Wiring Diagram Research Articles

Predicting visual function by interpreting a neuronal wiring diagram

As connectomics advances, it will become commonplace to know far more about the structure of a nervous system than about its function. The starting point for many investigations will become neuronal wiring diagrams, which will be interpreted to make theoretical predictions about function. Here I demonstrate this emerging approach with the Drosophila optic lobe, analysing its structure to predict that three Dm3 (refs. 1–4) and three TmY (refs. 2,4) cell types are part of a circuit that serves the function of form vision. Receptive fields are predicted from connectivity, and suggest that the cell types encode the local orientation of a visual stimulus. Extraclassical5,6 receptive fields are also predicted, with implications for robust orientation tuning7, position invariance8,9 and completion of noisy or illusory contours10,11. The TmY types synapse onto neurons that project from the optic lobe to the central brain12,13, which are conjectured to compute conjunctions and disjunctions of oriented features. My predictions can be tested through neurophysiology, which would constrain the parameters and biophysical mechanisms in neural network models of fly vision14.

Neuronal wiring diagram of an adult brain

Connections between neurons can be mapped by acquiring and analysing electron microscopic brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative1–6, but nevertheless inadequate for understanding brain function more globally. Here we present a neuronal wiring diagram of a whole brain containing 5 × 107 chemical synapses7 between 139,255 neurons reconstructed from an adult female Drosophila melanogaster8,9. The resource also incorporates annotations of cell classes and types, nerves, hemilineages and predictions of neurotransmitter identities10–12. Data products are available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources. We derive a projectome—a map of projections between regions—from the connectome and report on tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine and descending neurons) across both hemispheres and between the central brain and the optic lobes. Tracing from a subset of photoreceptors to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviours. The technologies and open ecosystem reported here set the stage for future large-scale connectome projects in other species.

Design and Development of AI based Wiring Harness Simulator for Pigtail Wiring Harness Development in Electrical Checkout System (ECOS)

Electrical Checkout System (ECOS) tool validates electrical loads by quantifying their resistance in a typical production line of a commercial vehicle manufacturing organization. Model specific pigtails needs development for connecting the ECOS equipment with commercial vehicles in production. Conventional manual approach is used for Pigtail ECOS harness design and development which is both time-consuming and prone for errors. This project is related to the accelerated design and development of pigtail ECOS harness utilizing the power of Artificial Intelligence in analyzing the input wiring diagrams spanning multiple sheets in PDF format and accurately identify the wire loads. The AI provides the result in the form of tabulated spreadsheets consisting the data of wiring loads and pin details. Through this project the lead time for harness design and development is reduced significantly

Morphological Brain Networks of White Matter: Mapping, Evaluation, Characterization, and Application.

Although white matter (WM) accounts for nearly half of adult brain, its wiring diagram is largely unknown. Here, an approach is developed to construct WM networks by estimating interregional morphological similarity based on structural magnetic resonance imaging. It is found that morphological WM networks showed nontrivial topology, presented good-to-excellent test-retest reliability, accounted for phenotypic interindividual differences in cognition, and are under genetic control. Through integration with multimodal and multiscale data, it is further showed that morphological WM networks are able to predict the patterns of hamodynamic coherence, metabolic synchronization, gene co-expression, and chemoarchitectonic covariance, and associated with structural connectivity. Moreover, the prediction followed WM functional connectomic hierarchy for the hamodynamic coherence, is related to genes enriched in the forebrain neuron development and differentiation for the gene co-expression, and is associated with serotonergic system-related receptors and transporters for the chemoarchitectonic covariance. Finally, applying this approach to multiple sclerosis and neuromyelitis optica spectrum disorders, it is found that both diseases exhibited morphological dysconnectivity, which are correlated with clinical variables of patients and are able to diagnose and differentiate the diseases. Altogether, these findings indicate that morphological WM networks provide a reliable and biologically meaningful means to explore WM architecture in health and disease.

