Olfactory bulb removal - Effects on brain norepinephrine.
Olfactory bulb removal effects on uptake decline of telencephalic norepinephrine, noting use for mapping adrenergic pathways
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Olfactory bulb removal effects on uptake decline of telencephalic norepinephrine, noting use for mapping adrenergic pathways
Drosophila atonal (ato) is the proneural gene of the chordotonal organs (CHOs) in the peripheral nervous system (PNS) and the larval and adult photoreceptor organs. Here, we show that ato is expressed at multiple stages during the development of a lineage of central brain neurons that innervate the optic lobes and are required for eclosion. A novel fate mapping approach shows that ato is expressed in the embryonic precursors of these neurons and that its expression is reactivated in third instar larvae (L3). In contrast to its function in the PNS, ato does not act as a proneural gene in the embryonic brain. Instead, ato performs a novel function, regulating arborization during larval and pupal development by interacting with Notch.
Near-infrared spectroscopy (NIRS) has been used to noninvasively monitor adult human brain function in a wide variety of tasks. While rough spatial correspondences with maps generated from functional magnetic resonance imaging (fMRI) have been found in such experiments, the amplitude correspondences between the two recording modalities have not been fully characterized. To do so, we simultaneously acquired NIRS and blood-oxygenation level-dependent (BOLD) fMRI data and compared Delta(1/BOLD) (approximately R(2)(*)) to changes in oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations derived from the NIRS data from subjects performing a simple motor task. We expected the correlation with deoxyhemoglobin to be strongest, due to the causal relation between changes in deoxyhemoglobin concentrations and BOLD signal. Instead we found highly variable correlations, suggesting the need to account for individual subject differences in our NIRS calculations. We argue that the variability resulted from systematic errors associated with each of the signals, including: (1) partial volume errors due to focal concentration changes, (2) wavelength dependence of this partial volume effect, (3) tissue model errors, and (4) possible spatial incongruence between oxy- and deoxyhemoglobin concentration changes. After such effects were accounted for, strong correlations were found between fMRI changes and all optical measures, with oxyhemoglobin providing the strongest correlation. Importantly, this finding held even when including scalp, skull, and inactive brain tissue in the average BOLD signal. This may reflect, at least in part, the superior contrast-to-noise ratio for oxyhemoglobin relative to deoxyhemoglobin (from optical measurements), rather than physiology related to BOLD signal interpretation.
A callosotomy patient was tested in two dual-task experiments requiring successive speeded responses to lateralized stimuli. In accord with the recent findings of Pashler, O'Brien, Luck, Hillyard, Mangun, and Gazzaniga (in press), the patient showed a robust psychological refractory period effect (PRP) responses on Task 2 were inversely related to the stimulus-onset asynchrony (SOA). However, three aspects of our data indicated that the processing limitations for the patient were different than those observed with control subjects. First, the split-brain patient did not show an increase in reaction time when the two tasks required responses from a common output system (i.e., both manual responses) in comparison to when different output systems were used (i.e., manual-vocal). Second, inconsistent stimulus-response mappings for the two tasks greatly inflated response latencies for the control subjects, but had minimal effect on the performance of the split-brain patient. Third, the consistency manipulation was underadditive with SOA for only the patient, suggesting a later bottleneck in processing following callosotomy than was observed for the control subjects. It is proposed that sectioning the corpus callosum eliminates interference resulting from competing stimulus response codes. Nonetheless, dual-task interference persists for the split-brain subject because a subcortical gate constrains when selected responses can be implemented.
We have developed a prototype imaging system that can perform simultaneous x-ray transmission CT and SPECT phantom studies. This system employs a 23-element high-purity-germanium detector array. The detector array is coupled to a collimator with septa angled toward the focal spot of an x-ray tube. During image acquisition, the x-ray fan beam and the detector array move synchronously along an arc pivoted at the x-ray source. Multiple projections are obtained by rotating the object, which is mounted at the center of rotation of the system. The detector array and electronics can count up to 10(6) cps/element with sufficient energy-resolution to discriminate between x-rays at 100-120 kVp and gamma rays from 99mTc. We have used this device to acquire x-ray CT and SPECT images of a three-dimensional Hoffman brain phantom. The emission and transmission images may be superimposed in order to localize the emission image on the transmission map.
