the function and structure of the central nervous system. Accurate non-invasive mapping of micron-sized axon radii using commonly applied neuroimaging techniques, that is, diffusion-weighted MRI, has been bolstered by recent hardware developments, specifically MR gradient design. Here the whole brain characterization of the effective MR axon radius is presented and the inter- and intra-scanner test-retest repeatability and reproducibility are evaluated to promote the further development of the effective MR axon radius as a neuroimaging biomarker. A coefficient-of-variability of approximately 10% in the voxelwise estimation of the effective MR radius is observed in the test-retest analysis, but it is shown that the performance can be improved fourfold using a customized along-tract analysis.

Efficient population coding depends on stimulus convergence and source of noise

Sensory organs transmit information to downstream brain circuits using a neural code comprised of spikes from multiple neurons. According to the prominent efficient coding framework, the properties of sensory populations have evolved to encode maximum information about stimuli given biophysical constraints. How information coding depends on the way sensory signals from multiple channels converge downstream is still unknown, especially in the presence of noise which corrupts the signal at different points along the pathway. Here, we calculated the optimal information transfer of a population of nonlinear neurons under two scenarios. First, a lumped-coding channel where the information from different inputs converges to a single channel, thus reducing the number of neurons. Second, an independent-coding channel when different inputs contribute independent information without convergence. In each case, we investigated information loss when the sensory signal was corrupted by two sources of noise. We determined critical noise levels at which the optimal number of distinct thresholds of individual neurons in the population changes. Comparing our system to classical physical systems, these changes correspond to first- or second-order phase transitions for the lumped- or the independent-coding channel, respectively. We relate our theoretical predictions to coding in a population of auditory nerve fibers recorded experimentally, and find signatures of efficient coding. Our results yield important insights into the diverse coding strategies used by neural populations to optimally integrate sensory stimuli in the presence of distinct sources of noise.

Energy Metabolism in the Inner Retina in Health and Glaucoma

Glaucoma, the leading cause of irreversible blindness, is a heterogeneous group of diseases characterized by progressive loss of retinal ganglion cells (RGCs) and their axons and leads to visual loss and blindness. Risk factors for the onset and progression of glaucoma include systemic and ocular factors such as older age, lower ocular perfusion pressure, and intraocular pressure (IOP). Early signs of RGC damage comprise impairment of axonal transport, downregulation of specific genes and metabolic changes. The brain is often cited to be the highest energy-demanding tissue of the human body. The retina is estimated to have equally high demands. RGCs are particularly active in metabolism and vulnerable to energy insufficiency. Understanding the energy metabolism of the inner retina, especially of the RGCs, is pivotal for understanding glaucoma’s pathophysiology. Here we review the key contributors to the high energy demands in the retina and the distinguishing features of energy metabolism of the inner retina. The major features of glaucoma include progressive cell death of retinal ganglions and optic nerve damage. Therefore, this review focuses on the energetic budget of the retinal ganglion cells, optic nerve and the relevant cells that surround them.

Glial Cells in Glaucoma: Friends, Foes, and Potential Therapeutic Targets

Glaucoma is the second leading cause of blindness worldwide, affecting ~80 million people by 2020 (1, 2). The condition is characterized by a progressive loss of retinal ganglion cells (RGCs) and their axons accompanied by visual field loss. The underlying pathophysiology of glaucoma remains elusive. Glaucoma is recognized as a multifactorial disease, and lowering intraocular pressure (IOP) is the only treatment that has been shown to slow the progression of the condition. However, a significant number of glaucoma patients continue to go blind despite intraocular pressure-lowering treatment (2). Thus, the need for alternative treatment strategies is indisputable. Accumulating evidence suggests that glial cells play a significant role in supporting RGC function and that glial dysfunction may contribute to optic nerve disease. Here, we review recent advances in understanding the role of glial cells in the pathophysiology of glaucoma. A particular focus is on the dynamic and essential interactions between glial cells and RGCs and potential therapeutic approaches to glaucoma by targeting glial cells.

