Synthetic Analog and Digital Circuits for Cellular Computation and Memory
Purcell, Oliver; Lu, Timothy K.
2014-01-01
Biological computation is a major area of focus in synthetic biology because it has the potential to enable a wide range of applications. Synthetic biologists have applied engineering concepts to biological systems in order to construct progressively more complex gene circuits capable of processing information in living cells. Here, we review the current state of computational genetic circuits and describe artificial gene circuits that perform digital and analog computation. We then discuss recent progress in designing gene circuits that exhibit memory, and how memory and computation have been integrated to yield more complex systems that can both process and record information. Finally, we suggest new directions for engineering biological circuits capable of computation. PMID:24794536
Synthetic analog and digital circuits for cellular computation and memory.
Purcell, Oliver; Lu, Timothy K
2014-10-01
Biological computation is a major area of focus in synthetic biology because it has the potential to enable a wide range of applications. Synthetic biologists have applied engineering concepts to biological systems in order to construct progressively more complex gene circuits capable of processing information in living cells. Here, we review the current state of computational genetic circuits and describe artificial gene circuits that perform digital and analog computation. We then discuss recent progress in designing gene networks that exhibit memory, and how memory and computation have been integrated to yield more complex systems that can both process and record information. Finally, we suggest new directions for engineering biological circuits capable of computation. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
Nonvolatile “AND,” “OR,” and “NOT” Boolean logic gates based on phase-change memory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Y.; Zhong, Y. P.; Deng, Y. F.
2013-12-21
Electronic devices or circuits that can implement both logic and memory functions are regarded as the building blocks for future massive parallel computing beyond von Neumann architecture. Here we proposed phase-change memory (PCM)-based nonvolatile logic gates capable of AND, OR, and NOT Boolean logic operations verified in SPICE simulations and circuit experiments. The logic operations are parallel computing and results can be stored directly in the states of the logic gates, facilitating the combination of computing and memory in the same circuit. These results are encouraging for ultralow-power and high-speed nonvolatile logic circuit design based on novel memory devices.
Fault-tolerant computer study. [logic designs for building block circuits
NASA Technical Reports Server (NTRS)
Rennels, D. A.; Avizienis, A. A.; Ercegovac, M. D.
1981-01-01
A set of building block circuits is described which can be used with commercially available microprocessors and memories to implement fault tolerant distributed computer systems. Each building block circuit is intended for VLSI implementation as a single chip. Several building blocks and associated processor and memory chips form a self checking computer module with self contained input output and interfaces to redundant communications buses. Fault tolerance is achieved by connecting self checking computer modules into a redundant network in which backup buses and computer modules are provided to circumvent failures. The requirements and design methodology which led to the definition of the building block circuits are discussed.
Hopfield, J J
2008-05-01
The algorithms that simple feedback neural circuits representing a brain area can rapidly carry out are often adequate to solve easy problems but for more difficult problems can return incorrect answers. A new excitatory-inhibitory circuit model of associative memory displays the common human problem of failing to rapidly find a memory when only a small clue is present. The memory model and a related computational network for solving Sudoku puzzles produce answers that contain implicit check bits in the representation of information across neurons, allowing a rapid evaluation of whether the putative answer is correct or incorrect through a computation related to visual pop-out. This fact may account for our strong psychological feeling of right or wrong when we retrieve a nominal memory from a minimal clue. This information allows more difficult computations or memory retrievals to be done in a serial fashion by using the fast but limited capabilities of a computational module multiple times. The mathematics of the excitatory-inhibitory circuits for associative memory and for Sudoku, both of which are understood in terms of energy or Lyapunov functions, is described in detail.
NASA Astrophysics Data System (ADS)
Pavlichin, Dmitri S.; Mabuchi, Hideo
2014-06-01
Nanoscale integrated photonic devices and circuits offer a path to ultra-low power computation at the few-photon level. Here we propose an optical circuit that performs a ubiquitous operation: the controlled, random-access readout of a collection of stored memory phases or, equivalently, the computation of the inner product of a vector of phases with a binary selector" vector, where the arithmetic is done modulo 2pi and the result is encoded in the phase of a coherent field. This circuit, a collection of cascaded interferometers driven by a coherent input field, demonstrates the use of coherence as a computational resource, and of the use of recently-developed mathematical tools for modeling optical circuits with many coupled parts. The construction extends in a straightforward way to the computation of matrix-vector and matrix-matrix products, and, with the inclusion of an optical feedback loop, to the computation of a weighted" readout of stored memory phases. We note some applications of these circuits for error correction and for computing tasks requiring fast vector inner products, e.g. statistical classification and some machine learning algorithms.
NASA Astrophysics Data System (ADS)
Ogiwara, Akifumi; Maekawa, Hikaru; Watanabe, Minoru; Moriwaki, Retsu
2014-02-01
A holographic polymer-dispersed liquid crystal (HPDLC) memory to record multi-context information for an optically reconfigurable gate array is formed by the angle-multiplexing recording using a successive laser exposure in liquid crystal (LC) composites. The laser illumination system is constructed using the half mirror and photomask written by the different configuration contexts placed on the motorized stages under the control of a personal computer. The fabricated holographic memory implements a precise reconstruction of configuration contexts corresponding to the various logical circuits such as OR circuit and NOR circuit by the laser illumination at different incident angle in the HPDLC memory.
Working Memory and Decision-Making in a Frontoparietal Circuit Model
2017-01-01
Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models. SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental “building blocks” of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks. PMID:29114071
Working Memory and Decision-Making in a Frontoparietal Circuit Model.
Murray, John D; Jaramillo, Jorge; Wang, Xiao-Jing
2017-12-13
Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models. SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks. Copyright © 2017 the authors 0270-6474/17/3712167-20$15.00/0.
Parallel reduced-instruction-set-computer architecture for real-time symbolic pattern matching
NASA Astrophysics Data System (ADS)
Parson, Dale E.
1991-03-01
This report discusses ongoing work on a parallel reduced-instruction- set-computer (RISC) architecture for automatic production matching. The PRIOPS compiler takes advantage of the memoryless character of automatic processing by translating a program's collection of automatic production tests into an equivalent combinational circuit-a digital circuit without memory, whose outputs are immediate functions of its inputs. The circuit provides a highly parallel, fine-grain model of automatic matching. The compiler then maps the combinational circuit onto RISC hardware. The heart of the processor is an array of comparators capable of testing production conditions in parallel, Each comparator attaches to private memory that contains virtual circuit nodes-records of the current state of nodes and busses in the combinational circuit. All comparator memories hold identical information, allowing simultaneous update for a single changing circuit node and simultaneous retrieval of different circuit nodes by different comparators. Along with the comparator-based logic unit is a sequencer that determines the current combination of production-derived comparisons to try, based on the combined success and failure of previous combinations of comparisons. The memoryless nature of automatic matching allows the compiler to designate invariant memory addresses for virtual circuit nodes, and to generate the most effective sequences of comparison test combinations. The result is maximal utilization of parallel hardware, indicating speed increases and scalability beyond that found for course-grain, multiprocessor approaches to concurrent Rete matching. Future work will consider application of this RISC architecture to the standard (controlled) Rete algorithm, where search through memory dominates portions of matching.
Transfluxor circuit amplifies sensing current for computer memories
NASA Technical Reports Server (NTRS)
Milligan, G. C.
1964-01-01
To transfer data from the magnetic memory core to an independent core, a reliable sensing amplifier has been developed. Later the data in the independent core is transferred to the arithmetical section of the computer.
Integrated semiconductor-magnetic random access memory system
NASA Technical Reports Server (NTRS)
Katti, Romney R. (Inventor); Blaes, Brent R. (Inventor)
2001-01-01
The present disclosure describes a non-volatile magnetic random access memory (RAM) system having a semiconductor control circuit and a magnetic array element. The integrated magnetic RAM system uses CMOS control circuit to read and write data magnetoresistively. The system provides a fast access, non-volatile, radiation hard, high density RAM for high speed computing.
FPGA-Based, Self-Checking, Fault-Tolerant Computers
NASA Technical Reports Server (NTRS)
Some, Raphael; Rennels, David
2004-01-01
A proposed computer architecture would exploit the capabilities of commercially available field-programmable gate arrays (FPGAs) to enable computers to detect and recover from bit errors. The main purpose of the proposed architecture is to enable fault-tolerant computing in the presence of single-event upsets (SEUs). [An SEU is a spurious bit flip (also called a soft error) caused by a single impact of ionizing radiation.] The architecture would also enable recovery from some soft errors caused by electrical transients and, to some extent, from intermittent and permanent (hard) errors caused by aging of electronic components. A typical FPGA of the current generation contains one or more complete processor cores, memories, and highspeed serial input/output (I/O) channels, making it possible to shrink a board-level processor node to a single integrated-circuit chip. Custom, highly efficient microcontrollers, general-purpose computers, custom I/O processors, and signal processors can be rapidly and efficiently implemented by use of FPGAs. Unfortunately, FPGAs are susceptible to SEUs. Prior efforts to mitigate the effects of SEUs have yielded solutions that degrade performance of the system and require support from external hardware and software. In comparison with other fault-tolerant- computing architectures (e.g., triple modular redundancy), the proposed architecture could be implemented with less circuitry and lower power demand. Moreover, the fault-tolerant computing functions would require only minimal support from circuitry outside the central processing units (CPUs) of computers, would not require any software support, and would be largely transparent to software and to other computer hardware. There would be two types of modules: a self-checking processor module and a memory system (see figure). The self-checking processor module would be implemented on a single FPGA and would be capable of detecting its own internal errors. It would contain two CPUs executing identical programs in lock step, with comparison of their outputs to detect errors. It would also contain various cache local memory circuits, communication circuits, and configurable special-purpose processors that would use self-checking checkers. (The basic principle of the self-checking checker method is to utilize logic circuitry that generates error signals whenever there is an error in either the checker or the circuit being checked.) The memory system would comprise a main memory and a hardware-controlled check-pointing system (CPS) based on a buffer memory denoted the recovery cache. The main memory would contain random-access memory (RAM) chips and FPGAs that would, in addition to everything else, implement double-error-detecting and single-error-correcting memory functions to enable recovery from single-bit errors.
Almeida, Rita; Barbosa, João; Compte, Albert
2015-09-01
The amount of information that can be retained in working memory (WM) is limited. Limitations of WM capacity have been the subject of intense research, especially in trying to specify algorithmic models for WM. Comparatively, neural circuit perspectives have barely been used to test WM limitations in behavioral experiments. Here we used a neuronal microcircuit model for visuo-spatial WM (vsWM) to investigate memory of several items. The model assumes that there is a topographic organization of the circuit responsible for spatial memory retention. This assumption leads to specific predictions, which we tested in behavioral experiments. According to the model, nearby locations should be recalled with a bias, as if the two memory traces showed attraction or repulsion during the delay period depending on distance. Another prediction is that the previously reported loss of memory precision for an increasing number of memory items (memory load) should vanish when the distances between items are controlled for. Both predictions were confirmed experimentally. Taken together, our findings provide support for a topographic neural circuit organization of vsWM, they suggest that interference between similar memories underlies some WM limitations, and they put forward a circuit-based explanation that reconciles previous conflicting results on the dependence of WM precision with load. Copyright © 2015 the American Physiological Society.
2010-07-22
dependent , providing a natural bandwidth match between compute cores and the memory subsystem. • High Bandwidth Dcnsity. Waveguides crossing the chip...simulate this memory access architecture on a 2S6-core chip with a concentrated 64-node network lIsing detailed traces of high-performance embedded...memory modulcs, wc placc memory access poi nts (MAPs) around the pcriphery of the chip connected to thc nctwork. These MAPs, shown in Figure 4, contain
Moradi, Saber; Qiao, Ning; Stefanini, Fabio; Indiveri, Giacomo
2018-02-01
Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here, we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multicore neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.
Transitional circuitry for studying the properties of DNA
NASA Astrophysics Data System (ADS)
Trubochkina, N.
2018-01-01
The article is devoted to a new view of the structure of DNA as an intellectual scheme possessing the properties of logic and memory. The theory of transient circuitry, developed by the author for optimal computer circuits, revealed an amazing structural similarity between mathematical models of transition silicon elements and logic and memory circuits of solid state transient circuitry and atomic models of parts of DNA.
Analog Nonvolatile Computer Memory Circuits
NASA Technical Reports Server (NTRS)
MacLeod, Todd
2007-01-01
In nonvolatile random-access memory (RAM) circuits of a proposed type, digital data would be stored in analog form in ferroelectric field-effect transistors (FFETs). This type of memory circuit would offer advantages over prior volatile and nonvolatile types: In a conventional complementary metal oxide/semiconductor static RAM, six transistors must be used to store one bit, and storage is volatile in that data are lost when power is turned off. In a conventional dynamic RAM, three transistors must be used to store one bit, and the stored bit must be refreshed every few milliseconds. In contrast, in a RAM according to the proposal, data would be retained when power was turned off, each memory cell would contain only two FFETs, and the cell could store multiple bits (the exact number of bits depending on the specific design). Conventional flash memory circuits afford nonvolatile storage, but they operate at reading and writing times of the order of thousands of conventional computer memory reading and writing times and, hence, are suitable for use only as off-line storage devices. In addition, flash memories cease to function after limited numbers of writing cycles. The proposed memory circuits would not be subject to either of these limitations. Prior developmental nonvolatile ferroelectric memories are limited to one bit per cell, whereas, as stated above, the proposed memories would not be so limited. The design of a memory circuit according to the proposal must reflect the fact that FFET storage is only partly nonvolatile, in that the signal stored in an FFET decays gradually over time. (Retention times of some advanced FFETs exceed ten years.) Instead of storing a single bit of data as either a positively or negatively saturated state in a ferroelectric device, each memory cell according to the proposal would store two values. The two FFETs in each cell would be denoted the storage FFET and the control FFET. The storage FFET would store an analog signal value, between the positive and negative FFET saturation values. This signal value would represent a numerical value of interest corresponding to multiple bits: for example, if the memory circuit were designed to distinguish among 16 different analog values, then each cell could store 4 bits. Simultaneously with writing the signal value in the storage FFET, a negative saturation signal value would be stored in the control FFET. The decay of this control-FFET signal from the saturation value would serve as a model of the decay, for use in regenerating the numerical value of interest from its decaying analog signal value. The memory circuit would include addressing, reading, and writing circuitry that would have features in common with the corresponding parts of other memory circuits, but would also have several distinctive features. The writing circuitry would include a digital-to-analog converter (DAC); the reading circuitry would include an analog-to-digital converter (ADC). For writing a numerical value of interest in a given cell, that cell would be addressed, the saturation value would be written in the control FFET in that cell, and the non-saturation analog value representing the numerical value of interest would be generated by use of the DAC and stored in the storage FFET in that cell. For reading the numerical value of interest stored in a given cell, the cell would be addressed, the ADC would convert the decaying control and storage analog signal values to digital values, and an associated fast digital processing circuit would regenerate the numerical value from digital values.
Multilevel Resistance Programming in Conductive Bridge Resistive Memory
NASA Astrophysics Data System (ADS)
Mahalanabis, Debayan
This work focuses on the existence of multiple resistance states in a type of emerging non-volatile resistive memory device known commonly as Programmable Metallization Cell (PMC) or Conductive Bridge Random Access Memory (CBRAM), which can be important for applications such as multi-bit memory as well as non-volatile logic and neuromorphic computing. First, experimental data from small signal, quasi-static and pulsed mode electrical characterization of such devices are presented which clearly demonstrate the inherent multi-level resistance programmability property in CBRAM devices. A physics based analytical CBRAM compact model is then presented which simulates the ion-transport dynamics and filamentary growth mechanism that causes resistance change in such devices. Simulation results from the model are fitted to experimental dynamic resistance switching characteristics. The model designed using Verilog-a language is computation-efficient and can be integrated with industry standard circuit simulation tools for design and analysis of hybrid circuits involving both CMOS and CBRAM devices. Three main circuit applications for CBRAM devices are explored in this work. Firstly, the susceptibility of CBRAM memory arrays to single event induced upsets is analyzed via compact model simulation and experimental heavy ion testing data that show possibility of both high resistance to low resistance and low resistance to high resistance transitions due to ion strikes. Next, a non-volatile sense amplifier based flip-flop architecture is proposed which can help make leakage power consumption negligible by allowing complete shutdown of power supply while retaining its output data in CBRAM devices. Reliability and energy consumption of the flip-flop circuit for different CBRAM low resistance levels and supply voltage values are analyzed and compared to CMOS designs. Possible extension of this architecture for threshold logic function computation using the CBRAM devices as re-configurable resistive weights is also discussed. Lastly, Spike timing dependent plasticity (STDP) based gradual resistance change behavior in CBRAM device fabricated in back-end-of-line on a CMOS die containing integrate and fire CMOS neuron circuits is demonstrated for the first time which indicates the feasibility of using CBRAM devices as electronic synapses in spiking neural network hardware implementations for non-Boolean neuromorphic computing.
Silicon photonic integrated circuits with electrically programmable non-volatile memory functions.
Song, J-F; Lim, A E-J; Luo, X-S; Fang, Q; Li, C; Jia, L X; Tu, X-G; Huang, Y; Zhou, H-F; Liow, T-Y; Lo, G-Q
2016-09-19
Conventional silicon photonic integrated circuits do not normally possess memory functions, which require on-chip power in order to maintain circuit states in tuned or field-configured switching routes. In this context, we present an electrically programmable add/drop microring resonator with a wavelength shift of 426 pm between the ON/OFF states. Electrical pulses are used to control the choice of the state. Our experimental results show a wavelength shift of 2.8 pm/ms and a light intensity variation of ~0.12 dB/ms for a fixed wavelength in the OFF state. Theoretically, our device can accommodate up to 65 states of multi-level memory functions. Such memory functions can be integrated into wavelength division mutiplexing (WDM) filters and applied to optical routers and computing architectures fulfilling large data downloading demands.
Microterminal/Microfiche System for Computer-Based Instruction: Hardware and Software Development.
1980-10-01
Circuit Description and Schematic of Adaptor Module 57 Appendix C Circuit Description The schematics for circuitry used in the microfiche viewer and the...composed of four major components and associated interfaces. The major components are (a) mirroterminal. (Is) microfiche reader. (0) memory module , and (d...sensing of the position of the platen containing the microfiche so that frame locations can be verified by the microterminal software. The memory module is
TiO2-based memristors and ReRAM: materials, mechanisms and models (a review)
NASA Astrophysics Data System (ADS)
Gale, Ella
2014-10-01
The memristor is the fundamental nonlinear circuit element, with uses in computing and computer memory. Resistive Random Access Memory (ReRAM) is a resistive switching memory proposed as a non-volatile memory. In this review we shall summarize the state of the art for these closely-related fields, concentrating on titanium dioxide, the well-utilized and archetypal material for both. We shall cover material properties, switching mechanisms and models to demonstrate what ReRAM and memristor scientists can learn from each other and examine the outlook for these technologies.
NASA Astrophysics Data System (ADS)
Chang, S. S. L.
State of the art technology in circuits, fields, and electronics is discussed. The principles and applications of these technologies to industry, digital processing, microwave semiconductors, and computer-aided design are explained. Important concepts and methodologies in mathematics and physics are reviewed, and basic engineering sciences and associated design methods are dealt with, including: circuit theory and the design of magnetic circuits and active filter synthesis; digital signal processing, including FIR and IIR digital filter design; transmission lines, electromagnetic wave propagation and surface acoustic wave devices. Also considered are: electronics technologies, including power electronics, microwave semiconductors, GaAs devices, and magnetic bubble memories; digital circuits and logic design.
A learnable parallel processing architecture towards unity of memory and computing
NASA Astrophysics Data System (ADS)
Li, H.; Gao, B.; Chen, Z.; Zhao, Y.; Huang, P.; Ye, H.; Liu, L.; Liu, X.; Kang, J.
2015-08-01
Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named “iMemComp”, where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped “iMemComp” with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on “iMemComp” can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area.
A learnable parallel processing architecture towards unity of memory and computing.
Li, H; Gao, B; Chen, Z; Zhao, Y; Huang, P; Ye, H; Liu, L; Liu, X; Kang, J
2015-08-14
Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named "iMemComp", where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped "iMemComp" with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on "iMemComp" can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area.
Cholinergic modulation of cognitive processing: insights drawn from computational models
Newman, Ehren L.; Gupta, Kishan; Climer, Jason R.; Monaghan, Caitlin K.; Hasselmo, Michael E.
2012-01-01
Acetylcholine plays an important role in cognitive function, as shown by pharmacological manipulations that impact working memory, attention, episodic memory, and spatial memory function. Acetylcholine also shows striking modulatory influences on the cellular physiology of hippocampal and cortical neurons. Modeling of neural circuits provides a framework for understanding how the cognitive functions may arise from the influence of acetylcholine on neural and network dynamics. We review the influences of cholinergic manipulations on behavioral performance in working memory, attention, episodic memory, and spatial memory tasks, the physiological effects of acetylcholine on neural and circuit dynamics, and the computational models that provide insight into the functional relationships between the physiology and behavior. Specifically, we discuss the important role of acetylcholine in governing mechanisms of active maintenance in working memory tasks and in regulating network dynamics important for effective processing of stimuli in attention and episodic memory tasks. We also propose that theta rhythm plays a crucial role as an intermediary between the physiological influences of acetylcholine and behavior in episodic and spatial memory tasks. We conclude with a synthesis of the existing modeling work and highlight future directions that are likely to be rewarding given the existing state of the literature for both empiricists and modelers. PMID:22707936
A memristor-based nonvolatile latch circuit
NASA Astrophysics Data System (ADS)
Robinett, Warren; Pickett, Matthew; Borghetti, Julien; Xia, Qiangfei; Snider, Gregory S.; Medeiros-Ribeiro, Gilberto; Williams, R. Stanley
2010-06-01
Memristive devices, which exhibit a dynamical conductance state that depends on the excitation history, can be used as nonvolatile memory elements by storing information as different conductance states. We describe the implementation of a nonvolatile synchronous flip-flop circuit that uses a nanoscale memristive device as the nonvolatile memory element. Controlled testing of the circuit demonstrated successful state storage and restoration, with an error rate of 0.1%, during 1000 power loss events. These results indicate that integration of digital logic devices and memristors could open the way for nonvolatile computation with applications in small platforms that rely on intermittent power sources. This demonstrated feasibility of tight integration of memristors with CMOS (complementary metal-oxide-semiconductor) circuitry challenges the traditional memory hierarchy, in which nonvolatile memory is only available as a large, slow, monolithic block at the bottom of the hierarchy. In contrast, the nonvolatile, memristor-based memory cell can be fast, fine-grained and small, and is compatible with conventional CMOS electronics. This threatens to upset the traditional memory hierarchy, and may open up new architectural possibilities beyond it.
Parallel structures in human and computer memory
NASA Astrophysics Data System (ADS)
Kanerva, Pentti
1986-08-01
If we think of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library: We recognize a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. This paper is about how to construct a computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do. Such a memory is remarkably similar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. The paper concludes that the frame problem of artificial intelligence could be solved by the use of such a memory if we were able to encode information about the world properly.
Parallel structures in human and computer memory
NASA Technical Reports Server (NTRS)
Kanerva, P.
1986-01-01
If one thinks of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library. One recognizes a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. A computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do is constructed. Such a memory is remarkably similiar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. It is concluded that the frame problem of artificial intelligence could be solved by the use of such a memory if one were able to encode information about the world properly.
Pfeiffer, P.; Egusquiza, I. L.; Di Ventra, M.; ...
