Faculty Bibliography

Spreading depolarization (SD) is a slow-moving wave of neuronal depolarization accompanied by a breakdown of ion concentration homeostasis, followed by long periods of neuronal silence (spreading depression), and associated with several neurological conditions. We developed multiscale (ions to tissue slice) computer models of SD in brain slices using the NEURON simulator: 36,000 neurons (2 voltage-gated ion channels; 3 leak channels; 3 ion exchangers/pumps) in the extracellular space (ECS) of a slice (1 mm sides, varying thickness) with ion (K⁺, Cl^-, Na⁺) and O₂ diffusion and equilibration with a surrounding bath. Glia and neurons cleared K⁺ from the ECS via Na⁺/K⁺ pumps. SD propagated through the slices at realistic speeds of 2-4 mm/min, which increased by as much as 50% in models incorporating the effects of hypoxia or propionate. In both cases, the speedup was mediated principally by ECS shrinkage. Our model allows us to make testable predictions, including: 1. SD can be inhibited by enlarging ECS volume; 2. SD velocity will be greater in areas with greater neuronal density, total neuronal volume, or larger/more dendrites; 3. SD is all-or-none: initiating K⁺ bolus properties have little impact on SD speed; 4. Slice thickness influences SD due to relative hypoxia in the slice core, exacerbated by SD in a pathological cycle; 5. SD and high neuronal spike rates will be observed in the core of the slice. Cells in the periphery of the slice near an oxygenated bath will resist SD.SignificanceSpreading depolarization (SD) is a slow moving wave of electrical and ionic imbalances in brain tissue and is a hallmark of several neurological disorders. We developed a multiscale computer model of brain slices with realistic neuronal densities, ions, and oxygenation. Our model shows that SD is exacerbated by and causes hypoxia, resulting in strong SD dependence on slice thickness. Our model also predicts that the velocity of SD propagation is not dependent on its initiation, but instead on tissue properties, including the amount of extracellular space and the total area of neuronal membrane, suggesting faster SD following ischemic stroke or traumatic brain injury.

Spinal motoneurons are a remarkably diverse class of neurons responsible for facilitating a broad range of motor behaviors and autonomic functions. Studies of motoneuron differentiation have provided fundamental insights into the developmental mechanisms of neuronal diversification, and have illuminated principles of neural fate specification that operate throughout the central nervous system. Because of their relative anatomical simplicity and accessibility, motoneurons have provided a tractable model system to address multiple facets of neural development, including early patterning, neuronal migration, axon guidance, and synaptic specificity. Beyond their roles in providing direct communication between central circuits and muscle, recent studies have revealed that motoneuron subtype-specific programs also play important roles in determining the central connectivity and function of motor circuits. Cross-species comparative analyses have provided novel insights into how evolutionary changes in subtype specification programs may have contributed to adaptive changes in locomotor behaviors. This chapter focusses on the gene regulatory networks governing spinal motoneuron specification, and how studies of spinal motoneurons have informed our understanding of the basic mechanisms of neuronal specification and spinal circuit assembly.

As the use of Radio Frequency (RF) technologies increases, the impact of RF radiation on neurological function continues to receive attention. Whether RF radiation can modulate ongoing neuronal activity by non-thermal mechanisms has been debated for decades. However, the interactions between radiated energy and metal-based neural probes during experimentation could impact neural activity, making interpretation of the results difficult. To address this problem, we modified a miniature 1-photon Ca²⁺ imaging device to record interference-free neural activity and compared the results to those acquired using metal-containing silicon probes. We monitored the neuronal activity of awake rodent-brains under RF energy exposure (at 950 MHz) and in sham control paradigms. Spiking activity was reliably affected by RF energy in metal containing systems. However, we did not observe neuronal responses using metal-free optical recordings at induced local electric field strengths up to 230 V/m. Our results suggest that RF exposure higher than levels that are allowed by regulatory limits in real-life scenarios do not affect neuronal activity.

The article considers the problem of dividing the encephalography data into two time series, that generated by the brain and that generated by other electrical sources located in the human head. The magnetic encephalograms and magnetic resonance images of the head were recorded in the Center for Neuromagnetism at NYU Grossman School of Medicine. Data obtained at McGill University and Montreal University were also used. Recordings were made in a magnetically shielded room and the gradiometers were designed to suppress external noise, making it possible to eliminate them from the data analysis. Magnetic encephalograms were analyzed by the method of functional tomography, based on the Fourier transform and on the solution of inverse problem for all frequencies. In this method, one spatial position is assigned to each frequency component. Magnetic resonance images of the head were evaluated to annotate the space to be included in the analysis. The included space was divided into two parts: «brain» and «non-brain». The frequency components were classified by the feature of their inclusion in one or the other part. The set of frequencies, designated as «brain», represented the partial spectrum of the brain signal, while the set of frequencies designated as «non-brain», represented the partial spectrum of the physiological noise produced by the head. Both partial spectra shared the same frequency band. From the partial spectra, a time series of the «brain» area signal and «non-brain» area head noise were reconstructed. Summary spectral power of the signal was found to be ten times greater than the noise. The proposed method makes it possible to analyze in detail both the signal and the noise components of the encephalogram and to filter the magnetic encephalogram.

