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At least 235 records · Page 13

Biphasic response of human iPSC-derived neural network activity following exposure to a sarin-surrogate nerve agent

Organophosphorus nerve agents (OPNA) are hazardous environmental exposures to the civilian population and have been historically weaponized as chemical warfare agents (CWA). OPNA exposure can lead to several neurological, sensory, and motor symptoms that can manifest into chronic neurological illnesses later in life. There is still a large need for technological advancement to better understand changes in brain function following OPNA exposure. The human-relevant in vitro multi-electrode array (MEA) system, which combines the MEA technology with human stem cell technology, has the potential to monitor the acute, sub-chronic, and chronic consequences of OPNA exposure on brain activity. However, the application of this system to assess OPNA hazards and risks to human brain function remains to be investigated. In a concentration-response study, we have employed a human-relevant MEA system to monitor and detect changes in the electrical activity of engineered neural networks to increasing concentrations of the sarin surrogate 4-nitrophenyl isopropyl methylphosphonate (NIMP). We report a biphasic response in the spiking (but not bursting) activity of neurons exposed to low (i.e., 0.4 and 4 μM) versus high concentrations (i.e., 40 and 100 μM) of NIMP, which was monitored during the exposure period and up to 6 days post-exposure. Regardless of the NIMP concentration, at a network level, communication or coordination of neuronal activity decreased as early as 60 min and persisted at 24 h of NIMP exposure. Once NIMP was removed, coordinated activity was no different than control (0 μM of NIMP). Interestingly, only in the high concentration of NIMP did coordination of activity at a network level begin to decrease again at 2 days post-exposure and persisted on day 6 post-exposure. Notably, cell viability was not affected during or after NIMP exposure. Also, while the catalytic activity of AChE decreased during NIMP exposure, its activity recovered once NIMP was removed. Gene expression analysis suggests that human iPSC-derived neurons and primary human astrocytes resulted in altered genes related to the cell’s interaction with the extracellular environment, its intracellular calcium signaling pathways, and inflammation, which could have contributed to how neurons communicated at a network level.

59 BASIC BIOLOGICAL SCIENCES↗

Sensory processing in the vestibular nuclei during active head movements

Many secondary vestibular neurons are sensitive to head on trunk rotation during reflex-induced and voluntary head movements. During passive whole body rotation the interaction of head on trunk signals related to the vestibulo-collic reflex with vestibular signals increases the rotational gain of many secondary vestibular neurons, including many that project to the spinal cord. In some units, the sensitivity to head on trunk and vestibular input is matched and the resulting interaction produces an output that is related to the trunk velocity in space. In other units the head on trunk inputs are stronger and the resulting interaction produces an output that is larger during the reflex. During voluntary head movements, inputs related to head on trunk movement combine destructively with vestibular signals, and often cancel the sensory reafferent consequences of self-generated movements. Cancellation of sensory vestibular signals was observed in all of the antidromically identified secondary vestibulospinal units, even though many of these units were not significantly affected by reflexive head on trunk movements. The results imply that the inputs to vestibular neurons related to head on trunk rotation during reflexive and voluntary movements arise from different sources. We suggest that the relative strength of reflexive head on trunk input to different vestibular neurons might reflect the different functional roles they have in controlling the posture of the neck and body.

Non-NASA Center↗

A dopaminergic projection to the rat mammillary nuclei demonstrated by retrograde transport of wheat germ agglutinin-horseradish peroxidase and tyrosine hydroxylase immunohistochemistry

The presence and distribution of dopaminergic neurons and terminals in the hypothalamus of the rat were studied by tyrosine hydroxylase (TH) immunohistochemistry. Strongly labelled TH-immunoreactive neurons were seen in the dorsomedial hypothalamic nucleus, periventricular region, zona incerta, arcuate nucleus, and supramammillary nucleus. A few TH-positive neurons were also identified in the dorsal and ventral premammillary nucleus, as well as the lateral hypothalamic area. TH-immunoreactive fibres and terminals were unevenly distributed in the mammillary nuclei; small, weakly labelled terminals were scattered in the medial mammillary nucleus, while large, strongly labelled, varicose terminals were densely concentrated in the internal part of the lateral mammillary nucleus. A few dorsoventrally oriented TH-positive axon bundles were also identified in the lateral mammillary nucleus. A dopaminergic projection to the mammillary nuclei from the supramammillary nucleus and lateral hypothalamic area was identified by double labelling with retrograde transport of wheat germ agglutinin-horseradish peroxidase and TH-immunohistochemistry. The lateral mammillary nucleus receives a weak dopaminergic projection from the medial, and stronger projections from the lateral, caudal supramammillary nucleus. The double-labelled neurons in the lateral supramammillary nucleus appear to encapsulate the caudal end of the mammillary nuclei. The medial mammillary nucleus receives a very light dopaminergic projection from the caudal lateral hypothalamic area. These results suggest that the supramammillary nucleus is the principal source of the dopaminergic input to the mammillary nuclei, establishing a local TH-pathway in the mammillary complex. The supramammillary cell groups are able to modulate the limbic system through its dopaminergic input to the mammillary nuclei as well as through its extensive dopaminergic projection to the lateral septal nucleus.