2016-07-06
Technology based on memristors, resistors with memory whose resistance depends on the history of the crossing charges, has lately enhanced the classical paradigm of computation with neuromorphic architectures. However, in contrast to the known quantized models of passive circuit elements, such as inductors, capacitors or resistors, the design and realization of a quantum memristor is still missing. Here, we introduce the concept of a quantum memristor as a quantum dissipative device, whose decoherence mechanism is controlled by a continuous-measurement feedback scheme, which accounts for the memory. Indeed, we provide numerical simulations showing that memory effects actually persist in the quantummore » regime. Our quantization method, specifically designed for superconducting circuits, may be extended to other quantum platforms, allowing for memristor-type constructions in different quantum technologies. As a result, the proposed quantum memristor is then a building block for neuromorphic quantum computation and quantum simulations of non-Markovian systems.« less
Multi-port, optically addressed RAM
NASA Technical Reports Server (NTRS)
Johnston, Alan R. (Inventor); Nixon, Robert H. (Inventor); Bergman, Larry A. (Inventor); Esener, Sadik (Inventor)
1989-01-01
A random access memory addressing system utilizing optical links between memory and the read/write logic circuits comprises addressing circuits including a plurality of light signal sources, a plurality of optical gates including optical detectors associated with the memory cells, and a holographic optical element adapted to reflect and direct the light signals to the desired memory cell locations. More particularly, it is a multi-port, binary computer memory for interfacing with a plurality of computers. There are a plurality of storage cells for containing bits of binary information, the storage cells being disposed at the intersections of a plurality of row conductors and a plurality of column conductors. There is interfacing logic for receiving information from the computers directing access to ones of the storage cells. There are first light sources associated with the interfacing logic for transmitting a first light beam with the access information modulated thereon. First light detectors are associated with the storage cells for receiving the first light beam, for generating an electrical signal containing the access information, and for conducting the electrical signal to the one of the storage cells to which it is directed. There are holographic optical elements for reflecting the first light beam from the first light sources to the first light detectors.
A multiply-add engine with monolithically integrated 3D memristor crossbar/CMOS hybrid circuit.
Chakrabarti, B; Lastras-Montaño, M A; Adam, G; Prezioso, M; Hoskins, B; Payvand, M; Madhavan, A; Ghofrani, A; Theogarajan, L; Cheng, K-T; Strukov, D B
2017-02-14
Silicon (Si) based complementary metal-oxide semiconductor (CMOS) technology has been the driving force of the information-technology revolution. However, scaling of CMOS technology as per Moore's law has reached a serious bottleneck. Among the emerging technologies memristive devices can be promising for both memory as well as computing applications. Hybrid CMOS/memristor circuits with CMOL (CMOS + "Molecular") architecture have been proposed to combine the extremely high density of the memristive devices with the robustness of CMOS technology, leading to terabit-scale memory and extremely efficient computing paradigm. In this work, we demonstrate a hybrid 3D CMOL circuit with 2 layers of memristive crossbars monolithically integrated on a pre-fabricated CMOS substrate. The integrated crossbars can be fully operated through the underlying CMOS circuitry. The memristive devices in both layers exhibit analog switching behavior with controlled tunability and stable multi-level operation. We perform dot-product operations with the 2D and 3D memristive crossbars to demonstrate the applicability of such 3D CMOL hybrid circuits as a multiply-add engine. To the best of our knowledge this is the first demonstration of a functional 3D CMOL hybrid circuit.
A multiply-add engine with monolithically integrated 3D memristor crossbar/CMOS hybrid circuit
Chakrabarti, B.; Lastras-Montaño, M. A.; Adam, G.; Prezioso, M.; Hoskins, B.; Cheng, K.-T.; Strukov, D. B.
2017-01-01
Silicon (Si) based complementary metal-oxide semiconductor (CMOS) technology has been the driving force of the information-technology revolution. However, scaling of CMOS technology as per Moore’s law has reached a serious bottleneck. Among the emerging technologies memristive devices can be promising for both memory as well as computing applications. Hybrid CMOS/memristor circuits with CMOL (CMOS + “Molecular”) architecture have been proposed to combine the extremely high density of the memristive devices with the robustness of CMOS technology, leading to terabit-scale memory and extremely efficient computing paradigm. In this work, we demonstrate a hybrid 3D CMOL circuit with 2 layers of memristive crossbars monolithically integrated on a pre-fabricated CMOS substrate. The integrated crossbars can be fully operated through the underlying CMOS circuitry. The memristive devices in both layers exhibit analog switching behavior with controlled tunability and stable multi-level operation. We perform dot-product operations with the 2D and 3D memristive crossbars to demonstrate the applicability of such 3D CMOL hybrid circuits as a multiply-add engine. To the best of our knowledge this is the first demonstration of a functional 3D CMOL hybrid circuit. PMID:28195239
Large-Constraint-Length, Fast Viterbi Decoder
NASA Technical Reports Server (NTRS)
Collins, O.; Dolinar, S.; Hsu, In-Shek; Pollara, F.; Olson, E.; Statman, J.; Zimmerman, G.
1990-01-01
Scheme for efficient interconnection makes VLSI design feasible. Concept for fast Viterbi decoder provides for processing of convolutional codes of constraint length K up to 15 and rates of 1/2 to 1/6. Fully parallel (but bit-serial) architecture developed for decoder of K = 7 implemented in single dedicated VLSI circuit chip. Contains six major functional blocks. VLSI circuits perform branch metric computations, add-compare-select operations, and then store decisions in traceback memory. Traceback processor reads appropriate memory locations and puts out decoded bits. Used as building block for decoders of larger K.
NASA Technical Reports Server (NTRS)
1996-01-01
Through Goddard Space Flight Center and Jet Propulsion Laboratory Small Business Innovation Research contracts, Irvine Sensors developed a three-dimensional memory system for a spaceborne data recorder and other applications for NASA. From these contracts, the company created the Memory Short Stack product, a patented technology for stacking integrated circuits that offers higher processing speeds and levels of integration, and lower power requirements. The product is a three-dimensional semiconductor package in which dozens of integrated circuits are stacked upon each other to form a cube. The technology is being used in various computer and telecommunications applications.
Programmable Direct-Memory-Access Controller
NASA Technical Reports Server (NTRS)
Hendry, David F.
1990-01-01
Proposed programmable direct-memory-access controller (DMAC) operates with computer systems of 32000 series, which have 32-bit data buses and use addresses of 24 (or potentially 32) bits. Controller functions with or without help of central processing unit (CPU) and starts itself. Includes such advanced features as ability to compare two blocks of memory for equality and to search block of memory for specific value. Made as single very-large-scale integrated-circuit chip.
NASA Astrophysics Data System (ADS)
Ma, Yitao; Miura, Sadahiko; Honjo, Hiroaki; Ikeda, Shoji; Hanyu, Takahiro; Ohno, Hideo; Endoh, Tetsuo
2017-04-01
A high-density nonvolatile associative memory (NV-AM) based on spin transfer torque magnetoresistive random access memory (STT-MRAM), which achieves highly concurrent and ultralow-power nearest neighbor search with full adaptivity of the template data format, has been proposed and fabricated using the 90 nm CMOS/70 nm perpendicular-magnetic-tunnel-junction hybrid process. A truly compact current-mode circuitry is developed to realize flexibly controllable and high-parallel similarity evaluation, which makes the NV-AM adaptable to any dimensionality and component-bit of template data. A compact dual-stage time-domain minimum searching circuit is also developed, which can freely extend the system for more template data by connecting multiple NM-AM cores without additional circuits for integrated processing. Both the embedded STT-MRAM module and the computing circuit modules in this NV-AM chip are synchronously power-gated to completely eliminate standby power and maximally reduce operation power by only activating the currently accessed circuit blocks. The operations of a prototype chip at 40 MHz are demonstrated by measurement. The average operation power is only 130 µW, and the circuit density is less than 11 µm2/bit. Compared with the latest conventional works in both volatile and nonvolatile approaches, more than 31.3% circuit area reductions and 99.2% power improvements are achieved, respectively. Further power performance analyses are discussed, which verify the special superiority of the proposed NV-AM in low-power and large-memory-based VLSIs.
Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Shuangshuang; Chen, Yousu; Wu, Di
2015-12-09
Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Messagemore » Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.« less
NASA Astrophysics Data System (ADS)
Guarcello, Claudio; Solinas, Paolo; Braggio, Alessandro; Di Ventra, Massimiliano; Giazotto, Francesco
2018-01-01
We propose a superconducting thermal memory device that exploits the thermal hysteresis in a flux-controlled temperature-biased superconducting quantum-interference device (SQUID). This system reveals a flux-controllable temperature bistability, which can be used to define two well-distinguishable thermal logic states. We discuss a suitable writing-reading procedure for these memory states. The time of the memory writing operation is expected to be on the order of approximately 0.2 ns for a Nb-based SQUID in thermal contact with a phonon bath at 4.2 K. We suggest a noninvasive readout scheme for the memory states based on the measurement of the effective resonance frequency of a tank circuit inductively coupled to the SQUID. The proposed device paves the way for a practical implementation of thermal logic and computation. The advantage of this proposal is that it represents also an example of harvesting thermal energy in superconducting circuits.
Computing with volatile memristors: an application of non-pinched hysteresis
NASA Astrophysics Data System (ADS)
Pershin, Y. V.; Shevchenko, S. N.
2017-02-01
The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated theoretically. We have adopted a hysteretic graphene-based field emission structure as a prototype of a volatile memristor, which is characterized by a non-pinched hysteresis loop. A memristive model of the structure is developed and used to simulate a polymorphic circuit implementing stateful logic gates, such as the material implication. Specific regions of parameter space realizing useful logic functions are identified. Our results are applicable to other realizations of volatile memory devices, such as certain NEMS switches.
NASA Astrophysics Data System (ADS)
Lu, Bin; Cheng, Xiaomin; Feng, Jinlong; Guan, Xiawei; Miao, Xiangshui
2016-07-01
Nonvolatile memory devices or circuits that can implement both storage and calculation are a crucial requirement for the efficiency improvement of modern computer. In this work, we realize logic functions by using [GeTe/Sb2Te3]n super lattice phase change memory (PCM) cell in which higher threshold voltage is needed for phase change with a magnetic field applied. First, the [GeTe/Sb2Te3]n super lattice cells were fabricated and the R-V curve was measured. Then we designed the logic circuits with the super lattice PCM cell verified by HSPICE simulation and experiments. Seven basic logic functions are first demonstrated in this letter; then several multi-input logic gates are presented. The proposed logic devices offer the advantages of simple structures and low power consumption, indicating that the super lattice PCM has the potential in the future nonvolatile central processing unit design, facilitating the development of massive parallel computing architecture.
Nere, Andrew; Hashmi, Atif; Cirelli, Chiara; Tononi, Giulio
2013-01-01
Sleep can favor the consolidation of both procedural and declarative memories, promote gist extraction, help the integration of new with old memories, and desaturate the ability to learn. It is often assumed that such beneficial effects are due to the reactivation of neural circuits in sleep to further strengthen the synapses modified during wake or transfer memories to different parts of the brain. A different possibility is that sleep may benefit memory not by further strengthening synapses, but rather by renormalizing synaptic strength to restore cellular homeostasis after net synaptic potentiation in wake. In this way, the sleep-dependent reactivation of neural circuits could result in the competitive down-selection of synapses that are activated infrequently and fit less well with the overall organization of memories. By using computer simulations, we show here that synaptic down-selection is in principle sufficient to explain the beneficial effects of sleep on the consolidation of procedural and declarative memories, on gist extraction, and on the integration of new with old memories, thereby addressing the plasticity-stability dilemma. PMID:24137153
A FPGA-based Measurement System for Nonvolatile Semiconductor Memory Characterization
NASA Astrophysics Data System (ADS)
Bu, Jiankang; White, Marvin
2002-03-01
Low voltage, long retention, high density SONOS nonvolatile semiconductor memory (NVSM) devices are ideally suited for PCMCIA, FLASH and 'smart' cards. The SONOS memory transistor requires characterization with an accurate, rapid measurement system with minimum disturbance to the device. The FPGA-based measurement system includes three parts: 1) a pattern generator implemented with XILINX FPGAs and corresponding software, 2) a high-speed, constant-current, threshold voltage detection circuit, 3) and a data evaluation program, implemented with a LABVIEW program. Fig. 1 shows the general block diagram of the FPGA-based measurement system. The function generator is designed and simulated with XILINX Foundation Software. Under the control of the specific erase/write/read pulses, the analog detect circuit applies operational modes to the SONOS device under test (DUT) and determines the change of the memory-state of the SONOS nonvolatile memory transistor. The TEK460 digitizes the analog threshold voltage output and sends to the PC computer. The data is filtered and averaged with a LABVIEWTM program running on the PC computer and displayed on the monitor in real time. We have implemented the pattern generator with XILINX FPGAs. Fig. 2 shows the block diagram of the pattern generator. We realized the logic control by a method of state machine design. Fig. 3 shows a small part of the state machine. The flexibility of the FPGAs enhances the capabilities of this system and allows measurement variations without hardware changes. The characterization of the nonvolatile memory transistor device under test (DUT), as function of programming voltage and time, is achieved by a high-speed, constant-current threshold voltage detection circuit. The analog detection circuit incorporating fast analog switches controlled digitally with the FPGAs. The schematic circuit diagram is shown in Fig. 4. The various operational modes for the DUT are realized with control signals applied to the analog switches (SW) as shown in Fig. 5. A LABVIEWTM program, on a PC platform, collects and processes the data. The data is displayed on the monitor in real time. This time-domain filtering reduces the digitizing error. Fig. 6 shows the data processing. SONOS nonvolatile semiconductor memories are characterized by erase/write, retention and endurance measurements. Fig. 7 shows the erase/write characteristics of an n-Channel, 5V prog-rammable SONOS memory transistor. Fig.8 shows the retention characteristic of the same SONOS transistor. We have used this system to characterize SONOS nonvolatile semiconductor memory transistors. The attractive features of the test system design lies in the cost-effectiveness and flexibility of the test pattern implementation, fast read-out of memory state, low power, high precision determination of the device threshold voltage, and perhaps most importantly, minimum disturbance, which is indispensable for nonvolatile memory characterization.
Exploring the Nature of Cortical Recurrent Interactions
NASA Astrophysics Data System (ADS)
Morita, Kenji; Kalra, Rita; Aihara, Kazuyuki; Robinson, Hugh P. C.
2011-09-01
Fast rhythmic activity of neural population has been frequently observed in cortical circuits, and suggested to be associated with various cognitive functions including working memory and selective attention. However, precisely how recurrent synaptic interactions, that are prominent in these circuits, shape and/or modulate such population rhythm has not been fully elucidated. We have addressed this issue by combining electrophysiological and computational approaches.
Gao, Shuang; Liu, Gang; Chen, Qilai; Xue, Wuhong; Yang, Huali; Shang, Jie; Chen, Bin; Zeng, Fei; Song, Cheng; Pan, Feng; Li, Run-Wei
2018-02-21
Resistive random access memory (RRAM) with inherent logic-in-memory capability exhibits great potential to construct beyond von-Neumann computers. Particularly, unipolar RRAM is more promising because its single polarity operation enables large-scale crossbar logic-in-memory circuits with the highest integration density and simpler peripheral control circuits. However, unipolar RRAM usually exhibits poor switching uniformity because of random activation of conducting filaments and consequently cannot meet the strict uniformity requirement for logic-in-memory application. In this contribution, a new methodology that constructs cone-shaped conducting filaments by using chemically a active metal cathode is proposed to improve unipolar switching uniformity. Such a peculiar metal cathode will react spontaneously with the oxide switching layer to form an interfacial layer, which together with the metal cathode itself can act as a load resistor to prevent the overgrowth of conducting filaments and thus make them more cone-like. In this way, the rupture of conducting filaments can be strictly limited to the tip region, making their residual parts favorable locations for subsequent filament growth and thus suppressing their random regeneration. As such, a novel "one switch + one unipolar RRAM cell" hybrid structure is capable to realize all 16 Boolean logic functions for large-scale logic-in-memory circuits.
NASA Astrophysics Data System (ADS)
Haron, Adib; Mahdzair, Fazren; Luqman, Anas; Osman, Nazmie; Junid, Syed Abdul Mutalib Al
2018-03-01
One of the most significant constraints of Von Neumann architecture is the limited bandwidth between memory and processor. The cost to move data back and forth between memory and processor is considerably higher than the computation in the processor itself. This architecture significantly impacts the Big Data and data-intensive application such as DNA analysis comparison which spend most of the processing time to move data. Recently, the in-memory processing concept was proposed, which is based on the capability to perform the logic operation on the physical memory structure using a crossbar topology and non-volatile resistive-switching memristor technology. This paper proposes a scheme to map digital equality comparator circuit on memristive memory crossbar array. The 2-bit, 4-bit, 8-bit, 16-bit, 32-bit, and 64-bit of equality comparator circuit are mapped on memristive memory crossbar array by using material implication logic in a sequential and parallel method. The simulation results show that, for the 64-bit word size, the parallel mapping exhibits 2.8× better performance in total execution time than sequential mapping but has a trade-off in terms of energy consumption and area utilization. Meanwhile, the total crossbar area can be reduced by 1.2× for sequential mapping and 1.5× for parallel mapping both by using the overlapping technique.
Contour Detector and Data Acquisition System for the Left Ventricular Outline
NASA Technical Reports Server (NTRS)
Reiber, J. H. C. (Inventor)
1978-01-01
A real-time contour detector and data acquisition system is described for an angiographic apparatus having a video scanner for converting an X-ray image of a structure characterized by a change in brightness level compared with its surrounding into video format and displaying the X-ray image in recurring video fields. The real-time contour detector and data acqusition system includes track and hold circuits; a reference level analog computer circuit; an analog compartor; a digital processor; a field memory; and a computer interface.
Controlled data storage for non-volatile memory cells embedded in nano magnetic logic
NASA Astrophysics Data System (ADS)
Riente, Fabrizio; Ziemys, Grazvydas; Mattersdorfer, Clemens; Boche, Silke; Turvani, Giovanna; Raberg, Wolfgang; Luber, Sebastian; Breitkreutz-v. Gamm, Stephan
2017-05-01
Among the beyond-CMOS technologies, perpendicular Nano Magnetic Logic (pNML) is a promising candidate due to its low power consumption, its non-volatility and its monolithic 3D integrability, which makes it possible to integrate memory and logic into the same device by exploiting the interaction of bi-stable nanomagnets with perpendicular magnetic anisotropy. Logic computation and signal synchronization are achieved by focus ion beam irradiation and by pinning domain walls in magnetic notches. However, in realistic circuits, the information storage and their read-out are crucial issues, often ignored in the exploration of beyond-CMOS devices. In this paper we address these issues by experimentally demonstrating a pNML memory element, whose read and write operations can be controlled by two independent pulsed currents. Our results prove the correct behavior of the proposed structure that enables high density memory embedded in the logic plane of 3D-integrated pNML circuits.
Complex dynamics of memristive circuits: Analytical results and universal slow relaxation
NASA Astrophysics Data System (ADS)
Caravelli, F.; Traversa, F. L.; Di Ventra, M.
2017-02-01
Networks with memristive elements (resistors with memory) are being explored for a variety of applications ranging from unconventional computing to models of the brain. However, analytical results that highlight the role of the graph connectivity on the memory dynamics are still few, thus limiting our understanding of these important dynamical systems. In this paper, we derive an exact matrix equation of motion that takes into account all the network constraints of a purely memristive circuit, and we employ it to derive analytical results regarding its relaxation properties. We are able to describe the memory evolution in terms of orthogonal projection operators onto the subspace of fundamental loop space of the underlying circuit. This orthogonal projection explicitly reveals the coupling between the spatial and temporal sectors of the memristive circuits and compactly describes the circuit topology. For the case of disordered graphs, we are able to explain the emergence of a power-law relaxation as a superposition of exponential relaxation times with a broad range of scales using random matrices. This power law is also universal, namely independent of the topology of the underlying graph but dependent only on the density of loops. In the case of circuits subject to alternating voltage instead, we are able to obtain an approximate solution of the dynamics, which is tested against a specific network topology. These results suggest a much richer dynamics of memristive networks than previously considered.
Toward a Neurobiology of Delusions
Corlett, P.R.; Taylor, J.R.; Wang, X.-J.; Fletcher, P.C.; Krystal, J.H.
2013-01-01
Delusions are the false and often incorrigible beliefs that can cause severe suffering in mental illness. We cannot yet explain them in terms of underlying neurobiological abnormalities. However, by drawing on recent advances in the biological, computational and psychological processes of reinforcement learning, memory, and perception it may be feasible to account for delusions in terms of cognition and brain function. The account focuses on a particular parameter, prediction error – the mismatch between expectation and experience – that provides a computational mechanism common to cortical hierarchies, frontostriatal circuits and the amygdala as well as parietal cortices. We suggest that delusions result from aberrations in how brain circuits specify hierarchical predictions, and how they compute and respond to prediction errors. Defects in these fundamental brain mechanisms can vitiate perception, memory, bodily agency and social learning such that individuals with delusions experience an internal and external world that healthy individuals would find difficult to comprehend. The present model attempts to provide a framework through which we can build a mechanistic and translational understanding of these puzzling symptoms. PMID:20558235
Outline of a novel architecture for cortical computation.
Majumdar, Kaushik
2008-03-01
In this paper a novel architecture for cortical computation has been proposed. This architecture is composed of computing paths consisting of neurons and synapses. These paths have been decomposed into lateral, longitudinal and vertical components. Cortical computation has then been decomposed into lateral computation (LaC), longitudinal computation (LoC) and vertical computation (VeC). It has been shown that various loop structures in the cortical circuit play important roles in cortical computation as well as in memory storage and retrieval, keeping in conformity with the molecular basis of short and long term memory. A new learning scheme for the brain has also been proposed and how it is implemented within the proposed architecture has been explained. A few mathematical results about the architecture have been proposed, some of which are without proof.
Deciphering Neural Codes of Memory during Sleep
Chen, Zhe; Wilson, Matthew A.
2017-01-01
Memories of experiences are stored in the cerebral cortex. Sleep is critical for consolidating hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms on memory consolidation, and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here, we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches for analyzing sleep-associated neural codes (SANC). We focus on two analysis paradigms for sleep-associated memory, and propose a new unsupervised learning framework (“memory first, meaning later”) for unbiased assessment of SANC. PMID:28390699
ERIC Educational Resources Information Center
Miller, Michael J.
1984-01-01
Description of the Macintosh personal, educational, and business computer produced by Apple covers cost; physical characteristics including display devices, circuit boards, and built-in features; company-produced software; third-party produced software; memory and storage capacity; word-processing features; and graphics capabilities. (MBR)
Density-matrix simulation of small surface codes under current and projected experimental noise
NASA Astrophysics Data System (ADS)
O'Brien, T. E.; Tarasinski, B.; DiCarlo, L.
2017-09-01
We present a density-matrix simulation of the quantum memory and computing performance of the distance-3 logical qubit Surface-17, following a recently proposed quantum circuit and using experimental error parameters for transmon qubits in a planar circuit QED architecture. We use this simulation to optimize components of the QEC scheme (e.g., trading off stabilizer measurement infidelity for reduced cycle time) and to investigate the benefits of feedback harnessing the fundamental asymmetry of relaxation-dominated error in the constituent transmons. A lower-order approximate calculation extends these predictions to the distance-5 Surface-49. These results clearly indicate error rates below the fault-tolerance threshold of the surface code, and the potential for Surface-17 to perform beyond the break-even point of quantum memory. However, Surface-49 is required to surpass the break-even point of computation at state-of-the-art qubit relaxation times and readout speeds.
2D bifurcations and Newtonian properties of memristive Chua's circuits
NASA Astrophysics Data System (ADS)
Marszalek, W.; Podhaisky, H.
2016-01-01
Two interesting properties of Chua's circuits are presented. First, two-parameter bifurcation diagrams of Chua's oscillatory circuits with memristors are presented. To obtain various 2D bifurcation images a substantial numerical effort, possibly with parallel computations, is needed. The numerical algorithm is described first and its numerical code for 2D bifurcation image creation is available for free downloading. Several color 2D images and the corresponding 1D greyscale bifurcation diagrams are included. Secondly, Chua's circuits are linked to Newton's law φ ''= F(t,φ,φ')/m with φ=\\text{flux} , constant m > 0, and the force term F(t,φ,φ') containing memory terms. Finally, the jounce scalar equations for Chua's circuits are also discussed.