Adaptive responses to neurodegenerative stress in glaucoma

Glaucoma causes loss of vision through degeneration of the retinal ganglion cell (RGC) projection to the brain. The disease is characterized by sensitivity to intraocular pressure (IOP) conveyed at the optic nerve head, through which RGC axons pass unmyelinated to form the optic nerve. From this point, a pathogenic triumvirate comprising inflammatory, oxidative, and metabolic stress influence both proximal structures in the retina and distal structures in the optic projection. This review focuses on metabolic stress and how the optic projection may compensate through novel adaptive mechanisms to protect excitatory signaling to the brain. In the retina and proximal nerve head, the unmyelinated RGC axon segment is energy-inefficient, which leads to increased demand for adenosine-5'-triphosphate (ATP) at the risk of vulnerability to Ca²⁺-related metabolic and oxidative pressure. This vulnerability may underlie the bidirectional nature of progression. However, recent evidence highlights that the optic projection in glaucoma is not passive but rather demonstrates adaptive processes that may push back against neurodegeneration. In the retina, even as synaptic and dendritic pruning ensues, early progression involves enhanced excitability of RGCs. Enhancement involves depolarization of the resting membrane potential and increased response to light, independent of RGC morphological type. This response is axogenic, arising from increased levels and translocation of voltage-gated sodium channels (NaV) in the unmyelinated segment. During this same early period, large-scale networks of gap-junction coupled astrocytes redistribute metabolic resources to the optic projection stressed by elevated IOP to slow loss of axon function. This redistribution may reflect more local remodeling, as astrocyte processes respond to focal metabolic duress by boosting glycogen turnover in response to axonal activity in an effort to promote survival of the healthiest axons. Both enhanced excitability and metabolic redistribution are transient, indicating that the same adaptive mechanisms that apparently serve to slow progression ultimately may be too expensive for the system to sustain over longer periods.

High Contrast Allows the Retina to Compute More Than Just Contrast

The goal of sensory processing is to represent the environment of an animal. All sensory systems share a similar constraint: they need to encode a wide range of stimulus magnitudes within their narrow neuronal response range. The most efficient way, exploited by even the simplest nervous systems, is to encode relative changes in stimulus magnitude rather than the absolute magnitudes. For instance, the retina encodes contrast, which are the variations of light intensity occurring in time and in space. From this perspective, it is easy to understand why the bright plumage of a moving bird gains a lot of attention, while an octopus remains motionless and mimics its surroundings for concealment. Stronger contrasts simply cause stronger visual signals. However, the gains in retinal performance associated with higher contrast are far more than what can be attributed to just a trivial linear increase in signal strength. Here we discuss how this improvement in performance is reflected throughout different parts of the neural circuitry, within its neural code and how high contrast activates many non-linear mechanisms to unlock several sophisticated retinal computations that are virtually impossible in low contrast conditions.

Dopamine Transporter Localization in Medial Forebrain Bundle Axons Indicates Its Long-Range Transport Primarily by Membrane Diffusion with a Limited Contribution of Vesicular Traffic on Retromer-Positive Compartments

Dopamine transporter (DAT) controls dopamine neurotransmission by clearing synaptically released dopamine. However, trafficking itineraries of DAT, which determine its cell-surface concentration near synapses, are poorly characterized. It is especially unknown how DAT is transported between spatially distant midbrain somatodendritic and striatal axonal compartments. To examine this "long-range" trafficking, the localization and membrane diffusion of HA-epitope tagged DAT in the medial forebrain bundle (MFB) of a knock-in mouse (both sexes) were analyzed using confocal, super-resolution and EM in intact brain and acute brain slices. HA-DAT was abundant in the plasma membrane of MFB axons, similar to the striatum, although the intracellular fraction of HA-DAT in MFB was more substantial. Intracellular HA-DAT colocalized with VPS35, a subunit of the retromer complex mediating recycling from endosomes, in a subset of axons. Late endosomes, lysosomes, and endoplasmic reticulum were abundant in the soma but minimally present in MFB axons, suggesting that biosynthesis and lysosomal degradation of DAT are confined to soma. Together, the data suggest that membrane diffusion is the main mode of long-range DAT transport through MFB, although the contribution of vesicular traffic can be significant in a population of MFB axons. Based on HA-DAT diffusion rates, plasma membrane DAT in MFB axons turns over with a halftime of ∼20 d, which explains the extremely slow turnover of DAT protein in the brain. Unexpectedly, the mean diameter of DAT-labeled MFB axons was observed to be twice larger than reported for striatum. The implications of this finding for dopamine neuron physiology are discussed.SIGNIFICANCE STATEMENT The dopamine transporter (DAT) is a key regulator of dopamine neurotransmission and a target of abused psychostimulants. In the present study, we examined, for the first time, mechanisms of the long-range traffic of DAT in intact brain and acute brain slices from the knock-in mouse expressing epitope-tagged DAT. Using a combination of confocal, super-resolution and EM, we defined DAT localization and its membrane diffusion parameters in medial forebrain bundle axonal tracts connecting midbrain somatodendritic and striatal axonal compartments of dopaminergic neurons. In contrast to the widely accepted model of long-range axonal transport, our studies suggest that DAT traffics between midbrain and striatum, mainly by lateral diffusion in the plasma membrane with only a limited contribution of vesicular transport in recycling endosomes.