Non-NASA Center↗

A single-cell atlas of the bobtail squid visual and nervous system highlights molecular principles of convergent evolution

Abstract The cephalopod and vertebrate visual systems are a textbook example of convergent evolution with unknown molecular underpinnings. Here we characterize 98,537 single-cell transcriptomes in the bobtail squidEuprymna berryito understand how the cephalopod retina and optic lobes relate to the vertebrate retina. We confirm the overall relative simplicity of the cephalopod retina but identify two related photoreceptor cell subtypes expressing distinct r-opsins. By contrast, the adult optic lobe contains a diverse repertoire of neuronal and glial cell types, with a predominance of dopaminergic neurons. We show that cephalopod-specific gene duplicates probably contributed to this cell type diversification. Comparing neuronal cell population in the optic lobes of hatchlings and adults, we reveal a switch towards dopaminergic neurotransmitter usage with age, indicative of a maturation process. We further identify an FMRF-amide-based retrograde signal from the optic lobe towards the retina that supports the functional analogy of the cephalopod optic lobe cortex and the vertebrate inner retina in visual signal processing from a molecular standpoint. Finally, comparative analyses with vertebrate and arthropod cells suggest a scenario in which two photoreceptor types and two neuronal populations may have already been present in the eye of the bilaterian ancestor.

Environmental Sciences & Ecology↗

The chromatin remodeler ADNP regulates neurodevelopmental disorder risk genes and neocortical neurogenesis

Although chromatin remodelers are among the most important risk genes associated with neurodevelopmental disorders (NDDs), the roles of these complexes during brain development are in many cases unclear. Here, we focused on the recently discovered ChAHP chromatin remodeling complex. The zinc finger and homeodomain transcription factor ADNP is a core subunit of this complex, and de novoADNPmutations lead to intellectual disability and autism spectrum disorder. However, germlineAdnpknockout mice were previously shown to exhibit early embryonic lethality, obscuring subsequent roles for the ChAHP complex in neurogenesis. To circumvent this early developmental arrest, we generated a conditionalAdnpmutant allele. Using single-cell transcriptomics, cut&run-seq, and histological approaches, we show that during neocortical development, Adnp orchestrates the production of late-born, upper-layer neurons through a two-step process. First, Adnp is required to sustain progenitor proliferation specifically during the developmental window for upper-layer cortical neurogenesis. Accordingly, we found that Adnp recruits the ChAHP subunit Chd4 to genes associated with progenitor proliferation. Second, in postmitotic differentiated neurons, we define a network of risk genes linked to NDDs that are regulated by Adnp and Chd4. Taken together, these data demonstrate that ChAHP is critical for driving the expansion of upper-layer cortical neurons and for regulating neuronal gene expression programs, suggesting that these processes may potentially contribute to NDD etiology.

Science & Technology - Other Topics↗

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗

Accuracy optimized neural networks do not effectively model optic flow tuning in brain area MSTd

Accuracy-optimized convolutional neural networks (CNNs) have emerged as highly effective models at predicting neural responses in brain areas along the primate ventral stream, but it is largely unknown whether they effectively model neurons in the complementary primate dorsal stream. We explored how well CNNs model the optic flow tuning properties of neurons in dorsal area MSTd and we compared our results with the Non-Negative Matrix Factorization (NNMF) model, which successfully models many tuning properties of MSTd neurons. To better understand the role of computational properties in the NNMF model that give rise to optic flow tuning that resembles that of MSTd neurons, we created additional CNN model variants that implement key NNMF constraints – non-negative weights and sparse coding of optic flow. While the CNNs and NNMF models both accurately estimate the observer's self-motion from purely translational or rotational optic flow, NNMF and the CNNs with nonnegative weights yield substantially less accurate estimates than the other CNNs when tested on more complex optic flow that combines observer translation and rotation. Despite its poor accuracy, NNMF gives rise to tuning properties that align more closely with those observed in primate MSTd than any of the accuracy-optimized CNNs. This work offers a step toward a deeper understanding of the computational properties and constraints that describe the optic flow tuning of primate area MSTd.