Low-cost parallel delta robot for a pick-and-place application with the support of the vision system

The main topic of this paper is how to develop pick and place delta robot with high efficiency mechanical parts and prosaically assemble it, additionally built electrical wiring diagram all of this supported by vision computer system. The system has a low-cost part and solves many problems to build this robot. Electrical section has two main components master and slave the master is raspberry pi and slave is Arduino, master is used to vision detect object and Arduino is used to invers kinematics equation, move motors to target position, control in hydraulic system to pull the object with suction cup. The process of vison system is passing through some steps, detect the object by color range, contouring box then send the real position to an Arduino. The experimental process proved the effectiveness and accuracy of the delta robot vision system in the sorting process from conveyor system. The target of system that function is applied with a low cost.

Design of Rotary Motor Wiring Diagram for Tugboat Ship Maneuvering System Using Cam Switch Control

The maneuverability of tugboats is very necessary for narrow turning areas, so many tugboat maneuvering systems use motors which are currently applied with cam switches. It is important to plan a wiring system to anticipate disruptions to distribution electricity. Therefore, the electricity supply for the equipment can be met and run as expected. The aim of this research is to obtain rotary motor wiring diagram system for tugboat ship maneuvering system using cam switch control. The R&D (Research and Development) method combined with experiments was carried out to obtain an ideal rotary motor wiring diagram system based on the dimensions of the tugboat's engine room. In forward rotation for this motor is a decrease before stabilization occurs, the voltage is 18% meanwhile, reverse rotation experienced a decrease of 32%. This difference with motor if workload which is charged which also experiences variations, for forward rotation the increase is 48%, also for reverse rotation it is 43%.

Whole-brain spatial organization of hippocampal single-neuron projectomes.

Mapping single-neuron projections is essential for understanding brain-wide connectivity and diverse functions of the hippocampus (HIP). Here, we reconstructed 10,100 single-neuron projectomes of mouse HIP and classified 43 projectome subtypes with distinct projection patterns. The number of projection targets and axon-tip distribution depended on the soma location along HIP longitudinal and transverse axes. Many projectome subtypes were enriched in specific HIP subdomains defined by spatial transcriptomic profiles. Furthermore, we delineated comprehensive wiring diagrams for HIP neurons projecting exclusively within the HIP formation (HPF) and for those projecting to both intra- and extra-HPF targets. Bihemispheric projecting neurons generally projected to one pair of homologous targets with ipsilateral preference. These organization principles of single-neuron projectomes provide a structural basis for understanding the function of HIP neurons.

The neuropeptidergic connectome of C. elegans

Efforts are ongoing to map synaptic wiring diagrams, or connectomes, to understand the neural basis of brain function. However, chemical synapses represent only one type of functionally important neuronal connection; in particular, extrasynaptic, "wireless" signaling by neuropeptides is widespread and plays essential roles in all nervous systems. By integrating single-cell anatomical and gene-expression datasets with biochemical analysis of receptor-ligand interactions, we have generated a draft connectome of neuropeptide signaling in the C.elegans nervous system. This network is characterized by high connection density, extended signaling cascades, autocrine foci, and a decentralized topology, with a large, highly interconnected core containing three constituent communities sharing similar patterns of input connectivity. Intriguingly, several key network hubs are little-studied neurons that appear specialized for peptidergic neuromodulation. We anticipate that the C.elegans neuropeptidergic connectome will serve as a prototype to understand how networks of neuromodulatory signaling are organized.