Increased Susceptibility to Glaucomatous Damage in Microfibril Deficient Mice

Purpose

To test whether mice with microfibril deficiency due to the Tsk mutation of fibrillin-1 (Fbn1Tsk/+) have increased susceptibility to pressure-induced retinal ganglion cell (RGC) degeneration.

Methods

Intraocular pressure (IOP) elevation was induced in Fbn1Tsk/+ and wild type (wt) mice by injecting microbeads into the anterior chamber. Mice were then followed up for four months, with IOP measurements every three to six days. Retinas were stained for Brn3a to determine RGC number. Optic nerve cross-sections were stained with p-phenylene diamine to determine nerve area, axon number, and caliber and thickness of the pia mater.

Results

Microbead injection induced significant IOP elevation that was significantly less for Fbn1Tsk/+ mice compared with wt. The optic nerves and optic nerve axons were larger, and the elastic fiber-rich pia mater was thinner in Fbn1Tsk/+ mice. Microbead injection resulted in reduced optic nerve size, thicker pia mater, and a slight decrease in axon size. Fbn1Tsk/+ mice had significantly greater loss of RGCs and optic nerve axons compared with wt (14.8% vs. 5.8%, P = 0.002, and 17.0% vs. 7.5%, P = 0.002, respectively).

Conclusions

Fbn1Tsk/+mice had altered optic nerve structure as indicated by larger optic nerves, larger optic nerve axons and thinner pia mater, consistent with our previous findings. Despite lower IOP elevation, Fbn1Tsk/+mice had greater loss of RGCs and optic nerve axons, suggesting increased susceptibility to IOP-induced optic nerve degeneration in microfibril-deficient mice.

The sensitivity of diffusion MRI to microstructural properties and experimental factors

Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic.

Spatio-chromatic information available from different neural layers via Gaussianization

How much visual information about the retinal images can be extracted from the different layers of the visual pathway? This question depends on the complexity of the visual input, the set of transforms applied to this multivariate input, and the noise of the sensors in the considered layer. Separate subsystems (e.g. opponent channels, spatial filters, nonlinearities of the texture sensors) have been suggested to be organized for optimal information transmission. However, the efficiency of these different layers has not been measured when they operate together on colorimetrically calibrated natural images and using multivariate information-theoretic units over the joint spatio-chromatic array of responses.In this work, we present a statistical tool to address this question in an appropriate (multivariate) way. Specifically, we propose an empirical estimate of the information transmitted by the system based on a recent Gaussianization technique. The total correlation measured using the proposed estimator is consistent with predictions based on the analytical Jacobian of a standard spatio-chromatic model of the retina-cortex pathway. If the noise at certain representation is proportional to the dynamic range of the response, and one assumes sensors of equivalent noise level, then transmitted information shows the following trends: (1) progressively deeper representations are better in terms of the amount of captured information, (2) the transmitted information up to the cortical representation follows the probability of natural scenes over the chromatic and achromatic dimensions of the stimulus space, (3) the contribution of spatial transforms to capture visual information is substantially greater than the contribution of chromatic transforms, and (4) nonlinearities of the responses contribute substantially to the transmitted information but less than the linear transforms.