60 APPLIED LIFE SCIENCES↗

Anatomy of the Vestibulo-automatic Outflow to the Gut

Motion sickness can be induced by vestibular effects on the sympathetic portion of the autonomic nervous system. However, the pathways linking the vestibular and autonomic pathways are unknown. As a first step in this analysis, the locations of preganglionic sympathetic neurons (PSN) and dorsal root afferent ganglionic neurons (DRG) which supply sympathetic innervation to major portions of the gastrointestinal tract in rabbits were identified. The objective of a second series of experiments is to determine which of the brainstem nuclei project to the autonomic regions of the spinal cord that control gastrointestinal motility. To achieve this goal, a trans-synaptic retrograde tracer (3H-tetanus toxoid) is applied to the greater splanchnic nerve. This method allows the labeling of neurons within the brainstem that project only to the preganglionic synpathetic neurons. One structure that has been strongly implicated in mediating vestibulo-autonomic control is the cerebellum (i.e., nodulus and uvula). The outflow of these lobules to the autonomic regions of the brainstem is mediated by the fastigial nucleus. To determine the precise projections of the fastigial nucleus to the brainstem nuclei involved in emesis, anterograde tracer (3H-leucine) was injected into the fastigial nucleus in a third series of experiments.

Torigoe, Y.↗

Changes in functional metabolism in the rat central nervous system following spaceflight

The neuronal metabolism and soma size of neurons within the paraventricular nucleus (PVN) and the supraoptic nucleus of rats are analyzed. Five male Sprague-Dawley rats were flown on Spacelab 3 for 7 days under a 12:12 light/dark cycle and unlimited food and water, and a control group was kept on the ground under similar conditions. The preparation of the hypothalamus of the rats for microscopic examination using thionin or the cytochrome oxidase (CYOX) technique is described. CYOX activity and soma size within the PVN are evaluated. The effects of water drinking pattern and space flight on CYOX activity and soma size are investigated. The data reveal that the flight rats with normal drinking patterns display a decrease in neuronal metabolism within the vasopressin-containing neurons of the hypothalamus and this metabolic change may reflect fluid shifts caused by microgravity.

Murakami, D. M.↗

Synchronization in neural nets

The paper presents an artificial neural network concept (the Synchronizable Oscillator Networks) where the instants of individual firings in the form of point processes constitute the only form of information transmitted between joining neurons. In the model, neurons fire spontaneously and regularly in the absence of perturbation. When interaction is present, the scheduled firings are advanced or delayed by the firing of neighboring neurons. Networks of such neurons become global oscillators which exhibit multiple synchronizing attractors. From arbitrary initial states, energy minimization learning procedures can make the network converge to oscillatory modes that satisfy multi-dimensional constraints. Such networks can directly represent routing and scheduling problems that consist of ordering sequences of events.

Vidal, Jacques J.↗

Projections from the rostral mesencephalic reticular formation to the spinal cord - An HRP and autoradiographical tracing study in the cat

Horseradish peroxidase was injected, or implanted unilaterally, into various levels of the spinal cord of anesthetized cats, to trace the distribution of projections to the spinal cord, of neurons in Field H of Forel, including the rostral interstitial nucleus of the medial longitudinal fasciculus (riMLF), and the interstitial nucleus of Cajal with adjacent reticular formation (INC-RF). Results indicate that, unlike the neurons projecting to the extraocular muscle motoneurons, the major portion of the spinally projecting neurons are not located in the riMLF or INC proper, but in adjacent areas, i.e., the ventral and lateral parts of the caudal third of the Field H of Forel and in the INC-RF. Neurons in caudal Field H of Forel, project, via the ventral part of the ventral funicululs, to the lateral part of the upper cervical ventral horn.

Holstege, G.↗

Sensitivity of feedforward neural networks to weight errors

An analysis is made of the sensitivity of feedforward layered networks of Adaline elements (threshold logic units) to weight errors. An approximation is derived which expresses the probability of error for an output neuron of a large network (a network with many neurons per layer) as a function of the percentage change in the weights. As would be expected, the probability of error increases with the number of layers in the network and with the percentage change in the weights. The probability of error is essentially independent of the number of weights per neuron and of the number of neurons per layer, as long as these numbers are large (on the order of 100 or more).

Stevenson, Maryhelen↗

Transfer of contrast sensitivity in linear visual networks

Contrast sensitivity is a useful measure of the ability of an observer to distinguish contrast signals from noise. Although usually applied to human observers, contrast sensitivity can also be defined operationally for individual visual neurons. In a model linear neuron consisting of a filter and noise source, this operational measure is a function of filter gain, noise power spectrum, signal duration, and a performance criterion. This definition allows one to relate the sensitivities of linear neurons at different levels in the visual pathway. Mathematical formulas describing these relationships are derived, and the general model is applied to the specific problem of relating the sensitivities of parvocellular LGN neurons and cortical simple cells in the primate.