A sign-inverted receptive field of inhibitory interneurons provides a pathway for ON-OFF interactions in the retina

A fundamental organizing plan of the retina is that visual information is divided into ON and OFF streams that are processed in separate layers. This functional dichotomy originates in the ON and OFF bipolar cells, which then make excitatory glutamatergic synapses onto amacrine and ganglion cells in the inner plexiform layer. We have identified an amacrine cell (AC), the sign-inverting (SI) AC, that challenges this fundamental plan. The glycinergic, ON-stratifying SI-AC has OFF light responses. In opposition to the classical wiring diagrams, it receives inhibitory inputs from glutamatergic ON bipolar cells at mGluR8 synapses, and excitatory inputs from an OFF wide-field AC at electrical synapses. This “inhibitory ON center - excitatory OFF surround” receptive-field of the SI-AC allows it to use monostratified dendrites to conduct crossover inhibition and push-pull activation to enhance light detection by ACs and RGCs in the dark and feature discrimination in the light.

МОДЕРНИЗАЦИЯ СИСТЕМЫ УПРАВЛЕНИЯ СТАНЦИЕЙ ВОДОПОДГОТОВКИ С ИСПОЛЬЗОВАНИЕМ ТЕХНОЛОГИИ ОБРАТНОГО ОСМОСА

A system for managing the emergency condition of the water treatment plant has been developed. The development process is described. A functional diagram, a wiring diagram of electrical equipment and a program for automatization of this mode have been developed. The description of the main elements of the system is given. The main advantages of using emergency operation mode are described. The advantages of the new operation mode of the station are described.

Directed stepwise tracing of polysynaptic neuronal circuits with replication-deficient pseudorabies virus

Brain functions are accomplished by polysynaptic circuits formed by neurons wired together through multiple orders of synaptic connections. Polysynaptic connectivity has been difficult to examine due to a lack of methods of continuously tracing the pathways in a controlled manner. Here, we demonstrate directed, stepwise retrograde polysynaptic tracing by inducible reconstitution of replication-deficient trans-neuronal pseudorabies virus (PRVΔIE) in the brain. Furthermore, PRVΔIE replication can be temporally restricted to minimize its neurotoxicity. With this tool, we delineate a wiring diagram between the hippocampus and striatum-two major brain systems for learning, memory, and navigation-that consists of projections from specific hippocampal domains to specific striatal areas via distinct intermediate brain regions. Therefore, this inducible PRVΔIE system provides a tool for dissecting polysynaptic circuits underlying complex brain functions.

Cyclic structure with cellular precision in a vertebrate sensorimotor neural circuit

Neuronal wiring diagrams reconstructed by electron microscopy1,2,3,4,5 pose new questions about the organization of nervous systems following the time-honored tradition of cross-species comparisons.6,7 The C.elegans connectome has been conceptualized as a sensorimotor circuit that is approximately feedforward,8,9,10,11 starting from sensory neurons proceeding to interneurons and ending with motor neurons. Overrepresentation of a 3-cell motif often known as the "feedforward loop" has provided further evidence for feedforwardness.10,12 Here, we contrast with another sensorimotor wiring diagram that was recently reconstructed from a larval zebrafish brainstem.13 We show that the 3-cycle, another 3-cell motif, is highly overrepresented in the oculomotor module of this wiring diagram. This is a first for any neuronal wiring diagram reconstructed by electron microscopy, whether invertebrate12,14 or mammalian.15,16,17 The 3-cycle of cells is "aligned" with a 3-cycle of neuronal groups in a stochastic block model (SBM)18 of the oculomotor module. However, the cellular cycles exhibit more specificity than can be explained by the group cycles-recurrence to the same neuron is surprisingly common. Cyclic structure could be relevant for theories of oculomotor function that depend on recurrent connectivity. The cyclic structure coexists with the classic vestibulo-ocular reflex arc for horizontal eye movements,19 and could be relevant for recurrent network models of temporal integration by the oculomotor system.20,21.