Xyce parallel electronic simulator users guide, version 6.1
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keiter, Eric R; Mei, Ting; Russo, Thomas V.
This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas; Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers; A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to developmore » new types of analysis without requiring the implementation of analysis-specific device models; Device models that are specifically tailored to meet Sandia's needs, including some radiationaware devices (for Sandia users only); and Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase-a message passing parallel implementation-which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.« less
Xyce parallel electronic simulator users' guide, Version 6.0.1.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keiter, Eric R; Mei, Ting; Russo, Thomas V.
This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to developmore » new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandias needs, including some radiationaware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase a message passing parallel implementation which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.« less
Xyce parallel electronic simulator users guide, version 6.0.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keiter, Eric R; Mei, Ting; Russo, Thomas V.
This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to developmore » new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandias needs, including some radiationaware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase a message passing parallel implementation which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.« less
A Test Methodology for Determining Space-Readiness of Xilinx SRAM-Based FPGA Designs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Quinn, Heather M; Graham, Paul S; Morgan, Keith S
2008-01-01
Using reconfigurable, static random-access memory (SRAM) based field-programmable gate arrays (FPGAs) for space-based computation has been an exciting area of research for the past decade. Since both the circuit and the circuit's state is stored in radiation-tolerant memory, both could be alterd by the harsh space radiation environment. Both the circuit and the circuit's state can be prote cted by triple-moduler redundancy (TMR), but applying TMR to FPGA user designs is often an error-prone process. Faulty application of TMR could cause the FPGA user circuit to output incorrect data. This paper will describe a three-tiered methodology for testing FPGA usermore » designs for space-readiness. We will describe the standard approach to testing FPGA user designs using a particle accelerator, as well as two methods using fault injection and a modeling tool. While accelerator testing is the current 'gold standard' for pre-launch testing, we believe the use of fault injection and modeling tools allows for easy, cheap and uniform access for discovering errors early in the design process.« less
Beyond Moore’s technologies: operation principles of a superconductor alternative
Klenov, Nikolay V; Bakurskiy, Sergey V; Kupriyanov, Mikhail Yu; Gudkov, Alexander L; Sidorenko, Anatoli S
2017-01-01
The predictions of Moore’s law are considered by experts to be valid until 2020 giving rise to “post-Moore’s” technologies afterwards. Energy efficiency is one of the major challenges in high-performance computing that should be answered. Superconductor digital technology is a promising post-Moore’s alternative for the development of supercomputers. In this paper, we consider operation principles of an energy-efficient superconductor logic and memory circuits with a short retrospective review of their evolution. We analyze their shortcomings in respect to computer circuits design. Possible ways of further research are outlined. PMID:29354341
A review of emerging non-volatile memory (NVM) technologies and applications
NASA Astrophysics Data System (ADS)
Chen, An
2016-11-01
This paper will review emerging non-volatile memory (NVM) technologies, with the focus on phase change memory (PCM), spin-transfer-torque random-access-memory (STTRAM), resistive random-access-memory (RRAM), and ferroelectric field-effect-transistor (FeFET) memory. These promising NVM devices are evaluated in terms of their advantages, challenges, and applications. Their performance is compared based on reported parameters of major industrial test chips. Memory selector devices and cell structures are discussed. Changing market trends toward low power (e.g., mobile, IoT) and data-centric applications create opportunities for emerging NVMs. High-performance and low-cost emerging NVMs may simplify memory hierarchy, introduce non-volatility in logic gates and circuits, reduce system power, and enable novel architectures. Storage-class memory (SCM) based on high-density NVMs could fill the performance and density gap between memory and storage. Some unique characteristics of emerging NVMs can be utilized for novel applications beyond the memory space, e.g., neuromorphic computing, hardware security, etc. In the beyond-CMOS era, emerging NVMs have the potential to fulfill more important functions and enable more efficient, intelligent, and secure computing systems.
Atomic memory access hardware implementations
Ahn, Jung Ho; Erez, Mattan; Dally, William J
2015-02-17
Atomic memory access requests are handled using a variety of systems and methods. According to one example method, a data-processing circuit having an address-request generator that issues requests to a common memory implements a method of processing the requests using a memory-access intervention circuit coupled between the generator and the common memory. The method identifies a current atomic-memory access request from a plurality of memory access requests. A data set is stored that corresponds to the current atomic-memory access request in a data storage circuit within the intervention circuit. It is determined whether the current atomic-memory access request corresponds to at least one previously-stored atomic-memory access request. In response to determining correspondence, the current request is implemented by retrieving data from the common memory. The data is modified in response to the current request and at least one other access request in the memory-access intervention circuit.
Computer hardware for radiologists: Part I
Indrajit, IK; Alam, A
2010-01-01
Computers are an integral part of modern radiology practice. They are used in different radiology modalities to acquire, process, and postprocess imaging data. They have had a dramatic influence on contemporary radiology practice. Their impact has extended further with the emergence of Digital Imaging and Communications in Medicine (DICOM), Picture Archiving and Communication System (PACS), Radiology information system (RIS) technology, and Teleradiology. A basic overview of computer hardware relevant to radiology practice is presented here. The key hardware components in a computer are the motherboard, central processor unit (CPU), the chipset, the random access memory (RAM), the memory modules, bus, storage drives, and ports. The personnel computer (PC) has a rectangular case that contains important components called hardware, many of which are integrated circuits (ICs). The fiberglass motherboard is the main printed circuit board and has a variety of important hardware mounted on it, which are connected by electrical pathways called “buses”. The CPU is the largest IC on the motherboard and contains millions of transistors. Its principal function is to execute “programs”. A Pentium® 4 CPU has transistors that execute a billion instructions per second. The chipset is completely different from the CPU in design and function; it controls data and interaction of buses between the motherboard and the CPU. Memory (RAM) is fundamentally semiconductor chips storing data and instructions for access by a CPU. RAM is classified by storage capacity, access speed, data rate, and configuration. PMID:21042437
NASA Astrophysics Data System (ADS)
Neklyudov, A. A.; Savenkov, V. N.; Sergeyez, A. G.
1984-06-01
Memories are improved by increasing speed or the memory volume on a single chip. The most effective means for increasing speeds in bipolar memories are current control circuits with the lowest extraction times for a specific power consumption (1/4 pJ/bit). The control current circuitry involves multistage current switches and circuits accelerating transient processes in storage elements and links. Circuit principles for the design of bipolar memories with maximum speeds for an assigned minimum of circuit topology are analyzed. Two main classes of storage with current control are considered: the ECL type and super-integrated injection type storage with data capacities of N = 1/4 and N 4/16, respectively. The circuits reduce logic voltage differentials and the volumes of lexical and discharge buses and control circuit buses. The limiting speed is determined by the antiinterference requirements of the memory in storage and extraction modes.
A silicon-nanowire memory driven by optical gradient force induced bistability
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dong, B.; Institute of Microelectronics, A*STAR; Cai, H., E-mail: caih@ime.a-star.edu.sg
2015-12-28
In this paper, a bistable optical-driven silicon-nanowire memory is demonstrated, which employs ring resonator to generate optical gradient force over a doubly clamped silicon-nanowire. Two stable deformation positions of a doubly clamped silicon-nanowire represent two memory states (“0” and “1”) and can be set/reset by modulating the light intensity (<3 mW) based on the optical force induced bistability. The time response of the optical-driven memory is less than 250 ns. It has applications in the fields of all optical communication, quantum computing, and optomechanical circuits.
Quantum computers: Definition and implementations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Perez-Delgado, Carlos A.; Kok, Pieter
The DiVincenzo criteria for implementing a quantum computer have been seminal in focusing both experimental and theoretical research in quantum-information processing. These criteria were formulated specifically for the circuit model of quantum computing. However, several new models for quantum computing (paradigms) have been proposed that do not seem to fit the criteria well. Therefore, the question is what are the general criteria for implementing quantum computers. To this end, a formal operational definition of a quantum computer is introduced. It is then shown that, according to this definition, a device is a quantum computer if it obeys the following criteria:more » Any quantum computer must consist of a quantum memory, with an additional structure that (1) facilitates a controlled quantum evolution of the quantum memory; (2) includes a method for information theoretic cooling of the memory; and (3) provides a readout mechanism for subsets of the quantum memory. The criteria are met when the device is scalable and operates fault tolerantly. We discuss various existing quantum computing paradigms and how they fit within this framework. Finally, we present a decision tree for selecting an avenue toward building a quantum computer. This is intended to help experimentalists determine the most natural paradigm given a particular physical implementation.« less
Similarity between the response of memristive and memcapacitive circuits subjected to ramped voltage
NASA Astrophysics Data System (ADS)
Kanygin, Mikhail A.; Katkov, Mikhail V.; Pershin, Yuriy V.
2017-07-01
We report a similar feature in the response of resistor-memristor and capacitor-memcapacitor circuits with threshold-type memory devices driven by triangular waveform voltage. In both cases, the voltage across the memory device is stabilized during the switching of the memory device state. While in the memristive circuit this feature is observed when the applied voltage changes in one direction, the memcapacitive circuit with a ferroelectric memcapacitor demonstrates the voltage stabilization effect at both sweep directions. The discovered behavior of capacitor-memcapacitor circuit is also demonstrated experimentally. We anticipate that our observation can be used in the design of electronic circuits with emergent memory devices as well as in the identification and characterization of memory effects in threshold-type memory devices.
Szalisznyó, Krisztina; Silverstein, David; Teichmann, Marc; Duffau, Hugues; Smits, Anja
2017-01-01
A growing body of literature supports a key role of fronto-striatal circuits in language perception. It is now known that the striatum plays a role in engaging attentional resources and linguistic rule computation while also serving phonological short-term memory capabilities. The ventral semantic and the dorsal phonological stream dichotomy assumed for spoken language processing also seems to play a role in cortico-striatal perception. Based on recent studies that correlate deep Broca-striatal pathways with complex syntax performance, we used a previously developed computational model of frontal-striatal syntax circuits and hypothesized that different parallel language pathways may contribute to canonical and non-canonical sentence comprehension separately. We modified and further analyzed a thematic role assignment task and corresponding reservoir computing model of language circuits, as previously developed by Dominey and coworkers. We examined the models performance under various parameter regimes, by influencing how fast the presented language input decays and altering the temporal dynamics of activated word representations. This enabled us to quantify canonical and non-canonical sentence comprehension abilities. The modeling results suggest that separate cortico-cortical and cortico-striatal circuits may be recruited differently for processing syntactically more difficult and less complicated sentences. Alternatively, a single circuit would need to dynamically and adaptively adjust to syntactic complexity. Copyright © 2016. Published by Elsevier Inc.
Merlin - Massively parallel heterogeneous computing
NASA Technical Reports Server (NTRS)
Wittie, Larry; Maples, Creve
1989-01-01
Hardware and software for Merlin, a new kind of massively parallel computing system, are described. Eight computers are linked as a 300-MIPS prototype to develop system software for a larger Merlin network with 16 to 64 nodes, totaling 600 to 3000 MIPS. These working prototypes help refine a mapped reflective memory technique that offers a new, very general way of linking many types of computer to form supercomputers. Processors share data selectively and rapidly on a word-by-word basis. Fast firmware virtual circuits are reconfigured to match topological needs of individual application programs. Merlin's low-latency memory-sharing interfaces solve many problems in the design of high-performance computing systems. The Merlin prototypes are intended to run parallel programs for scientific applications and to determine hardware and software needs for a future Teraflops Merlin network.
Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition.
Grossberg, Stephen
2007-01-01
A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of preattentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.
System architecture of a gallium arsenide one-gigahertz digital IC tester
NASA Technical Reports Server (NTRS)
Fouts, Douglas J.; Johnson, John M.; Butner, Steven E.; Long, Stephen I.
1987-01-01
The design for a 1-GHz digital integrated circuit tester for the evaluation of custom GaAs chips and subsystems is discussed. Technology-related problems affecting the design of a GaAs computer are discussed, with emphasis on the problems introduced by long printed-circuit-board interconnect. High-speed interface modules provide a link between the low-speed microprocessor and the chip under test. Memory-multiplexer and memory-shift register architectures for the storage of test vectors are described in addition to an architecture for local data storage consisting of a long chain of GaAs shift registers. The tester is constructed around a VME system card cage and backplane, and very little high-speed interconnect exists between boards. The tester has a three part self-test consisting of a CPU board confidence test, a main memory confidence test, and a high-speed interface module functional test.
Theory of Connectivity: Nature and Nurture of Cell Assemblies and Cognitive Computation.
Li, Meng; Liu, Jun; Tsien, Joe Z
2016-01-01
Richard Semon and Donald Hebb are among the firsts to put forth the notion of cell assembly-a group of coherently or sequentially-activated neurons-to represent percept, memory, or concept. Despite the rekindled interest in this century-old idea, the concept of cell assembly still remains ill-defined and its operational principle is poorly understood. What is the size of a cell assembly? How should a cell assembly be organized? What is the computational logic underlying Hebbian cell assemblies? How might Nature vs. Nurture interact at the level of a cell assembly? In contrast to the widely assumed randomness within the mature but naïve cell assembly, the Theory of Connectivity postulates that the brain consists of the developmentally pre-programmed cell assemblies known as the functional connectivity motif (FCM). Principal cells within such FCM is organized by the power-of-two-based mathematical principle that guides the construction of specific-to-general combinatorial connectivity patterns in neuronal circuits, giving rise to a full range of specific features, various relational patterns, and generalized knowledge. This pre-configured canonical computation is predicted to be evolutionarily conserved across many circuits, ranging from these encoding memory engrams and imagination to decision-making and motor control. Although the power-of-two-based wiring and computational logic places a mathematical boundary on an individual's cognitive capacity, the fullest intellectual potential can be brought about by optimized nature and nurture. This theory may also open up a new avenue to examining how genetic mutations and various drugs might impair or improve the computational logic of brain circuits.
Theory of Connectivity: Nature and Nurture of Cell Assemblies and Cognitive Computation
Li, Meng; Liu, Jun; Tsien, Joe Z.
2016-01-01
Richard Semon and Donald Hebb are among the firsts to put forth the notion of cell assembly—a group of coherently or sequentially-activated neurons—to represent percept, memory, or concept. Despite the rekindled interest in this century-old idea, the concept of cell assembly still remains ill-defined and its operational principle is poorly understood. What is the size of a cell assembly? How should a cell assembly be organized? What is the computational logic underlying Hebbian cell assemblies? How might Nature vs. Nurture interact at the level of a cell assembly? In contrast to the widely assumed randomness within the mature but naïve cell assembly, the Theory of Connectivity postulates that the brain consists of the developmentally pre-programmed cell assemblies known as the functional connectivity motif (FCM). Principal cells within such FCM is organized by the power-of-two-based mathematical principle that guides the construction of specific-to-general combinatorial connectivity patterns in neuronal circuits, giving rise to a full range of specific features, various relational patterns, and generalized knowledge. This pre-configured canonical computation is predicted to be evolutionarily conserved across many circuits, ranging from these encoding memory engrams and imagination to decision-making and motor control. Although the power-of-two-based wiring and computational logic places a mathematical boundary on an individual’s cognitive capacity, the fullest intellectual potential can be brought about by optimized nature and nurture. This theory may also open up a new avenue to examining how genetic mutations and various drugs might impair or improve the computational logic of brain circuits. PMID:27199674
Updating Procedures Can Reorganize the Neural Circuit Supporting a Fear Memory.
Kwapis, Janine L; Jarome, Timothy J; Ferrara, Nicole C; Helmstetter, Fred J
2017-07-01
Established memories undergo a period of vulnerability following retrieval, a process termed 'reconsolidation.' Recent work has shown that the hypothetical process of reconsolidation is only triggered when new information is presented during retrieval, suggesting that this process may allow existing memories to be modified. Reconsolidation has received increasing attention as a possible therapeutic target for treating disorders that stem from traumatic memories, yet little is known about how this process changes the original memory. In particular, it is unknown whether reconsolidation can reorganize the neural circuit supporting an existing memory after that memory is modified with new information. Here, we show that trace fear memory undergoes a protein synthesis-dependent reconsolidation process following exposure to a single updating trial of delay conditioning. Further, this reconsolidation-dependent updating process appears to reorganize the neural circuit supporting the trace-trained memory, so that it better reflects the circuit supporting delay fear. Specifically, after a trace-to-delay update session, the amygdala is now required for extinction of the updated memory but the retrosplenial cortex is no longer required for retrieval. These results suggest that updating procedures could be used to force a complex, poorly defined memory circuit to rely on a better-defined neural circuit that may be more amenable to behavioral or pharmacological manipulation. This is the first evidence that exposure to new information can fundamentally reorganize the neural circuit supporting an existing memory.
NASA Space Engineering Research Center for VLSI systems design
NASA Technical Reports Server (NTRS)
1991-01-01
This annual review reports the center's activities and findings on very large scale integration (VLSI) systems design for 1990, including project status, financial support, publications, the NASA Space Engineering Research Center (SERC) Symposium on VLSI Design, research results, and outreach programs. Processor chips completed or under development are listed. Research results summarized include a design technique to harden complementary metal oxide semiconductors (CMOS) memory circuits against single event upset (SEU); improved circuit design procedures; and advances in computer aided design (CAD), communications, computer architectures, and reliability design. Also described is a high school teacher program that exposes teachers to the fundamentals of digital logic design.
Interface Provides Standard-Bus Communication
NASA Technical Reports Server (NTRS)
Culliton, William G.
1995-01-01
Microprocessor-controlled interface (IEEE-488/LVABI) incorporates service-request and direct-memory-access features. Is circuit card enabling digital communication between system called "laser auto-covariance buffer interface" (LVABI) and compatible personal computer via general-purpose interface bus (GPIB) conforming to Institute for Electrical and Electronics Engineers (IEEE) Standard 488. Interface serves as second interface enabling first interface to exploit advantages of GPIB, via utility software written specifically for GPIB. Advantages include compatibility with multitasking and support of communication among multiple computers. Basic concept also applied in designing interfaces for circuits other than LVABI for unidirectional or bidirectional handling of parallel data up to 16 bits wide.
Deciphering Neural Codes of Memory during Sleep.
Chen, Zhe; Wilson, Matthew A
2017-05-01
Memories of experiences are stored in the cerebral cortex. Sleep is critical for the consolidation of hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms in memory consolidation and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches to the analysis of sleep-associated neural codes (SANCs). We focus on two analysis paradigms for sleep-associated memory and propose a new unsupervised learning framework ('memory first, meaning later') for unbiased assessment of SANCs. Copyright © 2017 Elsevier Ltd. All rights reserved.
New World Vistas: New Models of Computation Lattice Based Quantum Computation
1996-07-25
ro ns Eniac (18,000 vacuum tubes) UNIVAC II (core memory) Digital Devices magnetostrictive delay line Intel 1103 integrated circuit IBM 3340 disk...in areal size of a bit for the last fifty years since the 1946 Eniac computer. 1 Planned Research I propose to consider the feasibility of implement...tech- nology. Fiqure 1 is a log-linear plot of data for the areal size of a bit over the last fifty years (from 18,000 bits in the 1946 Eniac computer
From Contextual Fear to a Dynamic View of Memory Systems
Fanselow, Michael S
2009-01-01
The brain does not learn and remember in a unitary fashion. Rather, different circuits specialize in certain classes of problems and encode different types of information. Damage to one of these systems typically results in amnesia only for the form of memory that is the affected region's specialty. How does the brain allocate a specific category of memory to a particular circuit? This question has received little attention. The currently dominant view, Multiple Memory Systems Theory, assumes that such abilities are hard-wired. Using fear conditioning as a paradigmatic case, I propose an alternative model in which mnemonic processing is allocated to specific circuits through a dynamic process. Potential circuits compete to form memories with the most efficient circuits emerging as winners. However, alternate circuits compensate when these “primary” circuits are compromised. PMID:19939724
SODR Memory Control Buffer Control ASIC
NASA Technical Reports Server (NTRS)
Hodson, Robert F.
1994-01-01
The Spacecraft Optical Disk Recorder (SODR) is a state of the art mass storage system for future NASA missions requiring high transmission rates and a large capacity storage system. This report covers the design and development of an SODR memory buffer control applications specific integrated circuit (ASIC). The memory buffer control ASIC has two primary functions: (1) buffering data to prevent loss of data during disk access times, (2) converting data formats from a high performance parallel interface format to a small computer systems interface format. Ten 144 p in, 50 MHz CMOS ASIC's were designed, fabricated and tested to implement the memory buffer control function.
Uncertain behaviours of integrated circuits improve computational performance.
Yoshimura, Chihiro; Yamaoka, Masanao; Hayashi, Masato; Okuyama, Takuya; Aoki, Hidetaka; Kawarabayashi, Ken-ichi; Mizuno, Hiroyuki
2015-11-20
Improvements to the performance of conventional computers have mainly been achieved through semiconductor scaling; however, scaling is reaching its limitations. Natural phenomena, such as quantum superposition and stochastic resonance, have been introduced into new computing paradigms to improve performance beyond these limitations. Here, we explain that the uncertain behaviours of devices due to semiconductor scaling can improve the performance of computers. We prototyped an integrated circuit by performing a ground-state search of the Ising model. The bit errors of memory cell devices holding the current state of search occur probabilistically by inserting fluctuations into dynamic device characteristics, which will be actualised in the future to the chip. As a result, we observed more improvements in solution accuracy than that without fluctuations. Although the uncertain behaviours of devices had been intended to be eliminated in conventional devices, we demonstrate that uncertain behaviours has become the key to improving computational performance.
NASA Astrophysics Data System (ADS)
La Barbera, Selina; Vincent, Adrien F.; Vuillaume, Dominique; Querlioz, Damien; Alibart, Fabien
2016-12-01
Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Braiman, Yehuda; Neschke, Brendan; Nair, Niketh S.
Here, we study memory states of a circuit consisting of a small inductively coupled Josephson junction array and introduce basic (write, read, and reset) memory operations logics of the circuit. The presented memory operation paradigm is fundamentally different from conventional single quantum flux operation logics. We calculate stability diagrams of the zero-voltage states and outline memory states of the circuit. We also calculate access times and access energies for basic memory operations.
NASA Technical Reports Server (NTRS)
Ross, Muriel D.
1991-01-01
The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.
Logic computation in phase change materials by threshold and memory switching.
Cassinerio, M; Ciocchini, N; Ielmini, D
2013-11-06
Memristors, namely hysteretic devices capable of changing their resistance in response to applied electrical stimuli, may provide new opportunities for future memory and computation, thanks to their scalable size, low switching energy and nonvolatile nature. We have developed a functionally complete set of logic functions including NOR, NAND and NOT gates, each utilizing a single phase-change memristor (PCM) where resistance switching is due to the phase transformation of an active chalcogenide material. The logic operations are enabled by the high functionality of nanoscale phase change, featuring voltage comparison, additive crystallization and pulse-induced amorphization. The nonvolatile nature of memristive states provides the basis for developing reconfigurable hybrid logic/memory circuits featuring low-power and high-speed switching. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A Survey of Memristive Threshold Logic Circuits.
Maan, Akshay Kumar; Jayadevi, Deepthi Anirudhan; James, Alex Pappachen
2017-08-01
In this paper, we review different memristive threshold logic (MTL) circuits that are inspired from the synaptic action of the flow of neurotransmitters in the biological brain. The brainlike generalization ability and the area minimization of these threshold logic circuits aim toward crossing Moore's law boundaries at device, circuits, and systems levels. Fast switching memory, signal processing, control systems, programmable logic, image processing, reconfigurable computing, and pattern recognition are identified as some of the potential applications of MTL systems. The physical realization of nanoscale devices with memristive behavior from materials, such as TiO 2 , ferroelectrics, silicon, and polymers, has accelerated research effort in these application areas, inspiring the scientific community to pursue the design of high-speed, low-cost, low-power, and high-density neuromorphic architectures.