Watson, Andrew B.↗

Cascaded VLSI Chips Help Neural Network To Learn

Cascading provides 12-bit resolution needed for learning. Using conventional silicon chip fabrication technology of VLSI, fully connected architecture consisting of 32 wide-range, variable gain, sigmoidal neurons along one diagonal and 7-bit resolution, electrically programmable, synaptic 32 x 31 weight matrix implemented on neuron-synapse chip. To increase weight nominally from 7 to 13 bits, synapses on chip individually cascaded with respective synapses on another 32 x 32 matrix chip with 7-bit resolution synapses only (without neurons). Cascade correlation algorithm varies number of layers effectively connected into network; adds hidden layers one at a time during learning process in such way as to optimize overall number of neurons and complexity and configuration of network.

Duong, Tuan A.↗

Arbitrary nonlinearity is sufficient to represent all functions by neural networks - A theorem

It is proved that if we have neurons implementing arbitrary linear functions and a neuron implementing one (arbitrary but smooth) nonlinear function g(x), then for every continuous function f(x sub 1,..., x sub m) of arbitrarily many variables, and for arbitrary e above 0, we can construct a network that consists of g-neurons and linear neurons, and computes f with precision e.

Kreinovich, Vladik YA.↗

Neural Network Burst Pressure Prediction in Graphite/Epoxy Pressure Vessels from Acoustic Emission Amplitude Data

Acoustic emission (AE) data were taken during hydroproof for three sets of ASTM standard 5.75 inch diameter filament wound graphite/epoxy bottles. All three sets of bottles had the same design and were wound from the same graphite fiber; the only difference was in the epoxies used. Two of the epoxies had similar mechanical properties, and because the acoustic properties of materials are a function of their stiffnesses, it was thought that the AE data from the two sets might also be similar; however, this was not the case. Therefore, the three resin types were categorized using dummy variables, which allowed the prediction of burst pressures all three sets of bottles using a single neural network. Three bottles from each set were used to train the network. The resin category, the AE amplitude distribution data taken up to 25 % of the expected burst pressure, and the actual burst pressures were used as inputs. Architecturally, the network consisted of a forty-three neuron input layer (a single categorical variable defining the resin type plus forty-two continuous variables for the AE amplitude frequencies), a fifteen neuron hidden layer for mapping, and a single output neuron for burst pressure prediction. The network trained on all three bottle sets was able to predict burst pressures in the remaining bottles with a worst case error of + 6.59%, slightly greater than the desired goal of + 5%. This larger than desired error was due to poor resolution in the amplitude data for the third bottle set. When the third set of bottles was eliminated from consideration, only four hidden layer neurons were necessary to generate a worst case prediction error of - 3.43%, well within the desired goal.

Hill, Eric v. K.↗

Quantitative Simulations of MST Visual Receptive Field Properties Using a Template Model of Heading Estimation

We previously developed a template model of primate visual self-motion processing that proposes a specific set of projections from MT-like local motion sensors onto output units to estimate heading and relative depth from optic flow. At the time, we showed that that the model output units have emergent properties similar to those of MSTd neurons, although there was little physiological evidence to test the model more directly. We have now systematically examined the properties of the model using stimulus paradigms used by others in recent single-unit studies of MST: 1) 2-D bell-shaped heading tuning. Most MSTd neurons and model output units show bell-shaped heading tuning. Furthermore, we found that most model output units and the finely-sampled example neuron in the Duffy-Wurtz study are well fit by a 2D gaussian (sigma approx. 35deg, r approx. 0.9). The bandwidth of model and real units can explain why Lappe et al. found apparent sigmoidal tuning using a restricted range of stimuli (+/-40deg). 2) Spiral Tuning and Invariance. Graziano et al. found that many MST neurons appear tuned to a specific combination of rotation and expansion (spiral flow) and that this tuning changes little for approx. 10deg shifts in stimulus placement. Simulations of model output units under the same conditions quantitatively replicate this result. We conclude that a template architecture may underlie MT inputs to MST.

Stone, Leland S.↗

Common endocrine control of body weight, reproduction, and bone mass

Bone mass is maintained constant between puberty and menopause by the balance between osteoblast and osteoclast activity. The existence of a hormonal control of osteoblast activity has been speculated for years by analogy to osteoclast biology. Through the search for such humoral signal(s) regulating bone formation, leptin has been identified as a strong inhibitor of bone formation. Furthermore, intracerebroventricular infusion of leptin has shown that the effect of this adipocyte-derived hormone on bone is mediated via a brain relay. Subsequent studies have led to the identification of hypothalamic groups of neurons involved in leptin's antiosteogenic function. In addition, those neurons or neuronal pathways are distinct from neurons responsible for the regulation of energy metabolism. Finally, the peripheral mediator of leptin's antiosteogenic function has been identified as the sympathetic nervous system. Sympathomimetics administered to mice decreased bone formation and bone mass. Conversely, beta-blockers increased bone formation and bone mass and blunted the bone loss induced by ovariectomy.

NASA Discipline Regulatory Physiology↗