Stability of linear Boolean networks

Stability is an important characteristic of network models that has implications for other desirable aspects such as controllability. The stability of a Boolean network (BN) depends on various factors, such as the topology of its wiring diagram and the type of the functions describing its dynamics. Linear Boolean networks can be completely described by their wiring diagram, and therefore the structure of linear networks plays a prominent role in determining their stability. In this paper, we study the stability of linear Boolean networks by computing Derrida curves and quantifying the number of attractors and cycle lengths imposed by their network topologies. Derrida curves are commonly used to measure the stability of Boolean networks and several parameters such as the average in-degree K and the output bias p can indicate if a network is stable, critical, or unstable. For random unbiased Boolean networks there is a critical connectivity value Kc=2 such that if K<Kc networks operate in the ordered regime, and if K>Kc networks operate in the chaotic regime. Here, we show that for linear networks, which are the least canalizing and most unstable, the phase transition from order to chaos already happens at an average in-degree of Kc=1. Consistently, we also show that unstable networks exhibit a large number of attractors with very long limit cycles while stable and critical networks exhibit fewer attractors with shorter limit cycles. Additionally, we present theoretical results to quantify important dynamical properties of linear networks. First, we present a formula for the proportion of attractor states in linear systems. Second, we show that the expected number of fixed points in linear systems is 2, while general Boolean networks possess on average one fixed point. Third, we present a formula to quantify the number of bijective linear Boolean networks and provide a lower bound for the percentage of this type of network.

Caenorhabditis elegans Connectomes of both Sexes as Image Classifiers

Connectome, the complete wiring diagram of the nervous system of an organism, is the biological substrate of the mind. While biological neural networks are crucial to the understanding of neural computation mechanisms, recent artificial neural networks (ANNs) have been developed independently from the study of real neural networks. Computational scientists are searching for various ANN architectures to improve machine learning since the architectures are associated with the accuracy of ANNs. A recent study used the hermaphrodite Caenorhabditis elegans (C. elegans) connectome for image classification tasks, where the edge directions were changed to construct a directed acyclic graph (DAG). In this study, we used the whole-animal connectomes of C. elegans hermaphrodite and male to construct a DAG that preserves the chief information flow in the connectomes and trained them for image classification of MNIST and fashion-MNIST datasets. The connectome-inspired neural networks exhibited over 99.5% and 92.6% of accuracy for MNIST and fashion-MNIST datasets, respectively, which increased from the previous study. Together, we conclude that realistic biological neural networks provide the basis of a plausible ANN architecture. This study suggests that biological networks can provide new inspiration to improve artificial intelligences (AIs).

A Proposed Human Structural Brain Connectivity Matrix in the Center for Morphometric Analysis Harvard-Oxford Atlas Framework: A Historical Perspective and Future Direction for Enhancing the Precision of Human Structural Connectivity with a Novel Neuroanatomical Typology