"Shape function + memory mechanism"-based hysteresis modeling of magnetorheological fluid actuators
NASA Astrophysics Data System (ADS)
Qian, Li-Jun; Chen, Peng; Cai, Fei-Long; Bai, Xian-Xu
2018-03-01
A hysteresis model based on "shape function + memory mechanism" is presented and its feasibility is verified through modeling the hysteresis behavior of a magnetorheological (MR) damper. A hysteresis phenomenon in resistor-capacitor (RC) circuit is first presented and analyzed. In the hysteresis model, the "memory mechanism" originating from the charging and discharging processes of the RC circuit is constructed by adopting a virtual displacement variable and updating laws for the reference points. The "shape function" is achieved and generalized from analytical solutions of the simple semi-linear Duhem model. Using the approach, the memory mechanism reveals the essence of specific Duhem model and the general shape function provides a direct and clear means to fit the hysteresis loop. In the frame of the structure of a "Restructured phenomenological model", the original hysteresis operator, i.e., the Bouc-Wen operator, is replaced with the new hysteresis operator. The comparative work with the Bouc-Wen operator based model demonstrates superior performances of high computational efficiency and comparable accuracy of the new hysteresis operator-based model.
A self-resetting spiking phase-change neuron
NASA Astrophysics Data System (ADS)
Cobley, R. A.; Hayat, H.; Wright, C. D.
2018-05-01
Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.
A self-resetting spiking phase-change neuron.
Cobley, R A; Hayat, H; Wright, C D
2018-05-11
Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.
Persistent activity in a recurrent circuit underlies courtship memory in Drosophila.
Zhao, Xiaoliang; Lenek, Daniela; Dag, Ugur; Dickson, Barry J; Keleman, Krystyna
2018-01-11
Recurrent connections are thought to be a common feature of the neural circuits that encode memories, but how memories are laid down in such circuits is not fully understood. Here we present evidence that courtship memory in Drosophila relies on the recurrent circuit between mushroom body gamma (MBγ), M6 output, and aSP13 dopaminergic neurons. We demonstrate persistent neuronal activity of aSP13 neurons and show that it transiently potentiates synaptic transmission from MBγ>M6 neurons. M6 neurons in turn provide input to aSP13 neurons, prolonging potentiation of MB γ >M6 synapses over time periods that match short-term memory. These data support a model in which persistent aSP13 activity within a recurrent circuit lays the foundation for a short-term memory. © 2018, Zhao et al.
Persistent activity in a recurrent circuit underlies courtship memory in Drosophila
Zhao, Xiaoliang; Lenek, Daniela; Dag, Ugur; Dickson, Barry J
2018-01-01
Recurrent connections are thought to be a common feature of the neural circuits that encode memories, but how memories are laid down in such circuits is not fully understood. Here we present evidence that courtship memory in Drosophila relies on the recurrent circuit between mushroom body gamma (MBγ), M6 output, and aSP13 dopaminergic neurons. We demonstrate persistent neuronal activity of aSP13 neurons and show that it transiently potentiates synaptic transmission from MBγ>M6 neurons. M6 neurons in turn provide input to aSP13 neurons, prolonging potentiation of MBγ>M6 synapses over time periods that match short-term memory. These data support a model in which persistent aSP13 activity within a recurrent circuit lays the foundation for a short-term memory. PMID:29322941
QCDOC: A 10-teraflops scale computer for lattice QCD
NASA Astrophysics Data System (ADS)
Chen, D.; Christ, N. H.; Cristian, C.; Dong, Z.; Gara, A.; Garg, K.; Joo, B.; Kim, C.; Levkova, L.; Liao, X.; Mawhinney, R. D.; Ohta, S.; Wettig, T.
2001-03-01
The architecture of a new class of computers, optimized for lattice QCD calculations, is described. An individual node is based on a single integrated circuit containing a PowerPC 32-bit integer processor with a 1 Gflops 64-bit IEEE floating point unit, 4 Mbyte of memory, 8 Gbit/sec nearest-neighbor communications and additional control and diagnostic circuitry. The machine's name, QCDOC, derives from "QCD On a Chip".
Reprogrammable read only variable threshold transistor memory with isolated addressing buffer
Lodi, Robert J.
1976-01-01
A monolithic integrated circuit, fully decoded memory comprises a rectangular array of variable threshold field effect transistors organized into a plurality of multi-bit words. Binary address inputs to the memory are decoded by a field effect transistor decoder into a plurality of word selection lines each of which activates an address buffer circuit. Each address buffer circuit, in turn, drives a word line of the memory array. In accordance with the word line selected by the decoder the activated buffer circuit directs reading or writing voltages to the transistors comprising the memory words. All of the buffer circuits additionally are connected to a common terminal for clearing all of the memory transistors to a predetermined state by the application to the common terminal of a large magnitude voltage of a predetermined polarity. The address decoder, the buffer and the memory array, as well as control and input/output control and buffer field effect transistor circuits, are fabricated on a common substrate with means provided to isolate the substrate of the address buffer transistors from the remainder of the substrate so that the bulk clearing function of simultaneously placing all of the memory transistors into a predetermined state can be performed.
Xyce™ Parallel Electronic Simulator Users' Guide, Version 6.5.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keiter, Eric R.; Aadithya, Karthik V.; Mei, Ting
This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to developmore » new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase -- a message passing parallel implementation -- which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The information herein is subject to change without notice. Copyright © 2002-2016 Sandia Corporation. All rights reserved.« less
Design structure for in-system redundant array repair in integrated circuits
Bright, Arthur A.; Crumley, Paul G.; Dombrowa, Marc; Douskey, Steven M.; Haring, Rudolf A.; Oakland, Steven F.; Quellette, Michael R.; Strissel, Scott A.
2008-11-25
A design structure for repairing an integrated circuit during operation of the integrated circuit. The integrated circuit comprising of a multitude of memory arrays and a fuse box holding control data for controlling redundancy logic of the arrays. The design structure provides the integrated circuit with a control data selector for passing the control data from the fuse box to the memory arrays; providing a source of alternate control data, external of the integrated circuit; and connecting the source of alternate control data to the control data selector. The design structure further passes the alternate control data from the source thereof, through the control data selector and to the memory arrays to control the redundancy logic of the memory arrays.
NASA Technical Reports Server (NTRS)
Stehle, Roy H.; Ogier, Richard G.
1993-01-01
Alternatives for realizing a packet-based network switch for use on a frequency division multiple access/time division multiplexed (FDMA/TDM) geostationary communication satellite were investigated. Each of the eight downlink beams supports eight directed dwells. The design needed to accommodate multicast packets with very low probability of loss due to contention. Three switch architectures were designed and analyzed. An output-queued, shared bus system yielded a functionally simple system, utilizing a first-in, first-out (FIFO) memory per downlink dwell, but at the expense of a large total memory requirement. A shared memory architecture offered the most efficiency in memory requirements, requiring about half the memory of the shared bus design. The processing requirement for the shared-memory system adds system complexity that may offset the benefits of the smaller memory. An alternative design using a shared memory buffer per downlink beam decreases circuit complexity through a distributed design, and requires at most 1000 packets of memory more than the completely shared memory design. Modifications to the basic packet switch designs were proposed to accommodate circuit-switched traffic, which must be served on a periodic basis with minimal delay. Methods for dynamically controlling the downlink dwell lengths were developed and analyzed. These methods adapt quickly to changing traffic demands, and do not add significant complexity or cost to the satellite and ground station designs. Methods for reducing the memory requirement by not requiring the satellite to store full packets were also proposed and analyzed. In addition, optimal packet and dwell lengths were computed as functions of memory size for the three switch architectures.
Generalization Through the Recurrent Interaction of Episodic Memories
Kumaran, Dharshan; McClelland, James L.
2012-01-01
In this article, we present a perspective on the role of the hippocampal system in generalization, instantiated in a computational model called REMERGE (recurrency and episodic memory results in generalization). We expose a fundamental, but neglected, tension between prevailing computational theories that emphasize the function of the hippocampus in pattern separation (Marr, 1971; McClelland, McNaughton, & O'Reilly, 1995), and empirical support for its role in generalization and flexible relational memory (Cohen & Eichenbaum, 1993; Eichenbaum, 1999). Our account provides a means by which to resolve this conflict, by demonstrating that the basic representational scheme envisioned by complementary learning systems theory (McClelland et al., 1995), which relies upon orthogonalized codes in the hippocampus, is compatible with efficient generalization—as long as there is recurrence rather than unidirectional flow within the hippocampal circuit or, more widely, between the hippocampus and neocortex. We propose that recurrent similarity computation, a process that facilitates the discovery of higher-order relationships between a set of related experiences, expands the scope of classical exemplar-based models of memory (e.g., Nosofsky, 1984) and allows the hippocampus to support generalization through interactions that unfold within a dynamically created memory space. PMID:22775499
ERIC Educational Resources Information Center
Wang, Gong-Wu; Liu, Jian; Wang, Xiao-Qin
2017-01-01
The ventral hippocampus (VH) and the basolateral amygdala (BLA) are both crucial in inhibitory avoidance (IA) memory. However, the exact role of the VH-BLA circuit in IA memory consolidation is unclear. This study investigated the effect of post-training reversible disconnection of the VH-BLA circuit in IA memory consolidation. Male Wistar rats…
Programmable data communications controller requirements
NASA Technical Reports Server (NTRS)
1977-01-01
The design requirements for a Programmable Data Communications Controller (PDCC) that reduces the difficulties in attaching data terminal equipment to a computer are presented. The PDCC is an interface between the computer I/O channel and the bit serial communication lines. Each communication line is supported by a communication port that handles all line control functions and performs most terminal control functions. The port is fabricated on a printed circuit board that plugs into a card chassis, mating with a connector that is joined to all other card stations by a data bus. Ports are individually programmable; each includes a microprocessor, a programmable read-only memory for instruction storage, and a random access memory for data storage.
Accelerating functional verification of an integrated circuit
Deindl, Michael; Ruedinger, Jeffrey Joseph; Zoellin, Christian G.
2015-10-27
Illustrative embodiments include a method, system, and computer program product for accelerating functional verification in simulation testing of an integrated circuit (IC). Using a processor and a memory, a serial operation is replaced with a direct register access operation, wherein the serial operation is configured to perform bit shifting operation using a register in a simulation of the IC. The serial operation is blocked from manipulating the register in the simulation of the IC. Using the register in the simulation of the IC, the direct register access operation is performed in place of the serial operation.
Protecting quantum information in superconducting circuits
NASA Astrophysics Data System (ADS)
Devoret, Michel
Can we prolong the coherence of a two-state manifold in a complex quantum system beyond the coherence of its longest-lived component? This question is the starting point in the construction of a scalable quantum computer. It translates in the search for processes that operate as some sort of Maxwell's demon and reliably correct the errors resulting from the coupling between qubits and their environment. The presentation will review recent experiments that test the dynamical protection by Josephson circuits of a logical qubit memory based on superpositions of particular coherent states of a superconducting resonator.
DOE Office of Scientific and Technical Information (OSTI.GOV)
James, Conrad D.; Schiess, Adrian B.; Howell, Jamie
2013-10-01
The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we willmore » instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.« less
An Introduction to the Memristor
ERIC Educational Resources Information Center
Atkin, Keith
2013-01-01
In recent years there has been a revolution in electronics, with a variety of physical phenomena being utilized in the construction of new types of memory circuits for computer application. A device which has had an increasing role is the memristor, whose description and properties have so far had little mention in physics education. This paper…
Recent Advances on Neuromorphic Systems Using Phase-Change Materials
NASA Astrophysics Data System (ADS)
Wang, Lei; Lu, Shu-Ren; Wen, Jing
2017-05-01
Realization of brain-like computer has always been human's ultimate dream. Today, the possibility of having this dream come true has been significantly boosted due to the advent of several emerging non-volatile memory devices. Within these innovative technologies, phase-change memory device has been commonly regarded as the most promising candidate to imitate the biological brain, owing to its excellent scalability, fast switching speed, and low energy consumption. In this context, a detailed review concerning the physical principles of the neuromorphic circuit using phase-change materials as well as a comprehensive introduction of the currently available phase-change neuromorphic prototypes becomes imperative for scientists to continuously progress the technology of artificial neural networks. In this paper, we first present the biological mechanism of human brain, followed by a brief discussion about physical properties of phase-change materials that recently receive a widespread application on non-volatile memory field. We then survey recent research on different types of neuromorphic circuits using phase-change materials in terms of their respective geometrical architecture and physical schemes to reproduce the biological events of human brain, in particular for spike-time-dependent plasticity. The relevant virtues and limitations of these devices are also evaluated. Finally, the future prospect of the neuromorphic circuit based on phase-change technologies is envisioned.
Recent Advances on Neuromorphic Systems Using Phase-Change Materials.
Wang, Lei; Lu, Shu-Ren; Wen, Jing
2017-12-01
Realization of brain-like computer has always been human's ultimate dream. Today, the possibility of having this dream come true has been significantly boosted due to the advent of several emerging non-volatile memory devices. Within these innovative technologies, phase-change memory device has been commonly regarded as the most promising candidate to imitate the biological brain, owing to its excellent scalability, fast switching speed, and low energy consumption. In this context, a detailed review concerning the physical principles of the neuromorphic circuit using phase-change materials as well as a comprehensive introduction of the currently available phase-change neuromorphic prototypes becomes imperative for scientists to continuously progress the technology of artificial neural networks. In this paper, we first present the biological mechanism of human brain, followed by a brief discussion about physical properties of phase-change materials that recently receive a widespread application on non-volatile memory field. We then survey recent research on different types of neuromorphic circuits using phase-change materials in terms of their respective geometrical architecture and physical schemes to reproduce the biological events of human brain, in particular for spike-time-dependent plasticity. The relevant virtues and limitations of these devices are also evaluated. Finally, the future prospect of the neuromorphic circuit based on phase-change technologies is envisioned.
Interference and memory capacity effects in memristive systems
NASA Astrophysics Data System (ADS)
Hermiz, John; Chang, Ting; Du, Chao; Lu, Wei
2013-02-01
Short-term memory implies the existence of a capacity limit beyond which memory cannot be securely formed and retained. The underlying mechanisms are believed to be two primary factors: decay and interference. Here, we demonstrate through both simulation and experiment that the memory capacity effect can be implemented in a parallel memristor circuit, where decay and interference are achieved by the inherent ion diffusion in the device and the competition for current supply in the circuit, respectively. This study suggests it is possible to emulate high-level biological behaviors with memristor circuits and will stimulate continued studies on memristor-based neuromorphic circuits.
Li, Guoqi; Deng, Lei; Wang, Dong; Wang, Wei; Zeng, Fei; Zhang, Ziyang; Li, Huanglong; Song, Sen; Pei, Jing; Shi, Luping
2016-01-01
Chunking refers to a phenomenon whereby individuals group items together when performing a memory task to improve the performance of sequential memory. In this work, we build a bio-plausible hierarchical chunking of sequential memory (HCSM) model to explain why such improvement happens. We address this issue by linking hierarchical chunking with synaptic plasticity and neuromorphic engineering. We uncover that a chunking mechanism reduces the requirements of synaptic plasticity since it allows applying synapses with narrow dynamic range and low precision to perform a memory task. We validate a hardware version of the model through simulation, based on measured memristor behavior with narrow dynamic range in neuromorphic circuits, which reveals how chunking works and what role it plays in encoding sequential memory. Our work deepens the understanding of sequential memory and enables incorporating it for the investigation of the brain-inspired computing on neuromorphic architecture. PMID:28066223
Three-dimensional integration of nanotechnologies for computing and data storage on a single chip
NASA Astrophysics Data System (ADS)
Shulaker, Max M.; Hills, Gage; Park, Rebecca S.; Howe, Roger T.; Saraswat, Krishna; Wong, H.-S. Philip; Mitra, Subhasish
2017-07-01
The computing demands of future data-intensive applications will greatly exceed the capabilities of current electronics, and are unlikely to be met by isolated improvements in transistors, data storage technologies or integrated circuit architectures alone. Instead, transformative nanosystems, which use new nanotechnologies to simultaneously realize improved devices and new integrated circuit architectures, are required. Here we present a prototype of such a transformative nanosystem. It consists of more than one million resistive random-access memory cells and more than two million carbon-nanotube field-effect transistors—promising new nanotechnologies for use in energy-efficient digital logic circuits and for dense data storage—fabricated on vertically stacked layers in a single chip. Unlike conventional integrated circuit architectures, the layered fabrication realizes a three-dimensional integrated circuit architecture with fine-grained and dense vertical connectivity between layers of computing, data storage, and input and output (in this instance, sensing). As a result, our nanosystem can capture massive amounts of data every second, store it directly on-chip, perform in situ processing of the captured data, and produce ‘highly processed’ information. As a working prototype, our nanosystem senses and classifies ambient gases. Furthermore, because the layers are fabricated on top of silicon logic circuitry, our nanosystem is compatible with existing infrastructure for silicon-based technologies. Such complex nano-electronic systems will be essential for future high-performance and highly energy-efficient electronic systems.
Three-dimensional integration of nanotechnologies for computing and data storage on a single chip.
Shulaker, Max M; Hills, Gage; Park, Rebecca S; Howe, Roger T; Saraswat, Krishna; Wong, H-S Philip; Mitra, Subhasish
2017-07-05
The computing demands of future data-intensive applications will greatly exceed the capabilities of current electronics, and are unlikely to be met by isolated improvements in transistors, data storage technologies or integrated circuit architectures alone. Instead, transformative nanosystems, which use new nanotechnologies to simultaneously realize improved devices and new integrated circuit architectures, are required. Here we present a prototype of such a transformative nanosystem. It consists of more than one million resistive random-access memory cells and more than two million carbon-nanotube field-effect transistors-promising new nanotechnologies for use in energy-efficient digital logic circuits and for dense data storage-fabricated on vertically stacked layers in a single chip. Unlike conventional integrated circuit architectures, the layered fabrication realizes a three-dimensional integrated circuit architecture with fine-grained and dense vertical connectivity between layers of computing, data storage, and input and output (in this instance, sensing). As a result, our nanosystem can capture massive amounts of data every second, store it directly on-chip, perform in situ processing of the captured data, and produce 'highly processed' information. As a working prototype, our nanosystem senses and classifies ambient gases. Furthermore, because the layers are fabricated on top of silicon logic circuitry, our nanosystem is compatible with existing infrastructure for silicon-based technologies. Such complex nano-electronic systems will be essential for future high-performance and highly energy-efficient electronic systems.
Wang, Gong-Wu; Liu, Jian; Wang, Xiao-Qin
2017-11-01
The ventral hippocampus (VH) and the basolateral amygdala (BLA) are both crucial in inhibitory avoidance (IA) memory. However, the exact role of the VH-BLA circuit in IA memory consolidation is unclear. This study investigated the effect of post-training reversible disconnection of the VH-BLA circuit in IA memory consolidation. Male Wistar rats with implanted guide cannulae were trained with a one-trial IA task, then received immediate intracerebral injections of muscimol or saline, and were tested 24 h later. Muscimol injection into the bilateral BLA, or the unilateral VH and contralateral BLA, but not the unilateral VH and ipsilateral BLA, significantly decreased the retention latencies (versus saline treatment). The results suggest that the VH-BLA circuit could be an important circuit to modulate consolidation of IA memory in rats. © 2017 Wang et al.; Published by Cold Spring Harbor Laboratory Press.
Fisher, Dimitry; Olasagasti, Itsaso; Tank, David W; Aksay, Emre R F; Goldman, Mark S
2013-09-04
Although many studies have identified neural correlates of memory, relatively little is known about the circuit properties connecting single-neuron physiology to behavior. Here we developed a modeling framework to bridge this gap and identify circuit interactions capable of maintaining short-term memory. Unlike typical studies that construct a phenomenological model and test whether it reproduces select aspects of neuronal data, we directly fit the synaptic connectivity of an oculomotor memory circuit to a broad range of anatomical, electrophysiological, and behavioral data. Simultaneous fits to all data, combined with sensitivity analyses, revealed complementary roles of synaptic and neuronal recruitment thresholds in providing the nonlinear interactions required to generate the observed circuit behavior. This work provides a methodology for identifying the cellular and synaptic mechanisms underlying short-term memory and demonstrates how the anatomical structure of a circuit may belie its functional organization. Copyright © 2013 Elsevier Inc. All rights reserved.
Xyce Parallel Electronic Simulator Users' Guide Version 6.8
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keiter, Eric R.; Aadithya, Karthik Venkatraman; Mei, Ting
This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been de- signed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel com- puting platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows onemore » to develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase$-$ a message passing parallel implementation $-$ which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows.« less
Dual redundant core memory systems
NASA Technical Reports Server (NTRS)
Hull, F. E.
1972-01-01
Electronic memory system consisting of series redundant drive switch circuits, triple redundant majority voted memory timing functions, and two data registers to provide functional dual redundancy is described. Signal flow through the circuits is illustrated and equence of events which occur within the memory system is explained.
Memory and cognitive control circuits in mathematical cognition and learning.
Menon, V
2016-01-01
Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal-frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal-frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed. © 2016 Elsevier B.V. All rights reserved.
Memory and cognitive control circuits in mathematical cognition and learning
Menon, V.
2018-01-01
Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal–frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal–frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed. PMID:27339012
Ham, Timothy S; Lee, Sung K; Keasling, Jay D; Arkin, Adam P
2008-07-30
Inversion recombination elements present unique opportunities for computing and information encoding in biological systems. They provide distinct binary states that are encoded into the DNA sequence itself, allowing us to overcome limitations posed by other biological memory or logic gate systems. Further, it is in theory possible to create complex sequential logics by careful positioning of recombinase recognition sites in the sequence. In this work, we describe the design and synthesis of an inversion switch using the fim and hin inversion recombination systems to create a heritable sequential memory switch. We have integrated the two inversion systems in an overlapping manner, creating a switch that can have multiple states. The switch is capable of transitioning from state to state in a manner analogous to a finite state machine, while encoding the state information into DNA. This switch does not require protein expression to maintain its state, and "remembers" its state even upon cell death. We were able to demonstrate transition into three out of the five possible states showing the feasibility of such a switch. We demonstrate that a heritable memory system that encodes its state into DNA is possible, and that inversion recombination system could be a starting point for more complex memory circuits. Although the circuit did not fully behave as expected, we showed that a multi-state, temporal memory is achievable.
Ham, Timothy S.; Lee, Sung K.; Keasling, Jay D.; Arkin, Adam P.
2008-01-01
Background Inversion recombination elements present unique opportunities for computing and information encoding in biological systems. They provide distinct binary states that are encoded into the DNA sequence itself, allowing us to overcome limitations posed by other biological memory or logic gate systems. Further, it is in theory possible to create complex sequential logics by careful positioning of recombinase recognition sites in the sequence. Methodology/Principal Findings In this work, we describe the design and synthesis of an inversion switch using the fim and hin inversion recombination systems to create a heritable sequential memory switch. We have integrated the two inversion systems in an overlapping manner, creating a switch that can have multiple states. The switch is capable of transitioning from state to state in a manner analogous to a finite state machine, while encoding the state information into DNA. This switch does not require protein expression to maintain its state, and “remembers” its state even upon cell death. We were able to demonstrate transition into three out of the five possible states showing the feasibility of such a switch. Conclusions/Significance We demonstrate that a heritable memory system that encodes its state into DNA is possible, and that inversion recombination system could be a starting point for more complex memory circuits. Although the circuit did not fully behave as expected, we showed that a multi-state, temporal memory is achievable. PMID:18665232
Designing Nanoscale Counter Using Reversible Gate Based on Quantum-Dot Cellular Automata
NASA Astrophysics Data System (ADS)
Moharrami, Elham; Navimipour, Nima Jafari
2018-04-01
Some new technologies such as Quantum-dot Cellular Automata (QCA) is suggested to solve the physical limits of the Complementary Metal-Oxide Semiconductor (CMOS) technology. The QCA as one of the novel technologies at nanoscale has potential applications in future computers. This technology has some advantages such as minimal size, high speed, low latency, and low power consumption. As a result, it is used for creating all varieties of memory. Counter circuits as one of the important circuits in the digital systems are composed of some latches, which are connected to each other in series and actually they count input pulses in the circuit. On the other hand, the reversible computations are very important because of their ability in reducing energy in nanometer circuits. Improving the energy efficiency, increasing the speed of nanometer circuits, increasing the portability of system, making smaller components of the circuit in a nuclear size and reducing the power consumption are considered as the usage of reversible logic. Therefore, this paper aims to design a two-bit reversible counter that is optimized on the basis of QCA using an improved reversible gate. The proposed reversible structure of 2-bit counter can be increased to 3-bit, 4-bit and more. The advantages of the proposed design have been shown using QCADesigner in terms of the delay in comparison with previous circuits.
