Memristor-based biomimetic compound eye for real-time collision detection

The lobula giant movement detector (LGMD) is the movement-sensitive, wide-field visual neuron positioned in the third visual neuropile of lobula. LGMD neuron can anticipate collision and trigger avoidance efficiently owing to the earlier occurring firing peak before collision. Vision chips inspired by the LGMD have been successfully implemented in very-large-scale-integration (VLSI) system. However, transistor-based chips and single devices to simulate LGMD neurons make them bulky, energy-inefficient and complicated. The devices with relatively compact structure and simple operation mode to mimic the escape response of LGMD neuron have not been realized yet. Here, the artificial LGMD visual neuron is implemented using light-mediated threshold switching memristor. The non-monotonic response to light flow field originated from the formation and break of Ag conductive filaments is analogue to the escape response of LGMD neuron. Furthermore, robot navigation with obstacle avoidance capability and biomimetic compound eyes with wide field-of-view (FoV) detection capability are demonstrated.

Rigged hand model for the Blender Game Engine

In a lot of virtual reality applications, it is necessary to display and animate the user's hand in the virtual world. In game engines, armatures are often used for modeling parts or the whole of the human body. The process of creating the armature and assigning parts of the mesh representing flesh and skin to the “bones” of the armature is called rigging. After performing rigging, moving the armature will result in the movement of the mesh, thus the virtual hand (or other object) is animated. The Blender Game Engine (BGE) is one of the few open-source game engines available. The paper gives a detailed description of the process of successfully building a complex rigged hand model for the BGE and gives guidance for driving this hand model with input data from the Leap Motion hand movement detector. The rigged hand model has been implemented, using the hand mesh from the LibHand library and an armature specifically built to match the hand representation of the Leap Motion. The model will be used for navigation and interaction in the virtual model of a power plant control room.

Design of IoT-based Tool for Temperature Control and Movement Detector using Arduino and Cayenne

The development of technology towards IoT or the Internet of Things has been very advanced so that the fulfillment of human needs is increasingly easy and comfortable. One example is the need to control and monitor the air temperature in the server room. The server room requires a cool and stable temperature so that the computer devices inside can function properly. In addition, the room also requires a security system to prevent undesirable things, such as intruders or people who are other than server admin officers. These needs can be fulfilled by creating an IoT-based device. Arduino as the main device and online Cayenne web-based application as a medium for controlling Arduino. This device is equipped with a motion detection security system using the PIR Motion Detector HCSR501 sensor while for temperature monitoring using a DHT22 sensor. Control of tools can be done using a web browser on a PC (Personal Computer) and an android smartphone via an internet connection

Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve discrimination of input synchrony

How neurons filter and integrate their complex patterns of synaptic inputs is central to their role in neural information processing. Synaptic filtering and integration are shaped by the frequency-dependent neuronal membrane impedance. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the membrane impedance of a collision detection neuron in the grasshopper Schistocerca americana. This neuron, the lobula giant movement detector (LGMD), exhibits consistent impedance properties across frequencies and membrane potentials. Two common active conductances gH and gM, mediated respectively by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels and by muscarine-sensitive M-type K+ channels, promote broadband integration with high temporal precision over the LGMD’s natural range of membrane potentials and synaptic input frequencies. Additionally, we found that a model based on the LGMD’s branching morphology increased the gain and decreased the delay associated with the mapping of synaptic input currents to membrane potential. More generally, this was true for a wide range of model neuron morphologies, including those of neocortical pyramidal neurons and cerebellar Purkinje cells. These findings show the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration. NEW & NOTEWORTHY Neuronal filtering and integration of synaptic input patterns depend on the electrochemical properties of dendrites. We used an identified collision detection neuron in grasshoppers to examine how its morphology and two conductances affect its membrane impedance in relation to the computations it performs. The neuronal properties examined are ubiquitous and therefore promote a general understanding of neuronal computations, including those in the human brain.

PENGENDALI LAMPU MONITORING RUMAH DENGAN SHORT MESSAGE SERVICE (SMS) BERBASIS ARDUINO UNO

The increasing activity of someone outside the home causes difficulties in controlling the lamps and monitoring the condition of the house from a distance, therefore it is necessary to control the lamps remotely. This research designed and built a lamps handling by short message service (SMS) based on arduino uno. Lamps handling by sms is a tool which act as the lamp and alarm switches at house, whenever without time limits as far as the GSM signal is still can be reached. Handling tool from distance by mobile sms act as an order producer, arduino uno as a microcontroller, sensor peer as a movement detector, gsm modul sim 900A as an information sender and acceptor and relay as a switcher of lamps or the alarms. The test results of this tool show that this too can be used based on the order which is given from distance to control the lamps and the alarms. Another function of this tool is to monitor the lamps condition by “cek” function to know in which lamp is on or off mode. It also can switch on an alarm and send some sms to the owner’s contact number when its sensor detected any object movements.

Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve membrane synchrony

Brains processes information through the coordinated efforts of billions of individual neurons, each encoding a small part of the overall information stream. Central to this is how neurons integrate and transform complex patterns of synaptic inputs. The neuronal membrane impedance sets the gain and timing for synaptic integration, determining a neuron's ability to discriminate between synaptic input patterns. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the membrane impedance of a collision detection neuron in the grasshopper, Schistocerca americana. We examined how the cellular properties of the lobula giant movement detector (LGMD) neuron are tuned to enable the discrimination of synaptic input patterns key to its role in collision detection. We found that two common active conductances gH and gM, mediated respectively by hyperpolarization-activated cyclic nucleotide gated (HCN) channels and by muscarine sensitive M-type K+ channels, promote broadband integration with high temporal precision over the LGMD's natural range of membrane potentials and synaptic input frequencies. Additionally, we found that the LGMD's branching morphology increased the gain and decreased delays associated with the mapping of synaptic input currents to membrane potential. We investigated whether other branching dendritic morphologies fulfill a similar function and found this to be true for a wide range of morphologies, including those of neocortical pyramidal neurons and cerebellar Purkinje cells. These findings further our understanding of the integration properties of individual neurons by showing the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration.

Optogenetic manipulation of medullary neurons in the locust optic lobe

The locust is a widely used animal model for studying sensory processing and its relation to behavior. Due to the lack of genomic information, genetic tools to manipulate neural circuits in locusts are not yet available. We examined whether Semliki Forest virus is suitable to mediate exogenous gene expression in neurons of the locust optic lobe. We subcloned a channelrhodopsin variant and the yellow fluorescent protein Venus into a Semliki Forest virus vector and injected the virus into the optic lobe of locusts ( Schistocerca americana). Fluorescence was observed in all injected optic lobes. Most neurons that expressed the recombinant proteins were located in the first two neuropils of the optic lobe, the lamina and medulla. Extracellular recordings demonstrated that laser illumination increased the firing rate of medullary neurons expressing channelrhodopsin. The optogenetic activation of the medullary neurons also triggered excitatory postsynaptic potentials and firing of a postsynaptic, looming-sensitive neuron, the lobula giant movement detector. These results indicate that Semliki Forest virus is efficient at mediating transient exogenous gene expression and provides a tool to manipulate neural circuits in the locust nervous system and likely other insects.NEW & NOTEWORTHY Using Semliki Forest virus, we efficiently delivered channelrhodopsin into neurons of the locust optic lobe. We demonstrate that laser illumination increases the firing of the medullary neurons expressing channelrhodopsin and elicits excitatory postsynaptic potentials and spiking in an identified postsynaptic target neuron, the lobula giant movement detector neuron. This technique allows the manipulation of neuronal activity in locust neural circuits using optogenetics.

M current regulates firing mode and spike reliability in a collision-detecting neuron

All animals must detect impending collisions to escape and reliably discriminate them from nonthreatening stimuli, thus preventing false alarms. Therefore, it is no surprise that animals have evolved highly selective and sensitive neurons dedicated to such tasks. We examined a well-studied collision-detection neuron in the grasshopper ( Schistocerca americana) using in vivo electrophysiology, pharmacology, and computational modeling. This lobula giant movement detector (LGMD) neuron is excitable by inputs originating from each ommatidia of the compound eye. It possesses many intrinsic properties that increase its selectivity to objects approaching on a collision course, including switching between burst and nonburst firing. In this study, we demonstrate that the LGMD neuron exhibits a large M current, generated by noninactivating K+ channels, that shortens the temporal window of dendritic integration, regulates a firing mode switch between burst and isolated spiking, increases the precision of spike timing, and increases the reliability of spike propagation to downstream motor centers. By revealing how the M current increases the LGMD’s ability to detect impending collisions, our results suggest that similar channels may play an analogous role in other collision detection circuits. NEW & NOTEWORTHY The ability to reliably detect impending collisions is a critical survival skill. The nervous systems of many animals have developed dedicated neurons for accomplishing this task. We used a mix of in vivo electrophysiology and computational modeling to investigate the role of M potassium channels within one such collision-detecting neuron and show that through regulation of burst firing and enhancement of spiking reliability, the M current increases the ability to detect impending collisions.