Recent advances in magnetic resonance imaging are enabling the efficient creation of high-dimensional, multiparametric images, containing a wealth of potential information about the structure and function of many organs, including the cardiovascular system. However, the sizes of these rich data sets are so large that they are outstripping our ability to adequately visualize and analyze them, thus limiting their clinical impact. While there are some intrinsic limitations of human perception and of conventional display devices which hamper our ability to effectively use these data, newer computational methods for handling the data may aid our ability to extract and visualize the salient components of these high-dimensional data sets.

Myelin is classically known for its role in facilitating nerve conduction. However, recent work casts myelin as a key player in both proper neuronal circuit development and function. With this expanding role comes a demand for new approaches to characterize and perturb myelin in the context of tractable neural circuits as they mature. Here we argue that the simplicity, strong conservation, and clinical relevance of the vestibular system offer a way forward. Further, the tractability of the larval zebrafish affords a uniquely powerful means to test open hypotheses of myelin's role in normal development and disordered vestibular circuits. We end by identifying key open questions in myelin neurobiology that the zebrafish vestibular system is particularly well-suited to address.

The vast majority of extant vertebrate diversity lies within the bony and cartilaginous fish lineages of jawed vertebrates. There is a long history of elegant experimental investigation of development in bony vertebrate model systems (e.g., mouse, chick, frog and zebrafish). However, studies on the development of cartilaginous fishes (sharks, skates and rays) have, until recently, been largely descriptive, owing to the challenges of embryonic manipulation and culture in this group. This, in turn, has hindered understanding of the evolution of developmental mechanisms within cartilaginous fishes and, more broadly, within jawed vertebrates. The little skate (Leucoraja erinacea) is an oviparous cartilaginous fish and has emerged as a powerful and experimentally tractable developmental model system. Here, we discuss the collection, husbandry and management of little skate brood stock and eggs, and we present an overview of key stages of skate embryonic development. We also discuss methods for the manipulation and culture of skate embryos and illustrate the range of tools and approaches available for studying this system. Finally, we summarize a selection of recent studies on skate development that highlight the utility of this system for inferring ancestral anatomical and developmental conditions for jawed vertebrates, as well as unique aspects of cartilaginous fish biology.

Despite major anatomical differences with other mammalian sensory systems, olfaction shares with those systems a modulation by sleep/wake states. Sleep modulates odor sensitivity and serves as an important regulator of both perceptual and associative odor memory. In addition, however, olfaction also has an important modulatory impact on sleep. Odors can affect the latency to sleep onset, as well as the quality and duration of sleep. Olfactory modulation of sleep may be mediated by direct synaptic interaction between the olfactory system and sleep control nuclei, and/or indirectly through odor modulation of arousal and respiration. This reciprocal interaction between sleep and olfaction presents novel opportunities for sleep related modulation of memory and perception, as well as development of non-pharmacological olfactory treatments of simple sleep disorders.

The neurophysiological footprint of brain activity after cardiac arrest and during near-death experience (NDE) is not well understood. Although a hypoactive state of brain activity has been assumed, experimental animal studies have shown increased activity after cardiac arrest, particularly in the gamma-band, resulting from hypercapnia prior to and cessation of cerebral blood flow after cardiac arrest. No study has yet investigated this matter in humans. Here, we present continuous electroencephalography (EEG) recording from a dying human brain, obtained from an 87-year-old patient undergoing cardiac arrest after traumatic subdural hematoma. An increase of absolute power in gamma activity in the narrow and broad bands and a decrease in theta power is seen after suppression of bilateral hemispheric responses. After cardiac arrest, delta, beta, alpha and gamma power were decreased but a higher percentage of relative gamma power was observed when compared to the interictal interval. Cross-frequency coupling revealed modulation of left-hemispheric gamma activity by alpha and theta rhythms across all windows, even after cessation of cerebral blood flow. The strongest coupling is observed for narrow- and broad-band gamma activity by the alpha waves during left-sided suppression and after cardiac arrest. Albeit the influence of neuronal injury and swelling, our data provide the first evidence from the dying human brain in a non-experimental, real-life acute care clinical setting and advocate that the human brain may possess the capability to generate coordinated activity during the near-death period.