Josephson 4 K-bit cache memory design for a prototype signal processor. I - General overview
NASA Astrophysics Data System (ADS)
Henkels, W. H.; Geppert, L. M.; Kadlec, J.; Epperlein, P. W.; Beha, H.
1985-09-01
In the early stages of thg Josephson computer project conducted at an American computer company, it was recognized that a very fast cache memory was needed to complement Josephson logic. A subnanosecond access time memory was implemented experimentally on the basis of a 2.5-micron Pb-alloy technology. It was then decided to switch over to a Nb-base-electrode technology with the objective to alleviate problems with the long-term reliability and aging of Pb-based junctions. The present paper provides a general overview of the status of a 4 x 1 K-bit Josephson cache design employing a 2.5-micron Nb-edge-junction technology. Attention is given to the fabrication process and its implications, aspects of circuit design methodology, an overview of system environment and chip components, design changes and status, and various difficulties and uncertainties.
Computationally Efficient Modeling and Simulation of Large Scale Systems
NASA Technical Reports Server (NTRS)
Jain, Jitesh (Inventor); Koh, Cheng-Kok (Inventor); Balakrishnan, Vankataramanan (Inventor); Cauley, Stephen F (Inventor); Li, Hong (Inventor)
2014-01-01
A system for simulating operation of a VLSI interconnect structure having capacitive and inductive coupling between nodes thereof, including a processor, and a memory, the processor configured to perform obtaining a matrix X and a matrix Y containing different combinations of passive circuit element values for the interconnect structure, the element values for each matrix including inductance L and inverse capacitance P, obtaining an adjacency matrix A associated with the interconnect structure, storing the matrices X, Y, and A in the memory, and performing numerical integration to solve first and second equations.
Deterministic and storable single-photon source based on a quantum memory.
Chen, Shuai; Chen, Yu-Ao; Strassel, Thorsten; Yuan, Zhen-Sheng; Zhao, Bo; Schmiedmayer, Jörg; Pan, Jian-Wei
2006-10-27
A single-photon source is realized with a cold atomic ensemble (87Rb atoms). A single excitation, written in an atomic quantum memory by Raman scattering of a laser pulse, is retrieved deterministically as a single photon at a predetermined time. It is shown that the production rate of single photons can be enhanced considerably by a feedback circuit while the single-photon quality is conserved. Such a single-photon source is well suited for future large-scale realization of quantum communication and linear optical quantum computation.
Solitonic Josephson-based meminductive systems
NASA Astrophysics Data System (ADS)
Guarcello, Claudio; Solinas, Paolo; di Ventra, Massimiliano; Giazotto, Francesco
2017-04-01
Memristors, memcapacitors, and meminductors represent an innovative generation of circuit elements whose properties depend on the state and history of the system. The hysteretic behavior of one of their constituent variables, is their distinctive fingerprint. This feature endows them with the ability to store and process information on the same physical location, a property that is expected to benefit many applications ranging from unconventional computing to adaptive electronics to robotics. Therefore, it is important to find appropriate memory elements that combine a wide range of memory states, long memory retention times, and protection against unavoidable noise. Although several physical systems belong to the general class of memelements, few of them combine these important physical features in a single component. Here, we demonstrate theoretically a superconducting memory based on solitonic long Josephson junctions. Moreover, since solitons are at the core of its operation, this system provides an intrinsic topological protection against external perturbations. We show that the Josephson critical current behaves hysteretically as an external magnetic field is properly swept. Accordingly, long Josephson junctions can be used as multi-state memories, with a controllable number of available states, and in other emerging areas such as memcomputing, i.e., computing directly in/by the memory.
Radiation Tolerant Intelligent Memory Stack (RTIMS)
NASA Technical Reports Server (NTRS)
Ng, Tak-kwong; Herath, Jeffrey A.
2006-01-01
The Radiation Tolerant Intelligent Memory Stack (RTIMS), suitable for both geostationary and low earth orbit missions, has been developed. The memory module is fully functional and undergoing environmental and radiation characterization. A self-contained flight-like module is expected to be completed in 2006. RTIMS provides reconfigurable circuitry and 2 gigabits of error corrected or 1 gigabit of triple redundant digital memory in a small package. RTIMS utilizes circuit stacking of heterogeneous components and radiation shielding technologies. A reprogrammable field programmable gate array (FPGA), six synchronous dynamic random access memories, linear regulator, and the radiation mitigation circuitries are stacked into a module of 42.7mm x 42.7mm x 13.00mm. Triple module redundancy, current limiting, configuration scrubbing, and single event function interrupt detection are employed to mitigate radiation effects. The mitigation techniques significantly simplify system design. RTIMS is well suited for deployment in real-time data processing, reconfigurable computing, and memory intensive applications.
New-Sum: A Novel Online ABFT Scheme For General Iterative Methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tao, Dingwen; Song, Shuaiwen; Krishnamoorthy, Sriram
Emerging high-performance computing platforms, with large component counts and lower power margins, are anticipated to be more susceptible to soft errors in both logic circuits and memory subsystems. We present an online algorithm-based fault tolerance (ABFT) approach to efficiently detect and recover soft errors for general iterative methods. We design a novel checksum-based encoding scheme for matrix-vector multiplication that is resilient to both arithmetic and memory errors. Our design decouples the checksum updating process from the actual computation, and allows adaptive checksum overhead control. Building on this new encoding mechanism, we propose two online ABFT designs that can effectively recovermore » from errors when combined with a checkpoint/rollback scheme.« less
All-spin logic operations: Memory device and reconfigurable computing
NASA Astrophysics Data System (ADS)
Patra, Moumita; Maiti, Santanu K.
2018-02-01
Exploiting spin degree of freedom of electron a new proposal is given to characterize spin-based logical operations using a quantum interferometer that can be utilized as a programmable spin logic device (PSLD). The ON and OFF states of both inputs and outputs are described by spin state only, circumventing spin-to-charge conversion at every stage as often used in conventional devices with the inclusion of extra hardware that can eventually diminish the efficiency. All possible logic functions can be engineered from a single device without redesigning the circuit which certainly offers the opportunities of designing new generation spintronic devices. Moreover, we also discuss the utilization of the present model as a memory device and suitable computing operations with proposed experimental setups.
Retrieving fear memories, as time goes by…
Do Monte, Fabricio H.; Quirk, Gregory J.; Li, Bo; Penzo, Mario A.
2016-01-01
Fear conditioning researches have led to a comprehensive picture of the neuronal circuit underlying the formation of fear memories. In contrast, knowledge about the retrieval of fear memories is much more limited. This disparity may stem from the fact that fear memories are not rigid, but reorganize over time. To bring clarity and raise awareness on the time-dependent dynamics of retrieval circuits, we review current evidence on the neuronal circuitry participating in fear memory retrieval at both early and late time points after conditioning. We focus on the temporal recruitment of the paraventricular nucleus of the thalamus, and its BDNFergic efferents to the central nucleus of the amygdala, for the retrieval and maintenance of fear memories. Finally, we speculate as to why retrieval circuits change across time, and the functional benefits of recruiting structures such as the paraventricular nucleus into the retrieval circuit. PMID:27217148
Engrams and Circuits Crucial for Systems Consolidation of a Memory
Kitamura, Takashi; Ogawa, Sachie K.; Roy, Dheeraj S.; Okuyama, Teruhiro; Morrissey, Mark D.; Smith, Lillian M.; Redondo, Roger L.; Tonegawa, Susumu
2017-01-01
Episodic memories initially require rapid synaptic plasticity within the hippocampus for their formation and are gradually consolidated in neocortical networks for permanent storage. However, the engrams and circuits that support neocortical memory consolidation remain unknown. We found that neocortical prefrontal memory engram cells, critical for remote contextual fear memory, were rapidly generated during initial learning via inputs from both hippocampal-entorhinal cortex and basolateral amygdala. After their generation, the prefrontal engram cells, with support from hippocampal memory engram cells, became functionally mature with time. Whereas hippocampal engram cells gradually became silent with time, engram cells in the basolateral amygdala, which were necessary for fear memory, are maintained. Our data provide new insights into the functional reorganization of engrams and circuits underlying systems consolidation of memory. PMID:28386011
Sensor Authentication: Embedded Processor Code
DOE Office of Scientific and Technical Information (OSTI.GOV)
Svoboda, John
2012-09-25
Described is the c code running on the embedded Microchip 32bit PIC32MX575F256H located on the INL developed noise analysis circuit board. The code performs the following functions: Controls the noise analysis circuit board preamplifier voltage gains of 1, 10, 100, 000 Initializes the analog to digital conversion hardware, input channel selection, Fast Fourier Transform (FFT) function, USB communications interface, and internal memory allocations Initiates high resolution 4096 point 200 kHz data acquisition Computes complex 2048 point FFT and FFT magnitude. Services Host command set Transfers raw data to Host Transfers FFT result to host Communication error checking
Magnetic Random Access Memory for Embedded Computing
2007-10-29
layer, w he free layer hose resistan . ce 2. Develop and model data storage circuits based on the MTJ cells. 3. Integrated the MTJ cells into a CMOS...suggested the two methods shown in Fig. 4.5 [95]. The circuit shown at the top of the figure uses NMOS pass transistors to load data , which is the simplest... method but requires careful design to avoid charge sharing and accommodate the data -dependent loading seen at the DATA input. With additional
FPGA Implementation of Generalized Hebbian Algorithm for Texture Classification
Lin, Shiow-Jyu; Hwang, Wen-Jyi; Lee, Wei-Hao
2012-01-01
This paper presents a novel hardware architecture for principal component analysis. The architecture is based on the Generalized Hebbian Algorithm (GHA) because of its simplicity and effectiveness. The architecture is separated into three portions: the weight vector updating unit, the principal computation unit and the memory unit. In the weight vector updating unit, the computation of different synaptic weight vectors shares the same circuit for reducing the area costs. To show the effectiveness of the circuit, a texture classification system based on the proposed architecture is physically implemented by Field Programmable Gate Array (FPGA). It is embedded in a System-On-Programmable-Chip (SOPC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance and low area costs. PMID:22778640
Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device.
Park, Sangsu; Noh, Jinwoo; Choo, Myung-Lae; Sheri, Ahmad Muqeem; Chang, Man; Kim, Young-Bae; Kim, Chang Jung; Jeon, Moongu; Lee, Byung-Geun; Lee, Byoung Hun; Hwang, Hyunsang
2013-09-27
Efforts to develop scalable learning algorithms for implementation of networks of spiking neurons in silicon have been hindered by the considerable footprints of learning circuits, which grow as the number of synapses increases. Recent developments in nanotechnologies provide an extremely compact device with low-power consumption.In particular, nanoscale resistive switching devices (resistive random-access memory (RRAM)) are regarded as a promising solution for implementation of biological synapses due to their nanoscale dimensions, capacity to store multiple bits and the low energy required to operate distinct states. In this paper, we report the fabrication, modeling and implementation of nanoscale RRAM with multi-level storage capability for an electronic synapse device. In addition, we first experimentally demonstrate the learning capabilities and predictable performance by a neuromorphic circuit composed of a nanoscale 1 kbit RRAM cross-point array of synapses and complementary metal-oxide-semiconductor neuron circuits. These developments open up possibilities for the development of ubiquitous ultra-dense, ultra-low-power cognitive computers.
NASA Astrophysics Data System (ADS)
Huber, Ludwig
2014-09-01
This comment addresses the first component of Fitch's framework: the computational power of single neurons [3]. Although I agree that traditional models of neural computation have vastly underestimated the computational power of single neurons, I am hesitant to follow him completely. The exclusive focus on neurons is likely to underestimate the importance of other cells in the brain. In the last years, two such cell types have received appropriate attention by neuroscientists: interneurons and glia. Interneurons are small, tightly packed cells involved in the control of information processing in learning and memory. Rather than transmitting externally (like motor or sensory neurons), these neurons process information within internal circuits of the brain (therefore also called 'relay neurons'). Some specialized interneuron subtypes temporally regulate the flow of information in a given cortical circuit during relevant behavioral events [4]. In the human brain approx. 100 billion interneurons control information processing and are implicated in disorders such as epilepsy and Parkinson's.
Lee, Young Tack; Kwon, Hyeokjae; Kim, Jin Sung; Kim, Hong-Hee; Lee, Yun Jae; Lim, Jung Ah; Song, Yong-Won; Yi, Yeonjin; Choi, Won-Kook; Hwang, Do Kyung; Im, Seongil
2015-10-27
Two-dimensional van der Waals (2D vdWs) materials are a class of new materials that can provide important resources for future electronics and materials sciences due to their unique physical properties. Among 2D vdWs materials, black phosphorus (BP) has exhibited significant potential for use in electronic and optoelectronic applications because of its allotropic properties, high mobility, and direct and narrow band gap. Here, we demonstrate a few-layered BP-based nonvolatile memory transistor with a poly(vinylidenefluoride-trifluoroethylene) (P(VDF-TrFE)) ferroelectric top gate insulator. Experiments showed that our BP-based ferroelectric transistors operate satisfactorily at room temperature in ambient air and exhibit a clear memory window. Unlike conventional ambipolar BP transistors, our ferroelectric transistors showed only p-type characteristics due to the carbon-fluorine (C-F) dipole effect of the P(VDF-TrFE) layer, as well as the highest linear mobility value of 1159 cm(2) V(-1) s(-1) with a 10(3) on/off current ratio. For more advanced memory applications beyond unit memory devices, we implemented two memory inverter circuits, a resistive-load inverter circuit and a complementary inverter circuit, combined with an n-type molybdenum disulfide (MoS2) nanosheet. Our memory inverter circuits displayed a clear memory window of 15 V and memory output voltage efficiency of 95%.
Scalable quantum memory in the ultrastrong coupling regime.
Kyaw, T H; Felicetti, S; Romero, G; Solano, E; Kwek, L-C
2015-03-02
Circuit quantum electrodynamics, consisting of superconducting artificial atoms coupled to on-chip resonators, represents a prime candidate to implement the scalable quantum computing architecture because of the presence of good tunability and controllability. Furthermore, recent advances have pushed the technology towards the ultrastrong coupling regime of light-matter interaction, where the qubit-resonator coupling strength reaches a considerable fraction of the resonator frequency. Here, we propose a qubit-resonator system operating in that regime, as a quantum memory device and study the storage and retrieval of quantum information in and from the Z2 parity-protected quantum memory, within experimentally feasible schemes. We are also convinced that our proposal might pave a way to realize a scalable quantum random-access memory due to its fast storage and readout performances.
Scalable quantum memory in the ultrastrong coupling regime
Kyaw, T. H.; Felicetti, S.; Romero, G.; Solano, E.; Kwek, L.-C.
2015-01-01
Circuit quantum electrodynamics, consisting of superconducting artificial atoms coupled to on-chip resonators, represents a prime candidate to implement the scalable quantum computing architecture because of the presence of good tunability and controllability. Furthermore, recent advances have pushed the technology towards the ultrastrong coupling regime of light-matter interaction, where the qubit-resonator coupling strength reaches a considerable fraction of the resonator frequency. Here, we propose a qubit-resonator system operating in that regime, as a quantum memory device and study the storage and retrieval of quantum information in and from the Z2 parity-protected quantum memory, within experimentally feasible schemes. We are also convinced that our proposal might pave a way to realize a scalable quantum random-access memory due to its fast storage and readout performances. PMID:25727251
Scalable printed electronics: an organic decoder addressing ferroelectric non-volatile memory.
Ng, Tse Nga; Schwartz, David E; Lavery, Leah L; Whiting, Gregory L; Russo, Beverly; Krusor, Brent; Veres, Janos; Bröms, Per; Herlogsson, Lars; Alam, Naveed; Hagel, Olle; Nilsson, Jakob; Karlsson, Christer
2012-01-01
Scalable circuits of organic logic and memory are realized using all-additive printing processes. A 3-bit organic complementary decoder is fabricated and used to read and write non-volatile, rewritable ferroelectric memory. The decoder-memory array is patterned by inkjet and gravure printing on flexible plastics. Simulation models for the organic transistors are developed, enabling circuit designs tolerant of the variations in printed devices. We explain the key design rules in fabrication of complex printed circuits and elucidate the performance requirements of materials and devices for reliable organic digital logic.
MOSFET analog memory circuit achieves long duration signal storage
NASA Technical Reports Server (NTRS)
1966-01-01
Memory circuit maintains the signal voltage at the output of an analog signal amplifier when the input signal is interrupted or removed. The circuit uses MOSFET /Metal Oxide Semiconductor Field Effect Transistor/ devices as voltage-controlled switches, triggered by an external voltage-sensing device.
Gas-Sensing Flip-Flop Circuits
NASA Technical Reports Server (NTRS)
Buehler, Martin G.; Blaes, Brent R.; Williams, Roger; Ryan, Margaret A.
1995-01-01
Gas-sensing integrated circuits consisting largely of modified static random-access memories (SRAMs) undergoing development, building on experience gained in use of modified SRAMs as radiation sensors. Each SRAM memory cell includes flip-flop circuit; sensors exploit metastable state that lies between two stable states (corresponding to binary logic states) of flip-flop circuit. Voltages of metastable states vary with exposures of gas-sensitive resistors.
VLSI processors for signal detection in SETI
NASA Technical Reports Server (NTRS)
Duluk, J. F.; Linscott, I. R.; Peterson, A. M.; Burr, J.; Ekroot, B.; Twicken, J.
1989-01-01
The objective of the Search for Extraterrestrial Intelligence (SETI) is to locate an artificially created signal coming from a distant star. This is done in two steps: (1) spectral analysis of an incoming radio frequency band, and (2) pattern detection for narrow-band signals. Both steps are computationally expensive and require the development of specially designed computer architectures. To reduce the size and cost of the SETI signal detection machine, two custom VLSI chips are under development. The first chip, the SETI DSP Engine, is used in the spectrum analyzer and is specially designed to compute Discrete Fourier Transforms (DFTs). It is a high-speed arithmetic processor that has two adders, one multiplier-accumulator, and three four-port memories. The second chip is a new type of Content-Addressable Memory. It is the heart of an associative processor that is used for pattern detection. Both chips incorporate many innovative circuits and architectural features.
VLSI processors for signal detection in SETI.
Duluk, J F; Linscott, I R; Peterson, A M; Burr, J; Ekroot, B; Twicken, J
1989-01-01
The objective of the Search for Extraterrestrial Intelligence (SETI) is to locate an artificially created signal coming from a distant star. This is done in two steps: (1) spectral analysis of an incoming radio frequency band, and (2) pattern detection for narrow-band signals. Both steps are computationally expensive and require the development of specially designed computer architectures. To reduce the size and cost of the SETI signal detection machine, two custom VLSI chips are under development. The first chip, the SETI DSP Engine, is used in the spectrum analyzer and is specially designed to compute Discrete Fourier Transforms (DFTs). It is a high-speed arithmetic processor that has two adders, one multiplier-accumulator, and three four-port memories. The second chip is a new type of Content-Addressable Memory. It is the heart of an associative processor that is used for pattern detection. Both chips incorporate many innovative circuits and architectural features.
NASA Astrophysics Data System (ADS)
Ghosh, Amal K.; Basuray, Amitabha
2008-11-01
The memory devices in multi-valued logic are of most significance in modern research. This paper deals with the implementation of basic memory devices in multi-valued logic using Savart plate and spatial light modulator (SLM) based optoelectronic circuits. Photons are used here as the carrier to speed up the operations. Optical tree architecture (OTA) has been also utilized in the optical interconnection network. We have exploited the advantages of Savart plates, SLMs and OTA and proposed the SLM based high speed JK, D-type and T-type flip-flops in a trinary system.
Content addressable memory project
NASA Technical Reports Server (NTRS)
Hall, J. Storrs; Levy, Saul; Smith, Donald E.; Miyake, Keith M.
1992-01-01
A parameterized version of the tree processor was designed and tested (by simulation). The leaf processor design is 90 percent complete. We expect to complete and test a combination of tree and leaf cell designs in the next period. Work is proceeding on algorithms for the computer aided manufacturing (CAM), and once the design is complete we will begin simulating algorithms for large problems. The following topics are covered: (1) the practical implementation of content addressable memory; (2) design of a LEAF cell for the Rutgers CAM architecture; (3) a circuit design tool user's manual; and (4) design and analysis of efficient hierarchical interconnection networks.
Design, processing, and testing of lsi arrays for space station
NASA Technical Reports Server (NTRS)
Lile, W. R.; Hollingsworth, R. J.
1972-01-01
The design of a MOS 256-bit Random Access Memory (RAM) is discussed. Technological achievements comprise computer simulations that accurately predict performance; aluminum-gate COS/MOS devices including a 256-bit RAM with current sensing; and a silicon-gate process that is being used in the construction of a 256-bit RAM with voltage sensing. The Si-gate process increases speed by reducing the overlap capacitance between gate and source-drain, thus reducing the crossover capacitance and allowing shorter interconnections. The design of a Si-gate RAM, which is pin-for-pin compatible with an RCA bulk silicon COS/MOS memory (type TA 5974), is discussed in full. The Integrated Circuit Tester (ICT) is limited to dc evaluation, but the diagnostics and data collecting are under computer control. The Silicon-on-Sapphire Memory Evaluator (SOS-ME, previously called SOS Memory Exerciser) measures power supply drain and performs a minimum number of tests to establish operation of the memory devices. The Macrodata MD-100 is a microprogrammable tester which has capabilities of extensive testing at speeds up to 5 MHz. Beam-lead technology was successfully integrated with SOS technology to make a simple device with beam leads. This device and the scribing are discussed.
Boolean and brain-inspired computing using spin-transfer torque devices
NASA Astrophysics Data System (ADS)
Fan, Deliang
Several completely new approaches (such as spintronic, carbon nanotube, graphene, TFETs, etc.) to information processing and data storage technologies are emerging to address the time frame beyond current Complementary Metal-Oxide-Semiconductor (CMOS) roadmap. The high speed magnetization switching of a nano-magnet due to current induced spin-transfer torque (STT) have been demonstrated in recent experiments. Such STT devices can be explored in compact, low power memory and logic design. In order to truly leverage STT devices based computing, researchers require a re-think of circuit, architecture, and computing model, since the STT devices are unlikely to be drop-in replacements for CMOS. The potential of STT devices based computing will be best realized by considering new computing models that are inherently suited to the characteristics of STT devices, and new applications that are enabled by their unique capabilities, thereby attaining performance that CMOS cannot achieve. The goal of this research is to conduct synergistic exploration in architecture, circuit and device levels for Boolean and brain-inspired computing using nanoscale STT devices. Specifically, we first show that the non-volatile STT devices can be used in designing configurable Boolean logic blocks. We propose a spin-memristor threshold logic (SMTL) gate design, where memristive cross-bar array is used to perform current mode summation of binary inputs and the low power current mode spintronic threshold device carries out the energy efficient threshold operation. Next, for brain-inspired computing, we have exploited different spin-transfer torque device structures that can implement the hard-limiting and soft-limiting artificial neuron transfer functions respectively. We apply such STT based neuron (or 'spin-neuron') in various neural network architectures, such as hierarchical temporal memory and feed-forward neural network, for performing "human-like" cognitive computing, which show more than two orders of lower energy consumption compared to state of the art CMOS implementation. Finally, we show the dynamics of injection locked Spin Hall Effect Spin-Torque Oscillator (SHE-STO) cluster can be exploited as a robust multi-dimensional distance metric for associative computing, image/ video analysis, etc. Our simulation results show that the proposed system architecture with injection locked SHE-STOs and the associated CMOS interface circuits can be suitable for robust and energy efficient associative computing and pattern matching.