Using a 5 µm-diameter X-ray beam, we collected scanning X-ray microdiffraction in both the small-angle (SAXS) and the wide-angle (WAXS) regimes from thin sections of fixed human brain tissue from Alzheimer's subjects. The intensity of scattering in the SAXS regime of these patterns exhibits essentially no correlation with the observed intensity in the WAXS regime, indicating that the structures responsible for these two portions of the diffraction patterns, which reflect different length scales, are distinct. SAXS scattering exhibits a power-law behavior in which the log of intensity decreases linearly with the log of the scattering angle. The slope of the log–log curve is roughly proportional to the intensity in the SAXS regime and, surprisingly, inversely proportional to the intensity in the WAXS regime. We interpret these observations as being due to the presence of sub-micrometre-sized voids formed during dehydration of the fixed tissue. The SAXS intensity is due largely to scattering from these voids, while the WAXS intensity derives from the secondary structures of macromolecular material surrounding the voids. The ability to detect and map the presence of voids within thin sections of fixed tissue has the potential to provide novel information on the degradation of human brain tissue in neurodegenerative diseases.
Advances in novel hardware devices and architectures allow Spiking Neural Network (SNN) evaluation using ultra-low power, mixed-signal, memristor crossbar arrays. As individual network sizes quickly scale beyond the dimensional capabilities of single crossbars, networks must be mapped onto multiple crossbars. Crossbar sizes within modern Memristor Crossbar Architectures (MCAs) are determined predominately not by device technology but by network topology; more, smaller crossbars consume less area thanks to the high structural sparsity found in larger, brain-inspired SNNs. Motivated by continuing increases in SNN sparsity due to improvements in training methods, we propose utilizing heterogeneous crossbar sizes to further reduce area consumption. This approach was previously unachievable as prior compiler studies only explored solutions targeting homogeneous MCAs. Our work improves on the state-of-the-art by providing Integer Linear Programming (ILP) formulations supporting arbitrarily heterogeneous architectures. By modeling axonal interactions between neurons, our methods produce better mappings while removing inhibitive a priori knowledge requirements. We first show a 16.7-27.6% reduction in area consumption for square-crossbar homogeneous architectures. Then, we demonstrate 66.9-72.7% further reduction when using a reasonable configuration of heterogeneous crossbar dimensions. Next, we present a new optimization formulation capable of minimizing the number of inter-crossbar routes. When applied to solutions already near-optimal in area, an 11.9-26.4% routing reduction is observed without impacting area consumption. Finally, we present a profile-guided optimization capable of minimizing the number of runtime spikes between crossbars. Compared to the best-area-then-route optimized solutions, we observe a further 0.5-14.8% inter-crossbar spike reduction while requiring 1–3 orders of magnitude less solver time.
An increasing number of spatial multiomic workflows have been recently developed. Some of these approaches have leveraged initial mass spectrometry imaging (MSI)-based spatial metabolomics to inform region of interest (ROI) selection for downstream spatial proteomics. However, these workflows have been limited by varied substrate requirements between modalities or have required analyzing serial sections (i.e., one section per modality). To mitigate these issues, we present a novel multiomic workflow that uses desorption electrospray ionization (DESI)-MSI to identify representative spatial metabolite patterns on-tissue prior to spatial proteomic analyses on the same tissue section. Further, this workflow is demonstrated here with a model mammalian tissue (coronal rat brain section) mounted on a polyethylene naphthalate-membrane slide. Initial DESI-MSI resulted in 160 annotations (SwissLipids) within to the METASPACE platform (≤20% false discovery rate). A segmentation map from the annotated ion images informed downstream ROI selection for spatial proteomics characterization from the same sample. The unspecific substrate requirements and minimal sample disruption inherent to DESI-MSI allowed for an optimized, downstream spatial proteomics assay, resulting in 3888 ± 240 to 4717 ± 48 proteins being confidently directed per ROI (200 µm x 200 µm). Finally, we demonstrate the integration of multiomic information, where we found ceramide localization to be correlated with SMPD3 abundance (ceramide synthesis protein), and we also utilized protein abundance to resolve metabolite isomeric ambiguity. Overall, the integration of DESI-MSI into the multiomic workflow allows for complementary spatial and molecular-level information to be achieved from optimized implementations of each MS assay inherent to the workflow itself.