Myelination increases chemical energy support to the axon without modifying the basic physicochemical mechanism of nerve conduction

The existence of different conductive patterns in unmyelinated and myelinated axons is uncertain. It seems that considering exclusively physical electrical phenomena may be an oversimplification. A novel interpretation of the mechanism of nerve conduction in myelinated nerves is proposed, to explain how the basic mechanism of nerve conduction has been adapted to myelinated conditions. The neurilemma would bear the voltage-gated channels and Na⁺/K⁺-ATPase in both unmyelinated and myelinated conditions, the only difference being the sheath wrapping it. The dramatic increase in conduction speed of the myelinated axons would essentially depend on an increment in ATP availability within the internode: myelin would be an aerobic ATP supplier to the axoplasm, through connexons. In fact, neurons rely on aerobic metabolism and on trophic support from oligodendrocytes, that do not normally duplicate after infancy in humans. Such comprehensive framework of nerve impulse propagation in axons may shed new light on the pathophysiology of nervous system disease in humans, seemingly strictly dependent on the viability of the pre-existing oligodendrocyte.

Redistribution of metabolic resources through astrocyte networks mitigates neurodegenerative stress

In the central nervous system, glycogen-derived bioenergetic resources in astrocytes help promote tissue survival in response to focal neuronal stress. However, our understanding of the extent to which these resources are mobilized and utilized during neurodegeneration, especially in nearby regions that are not actively degenerating, remains incomplete. Here we modeled neurodegeneration in glaucoma, the world's leading cause of irreversible blindness, and measured how metabolites mobilize through astrocyte gap junctions composed of connexin 43 (Cx43). We elevated intraocular pressure in one eye and determined how astrocyte-derived metabolites in the contralateral optic projection responded. Remarkably, astrocyte networks expand and redistribute metabolites along distances even 10 mm in length, donating resources from the unstressed to the stressed projection in response to intraocular pressure elevation. While resource donation improves axon function and visual acuity in the directly stressed region, it renders the donating tissue susceptible to bioenergetic, structural, and physiological degradation. Intriguingly, when both projections are stressed in a WT animal, axon function and visual acuity equilibrate between the two projections even when each projection is stressed for a different length of time. This equilibration does not occur when Cx43 is not present. Thus, Cx43-mediated astrocyte metabolic networks serve as an endogenous mechanism used to mitigate bioenergetic stress and distribute the impact of neurodegenerative disease processes. Redistribution ultimately renders the donating optic nerve vulnerable to further metabolic stress, which could explain why local neurodegeneration does not remain confined, but eventually impacts healthy regions of the brain more broadly.

Retinal energy metabolism in health and glaucoma

Energy metabolism refers to the processes by which life transfers energy to do cellular work. The retina's relatively large energy demands make it vulnerable to energy insufficiency. In addition, evolutionary pressures to optimize human vision have been traded against retinal ganglion cell bioenergetic fragility. Details of the metabolic profiles of the different retinal cells remain poorly understood and are challenging to resolve. Detailed immunohistochemical mapping of the energy pathway enzymes and substrate transporters has provided some insights and highlighted interspecies differences. The different spatial metabolic patterns between the vascular and avascular retinas can account for some inconsistent data in the literature. There is a consilience of evidence that at least some individuals with glaucoma have impaired RGC energy metabolism, either due to impaired nutrient supply or intrinsic metabolic perturbations. Bioenergetic-based therapy for glaucoma has a compelling pathophysiological foundation and is supported by recent successes in animal models. Recent demonstrations of visual and electrophysiological neurorecovery in humans with glaucoma is highly encouraging and motivates longer duration trials investigating bioenergetic neuroprotection.

A time-dependent diffusion MRI signature of axon caliber variations and beading

MRI provides a unique non-invasive window into the brain, yet is limited to millimeter resolution, orders of magnitude coarser than cell dimensions. Here, we show that diffusion MRI is sensitive to the micrometer-scale variations in axon caliber or pathological beading, by identifying a signature power-law diffusion time-dependence of the along-fiber diffusion coefficient. We observe this signature in human brain white matter and identify its origins by Monte Carlo simulations in realistic substrates from 3-dimensional electron microscopy of mouse corpus callosum. Simulations reveal that the time-dependence originates from axon caliber variation, rather than from mitochondria or axonal undulations. We report a decreased amplitude of time-dependence in multiple sclerosis lesions, illustrating the potential sensitivity of our method to axonal beading in a plethora of neurodegenerative disorders. This specificity to microstructure offers an exciting possibility of bridging across scales to image cellular-level pathology with a clinically feasible MRI technique.