A complete structural definition of the human nervous system must include delineation of its wiring diagram (e.g., Swanson LW. Brain architecture: understanding the basic plan, 2012). The complete formulation of the human brain circuit diagram (BCD [Front Neuroanat. 2020;14:18]) has been hampered by an inability to determine connections in their entirety (i.e., not only pathway stems but also origins and terminations). From a structural point of view, a neuroanatomic formulation of the BCD should include the origins and terminations of each fiber tract as well as the topographic course of the fiber tract in three dimensions. Classic neuroanatomical studies have provided trajectory information for pathway stems and their speculative origins and terminations [Dejerine J and Dejerine-Klumpke A. Anatomie des Centres Nerveux, 1901; Dejerine J and Dejerine-Klumpke A. Anatomie des Centres Nerveux: Méthodes générales d’étude-embryologie-histogénèse et histologie. Anatomie du cerveau, 1895; Ludwig E and Klingler J. Atlas cerebri humani, 1956; Makris N. Delineation of human association fiber pathways using histologic and magnetic resonance methodologies; 1999; Neuroimage. 1999 Jan;9(1):18–45]. We have summarized these studies previously [Neuroimage. 1999 Jan;9(1):18–45] and present them here in a macroscale-level human cerebral structural connectivity matrix. A matrix in the present context is an organizational construct that embodies anatomical knowledge about cortical areas and their connections. This is represented in relation to parcellation units according to the Harvard-Oxford Atlas neuroanatomical framework established by the Center for Morphometric Analysis at Massachusetts General Hospital in the early 2000s, which is based on the MRI volumetrics paradigm of Dr. Verne Caviness and colleagues [Brain Dev. 1999 Jul;21(5):289–95]. This is a classic connectional matrix based mainly on data predating the advent of DTI tractography, which we refer to as the “pre-DTI era” human structural connectivity matrix. In addition, we present representative examples that incorporate validated structural connectivity information from nonhuman primates and more recent information on human structural connectivity emerging from DTI tractography studies. We refer to this as the “DTI era” human structural connectivity matrix. This newer matrix represents a work in progress and is necessarily incomplete due to the lack of validated human connectivity findings on origins and terminations as well as pathway stems. Importantly, we use a neuroanatomical typology to characterize different types of connections in the human brain, which is critical for organizing the matrices and the prospective database. Although substantial in detail, the present matrices may be assumed to be only partially complete because the sources of data relating to human fiber system organization are limited largely to inferences from gross dissections of anatomic specimens or extrapolations of pathway tracing information from nonhuman primate experiments [Front Neuroanat. 2020;14:18, Front Neuroanat. 2022;16:1035420, and Brain Imaging Behav. 2021;15(3):1589–1621]. These matrices, which embody a systematic description of cerebral connectivity, can be used in cognitive and clinical studies in neuroscience and, importantly, to guide research efforts for further elucidating, validating, and completing the human BCD [Front Neuroanat. 2020;14:18].

Automated sprayer for processing agricultural crops

In order to successfully conduct agricultural work and obtain a competitive harvest, it is mandatory to carry out spraying operations of crops that require highly qualified personnel, expensive equipment and suitable weather conditions. The use of tractors for spraying fields is the most common solution available at the moment, has disadvantages: high cost, risk of damage to the crop by "hitting", "hooking" or otherwise; environmental damage; due to exhaust gases, the demolition of the solution increases with increasing speed. Using a device designed specifically for spraying equipment is an ideal solution. The purpose of the article is to develop a working model of an automated sprayer for processing agricultural crops. The methods used are: technical justification of a controlled device for processing agricultural crops. Calculation of functional capabilities, algorithms of operation of the proposed automated device: selection of the type of sprayer, engine, chassis, controller, battery, as well as justification of the possibilities of using alternative energy sources (wind energy, solar energy); development of a 3D model of an automation device for anti-weed processing of agricultural crops, printing of parts, assembly of mechanical and electronic parts. Making a prototype using 3D printing; development of the wiring diagram of electronics, software (firmware of the microcontroller; application that controls the settings), testing of the prototype, assembly of the current model; rationale for the optimal use of Arduino and Raspberry Pi boards in this device in a pair: Raspberry Pi will allow you to control processes on the Arduino and easily interact with the Internet when the Arduino itself will perform simple operations such as interacting with electronics and reading sensor readings. The manufactured operating model showed compliance with the goals, a high degree of controllability, environmental friendliness, reduction of energy consumed, labor resources and can be used to scale this device. The developed model of the automation device for anti-weed treatment of agricultural crops can be used not only in agricultural pollination, but also as a mechanism for studying soil parameters: humidity, mineralogical composition and chemical content in the ground, using electronic sensors, as well as an automated mobile platform for any purpose requiring accurate navigation through the territory.

A vertigo network derived from human brain lesions and brain stimulation.