The present and proposed capabilities of the Central Image Processing Laboratory, which provides a powerful resource for the advancement of programs in missile technology, space science, oceanography, and biomedical image analysis, are discussed. The use of image digitizing, digital image processing, and digital image output permits a variety of functional capabilities, including: enhancement, pseudocolor, convolution, computer output microfilm, presentation graphics, animations, transforms, geometric corrections, and feature extractions. The hardware and software of the Image Processing Laboratory, consisting of digitizing and processing equipment, software packages, and display equipment, is described. Attention is given to applications for imaging systems, map geometric correction, raster movie display of Seasat ocean data, Seasat and Skylab scenes of Nantucket Island, Space Shuttle imaging radar, differential radiography, and a computerized tomographic scan of the brain.
Aberrant activation of tau kinases (tauK) has been proposed as a major step in tau hyperphosphorylation and misfolding, and subsequent formation of neurofibrillary tangles (NFT) in Alzheimer's disease (AD). However, evidence of tauK hyperactivation in actual AD brains is scarce and inconsistent, and their role in age-related cognitive decline remains undocumented. We evaluated activated/inhibited species of CDK5/p35/p25, GSK3a/ß, and ERK1/2 as well as ten tau/phospho-tau (ptau) peptides (mapping Ser 202 , Thr 217 , Ser 262 , Ser 305 , and Ser 404 phospho-residues) by Western blot or selected reaction monitoring proteomics, respectively, in postmortem dorsolateral prefrontal cortex (DLPFC) and hippocampal samples of 150 participants from the Rush Memory and Aging Project (MAP). Regression models and mediation analyses assessed the contributions of these variables to tau phosphorylation, NFT deposition and antemortem cognitive status of MAP participants. Surprisingly, greater p25 and p35 (indices for CDK5 activation) and lower pSer 21/9 -GSK3a/ß (inhibited species) immunodensities were associated with lower ptau peptide amounts. Individuals with higher p25 cortical densities displayed better cognitive outcomes, particularly working memory. Statistical mediation analyses indicated that the beneficial effect of CDK5/p25 on cognition was mediated by lower densities of phospho-Thr 217 -tau and NFT deposition in DLPFC, and also identified Thr 217 and Ser 262 as the ptau sites with greatest influence in both NFT accumulation and cognitive impairment. The present data suggest that tau hyperphosphorylation, tangle deposition, and the subsequent cognitive impairment do not rely on aberrant activation of major tauKs. Additionally, novel evidence was provided for the beneficial contribution of cortical CDK5/p25 to the maintenance of working memory.
One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.
Tubulin proteins are the fundamental subunits of all polymeric microtubule-based eukaryotic structures. Long, hollow structures each composed of 13 protofilaments as revealed by electron microscopy, microtubules (240 angstroms in diameter) are nearly ubiquitous in eukaryotes. These proteins have been the subject of intense biochemical and biophyiscal interest since the early 1970s and are of evolutionary interest as well. If tubulin-based structures (i.e., neurotubules, mitotic spindle tubules, centrioles, kinetosomes, axonemes, etc.) evolved from spirochetes by way of motility symbioses, tubulin homologies with spirochete proteins should be detectable. Tubulin proteins are widely thought to be limited to eukaryotes. Yet both azotobacters and spirochetes have shown immunological cross-reactivity with antitubulin antibodies. In neither of these studies was tubulin isolated nor any specific antigen identified as responsible for the immunoreactivity. Furthermore, although far less uniform in structure than eukaryotic microtubules, various cytoplasmic fibers and tubules (as seen by electron microscopy) have been reported in several types of prokaryotes (e.g., Spirochaeta; large termite spirochetes; treponemes; cyanobacteria; and Azotobacter. This work forms a part of our long-range study of the possible prokaryotic origin of tubulin and microtubules. Spirochetes are helically shaped gram-negative motile prokaryotes. They differ from all other bacterial in that the position of their flagella is periplasmic: their flagella lie between the inner and outer membranes of the gram-negative cell wall. Some of the largest spirochetes have longitudinally aligned 240 angstrom microtubules. Unfortunately, in spite of many attempts, all of the larger spirochetes (family Pillotaceae) with well-defined cytoplasmic tubules and antitubulin immunoreactivity are not cultivable. However, a newly described spirochete species (Spirochaeta bajacaliforniensis) possessing cytoplasmic fibers displays antitubulin immunoreactivity in whole-cell preparations. Since preliminary observations suggested that Spirochaeta bajacaliforniensis proteins may be related to eukaryotic tubulins, their characterization was undertaken. Brain tubulin can be purified by utilizing its ability to polymerize at warm temperatures and to depolymerize in the cold. After several cycles of sedimentation and redissolution the microtubule fraction is comprised of 75% tubulin and 20% high molecular mass microtubule-associated proteins (MAPs). In this paper we report that components of cell lysates, prepared from a spirochete that contains cytoplasmic fibers (Spirochaeta bajacaliforniensis), also exhibit the property of temperature-dependent cyclical sedimentation. Additionally we report the identification and characterization of the polypeptide responsible for cross-reactivity with antitubulin antiserum.