Cytoskeletal organization of axons in vertebrates and invertebrates

The maintenance of axons for the lifetime of an organism requires an axonal cytoskeleton that is robust but also flexible to adapt to mechanical challenges and to support plastic changes of axon morphology. Furthermore, cytoskeletal organization has to adapt to axons of dramatically different dimensions, and to their compartment-specific requirements in the axon initial segment, in the axon shaft, at synapses or in growth cones. To understand how the cytoskeleton caters to these different demands, this review summarizes five decades of electron microscopic studies. It focuses on the organization of microtubules and neurofilaments in axon shafts in both vertebrate and invertebrate neurons, as well as the axon initial segments of vertebrate motor- and interneurons. Findings from these ultrastructural studies are being interpreted here on the basis of our contemporary molecular understanding. They strongly suggest that axon architecture in animals as diverse as arthropods and vertebrates is dependent on loosely cross-linked bundles of microtubules running all along axons, with only minor roles played by neurofilaments.

Time-dependent diffusion in undulating thin fibers: Impact on axon diameter estimation

Diffusion MRI may enable non-invasive mapping of axonal microstructure. Most approaches infer axon diameters from effects of time-dependent diffusion on the diffusion-weighted MR signal by modeling axons as straight cylinders. Axons do not, however, propagate in straight trajectories, and so far the impact of the axonal trajectory on diameter estimation has been insufficiently investigated. Here, we employ a toy model of axons, which we refer to as the undulating thin fiber model, to analyze the impact of undulating trajectories on the time dependence of diffusion. We study time-dependent diffusion in the frequency domain and characterize the diffusion spectrum by its height, width, and low-frequency behavior (power law exponent). Results show that microscopic orientation dispersion of the thin fibers is the main parameter that determines the characteristics of the diffusion spectra. At lower frequencies (longer diffusion times), straight cylinders and undulating thin fibers can have virtually identical spectra. If the straight-cylinder assumption is used to interpret data from undulating thin axons, the diameter is overestimated by an amount proportional to the undulation amplitude and microscopic orientation dispersion of the fibers. At higher frequencies (shorter diffusion times), spectra from cylinders and undulating thin fibers differ. The low-frequency behavior of the spectra from the undulating thin fibers may also differ from that of cylinders, because the power law exponent of undulating fibers can reach values below 2 for experimentally relevant frequency ranges. In conclusion, we argue that the non-straight nature of axonal trajectories should not be overlooked when analyzing and interpreting diffusion MRI data.

Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma

Glaucoma is a neurodegenerative disease characterised by progressive damage to the retinal ganglion cells (RGCs), the output neurons of the retina. RGCs are a heterogenous class of retinal neurons which can be classified into multiple types based on morphological, functional and genetic characteristics. This review examines the body of evidence supporting type-specific vulnerability of RGCs in glaucoma and explores potential mechanisms by which this might come about. Studies of donor tissue from glaucoma patients have generally noted greater vulnerability of larger RGC types. Models of glaucoma induced in primates, cats and mice also show selective effects on RGC types - particularly OFF RGCs. Several mechanisms may contribute to type-specific vulnerability, including differences in the expression of calcium-permeable receptors (for example pannexin-1, P2X7, AMPA and transient receptor potential vanilloid receptors), the relative proximity of RGCs and their dendrites to blood supply in the inner plexiform layer, as well as differing metabolic requirements of RGC types. Such differences may make certain RGCs more sensitive to intraocular pressure elevation and its associated biomechanical and vascular stress. A greater understanding of selective RGC vulnerability and its underlying causes will likely reveal a rich area of investigation for potential treatment targets.