Programmable computing with a single magnetoresistive element
NASA Astrophysics Data System (ADS)
Ney, A.; Pampuch, C.; Koch, R.; Ploog, K. H.
2003-10-01
The development of transistor-based integrated circuits for modern computing is a story of great success. However, the proved concept for enhancing computational power by continuous miniaturization is approaching its fundamental limits. Alternative approaches consider logic elements that are reconfigurable at run-time to overcome the rigid architecture of the present hardware systems. Implementation of parallel algorithms on such `chameleon' processors has the potential to yield a dramatic increase of computational speed, competitive with that of supercomputers. Owing to their functional flexibility, `chameleon' processors can be readily optimized with respect to any computer application. In conventional microprocessors, information must be transferred to a memory to prevent it from getting lost, because electrically processed information is volatile. Therefore the computational performance can be improved if the logic gate is additionally capable of storing the output. Here we describe a simple hardware concept for a programmable logic element that is based on a single magnetic random access memory (MRAM) cell. It combines the inherent advantage of a non-volatile output with flexible functionality which can be selected at run-time to operate as an AND, OR, NAND or NOR gate.
Engrams and circuits crucial for systems consolidation of a memory.
Kitamura, Takashi; Ogawa, Sachie K; Roy, Dheeraj S; Okuyama, Teruhiro; Morrissey, Mark D; Smith, Lillian M; Redondo, Roger L; Tonegawa, Susumu
2017-04-07
Episodic memories initially require rapid synaptic plasticity within the hippocampus for their formation and are gradually consolidated in neocortical networks for permanent storage. However, the engrams and circuits that support neocortical memory consolidation have thus far been unknown. We found that neocortical prefrontal memory engram cells, which are critical for remote contextual fear memory, were rapidly generated during initial learning through inputs from both the hippocampal-entorhinal cortex network and the basolateral amygdala. After their generation, the prefrontal engram cells, with support from hippocampal memory engram cells, became functionally mature with time. Whereas hippocampal engram cells gradually became silent with time, engram cells in the basolateral amygdala, which were necessary for fear memory, were maintained. Our data provide new insights into the functional reorganization of engrams and circuits underlying systems consolidation of memory. Copyright © 2017, American Association for the Advancement of Science.
In-situ, In-Memory Stateful Vector Logic Operations based on Voltage Controlled Magnetic Anisotropy.
Jaiswal, Akhilesh; Agrawal, Amogh; Roy, Kaushik
2018-04-10
Recently, the exponential increase in compute requirements demanded by emerging applications like artificial intelligence, Internet of things, etc. have rendered the state-of-art von-Neumann machines inefficient in terms of energy and throughput owing to the well-known von-Neumann bottleneck. A promising approach to mitigate the bottleneck is to do computations as close to the memory units as possible. One extreme possibility is to do in-situ Boolean logic computations by using stateful devices. Stateful devices are those that can act both as a compute engine and storage device, simultaneously. We propose such stateful, vector, in-memory operations using voltage controlled magnetic anisotropy (VCMA) effect in magnetic tunnel junctions (MTJ). Our proposal is based on the well known manufacturable 1-transistor - 1-MTJ bit-cell and does not require any modifications in the bit-cell circuit or the magnetic device. Instead, we leverage the very physics of the VCMA effect to enable stateful computations. Specifically, we exploit the voltage asymmetry of the VCMA effect to construct stateful IMP (implication) gate and use the precessional switching dynamics of the VCMA devices to propose a massively parallel NOT operation. Further, we show that other gates like AND, OR, NAND, NOR, NIMP (complement of implication) can be implemented using multi-cycle operations.
NASA Astrophysics Data System (ADS)
Okamoto, Atsushi; Ito, Terumasa; Bunsen, Masatoshi; Takayama, Yoshihisa
2005-11-01
The optical system, consisting of two photorefractive memories and a shutter-less optical feedback circuit, will be demonstrated to function as data mirroring. This function is known to automatically detect the data dropout and restore data, using unimpaired data in another memory, in the event that part or all of the data in either of them were lost for some reason. This memory system also can cope with a damaged hologram, a result of reading beams, which is a disadvantage of rewritable photorefractive memory, to ensure non-destructive holographic reading. It can be achieved by using no electronic circuits or mechanical structures; our optical experimental method in particular obtains this basic action.
Scalable printed electronics: an organic decoder addressing ferroelectric non-volatile memory
Ng, Tse Nga; Schwartz, David E.; Lavery, Leah L.; Whiting, Gregory L.; Russo, Beverly; Krusor, Brent; Veres, Janos; Bröms, Per; Herlogsson, Lars; Alam, Naveed; Hagel, Olle; Nilsson, Jakob; Karlsson, Christer
2012-01-01
Scalable circuits of organic logic and memory are realized using all-additive printing processes. A 3-bit organic complementary decoder is fabricated and used to read and write non-volatile, rewritable ferroelectric memory. The decoder-memory array is patterned by inkjet and gravure printing on flexible plastics. Simulation models for the organic transistors are developed, enabling circuit designs tolerant of the variations in printed devices. We explain the key design rules in fabrication of complex printed circuits and elucidate the performance requirements of materials and devices for reliable organic digital logic. PMID:22900143
Design of a Multi-Level/Analog Ferroelectric Memory Device
NASA Technical Reports Server (NTRS)
MacLeod, Todd C.; Phillips, Thomas A.; Ho, Fat D.
2006-01-01
Increasing the memory density and utilizing the dove1 characteristics of ferroelectric devices is important in making ferroelectric memory devices more desirable to the consumer. This paper describes a design that allows multiple levels to be stored in a ferroelectric based memory cell. It can be used to store multiple bits or analog values in a high speed nonvolatile memory. The design utilizes the hysteresis characteristic of ferroelectric transistors to store an analog value in the memory cell. The design also compensates for the decay of the polarization of the ferroelectric material over time. This is done by utilizing a pair of ferroelectric transistors to store the data. One transistor is used as a reference to determine the amount of decay that has occurred since the pair was programmed. The second transistor stores the analog value as a polarization value between zero and saturated. The design allows digital data to be stored as multiple bits in each memory cell. The number of bits per cell that can be stored will vary with the decay rate of the ferroelectric transistors and the repeatability of polarization between transistors. It is predicted that each memory cell may be able to store 8 bits or more. The design is based on data taken from actual ferroelectric transistors. Although the circuit has not been fabricated, a prototype circuit is now under construction. The design of this circuit is different than multi-level FLASH or silicon transistor circuits. The differences between these types of circuits are described in this paper. This memory design will be useful because it allows higher memory density, compensates for the environmental and ferroelectric aging processes, allows analog values to be directly stored in memory, compensates for the thermal and radiation environments associated with space operations, and relies only on existing technologies.
Solitonic Josephson-based meminductive systems
Guarcello, Claudio; Solinas, Paolo; Di Ventra, Massimiliano; ...
2017-04-24
Memristors, memcapacitors, and meminductors represent an innovative generation of circuit elements whose properties depend on the state and history of the system. The hysteretic behavior of one of their constituent variables, is their distinctive fingerprint. This feature endows them with the ability to store and process information on the same physical location, a property that is expected to benefit many applications ranging from unconventional computing to adaptive electronics to robotics. Therefore, it is important to find appropriate memory elements that combine a wide range of memory states, long memory retention times, and protection against unavoidable noise. Although several physical systemsmore » belong to the general class of memelements, few of them combine these important physical features in a single component. Here in this paper, we demonstrate theoretically a superconducting memory based on solitonic long Josephson junctions. Moreover, since solitons are at the core of its operation, this system provides an intrinsic topological protection against external perturbations. We show that the Josephson critical current behaves hysteretically as an external magnetic field is properly swept. Accordingly, long Josephson junctions can be used as multi-state memories, with a controllable number of available states, and in other emerging areas such as memcomputing, i.e., computing directly in/by the memory.« less
Solitonic Josephson-based meminductive systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Guarcello, Claudio; Solinas, Paolo; Di Ventra, Massimiliano
Memristors, memcapacitors, and meminductors represent an innovative generation of circuit elements whose properties depend on the state and history of the system. The hysteretic behavior of one of their constituent variables, is their distinctive fingerprint. This feature endows them with the ability to store and process information on the same physical location, a property that is expected to benefit many applications ranging from unconventional computing to adaptive electronics to robotics. Therefore, it is important to find appropriate memory elements that combine a wide range of memory states, long memory retention times, and protection against unavoidable noise. Although several physical systemsmore » belong to the general class of memelements, few of them combine these important physical features in a single component. Here in this paper, we demonstrate theoretically a superconducting memory based on solitonic long Josephson junctions. Moreover, since solitons are at the core of its operation, this system provides an intrinsic topological protection against external perturbations. We show that the Josephson critical current behaves hysteretically as an external magnetic field is properly swept. Accordingly, long Josephson junctions can be used as multi-state memories, with a controllable number of available states, and in other emerging areas such as memcomputing, i.e., computing directly in/by the memory.« less
Quantum Memristors with Superconducting Circuits
Salmilehto, J.; Deppe, F.; Di Ventra, M.; Sanz, M.; Solano, E.
2017-01-01
Memristors are resistive elements retaining information of their past dynamics. They have garnered substantial interest due to their potential for representing a paradigm change in electronics, information processing and unconventional computing. Given the advent of quantum technologies, a design for a quantum memristor with superconducting circuits may be envisaged. Along these lines, we introduce such a quantum device whose memristive behavior arises from quasiparticle-induced tunneling when supercurrents are cancelled. For realistic parameters, we find that the relevant hysteretic behavior may be observed using current state-of-the-art measurements of the phase-driven tunneling current. Finally, we develop suitable methods to quantify memory retention in the system. PMID:28195193
Method and apparatus for in-system redundant array repair on integrated circuits
Bright, Arthur A [Croton-on-Hudson, NY; Crumley, Paul G [Yorktown Heights, NY; Dombrowa, Marc B [Bronx, NY; Douskey, Steven M [Rochester, MN; Haring, Rudolf A [Cortlandt Manor, NY; Oakland, Steven F [Colchester, VT; Ouellette, Michael R [Westford, VT; Strissel, Scott A [Byron, MN
2008-07-29
Disclosed is a method of repairing an integrated circuit of the type comprising of a multitude of memory arrays and a fuse box holding control data for controlling redundancy logic of the arrays. The method comprises the steps of providing the integrated circuit with a control data selector for passing the control data from the fuse box to the memory arrays; providing a source of alternate control data, external of the integrated circuit; and connecting the source of alternate control data to the control data selector. The method comprises the further step of, at a given time, passing the alternate control data from the source thereof, through the control data selector and to the memory arrays to control the redundancy logic of the memory arrays.
Method and apparatus for in-system redundant array repair on integrated circuits
Bright, Arthur A [Croton-on-Hudson, NY; Crumley, Paul G [Yorktown Heights, NY; Dombrowa, Marc B [Bronx, NY; Douskey, Steven M [Rochester, MN; Haring, Rudolf A [Cortlandt Manor, NY; Oakland, Steven F [Colchester, VT; Ouellette, Michael R [Westford, VT; Strissel, Scott A [Byron, MN
2008-07-08
Disclosed is a method of repairing an integrated circuit of the type comprising of a multitude of memory arrays and a fuse box holding control data for controlling redundancy logic of the arrays. The method comprises the steps of providing the integrated circuit with a control data selector for passing the control data from the fuse box to the memory arrays; providing a source of alternate control data, external of the integrated circuit; and connecting the source of alternate control data to the control data selector. The method comprises the further step of, at a given time, passing the alternate control data from the source thereof, through the control data selector and to the memory arrays to control the redundancy logic of the memory arrays.
Method and apparatus for in-system redundant array repair on integrated circuits
Bright, Arthur A.; Crumley, Paul G.; Dombrowa, Marc B.; Douskey, Steven M.; Haring, Rudolf A.; Oakland, Steven F.; Ouellette, Michael R.; Strissel, Scott A.
2007-12-18
Disclosed is a method of repairing an integrated circuit of the type comprising of a multitude of memory arrays and a fuse box holding control data for controlling redundancy logic of the arrays. The method comprises the steps of providing the integrated circuit with a control data selector for passing the control data from the fuse box to the memory arrays; providing a source of alternate control data, external of the integrated circuit; and connecting the source of alternate control data to the control data selector. The method comprises the further step of, at a given time, passing the alternate control data from the source thereof, through the control data selector and to the memory arrays to control the redundancy logic of the memory arrays.
Justification of Estimates for Fiscal Year 1983 Submitted to Congress.
1982-02-01
hierarchies to aid software production; completion of the components of an adaptive suspension vehicle including a storage energy unit, hydraulics, laser...and corrosion (long storage times), and radiation-induced breakdown. Solid- lubricated main engine bearings for cruise missile engines would offer...environments will cause "soft error" (computational and memory storage errors) in advanced microelectronic circuits. Research on high-speed, low-power
Nonvolatile Array Of Synapses For Neural Network
NASA Technical Reports Server (NTRS)
Tawel, Raoul
1993-01-01
Elements of array programmed with help of ultraviolet light. A 32 x 32 very-large-scale integrated-circuit array of electronic synapses serves as building-block chip for analog neural-network computer. Synaptic weights stored in nonvolatile manner. Makes information content of array invulnerable to loss of power, and, by eliminating need for circuitry to refresh volatile synaptic memory, makes architecture simpler and more compact.
Xyce parallel electronic simulator : users' guide.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mei, Ting; Rankin, Eric Lamont; Thornquist, Heidi K.
2011-05-01
This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers; (2) Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-artmore » algorithms and novel techniques. (3) Device models which are specifically tailored to meet Sandia's needs, including some radiation-aware devices (for Sandia users only); and (4) Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing parallel implementation - which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Careful attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The development of Xyce provides a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms) research and development can be performed. As a result, Xyce is a unique electrical simulation capability, designed to meet the unique needs of the laboratory.« less
The Photon Shell Game and the Quantum von Neumann Architecture with Superconducting Circuits
NASA Astrophysics Data System (ADS)
Mariantoni, Matteo
2012-02-01
Superconducting quantum circuits have made significant advances over the past decade, allowing more complex and integrated circuits that perform with good fidelity. We have recently implemented a machine comprising seven quantum channels, with three superconducting resonators, two phase qubits, and two zeroing registers. I will explain the design and operation of this machine, first showing how a single microwave photon | 1 > can be prepared in one resonator and coherently transferred between the three resonators. I will also show how more exotic states such as double photon states | 2 > and superposition states | 0 >+ | 1 > can be shuffled among the resonators as well [1]. I will then demonstrate how this machine can be used as the quantum-mechanical analog of the von Neumann computer architecture, which for a classical computer comprises a central processing unit and a memory holding both instructions and data. The quantum version comprises a quantum central processing unit (quCPU) that exchanges data with a quantum random-access memory (quRAM) integrated on one chip, with instructions stored on a classical computer. I will also present a proof-of-concept demonstration of a code that involves all seven quantum elements: (1), Preparing an entangled state in the quCPU, (2), writing it to the quRAM, (3), preparing a second state in the quCPU, (4), zeroing it, and, (5), reading out the first state stored in the quRAM [2]. Finally, I will demonstrate that the quantum von Neumann machine provides one unit cell of a two-dimensional qubit-resonator array that can be used for surface code quantum computing. This will allow the realization of a scalable, fault-tolerant quantum processor with the most forgiving error rates to date. [4pt] [1] M. Mariantoni et al., Nature Physics 7, 287-293 (2011.)[0pt] [2] M. Mariantoni et al., Science 334, 61-65 (2011).
Test results for SEU and SEL immune memory circuits
NASA Technical Reports Server (NTRS)
Wiseman, D.; Canaris, J.; Whitaker, S.; Gambles, J.; Arave, K.; Arave, L.
1993-01-01
Test results for three SEU logic/circuit hardened CMOS memory circuits verify upset and latch-up immunity for two configurations to be in excess of 120 MeV cm(exp 2)/mg using a commercial, non-radiation hardened CMOS process. Test chips from three separate fabrication runs in two different process were evaluated.
Jin, Miaomiao; Cheng, Long; Li, Yi; Hu, Siyu; Lu, Ke; Chen, Jia; Duan, Nian; Wang, Zhuorui; Zhou, Yaxiong; Chang, Ting-Chang; Miao, Xiangshui
2018-06-27
Owing to the capability of integrating the information storage and computing in the same physical location, in-memory computing with memristors has become a research hotspot as a promising route for non von Neumann architecture. However, it is still a challenge to develop high performance devices as well as optimized logic methodologies to realize energy-efficient computing. Herein, filamentary Cu/GeTe/TiN memristor is reported to show satisfactory properties with nanosecond switching speed (< 60 ns), low voltage operation (< 2 V), high endurance (>104 cycles) and good retention (>104 s @85℃). It is revealed that the charge carrier conduction mechanisms in high resistance and low resistance states are Schottky emission and hopping transport between the adjacent Cu clusters, respectively, based on the analysis of current-voltage behaviors and resistance-temperature characteristics. An intuitive picture is given to describe the dynamic processes of resistive switching. Moreover, based on the basic material implication (IMP) logic circuit, we proposed a reconfigurable logic method and experimentally implemented IMP, NOT, OR, and COPY logic functions. Design of a one-bit full adder with reduction in computational sequences and its validation in simulation further demonstrate the potential practical application. The results provide important progress towards understanding of resistive switching mechanism and realization of energy-efficient in-memory computing architecture. © 2018 IOP Publishing Ltd.
Pattern separation in the hippocampus: distinct circuits under different conditions.
Kassab, Randa; Alexandre, Frédéric
2018-04-11
Pattern separation is a fundamental hippocampal process thought to be critical for distinguishing similar episodic memories, and has long been recognized as a natural function of the dentate gyrus (DG), supporting autoassociative learning in CA3. Understanding how neural circuits within the DG-CA3 network mediate this process has received much interest, yet the exact mechanisms behind remain elusive. Here, we argue for the case that sparse coding is necessary but not sufficient to ensure efficient separation and, alternatively, propose a possible interaction of distinct circuits which, nevertheless, act in synergy to produce a unitary function of pattern separation. The proposed circuits involve different functional granule-cell populations, a primary population mediates sparsification and provides recurrent excitation to the other populations which are related to additional pattern separation mechanisms with higher degrees of robustness against interference in CA3. A variety of top-down and bottom-up factors, such as motivation, emotion, and pattern similarity, control the selection of circuitry depending on circumstances. According to this framework, a computational model is implemented and tested against model variants in a series of numerical simulations and biological experiments. The results demonstrate that the model combines fast learning, robust pattern separation and high storage capacity. It also accounts for the controversy around the involvement of the DG during memory recall, explains other puzzling findings, and makes predictions that can inform future investigations.
Asymmetric Memory Circuit Would Resist Soft Errors
NASA Technical Reports Server (NTRS)
Buehler, Martin G.; Perlman, Marvin
1990-01-01
Some nonlinear error-correcting codes more efficient in presence of asymmetry. Combination of circuit-design and coding concepts expected to make integrated-circuit random-access memories more resistant to "soft" errors (temporary bit errors, also called "single-event upsets" due to ionizing radiation). Integrated circuit of new type made deliberately more susceptible to one kind of bit error than to other, and associated error-correcting code adapted to exploit this asymmetry in error probabilities.
Beyond the Bolus: Transgenic Tools for Investigating the Neurophysiology of Learning and Memory
ERIC Educational Resources Information Center
Lykken, Christine; Kentros, Clifford G.
2014-01-01
Understanding the neural mechanisms underlying learning and memory in the entorhinal-hippocampal circuit is a central challenge of systems neuroscience. For more than 40 years, electrophysiological recordings in awake, behaving animals have been used to relate the receptive fields of neurons in this circuit to learning and memory. However, the…
NASA Astrophysics Data System (ADS)
Gupta, Neha; Parihar, Priyanka; Neema, Vaibhav
2018-04-01
Researchers have proposed many circuit techniques to reduce leakage power dissipation in memory cells. If we want to reduce the overall power in the memory system, we have to work on the input circuitry of memory architecture i.e. row and column decoder. In this research work, low leakage power with a high speed row and column decoder for memory array application is designed and four new techniques are proposed. In this work, the comparison of cluster DECODER, body bias DECODER, source bias DECODER, and source coupling DECODER are designed and analyzed for memory array application. Simulation is performed for the comparative analysis of different DECODER design parameters at 180 nm GPDK technology file using the CADENCE tool. Simulation results show that the proposed source bias DECODER circuit technique decreases the leakage current by 99.92% and static energy by 99.92% at a supply voltage of 1.2 V. The proposed circuit also improves dynamic power dissipation by 5.69%, dynamic PDP/EDP 65.03% and delay 57.25% at 1.2 V supply voltage.
An evaluation of the Intel 2920 digital signal processing integrated circuit
NASA Technical Reports Server (NTRS)
Heller, J.
1981-01-01
The circuit consists of a digital to analog converter, accumulator, read write memory and UV erasable read only memory. The circuit can convert an analog signal to a digital representation, perform mathematical operations on the digital signal and subsequently convert the digital signal to an analog output. Development software tailored for programming the 2920 is presented.
Choice-specific sequences in parietal cortex during a virtual-navigation decision task
Harvey, Christopher D.; Coen, Philip; Tank, David W.
2012-01-01
The posterior parietal cortex (PPC) plays an important role in many cognitive behaviors; however, the neural circuit dynamics underlying PPC function are not well understood. Here we optically imaged the spatial and temporal activity patterns of neuronal populations in mice performing a PPC-dependent task that combined a perceptual decision and memory-guided navigation in a virtual environment. Individual neurons had transient activation staggered relative to one another in time, forming a sequence of neuronal activation spanning the entire length of a task trial. Distinct sequences of neurons were triggered on trials with opposite behavioral choices and defined divergent, choice-specific trajectories through a state space of neuronal population activity. Cells participating in the different sequences and at distinct time points in the task were anatomically intermixed over microcircuit length scales (< 100 micrometers). During working memory decision tasks the PPC may therefore perform computations through sequence-based circuit dynamics, rather than long-lived stable states, implemented using anatomically intermingled microcircuits. PMID:22419153
Plaçais, Pierre-Yves; Trannoy, Séverine; Friedrich, Anja B; Tanimoto, Hiromu; Preat, Thomas
2013-11-14
One of the challenges facing memory research is to combine network- and cellular-level descriptions of memory encoding. In this context, Drosophila offers the opportunity to decipher, down to single-cell resolution, memory-relevant circuits in connection with the mushroom bodies (MBs), prominent structures for olfactory learning and memory. Although the MB-afferent circuits involved in appetitive learning were recently described, the circuits underlying appetitive memory retrieval remain unknown. We identified two pairs of cholinergic neurons efferent from the MB α vertical lobes, named MB-V3, that are necessary for the retrieval of appetitive long-term memory (LTM). Furthermore, LTM retrieval was correlated to an enhanced response to the rewarded odor in these neurons. Strikingly, though, silencing the MB-V3 neurons did not affect short-term memory (STM) retrieval. This finding supports a scheme of parallel appetitive STM and LTM processing. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
Intelligent holographic databases
NASA Astrophysics Data System (ADS)
Barbastathis, George
Memory is a key component of intelligence. In the human brain, physical structure and functionality jointly provide diverse memory modalities at multiple time scales. How could we engineer artificial memories with similar faculties? In this thesis, we attack both hardware and algorithmic aspects of this problem. A good part is devoted to holographic memory architectures, because they meet high capacity and parallelism requirements. We develop and fully characterize shift multiplexing, a novel storage method that simplifies disk head design for holographic disks. We develop and optimize the design of compact refreshable holographic random access memories, showing several ways that 1 Tbit can be stored holographically in volume less than 1 m3, with surface density more than 20 times higher than conventional silicon DRAM integrated circuits. To address the issue of photorefractive volatility, we further develop the two-lambda (dual wavelength) method for shift multiplexing, and combine electrical fixing with angle multiplexing to demonstrate 1,000 multiplexed fixed holograms. Finally, we propose a noise model and an information theoretic metric to optimize the imaging system of a holographic memory, in terms of storage density and error rate. Motivated by the problem of interfacing sensors and memories to a complex system with limited computational resources, we construct a computer game of Desert Survival, built as a high-dimensional non-stationary virtual environment in a competitive setting. The efficacy of episodic learning, implemented as a reinforced Nearest Neighbor scheme, and the probability of winning against a control opponent improve significantly by concentrating the algorithmic effort to the virtual desert neighborhood that emerges as most significant at any time. The generalized computational model combines the autonomous neural network and von Neumann paradigms through a compact, dynamic central representation, which contains the most salient features of the sensory inputs, fused with relevant recollections, reminiscent of the hypothesized cognitive function of awareness. The Declarative Memory is searched both by content and address, suggesting a holographic implementation. The proposed computer architecture may lead to a novel paradigm that solves 'hard' cognitive problems at low cost.