Vertigo is a common neurological complaint, which can result in significant morbidity and decreased quality of life. While pathology to peripheral and subtentorial brain structures is a well-established cause of vertigo, cortical lesions have also been linked to vertigo and may lend insight into relevant neuroanatomy. Here, we investigate the supratentorial lesion locations associated with vertigo and test whether they map to a common brain network. We performed a systematic literature search and identified 23 cases of supratentorial brain lesions associated with vertigo. We mapped the lesion locations to a standard brain template and computed the network of brain regions functionally connected to each lesion location, using a 'wiring diagram' of the human brain termed the human connectome (n = 1000). Sensitivity was assessed by identifying the most common connection to lesion locations associated with vertigo, and specificity was assessed through comparison with control lesions associated with symptoms other than vertigo (n = 68). We found that functional connectivity between lesion locations and the bilateral ventral posterior insula was both sensitive (22/23 lesions) and specific (voxel-wise family-wise error-corrected P < 0.05) for lesion-induced vertigo. We computed connectivity with this hub region to define a lesion-based vertigo network, which included regions in the bilateral insula, somatosensory cortex, higher-level visual areas, cingulate sulcus, thalamus and multiple cerebellar regions in the territory of the posterior inferior cerebellar artery. Next, we used stereo-electroencephalography (80 stimulation sites across 17 patients) to test whether stimulation sites associated with vertigo mapped to this same network. We found that 36/42 (86%) of stimulation sites eliciting vertigo fell within the lesion-based vertigo network in contrast to 16/39 (41%) of stimulation sites that did not elicit vertigo. Connectivity between stimulation sites and our lesion-based hub in the ventral posterior insula was also significantly associated with vertigo (P < 0.0001). We conclude that cortical lesions and direct electrical stimulation sites associated with vertigo map to a common brain network, offering insights into the causal neuroanatomical substrate of vertigo.

Regional and cell-type-specific afferent and efferent projections of the mouse claustrum.

The claustrum (CLA) is a conspicuous subcortical structure interconnected with cortical and subcortical regions. Its regional anatomy and cell-type-specific connections in the mouse remain not fully determined. Using multimodal reference datasets, we confirmed the delineation of the mouse CLA as a single group of neurons embedded in the agranular insular cortex. We quantitatively investigated brain-wide inputs and outputs of CLA using bulk anterograde and retrograde viral tracing data and single neuron tracing data. We found that the prefrontal module has more cell types projecting to the CLA than other cortical modules, with layer 5 IT neurons predominating. We found nine morphological types of CLA principal neurons that topographically innervate functionally linked cortical targets, preferentially the midline cortical areas, secondary motor area, and entorhinal area. Together, this study provides a detailed wiring diagram of the cell-type-specific connections of the mouse CLA, laying a foundation for studying its functions at the cellular level.

Bayesian reconstruction of memories stored in neural networks from their connectivity.

The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in a recurrent network of neurons, given its synaptic connectivity matrix. Here, we address this question by determining when solving such an inference problem is theoretically possible in specific attractor network models and by providing a practical algorithm to do so. The algorithm builds on ideas from statistical physics to perform approximate Bayesian inference and is amenable to exact analysis. We study its performance on three different models, compare the algorithm to standard algorithms such as PCA, and explore the limitations of reconstructing stored patterns from synaptic connectivity.

PEMBELAJARAN KONTROL SISTEM PNEUMATIK SEBAGAI PENUNJANG KOMPETENSI SISTEM HIDROLIK DAN PNEUMATIK DI SMK NEGERI 1 ADIWERNA

Community Service Activities carried out are providing understanding and thinking patterns about pneumatic systems control that work electro-pneumatically to students of SMK Negeri 1 Adiwerna grade XII majoring in Technical Light Vehicle (TLV). Knowledge of pneumatic systems is one of the competencies that are usually difficult to understand by TLV students. Whereas pneumatic systems have many applications in the industrial world. By using a facility in the form of an Electro-Pneumatic Trainer, the delivery of discussions about pneumatic system control will be more easily understood by students. By referring to the wiring diagram, students are explained to be able to read and understand the intent and working process of the pneumatic systems control and put it into practice immediately. There are 3 types of pneumatic systems control delivered, (1) single-cylinder pneumatic control systems, (2) single-cycle multiple cylinder pneumatic control systems, (3) continuous cycle multiple cylinder pneumatic control systems. Students are very enthusiastic about receiving explanations and practicing all three control systems.