Distant-acting enhancers are central to human development1. However, our limited understanding of their functional sequence features prevents the interpretation of enhancer mutations in disease2. Here we determined the functional sensitivity to mutagenesis of human developmental enhancers in vivo. Focusing on seven enhancers that are active in the developing brain, heart, limb and face, we created over 1,700 transgenic mice for over 260 mutagenized enhancer alleles. Systematic mutation of 12-base-pair blocks collectively altered each sequence feature in each enhancer at least once. We show that 69% of all blocks are required for normal in vivo activity, with mutations more commonly resulting in loss (60%) than in gain (9%) of function. Using predictive modelling, we annotated critical nucleotides at the base-pair resolution. The vast majority of motifs predicted by these machine learning models (88%) coincided with changes in in vivo function, and the models showed considerable sensitivity, identifying 59% of all functional blocks. Taken together, our results reveal that human enhancers contain a high density of sequence features that are required for their normal in vivo function and provide a rich resource for further exploration of human enhancer logic.
Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.
Tubulin proteins are the fundamental subunits of all polymeric microtubule-based eukaryotic structures. Long, hollow structures each composed of 13 protofilaments as revealed by electron microscopy, microtubules (240 angstroms in diameter) are nearly ubiquitous in eukaryotes. These proteins have been the subject of intense biochemical and biophysical interest since the early 1970s and are of evolutionary interest as well. If tubulin-based structures (i.e., neurotubules, mitotic spindle tubules, centrioles, kinetosomes, axonemes, etc.) evolved from spirochetes by way of motility symbioses, tubulin homologies with spirochete proteins should be detectable. Tubulin proteins are widely thought to be limited to eukaryotes. Yet both azotobacters and spirochetes have shown immunological cross-reactivity with anitubulin antibodies. In neither of these studies was tubulin isolated nor any specific antigen identified as responsible for the immunoreactivity. Furthermore, although far less uniform in structure than eukaryotic microtubules, various cytoplasmic fibers and tubules (as seen by electron microscopy) have been reported in several types of prokaryotes (e.g., Spirochaeta; large termite spirochetes; treponemes; cyanobacteria; and Azotobacter. This work forms a part of our long-range study of the possible prokaryotic origin of tubulin and microtubules. Spirochetes are helically shaped gram-negative motile prokaryotes. They differ from all other bacteria in that the position of their flagella is periplasmic: their flagella lie between the inner and outer membranes of the gram-negative cell wall. Some of the largest spirochetes have longitudinally aligned 240 angstroms microtubules. Unfortunately, in spite of many attempts, all of the larger spirochetes (family Pillotaceae) with well-defined cytoplasmic tubules and antitubulin immunoreactivity are not cultivable. However, a newly described spirochete species (Spirochaeta bajacaliforniensis) possessing cytoplasmic fibers displays antitubulin immunoreactivity in whole-cell preparations. Since preliminary observations suggested that Spirochaeta bajacaliforniensis proteins may be related to eukaryotic tubulins, their characterization was undertaken. Brain tubulin can be purified by utilizing its ability to polymerize at warm temperatures and to depolymerize in the cold. After several cycles of sedimentation and redissolution the microtubule fraction is composed of 75% tubulin and 20% high molecular mass microtubule-associated proteins (MAPs). In this paper we report that components of cell lysates, prepared from a spirochete that contains cytoplasmic fibers (Spirochaeta bajacaliforniensis), also exhibit the property of temperature-dependent cyclical sedimentation. Additionally we report the identification and characterization of the polypeptide responsible for cross-reactivity with antitubulin antiserum.