General-Purpose Serial Interface For Remote Control
NASA Technical Reports Server (NTRS)
Busquets, Anthony M.; Gupton, Lawrence E.
1990-01-01
Computer controls remote television camera. General-purpose controller developed to serve as interface between host computer and pan/tilt/zoom/focus functions on series of automated video cameras. Interface port based on 8251 programmable communications-interface circuit configured for tristated outputs, and connects controller system to any host computer with RS-232 input/output (I/O) port. Accepts byte-coded data from host, compares them with prestored codes in read-only memory (ROM), and closes or opens appropriate switches. Six output ports control opening and closing of as many as 48 switches. Operator controls remote television camera by speaking commands, in system including general-purpose controller.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Romanov, E.S.; Ivoilov, N.G.
A buffer memory unit and an interface for the UNO-4096-90 accumulator with an Elektronika D3-28 microcomputer are described that allow simultaneous recording of four Moessbauer spectra with zero dead time. For complete elimination of dead time, the pulses from each detector are fed to two buffer counters units, which operate alternately in the write and interrogate modes. This organization of the buffer memory also completely eliminates the effect of the sensors on one another. The use of these circuits does not require any modifications of the computer or accumulator.
Radiation-Hardened Solid-State Drive
NASA Technical Reports Server (NTRS)
Sheldon, Douglas J.
2010-01-01
A method is provided for a radiationhardened (rad-hard) solid-state drive for space mission memory applications by combining rad-hard and commercial off-the-shelf (COTS) non-volatile memories (NVMs) into a hybrid architecture. The architecture is controlled by a rad-hard ASIC (application specific integrated circuit) or a FPGA (field programmable gate array). Specific error handling and data management protocols are developed for use in a rad-hard environment. The rad-hard memories are smaller in overall memory density, but are used to control and manage radiation-induced errors in the main, and much larger density, non-rad-hard COTS memory devices. Small amounts of rad-hard memory are used as error buffers and temporary caches for radiation-induced errors in the large COTS memories. The rad-hard ASIC/FPGA implements a variety of error-handling protocols to manage these radiation-induced errors. The large COTS memory is triplicated for protection, and CRC-based counters are calculated for sub-areas in each COTS NVM array. These counters are stored in the rad-hard non-volatile memory. Through monitoring, rewriting, regeneration, triplication, and long-term storage, radiation-induced errors in the large NV memory are managed. The rad-hard ASIC/FPGA also interfaces with the external computer buses.
Selective memory generalization by spatial patterning of protein synthesis
O’Donnell, Cian; Sejnowski, Terrence J.
2014-01-01
Summary Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings we proposed a novel two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. PMID:24742462
Selective memory generalization by spatial patterning of protein synthesis.
O'Donnell, Cian; Sejnowski, Terrence J
2014-04-16
Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings, we proposed a two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.
Computer-Aided Fabrication of Integrated Circuits
1989-09-30
baseline CMOS process. One result of this effort was the identification of several residual bugs in the PATRAN graphics processor . The vendor promises...virtual memory. The internal Nubus architecture uses a 32-bit LISP processor running at 10 megahertz (100 ns clock period). An ethernet controller is...For different patterns, we need different masks for the photo step, and for dif- ferent micro -structures of the wafers, we need different etching
Studies Of Single-Event-Upset Models
NASA Technical Reports Server (NTRS)
Zoutendyk, J. A.; Smith, L. S.; Soli, G. A.
1988-01-01
Report presents latest in series of investigations of "soft" bit errors known as single-event upsets (SEU). In this investigation, SEU response of low-power, Schottky-diode-clamped, transistor/transistor-logic (TTL) static random-access memory (RAM) observed during irradiation by Br and O ions in ranges of 100 to 240 and 20 to 100 MeV, respectively. Experimental data complete verification of computer model used to simulate SEU in this circuit.
The Aging Navigational System.
Lester, Adam W; Moffat, Scott D; Wiener, Jan M; Barnes, Carol A; Wolbers, Thomas
2017-08-30
The discovery of neuronal systems dedicated to computing spatial information, composed of functionally distinct cell types such as place and grid cells, combined with an extensive body of human-based behavioral and neuroimaging research has provided us with a detailed understanding of the brain's navigation circuit. In this review, we discuss emerging evidence from rodents, non-human primates, and humans that demonstrates how cognitive aging affects the navigational computations supported by these systems. Critically, we show 1) that navigational deficits cannot solely be explained by general deficits in learning and memory, 2) that there is no uniform decline across different navigational computations, and 3) that navigational deficits might be sensitive markers for impending pathological decline. Following an introduction to the mechanisms underlying spatial navigation and how they relate to general processes of learning and memory, the review discusses how aging affects the perception and integration of spatial information, the creation and storage of memory traces for spatial information, and the use of spatial information during navigational behavior. The closing section highlights the clinical potential of behavioral and neural markers of spatial navigation, with a particular emphasis on neurodegenerative disorders. Copyright © 2017 Elsevier Inc. All rights reserved.
Moorthi, P; Premkumar, P; Priyanka, R; Jayachandran, K S; Anusuyadevi, M
2015-08-20
Among vertebrates hippocampus forms the major component of the brain in consolidating information from short-term memory to long-term memory. Aging is considered as the major risk factor for memory impairment in sporadic Alzheimer's disease (SAD) like pathology. Present study thus aims at investigating whether age-specific degeneration of neuronal-circuits in hippocampal formation (neural-layout of Subiculum-hippocampus proper-dentate gyrus (DG)-entorhinal cortex (EC)) results in cognitive impairment. Furthermore, the neuroprotective effect of Resveratrol (RSV) was attempted to study in the formation of hippocampal neuronal-circuits. Radial-Arm-Maze was conducted to evaluate hippocampal-dependent spatial and learning memory in control and experimental rats. Nissl staining of frontal cortex (FC), subiculum, hippocampal-proper (CA1→CA2→CA3→CA4), DG, amygdala, cerebellum, thalamus, hypothalamus, layers of temporal and parietal lobe of the neocortex were examined for pathological changes in young and aged wistar rats, with and without RSV. Hippocampal trisynaptic circuit (EC layerII→DG→CA3→CA1) forming new memory and monosynaptic circuit (EC→CA1) that strengthen old memories were found disturbed in aged rats. Loss of Granular neuron observed in DG and polymorphic cells of CA4 can lead to decreased mossy fibers disturbing neural-transmission (CA4→CA3) in perforant pathway. Further, intensity of nissl granules (stratum lacunosum moleculare (SLM)-SR-SO) of CA3 pyramidal neurons was decreased, disturbing the communication in schaffer collaterals (CA3-CA1) during aging. We also noticed disarranged neuronal cell layer in Subiculum (presubiculum (PrS)-parasubiculum (PaS)), interfering output from hippocampus to prefrontal cortex (PFC), EC, hypothalamus, and amygdala that may result in interruption of thought processes. We conclude from our observations that poor memory performance of aged rats as evidenced through radial arm maze (RAM) analysis was due to the defect in neuronal-circuits of hippocampus (DG-CA4-CA1-Sub) that were significantly damaged leading to memory impairment. Interestingly, RSV was observed to culminate pathological events in the hippocampal neuronal circuit during aging, proving them as potent therapeutic drug against age-associated neurodegeneration and memory loss. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
VLSI 'smart' I/O module development
NASA Astrophysics Data System (ADS)
Kirk, Dan
The developmental history, design, and operation of the MIL-STD-1553A/B discrete and serial module (DSM) for the U.S. Navy AN/AYK-14(V) avionics computer are described and illustrated with diagrams. The ongoing preplanned product improvement for the AN/AYK-14(V) includes five dual-redundant MIL-STD-1553 channels based on DSMs. The DSM is a front-end processor for transferring data to and from a common memory, sharing memory with a host processor to provide improved 'smart' input/output performance. Each DSM comprises three hardware sections: three VLSI-6000 semicustomized CMOS arrays, memory units to support the arrays, and buffers and resynchronization circuits. The DSM hardware module design, VLSI-6000 design tools, controlware and test software, and checkout procedures (using a hardware simulator) are characterized in detail.
Xyce Parallel Electronic Simulator : users' guide, version 2.0.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hoekstra, Robert John; Waters, Lon J.; Rankin, Eric Lamont
2004-06-01
This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator capable of simulating electrical circuits at a variety of abstraction levels. Primarily, Xyce has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability the current state-of-the-art in the following areas: {sm_bullet} Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers. {sm_bullet} Improved performance for allmore » numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. {sm_bullet} Device models which are specifically tailored to meet Sandia's needs, including many radiation-aware devices. {sm_bullet} A client-server or multi-tiered operating model wherein the numerical kernel can operate independently of the graphical user interface (GUI). {sm_bullet} Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing of computing platforms. These include serial, shared-memory and distributed-memory parallel implementation - which allows it to run efficiently on the widest possible number parallel as well as heterogeneous platforms. Careful attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. One feature required by designers is the ability to add device models, many specific to the needs of Sandia, to the code. To this end, the device package in the Xyce These input formats include standard analytical models, behavioral models look-up Parallel Electronic Simulator is designed to support a variety of device model inputs. tables, and mesh-level PDE device models. Combined with this flexible interface is an architectural design that greatly simplifies the addition of circuit models. One of the most important feature of Xyce is in providing a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia now has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods) research and development can be performed. Ultimately, these capabilities are migrated to end users.« less
Encrypting Digital Camera with Automatic Encryption Key Deletion
NASA Technical Reports Server (NTRS)
Oakley, Ernest C. (Inventor)
2007-01-01
A digital video camera includes an image sensor capable of producing a frame of video data representing an image viewed by the sensor, an image memory for storing video data such as previously recorded frame data in a video frame location of the image memory, a read circuit for fetching the previously recorded frame data, an encryption circuit having an encryption key input connected to receive the previously recorded frame data from the read circuit as an encryption key, an un-encrypted data input connected to receive the frame of video data from the image sensor and an encrypted data output port, and a write circuit for writing a frame of encrypted video data received from the encrypted data output port of the encryption circuit to the memory and overwriting the video frame location storing the previously recorded frame data.
Spiers Memorial Lecture. Molecular mechanics and molecular electronics.
Beckman, Robert; Beverly, Kris; Boukai, Akram; Bunimovich, Yuri; Choi, Jang Wook; DeIonno, Erica; Green, Johnny; Johnston-Halperin, Ezekiel; Luo, Yi; Sheriff, Bonnie; Stoddart, Fraser; Heath, James R
2006-01-01
We describe our research into building integrated molecular electronics circuitry for a diverse set of functions, and with a focus on the fundamental scientific issues that surround this project. In particular, we discuss experiments aimed at understanding the function of bistable rotaxane molecular electronic switches by correlating the switching kinetics and ground state thermodynamic properties of those switches in various environments, ranging from the solution phase to a Langmuir monolayer of the switching molecules sandwiched between two electrodes. We discuss various devices, low bit-density memory circuits, and ultra-high density memory circuits that utilize the electrochemical switching characteristics of these molecules in conjunction with novel patterning methods. We also discuss interconnect schemes that are capable of bridging the micrometre to submicrometre length scales of conventional patterning approaches to the near-molecular length scales of the ultra-dense memory circuits. Finally, we discuss some of the challenges associated with fabricated ultra-dense molecular electronic integrated circuits.
NASA Astrophysics Data System (ADS)
Mehta, Pankaj; Lang, Alex H.; Schwab, David J.
2016-03-01
A central goal of synthetic biology is to design sophisticated synthetic cellular circuits that can perform complex computations and information processing tasks in response to specific inputs. The tremendous advances in our ability to understand and manipulate cellular information processing networks raises several fundamental physics questions: How do the molecular components of cellular circuits exploit energy consumption to improve information processing? Can one utilize ideas from thermodynamics to improve the design of synthetic cellular circuits and modules? Here, we summarize recent theoretical work addressing these questions. Energy consumption in cellular circuits serves five basic purposes: (1) increasing specificity, (2) manipulating dynamics, (3) reducing variability, (4) amplifying signal, and (5) erasing memory. We demonstrate these ideas using several simple examples and discuss the implications of these theoretical ideas for the emerging field of synthetic biology. We conclude by discussing how it may be possible to overcome these limitations using "post-translational" synthetic biology that exploits reversible protein modification.
Quantum Memristors with Superconducting Circuits
Salmilehto, J.; Deppe, F.; Di Ventra, M.; ...
2017-02-14
Memristors are resistive elements retaining information of their past dynamics. They have garnered substantial interest due to their potential for representing a paradigm change in electronics, information processing and unconventional computing. Given the advent of quantum technologies, a design for a quantum memristor with superconducting circuits may be envisaged. Along these lines, we introduce such a quantum device whose memristive behavior arises from quasiparticle-induced tunneling when supercurrents are cancelled. Here in this paper, for realistic parameters, we find that the relevant hysteretic behavior may be observed using current state-of-the-art measurements of the phase-driven tunneling current. Finally, we develop suitable methodsmore » to quantify memory retention in the system.« less
Redundancy approaches in bubble domain memories
NASA Technical Reports Server (NTRS)
Almasi, G. S.; Schuster, S. E.
1972-01-01
Fabrication of integrated circuit chips to compensate for faulty memory elements is discussed. Procedure for testing chips to determine extent of redundancy and faults is described. Mathematical model to define operation is presented. Schematic circuit diagram of test equipment is provided.
Method and apparatus for controlling multiple motors
Jones, Rollin G.; Kortegaard, Bert L.; Jones, David F.
1987-01-01
A method and apparatus are provided for simultaneously controlling a plurality of stepper motors. Addressing circuitry generates address data for each motor in a periodic address sequence. Memory circuits respond to the address data for each motor by accessing a corresponding memory location containing a first operational data set functionally related to a direction for moving the motor, speed data, and rate of speed change. First logic circuits respond to the first data set to generate a motor step command. Second logic circuits respond to the command from the first logic circuits to generate a third data set for replacing the first data set in memory with a current operational motor status, which becomes the first data set when the motor is next addressed.
Modeling and simulation of floating gate nanocrystal FET devices and circuits
NASA Astrophysics Data System (ADS)
Hasaneen, El-Sayed A. M.
The nonvolatile memory market has been growing very fast during the last decade, especially for mobile communication systems. The Semiconductor Industry Association International Technology Roadmap for Semiconductors states that the difficult challenge for nonvolatile semiconductor memories is to achieve reliable, low power, low voltage performance and high-speed write/erase. This can be achieved by aggressive scaling of the nonvolatile memory cells. Unfortunately, scaling down of conventional nonvolatile memory will further degrade the retention time due to the charge loss between the floating gate and drain/source contacts and substrate which makes conventional nonvolatile memory unattractive. Using nanocrystals as charge storage sites reduces dramatically the charge leakage through oxide defects and drain/source contacts. Floating gate nanocrystal nonvolatile memory, FG-NCNVM, is a candidate for future memory because it is advantageous in terms of high-speed write/erase, small size, good scalability, low-voltage, low-power applications, and the capability to store multiple bits per cell. Many studies regarding FG-NCNVMs have been published. Most of them have dealt with fabrication improvements of the devices and device characterizations. Due to the promising FG-NCNVM applications in integrated circuits, there is a need for circuit a simulation model to simulate the electrical characteristics of the floating gate devices. In this thesis, a FG-NCNVM circuit simulation model has been proposed. It is based on the SPICE BSIM simulation model. This model simulates the cell behavior during normal operation. Model validation results have been presented. The SPICE model shows good agreement with experimental results. Current-voltage characteristics, transconductance and unity gain frequency (fT) have been studied showing the effect of the threshold voltage shift (DeltaVth) due to nanocrystal charge on the device characteristics. The threshold voltage shift due to nanocrystal charge has a strong effect on the memory characteristics. Also, the programming operation of the memory cell has been investigated. The tunneling rate from quantum well channel to quantum dot (nanocrystal) gate is calculated. The calculations include various memory parameters, wavefunctions, and energies of quantum well channel and quantum dot gate. The use of floating gate nanocrystal memory as a transistor with a programmable threshold voltage has been demonstrated. The incorporation of FG-NCFETs to design programmable integrated circuit building blocks has been discussed. This includes the design of programmable current and voltage reference circuits. Finally, we demonstrated the design of tunable gain op-amp incorporating FG-NCFETs. Programmable integrated circuit building blocks can be used in intelligent analog and digital systems.
Digital MOS integrated circuits
NASA Astrophysics Data System (ADS)
Elmasry, M. I.
MOS in digital circuit design is considered along with aspects of digital VLSI, taking into account a comparison of MOSFET logic circuits, 1-micrometer MOSFET VLSI technology, a generalized guide for MOSFET miniaturization, processing technologies, novel circuit structures for VLSI, and questions of circuit and system design for VLSI. MOS memory cells and circuits are discussed, giving attention to a survey of high-density dynamic RAM cell concepts, one-device cells for dynamic random-access memories, variable resistance polysilicon for high density CMOS Ram, high performance MOS EPROMs using a stacked-gate cell, and the optimization of the latching pulse for dynamic flip-flop sensors. Programmable logic arrays are considered along with digital signal processors, microprocessors, static RAMs, and dynamic RAMs.
NASA Astrophysics Data System (ADS)
Tan, Kuan Yen; Partanen, Matti; Lake, Russell E.; Govenius, Joonas; Masuda, Shumpei; Möttönen, Mikko
2017-05-01
Quantum technology promises revolutionizing applications in information processing, communications, sensing and modelling. However, efficient on-demand cooling of the functional quantum degrees of freedom remains challenging in many solid-state implementations, such as superconducting circuits. Here we demonstrate direct cooling of a superconducting resonator mode using voltage-controllable electron tunnelling in a nanoscale refrigerator. This result is revealed by a decreased electron temperature at a resonator-coupled probe resistor, even for an elevated electron temperature at the refrigerator. Our conclusions are verified by control experiments and by a good quantitative agreement between theory and experimental observations at various operation voltages and bath temperatures. In the future, we aim to remove spurious dissipation introduced by our refrigerator and to decrease the operational temperature. Such an ideal quantum-circuit refrigerator has potential applications in the initialization of quantum electric devices. In the superconducting quantum computer, for example, fast and accurate reset of the quantum memory is needed.
EDITORIAL: Synaptic electronics Synaptic electronics
NASA Astrophysics Data System (ADS)
Demming, Anna; Gimzewski, James K.; Vuillaume, Dominique
2013-09-01
Conventional computers excel in logic and accurate scientific calculations but make hard work of open ended problems that human brains handle easily. Even von Neumann—the mathematician and polymath who first developed the programming architecture that forms the basis of today's computers—was already looking to the brain for future developments before his death in 1957 [1]. Neuromorphic computing uses approaches that better mimic the working of the human brain. Recent developments in nanotechnology are now providing structures with very accommodating properties for neuromorphic approaches. This special issue, with guest editors James K Gimzewski and Dominique Vuillaume, is devoted to research at the serendipitous interface between the two disciplines. 'Synaptic electronics', looks at artificial devices with connections that demonstrate behaviour similar to synapses in the nervous system allowing a new and more powerful approach to computing. Synapses and connecting neurons respond differently to incident signals depending on the history of signals previously experienced, ultimately leading to short term and long term memory behaviour. The basic characteristics of a synapse can be replicated with around ten simple transistors. However with the human brain having around 1011 neurons and 1015 synapses, artificial neurons and synapses from basic transistors are unlikely to accommodate the scalability required. The discovery of nanoscale elements that function as 'memristors' has provided a key tool for the implementation of synaptic connections [2]. Leon Chua first developed the concept of the 'The memristor—the missing circuit element' in 1971 [3]. In this special issue he presents a tutorial describing how memristor research has fed into our understanding of synaptic behaviour and how they can be applied in information processing [4]. He also describes, 'The new principle of local activity, which uncovers a minuscule life-enabling "Goldilocks zone", dubbed the edge of chaos, where complex phenomena, including creativity and intelligence, may emerge'. Also in this issue R Stanley Williams and colleagues report results from simulations that demonstrate the potential for using Mott transistors as building blocks for scalable neuristor-based integrated circuits without transistors [5]. The scalability of neural chip designs is also tackled in the design reported by Narayan Srinivasa and colleagues in the US [6]. Meanwhile Carsten Timm and Massimiliano Di Ventra describe simulations of a molecular transistor in which electrons strongly coupled to a vibrational mode lead to a Franck-Condon (FC) blockade that mimics the spiking action potentials in synaptic memory behaviour [7]. The 'atomic switches' used to demonstrate synaptic behaviour by a collaboration of researchers in California and Japan also come under further scrutiny in this issue. James K Gimzewski and colleagues consider the difference between the behaviour of an atomic switch in isolation and in a network [8]. As the authors point out, 'The work presented represents steps in a unified approach of experimentation and theory of complex systems to make atomic switch networks a uniquely scalable platform for neuromorphic computing'. Researchers in Germany [9] and Sweden [10] also report on theoretical approaches to modelling networks of memristive elements and complementary resistive switches for synaptic devices. As Vincent Derycke and colleagues in France point out, 'Actual experimental demonstrations of neural network type circuits based on non-conventional/non-CMOS memory devices and displaying function learning capabilities remain very scarce'. They describe how their work using carbon nanotubes provides a rare demonstration of actual function learning with synapses based on nanoscale building blocks [11]. However, this is far from the only experimental work reported in this issue, others include: short-term memory of TiO2-based electrochemical capacitors [12]; a neuromorphic circuit composed of a nanoscale 1-kbit resistive random-access memory (RRAM) cross-point array of synapses and complementary metal-oxide-semiconductor (CMOS) neuron circuits [13]; a WO3-x-based nanoionics device from Masakazu Aono's group with a wide scale of reprogrammable memorization functions [14]; a new spike-timing dependent plasticity scheme based on a MOS transistor as a selector and a RRAM as a variable resistance device [15]; a new hybrid memristor-CMOS neuromorphic circuit [16]; and a photo-assisted atomic switch [17]. Synaptic electronics evidently has many emerging facets, and Duygu Kuzum, Shimeng Yu, and H-S Philip Wong in the US provide a review of the field, including the materials, devices and applications [18]. In embracing the expertise acquired over thousands of years of evolution, biomimetics and bio-inspired design is a common, smart approach to technological innovation. Yet in successfully mimicking the physiological mechanisms of the human mind synaptic electronics research has a potential impact that is arguably unprecedented. That the quirks and eccentricities recently unearthed in the behaviour of nanomaterials should lend themselves so accommodatingly to emulating synaptic functions promises some very exciting developments in the field, as the articles in this special issue emphasize. References [1] von Neumann J (ed) 2012 The Computer and the Brain 3rd edn (Yale: Yale University Press) [2] Strukov D B, Snider G S, Stewart D R and Williams R S 2008 The missing memristor found Nature 453 80-3 [3] Chua L O 1971 Memristor—the missing circuit element IEEE Trans. Circuit Theory 18 507-19 [4] Chua L O 2013 Memristor, Hodgkin-Huxley, and Edge of Chaos Nanotechnology 24 383001 [5] Pickett M D and Williams R S 2013 Phase transitions enable computational universality in neuristor-based cellular automata Nanotechnology 24 384002 [6] Cruz-Albrecht J M, Derosier T and Srinivasa N 2013 Scalable neural chip with synaptic electronics using CMOS integrated memristors Nanotechnology 24 384011 [7] Timm C and Di Ventra M 2013 Molecular neuron based on the Franck-Condon blockade Nanotechnology 24 384001 [8] Sillin H O, Aguilera R, Shieh H-H, Avizienis A V, Aono M, Stieg A Z and Gimzewski J K 2013 A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing Nanotechnology 24 384004 [9] Linn E, Menzel S, Ferch S and Waser R 2013 Compact modeling of CRS devices based on ECM cells for memory, logic and neuromorphic applications Nanotechnology 24 384008 [10] Konkoli Z and Wendin G 2013 A generic simulator for large networks of memristive elements Nanotechnology 24 384007 [11] Gacem K, Retrouvey J-M, Chabi D, Filoramo A, Zhao W, Klein J-O and Derycke V 2013 Neuromorphic function learning with carbon nanotube-based synapses Nanotechnology 24 384013 [12] Lim H, Kim I, Kim J-S, Hwang C S and Jeong D S 2013 Short-term memory of TiO2-based electrochemical capacitors: empirical analysis with adoption of a sliding threshold Nanotechnology 24 384005 [13] Park S, Noh J, Choo M-L, Sheri A M, Chang M, Kim Y-B, Kim C J, Jeon M, Lee B-G, Lee B H and Hwang H 2013 Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device Nanotechnology 24 384009 [14] Yang R, Terabe K, Yao Y, Tsuruoka T, Hasegawa T, Gimzewski J K and Aono M 2013 Synaptic plasticity and memory functions achieved in WO3-x-based nanoionics device by using principle of atomic switch operation Nanotechnology 24 384002 [15] Ambrogio S, Balatti S, Nardi F, Facchinetti S and Ielmini D 2013 Spike-timing dependent plasticity in a transistor-selected resistive switching memory Nanotechnology 24 384012 [16] Indiveria G, Linares-Barranco B, Legenstein R, Deligeorgis G and Prodromakise T 2013 Integration of nanoscale memristor synapses in neuromorphic computing architectures Nanotechnology 24 384010 [17] Hino T, Hasegawa T, Tanaka H, Tsuruoka T, Terabe K, Ogawa T and Aono M 2013 Volatile and nonvolatile selective switching of a photo-assited initialized atomic switch Nanotechnology 24 384006 [18] Kuzum D, Yu S and Wong H-S P 2013 Synaptic electronics: materials, devices and applications Nanotechnology 24 382001
Numerical characteristics of quantum computer simulation
NASA Astrophysics Data System (ADS)
Chernyavskiy, A.; Khamitov, K.; Teplov, A.; Voevodin, V.; Voevodin, Vl.