Graded Coexpression of Ion Channel, Neurofilament, and Synaptic Genes in Fast-Spiking Vestibular Nucleus Neurons

Computations that require speed and temporal precision are implemented throughout the nervous system by neurons capable of firing at very high rates, rapidly encoding and transmitting a rich amount of information, but with substantial metabolic and physical costs. For economical fast spiking and high throughput information processing, neurons need to optimize multiple biophysical properties in parallel, but the mechanisms of this coordination remain unknown. We hypothesized that coordinated gene expression may underlie the coordinated tuning of the biophysical properties required for rapid firing and signal transmission. Taking advantage of the diversity of fast-spiking cell types in the medial vestibular nucleus of mice of both sexes, we examined the relationship between gene expression, ionic currents, and neuronal firing capacity. Across excitatory and inhibitory cell types, genes encoding voltage-gated ion channels responsible for depolarizing and repolarizing the action potential were tightly coexpressed, and their absolute expression levels increased with maximal firing rate. Remarkably, this coordinated gene expression extended to neurofilaments and specific presynaptic molecules, providing a mechanism for coregulating axon caliber and transmitter release to match firing capacity. These findings suggest the presence of a module of genes, which is coexpressed in a graded manner and jointly tunes multiple biophysical properties for economical differentiation of firing capacity. The graded tuning of fast-spiking capacity by the absolute expression levels of specific ion channels provides a counterexample to the widely held assumption that cell-type-specific firing patterns can be achieved via a vast combination of different ion channels.SIGNIFICANCE STATEMENT Although essential roles of fast-spiking neurons in various neural circuits have been widely recognized, it remains unclear how neurons efficiently coordinate the multiple biophysical properties required to maintain high rates of action potential firing and transmitter release. Taking advantage of diverse fast-firing capacities among medial vestibular nucleus neurons of mice, we identify a group of ion channel, synaptic, and structural genes that exhibit mutually correlated expression levels, which covary with firing capacity. Coexpression of this fast-spiking gene module may be a basic strategy for neurons to efficiently and coordinately tune the speed of action potential generation and propagation and transmitter release at presynaptic terminals.

Axonal Computations

Axons functionally link the somato-dendritic compartment to synaptic terminals. Structurally and functionally diverse, they accomplish a central role in determining the delays and reliability with which neuronal ensembles communicate. By combining their active and passive biophysical properties, they ensure a plethora of physiological computations. In this review, we revisit the biophysics of generation and propagation of electrical signals in the axon and their dynamics. We further place the computational abilities of axons in the context of intracellular and intercellular coupling. We discuss how, by means of sophisticated biophysical mechanisms, axons expand the repertoire of axonal computation, and thereby, of neural computation.

Reconciling Color Vision Models With Midget Ganglion Cell Receptive Fields

Midget retinal ganglion cells (RGCs) make up the majority of foveal RGCs in the primate retina. The receptive fields of midget RGCs exhibit both spectral and spatial opponency and are implicated in both color and achromatic form vision, yet the exact mechanisms linking their responses to visual perception remain unclear. Efforts to develop color vision models that accurately predict all the features of human color and form vision based on midget RGCs provide a case study connecting experimental and theoretical neuroscience, drawing on diverse research areas such as anatomy, physiology, psychophysics, and computer vision. Recent technological advances have allowed researchers to test some predictions of color vision models in new and precise ways, producing results that challenge traditional views. Here, we review the progress in developing models of color-coding receptive fields that are consistent with human psychophysics, the biology of the primate visual system and the response properties of midget RGCs.

Energetic substrate availability regulates synchronous activity in an excitatory neural network

Neural networks are required to meet significant metabolic demands associated with performing sophisticated computational tasks in the brain. The necessity for efficient transmission of information imposes stringent constraints on the metabolic pathways that can be used for energy generation at the synapse, and thus low availability of energetic substrates can reduce the efficacy of synaptic function. Here we study the effects of energetic substrate availability on global neural network behavior and find that glucose alone can sustain excitatory neurotransmission required to generate high-frequency synchronous bursting that emerges in culture. In contrast, obligatory oxidative energetic substrates such as lactate and pyruvate are unable to substitute for glucose, indicating that processes involving glucose metabolism form the primary energy-generating pathways supporting coordinated network activity. Our experimental results are discussed in the context of the role that metabolism plays in supporting the performance of individual synapses, including the relative contributions from postsynaptic responses, astrocytes, and presynaptic vesicle cycling. We propose a simple computational model for our excitatory cultures that accurately captures the inability of metabolically compromised synapses to sustain synchronous bursting when extracellular glucose is depleted.