The global energy shortage has driven the development of many energy-efficient computational platforms beyond Moore's law, among which brain-inspired neuromorphic computing is one of the promising solutions. Associative memory and pattern recognition are important computations solved by brain-inspired Hopfield networks. Classical Hopfield networks store memories via fixed point attractors of their dynamics. In oscillatory Hopfield networks, these attractors are replaced by periodic orbits. Here, we design an oscillatory Hopfield network based on coupled superconducting oscillators. We first employ a mathematical phase reduction approach to map networks of coupled superconducting rapid single flux quantum (RSFQ) ring oscillators to coupled Kuramoto phase-oscillator networks. We use this theory to numerically optimize the hardware's mutual inductances in order to directly match the phase-reduced superconducting oscillators to a model of phase-oscillator-based Hopfield networks. The resulting network can store multiple oscillatory phase-locked memory patterns and recover the patterns based on the initial phase conditions. As different pattern recognition tasks, or learning, require tunable connectivity strengths between the oscillatory nodes, we further employ a coupler circuit that enables tuning the coupling strength between two oscillators by applying an external flux. We demonstrate the functionality of our design through numerical simulations of a small example network with oscillators operating at 86 GHz and recognizing patterns within 10 ns. Our approach enables the learning and retrieval of dynamical memory patterns with a wide range of applications where rhythmic dynamic output is beneficial.
The radiation risk to astronauts has always been based on measurements using passive thermoluminescent dosimeters (TLDs). The skin dose is converted to dose equivalent using an average radiation quality factor based on model calculations. The radiological risk estimates, however, are based on organ and tissue doses. This paper describes results from the first space flight (STS-91, 51.65 degrees inclination and approximately 380 km altitude) of a fully instrumented Alderson Rando phantom torso (with head) to relate the skin dose to organ doses. Spatial distributions of absorbed dose in 34 1-inch-thick sections measured using TLDs are described. There is about a 30% change in dose as one moves from the front to the back of the phantom body. Small active dosimeters were developed specifically to provide time-resolved measurements of absorbed dose rates and quality factors at five organ locations (brain, thyroid, heart/lung, stomach and colon) inside the phantom. Using these dosimeters, it was possible to separate the trapped-proton and the galactic cosmic radiation components of the doses. A tissue-equivalent proportional counter (TEPC) and a charged-particle directional spectrometer (CPDS) were flown next to the phantom torso to provide data on the incident internal radiation environment. Accurate models of the shielding distributions at the site of the TEPC, the CPDS and a scalable Computerized Anatomical Male (CAM) model of the phantom torso were developed. These measurements provided a comprehensive data set to map the dose distribution inside a human phantom, and to assess the accuracy and validity of radiation transport models throughout the human body. The results show that for the conditions in the International Space Station (ISS) orbit during periods near the solar minimum, the ratio of the blood-forming organ dose rate to the skin absorbed dose rate is about 80%, and the ratio of the dose equivalents is almost one. The results show that the GCR model dose-rate predictions are 20% lower than the observations. Assuming that the trapped-belt models lead to a correct orbit-averaged energy spectrum, the measurements of dose rates inside the phantom cannot be fully understood. Passive measurements using 6Li- and 7Li-based detectors on the astronauts and inside the brain and thyroid of the phantom show the presence of a significant contribution due to thermal neutrons, an area requiring additional study.
A system is proposed which receives input information from many sensors that may have diverse scaling, dimension, and data representations. The proposed system tolerates sensory information with faults. The proposed self-adaptive processing technique has great promise in integrating the techniques of artificial intelligence and neural networks in an attempt to build a more intelligent computing environment. The proposed architecture can provide a detailed decision tree based on the input information, information stored in a long-term memory, and the adapted rule-based knowledge. A mathematical model for analysis will be obtained to validate the cited hypotheses. An extensive software program will be developed to simulate a typical example of pattern recognition problem. It is shown that the proposed model displays attention, expectation, spatio-temporal, and predictory behavior which are specific to the human brain. The anticipated results of this research project are: (1) creation of a new dynamic neural network structure, and (2) applications to and comparison with conventional multi-layer neural network structures. The anticipated benefits from this research are vast. The model can be used in a neuro-computer architecture as a building block which can perform complicated, nonlinear, time-varying mapping from a multitude of input excitory classes to an output or decision environment. It can be used for coordinating different sensory inputs and past experience of a dynamic system and actuating signals. The commercial applications of this project can be the creation of a special-purpose neuro-computer hardware which can be used in spatio-temporal pattern recognitions in such areas as air defense systems, e.g., target tracking, and recognition. Potential robotics-related applications are trajectory planning, inverse dynamics computations, hierarchical control, task-oriented control, and collision avoidance.