2016-12-01
The simulation of quantum circuits is significantly important for the implementation of quantum information technologies. The main difficulty of such modeling is the exponential growth of dimensionality, thus the usage of modern high-performance parallel computations is relevant. As it is well known, arbitrary quantum computation in circuit model can be done by only single- and two-qubit gates, and we analyze the computational structure and properties of the simulation of such gates. We investigate the fact that the unique properties of quantum nature lead to the computational properties of the considered algorithms: the quantum parallelism make the simulation of quantum gates highly parallel, and on the other hand, quantum entanglement leads to the problem of computational locality during simulation. We use the methodology of the AlgoWiki project (algowiki-project.org) to analyze the algorithm. This methodology consists of theoretical (sequential and parallel complexity, macro structure, and visual informational graph) and experimental (locality and memory access, scalability and more specific dynamic characteristics) parts. Experimental part was made by using the petascale Lomonosov supercomputer (Moscow State University, Russia). We show that the simulation of quantum gates is a good base for the research and testing of the development methods for data intense parallel software, and considered methodology of the analysis can be successfully used for the improvement of the algorithms in quantum information science.
To Replay, Perchance to Consolidate
Genzel, Lisa; Robertson, Edwin M.
2015-01-01
After a memory is formed, it continues to be processed by the brain. These “off-line” processes consolidate the memory, leading to its enhancement and to changes in memory circuits. Potentially, these memory changes are driven by off-line replay of the pattern of neuronal activity present when the memory was being formed. A new study by Dhaksin Ramanathan and colleagues, published in PLOS Biology, demonstrates that replay occurs predominately after the acquisition of a new motor skill and that it is related to changes in memory performance and to the subsequent changes in memory circuits. Together, these observations reveal the importance of neuronal replay in the consolidation of novel motor skills. PMID:26496145
NASA Astrophysics Data System (ADS)
An, Soyoung; Choi, Woochul; Paik, Se-Bum
2015-11-01
Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.
Command and data handling of science signals on Spacelab
NASA Technical Reports Server (NTRS)
Mccain, H. G.
1975-01-01
The Orbiter Avionics and the Spacelab Command and Data Management System (CDMS) combine to provide a relatively complete command, control, and data handling service to the instrument complement during a Shuttle Sortie Mission. The Spacelab CDMS services the instruments and the Orbiter in turn services the Spacelab. The CDMS computer system includes three computers, two I/O units, a mass memory, and a variable number of remote acquisition units. Attention is given to the CDMS high rate multiplexer, CDMS tape recorders, closed circuit television for the visual monitoring of payload bay and cabin area activities, methods of science data acquisition, questions of transmission and recording, CDMS experiment computer usage, and experiment electronics.
NASA Astrophysics Data System (ADS)
Duan, Haoran
1997-12-01
This dissertation presents the concepts, principles, performance, and implementation of input queuing and cell-scheduling modules for the Illinois Pulsar-based Optical INTerconnect (iPOINT) input-buffered Asynchronous Transfer Mode (ATM) testbed. Input queuing (IQ) ATM switches are well suited to meet the requirements of current and future ultra-broadband ATM networks. The IQ structure imposes minimum memory bandwidth requirements for cell buffering, tolerates bursty traffic, and utilizes memory efficiently for multicast traffic. The lack of efficient cell queuing and scheduling solutions has been a major barrier to build high-performance, scalable IQ-based ATM switches. This dissertation proposes a new Three-Dimensional Queue (3DQ) and a novel Matrix Unit Cell Scheduler (MUCS) to remove this barrier. 3DQ uses a linked-list architecture based on Synchronous Random Access Memory (SRAM) to combine the individual advantages of per-virtual-circuit (per-VC) queuing, priority queuing, and N-destination queuing. It avoids Head of Line (HOL) blocking and provides per-VC Quality of Service (QoS) enforcement mechanisms. Computer simulation results verify the QoS capabilities of 3DQ. For multicast traffic, 3DQ provides efficient usage of cell buffering memory by storing multicast cells only once. Further, the multicast mechanism of 3DQ prevents a congested destination port from blocking other less- loaded ports. The 3DQ principle has been prototyped in the Illinois Input Queue (iiQueue) module. Using Field Programmable Gate Array (FPGA) devices, SRAM modules, and integrated on a Printed Circuit Board (PCB), iiQueue can process incoming traffic at 800 Mb/s. Using faster circuit technology, the same design is expected to operate at the OC-48 rate (2.5 Gb/s). MUCS resolves the output contention by evaluating the weight index of each candidate and selecting the heaviest. It achieves near-optimal scheduling and has a very short response time. The algorithm originates from a heuristic strategy that leads to 'socially optimal' solutions, yielding a maximum number of contention-free cells being scheduled. A novel mixed digital-analog circuit has been designed to implement the MUCS core functionality. The MUCS circuit maps the cell scheduling computation to the capacitor charging and discharging procedures that are conducted fully in parallel. The design has a uniform circuit structure, low interconnect counts, and low chip I/O counts. Using 2 μm CMOS technology, the design operates on a 100 MHz clock and finds a near-optimal solution within a linear processing time. The circuit has been verified at the transistor level by HSPICE simulation. During this research, a five-port IQ-based optoelectronic iPOINT ATM switch has been developed and demonstrated. It has been fully functional with an aggregate throughput of 800 Mb/s. The second-generation IQ-based switch is currently under development. Equipped with iiQueue modules and MUCS module, the new switch system will deliver a multi-gigabit aggregate throughput, eliminate HOL blocking, provide per-VC QoS, and achieve near-100% link bandwidth utilization. Complete documentation of input modules and trunk module for the existing testbed, and complete documentation of 3DQ, iiQueue, and MUCS for the second-generation testbed are given in this dissertation.
Focal plane infrared readout circuit with automatic background suppression
NASA Technical Reports Server (NTRS)
Pain, Bedabrata (Inventor); Yang, Guang (Inventor); Sun, Chao (Inventor); Shaw, Timothy J. (Inventor); Wrigley, Chris J. (Inventor)
2002-01-01
A circuit for reading out a signal from an infrared detector includes a current-mode background-signal subtracting circuit having a current memory which can be enabled to sample and store a dark level signal from the infrared detector during a calibration phase. The signal stored by the current memory is subtracted from a signal received from the infrared detector during an imaging phase. The circuit also includes a buffered direct injection input circuit and a differential voltage readout section. By performing most of the background signal estimation and subtraction in a current mode, a low gain can be provided by the buffered direct injection input circuit to keep the gain of the background signal relatively small, while a higher gain is provided by the differential voltage readout circuit. An array of such readout circuits can be used in an imager having an array of infrared detectors. The readout circuits can provide a high effective handling capacity.
Auto-programmable impulse neural circuits
NASA Technical Reports Server (NTRS)
Watula, D.; Meador, J.
1990-01-01
Impulse neural networks use pulse trains to communicate neuron activation levels. Impulse neural circuits emulate natural neurons at a more detailed level than that typically employed by contemporary neural network implementation methods. An impulse neural circuit which realizes short term memory dynamics is presented. The operation of that circuit is then characterized in terms of pulse frequency modulated signals. Both fixed and programmable synapse circuits for realizing long term memory are also described. The implementation of a simple and useful unsupervised learning law is then presented. The implementation of a differential Hebbian learning rule for a specific mean-frequency signal interpretation is shown to have a straightforward implementation using digital combinational logic with a variation of a previously developed programmable synapse circuit. This circuit is expected to be exploited for simple and straightforward implementation of future auto-adaptive neural circuits.
Recent trends in hardware security exploiting hybrid CMOS-resistive memory circuits
NASA Astrophysics Data System (ADS)
Sahay, Shubham; Suri, Manan
2017-12-01
This paper provides a comprehensive review and insight of recent trends in the field of random number generator (RNG) and physically unclonable function (PUF) circuits implemented using different types of emerging resistive non-volatile (NVM) memory devices. We present a detailed review of hybrid RNG/PUF implementations based on the use of (i) Spin-Transfer Torque (STT-MRAM), and (ii) metal-oxide based (OxRAM), NVM devices. Various approaches on Hybrid CMOS-NVM RNG/PUF circuits are considered, followed by a discussion on different nanoscale device phenomena. Certain nanoscale device phenomena (variability/stochasticity etc), which are otherwise undesirable for reliable memory and storage applications, form the basis for low power and highly scalable RNG/PUF circuits. Detailed qualitative comparison and benchmarking of all implementations is performed.
Compact modeling of CRS devices based on ECM cells for memory, logic and neuromorphic applications.
Linn, E; Menzel, S; Ferch, S; Waser, R
2013-09-27
Dynamic physics-based models of resistive switching devices are of great interest for the realization of complex circuits required for memory, logic and neuromorphic applications. Here, we apply such a model of an electrochemical metallization (ECM) cell to complementary resistive switches (CRSs), which are favorable devices to realize ultra-dense passive crossbar arrays. Since a CRS consists of two resistive switching devices, it is straightforward to apply the dynamic ECM model for CRS simulation with MATLAB and SPICE, enabling study of the device behavior in terms of sweep rate and series resistance variations. Furthermore, typical memory access operations as well as basic implication logic operations can be analyzed, revealing requirements for proper spike and level read operations. This basic understanding facilitates applications of massively parallel computing paradigms required for neuromorphic applications.
Prefrontal neuronal circuits of contextual fear conditioning.
Rozeske, R R; Valerio, S; Chaudun, F; Herry, C
2015-01-01
Over the past years, numerous studies have provided a clear understanding of the neuronal circuits and mechanisms involved in the formation, expression and extinction phases of conditioned cued fear memories. Yet, despite a strong clinical interest, a detailed understanding of these memory phases for contextual fear memories is still missing. Besides the well-known role of the hippocampus in encoding contextual fear behavior, growing evidence indicates that specific regions of the medial prefrontal cortex differentially regulate contextual fear acquisition and storage in both animals and humans that ultimately leads to expression of contextual fear memories. In this review, we provide a detailed description of the recent literature on the role of distinct prefrontal subregions in contextual fear behavior and provide a working model of the neuronal circuits involved in the acquisition, expression and generalization of contextual fear memories. © 2014 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.
Pathophysiology and Treatment of Memory Dysfunction after Traumatic Brain Injury
Paterno, Rosalia; Folweiler, Kaitlin A.; Cohen, Akiva S.
2018-01-01
Memory is fundamental to everyday life, and cognitive impairments resulting from traumatic brain injury (TBI) have devastating effects on TBI survivors. A contributing component to memory impairments caused by TBI are alterations in the neural circuits associated with memory function. In this review, we aim to bring together experimental findings that characterize behavioral memory deficits and the underlying pathophysiology of memory-involved circuits after TBI. While there is little doubt that TBI causes memory and cognitive dysfunction, it is difficult to conclude which memory phase i.e., encoding, maintenance or retrieval is specifically altered by TBI. This is most likely due to variation in behavioral protocols and experimental models. Additionally we review a selection of experimental treatments that hold translational potential to mitigate memory dysfunction following injury. PMID:28500417
Variable-Resistivity Material For Memory Circuits
NASA Technical Reports Server (NTRS)
Nagasubramanian, Ganesan; Distefano, Salvador; Moacanin, Jovan
1989-01-01
Nonvolatile memory elements packed densely. Electrically-erasable, programmable, read-only memory matrices made with newly-synthesized organic material of variable electrical resistivity. Material, polypyrrole doped with tetracyanoquinhydrone (TCNQ), changes reversibly between insulating or higher-resistivity state and conducting or low-resistivity state. Thin film of conductive polymer separates layer of row conductors from layer of column conductors. Resistivity of film at each intersection and, therefore, resistance of memory element defined by row and column, increased or decreased by application of suitable switching voltage. Matrix circuits made with this material useful for experiments in associative electronic memories based on models of neural networks.
New Methods for Understanding Systems Consolidation
ERIC Educational Resources Information Center
Tayler, Kaycie K.; Wiltgen, Brian J.
2013-01-01
According to the standard model of systems consolidation (SMC), neocortical circuits are reactivated during the retrieval of declarative memories. This process initially requires the hippocampus. However, with the passage of time, neocortical circuits become strengthened and can eventually retrieve memory without input from the hippocampus.…
Reward signal in a recurrent circuit drives appetitive long-term memory formation.
Ichinose, Toshiharu; Aso, Yoshinori; Yamagata, Nobuhiro; Abe, Ayako; Rubin, Gerald M; Tanimoto, Hiromu
2015-11-17
Dopamine signals reward in animal brains. A single presentation of a sugar reward to Drosophila activates distinct subsets of dopamine neurons that independently induce short- and long-term olfactory memories (STM and LTM, respectively). In this study, we show that a recurrent reward circuit underlies the formation and consolidation of LTM. This feedback circuit is composed of a single class of reward-signaling dopamine neurons (PAM-α1) projecting to a restricted region of the mushroom body (MB), and a specific MB output cell type, MBON-α1, whose dendrites arborize that same MB compartment. Both MBON-α1 and PAM-α1 neurons are required during the acquisition and consolidation of appetitive LTM. MBON-α1 additionally mediates the retrieval of LTM, which is dependent on the dopamine receptor signaling in the MB α/β neurons. Our results suggest that a reward signal transforms a nascent memory trace into a stable LTM using a feedback circuit at the cost of memory specificity.
Controllable 0–π Josephson junctions containing a ferromagnetic spin valve
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gingrich, E. C.; Niedzielski, Bethany M.; Glick, Joseph A.
Superconductivity and ferromagnetism are antagonistic forms of order, and rarely coexist. Many interesting new phenomena occur, however, in hybrid superconducting/ferromagnetic systems. For example, a Josephson junction containing a ferromagnetic material can exhibit an intrinsic phase shift of π in its ground state for certain thicknesses of the material. Such ‘π-junctions’ were first realized experimentally in 2001, and have been proposed as circuit elements for both high-speed classical superconducting computing and for quantum computing. Here we demonstrate experimentally that the phase state of a Josephson junction containing two ferromagnetic layers can be toggled between 0 and pi by changing the relativemore » orientation of the two magnetizations. These controllable 0–π junctions have immediate applications in cryogenic memory, where they serve as a necessary component to an ultralow power superconducting computer. Such a fully superconducting computer is estimated to be orders of magnitude more energy-efficient than current semiconductor-based supercomputers. Here, phase-controllable junctions also open up new possibilities for superconducting circuit elements such as superconducting ‘programmable logic’, where they could function in superconducting analogues to field-programmable gate arrays.« less
A Method for Growing Bio-memristors from Slime Mold.
Miranda, Eduardo Reck; Braund, Edward
2017-11-02
Our research is aimed at gaining a better understanding of the electronic properties of organisms in order to engineer novel bioelectronic systems and computing architectures based on biology. This specific paper focuses on harnessing the unicellular slime mold Physarum polycephalum to develop bio-memristors (or biological memristors) and bio-computing devices. The memristor is a resistor that possesses memory. It is the 4th fundamental passive circuit element (the other three are the resistor, the capacitor, and the inductor), which is paving the way for the design of new kinds of computing systems; e.g., computers that might relinquish the distinction between storage and a central processing unit. When applied with an AC voltage, the current vs. voltage characteristic of a memristor is a pinched hysteresis loop. It has been shown that P. polycephalum produces pinched hysteresis loops under AC voltages and displays adaptive behavior that is comparable with the functioning of a memristor. This paper presents the method that we developed for implementing bio-memristors with P. polycephalum and introduces the development of a receptacle to culture the organism, which facilitates its deployment as an electronic circuit component. Our method has proven to decrease growth time, increase component lifespan, and standardize electrical observations.
Controllable 0–π Josephson junctions containing a ferromagnetic spin valve
Gingrich, E. C.; Niedzielski, Bethany M.; Glick, Joseph A.; ...
2016-03-14
Superconductivity and ferromagnetism are antagonistic forms of order, and rarely coexist. Many interesting new phenomena occur, however, in hybrid superconducting/ferromagnetic systems. For example, a Josephson junction containing a ferromagnetic material can exhibit an intrinsic phase shift of π in its ground state for certain thicknesses of the material. Such ‘π-junctions’ were first realized experimentally in 2001, and have been proposed as circuit elements for both high-speed classical superconducting computing and for quantum computing. Here we demonstrate experimentally that the phase state of a Josephson junction containing two ferromagnetic layers can be toggled between 0 and pi by changing the relativemore » orientation of the two magnetizations. These controllable 0–π junctions have immediate applications in cryogenic memory, where they serve as a necessary component to an ultralow power superconducting computer. Such a fully superconducting computer is estimated to be orders of magnitude more energy-efficient than current semiconductor-based supercomputers. Here, phase-controllable junctions also open up new possibilities for superconducting circuit elements such as superconducting ‘programmable logic’, where they could function in superconducting analogues to field-programmable gate arrays.« less
Programmable nanowire circuits for nanoprocessors.
Yan, Hao; Choe, Hwan Sung; Nam, SungWoo; Hu, Yongjie; Das, Shamik; Klemic, James F; Ellenbogen, James C; Lieber, Charles M
2011-02-10
A nanoprocessor constructed from intrinsically nanometre-scale building blocks is an essential component for controlling memory, nanosensors and other functions proposed for nanosystems assembled from the bottom up. Important steps towards this goal over the past fifteen years include the realization of simple logic gates with individually assembled semiconductor nanowires and carbon nanotubes, but with only 16 devices or fewer and a single function for each circuit. Recently, logic circuits also have been demonstrated that use two or three elements of a one-dimensional memristor array, although such passive devices without gain are difficult to cascade. These circuits fall short of the requirements for a scalable, multifunctional nanoprocessor owing to challenges in materials, assembly and architecture on the nanoscale. Here we describe the design, fabrication and use of programmable and scalable logic tiles for nanoprocessors that surmount these hurdles. The tiles were built from programmable, non-volatile nanowire transistor arrays. Ge/Si core/shell nanowires coupled to designed dielectric shells yielded single-nanowire, non-volatile field-effect transistors (FETs) with uniform, programmable threshold voltages and the capability to drive cascaded elements. We developed an architecture to integrate the programmable nanowire FETs and define a logic tile consisting of two interconnected arrays with 496 functional configurable FET nodes in an area of ∼960 μm(2). The logic tile was programmed and operated first as a full adder with a maximal voltage gain of ten and input-output voltage matching. Then we showed that the same logic tile can be reprogrammed and used to demonstrate full-subtractor, multiplexer, demultiplexer and clocked D-latch functions. These results represent a significant advance in the complexity and functionality of nanoelectronic circuits built from the bottom up with a tiled architecture that could be cascaded to realize fully integrated nanoprocessors with computing, memory and addressing capabilities.
Memory formation orchestrates the wiring of adult-born hippocampal neurons into brain circuits.
Petsophonsakul, Petnoi; Richetin, Kevin; Andraini, Trinovita; Roybon, Laurent; Rampon, Claire
2017-08-01
During memory formation, structural rearrangements of dendritic spines provide a mean to durably modulate synaptic connectivity within neuronal networks. New neurons generated throughout the adult life in the dentate gyrus of the hippocampus contribute to learning and memory. As these neurons become incorporated into the network, they generate huge numbers of new connections that modify hippocampal circuitry and functioning. However, it is yet unclear as to how the dynamic process of memory formation influences their synaptic integration into neuronal circuits. New memories are established according to a multistep process during which new information is first acquired and then consolidated to form a stable memory trace. Upon recall, memory is transiently destabilized and vulnerable to modification. Using contextual fear conditioning, we found that learning was associated with an acceleration of dendritic spines formation of adult-born neurons, and that spine connectivity becomes strengthened after memory consolidation. Moreover, we observed that afferent connectivity onto adult-born neurons is enhanced after memory retrieval, while extinction training induces a change of spine shapes. Together, these findings reveal that the neuronal activity supporting memory processes strongly influences the structural dendritic integration of adult-born neurons into pre-existing neuronal circuits. Such change of afferent connectivity is likely to impact the overall wiring of hippocampal network, and consequently, to regulate hippocampal function.
Recirculating cross-correlation detector
Andrews, W.H. Jr.; Roberts, M.J.
1985-01-18
A digital cross-correlation detector is provided in which two time-varying signals are correlated by repetitively comparing data samples stored in digital form to detect correlation between the two signals. The signals are sampled at a selected rate converted to digital form, and stored in separate locations in separate memories. When the memories are filled, the data samples from each memory are first fed word-by-word through a multiplier and summing circuit and each result is compared to the last in a peak memory circuit and if larger than the last is retained in the peak memory. Then the address line to leading signal memory is offset by one byte to affect one sample period delay of a known amount in that memory and the data in the two memories are then multiplied word-by-word once again and summed. If a new result is larger than a former sum, it is saved in the peak memory together with the time delay. The recirculating process continues with the address of the one memory being offset one additional byte each cycle until the address is shifted through the length of the memory. The correlation between the two signals is indicated by the peak signal stored in the peak memory together with the delay time at which the peak occurred. The circuit is faster and considerably less expensive than comparable accuracy correlation detectors.
Entorhinal-Hippocampal Neuronal Circuits Bridge Temporally Discontiguous Events
ERIC Educational Resources Information Center
Kitamura, Takashi; Macdonald, Christopher J.; Tonegawa, Susumu
2015-01-01
The entorhinal cortex (EC)-hippocampal (HPC) network plays an essential role for episodic memory, which preserves spatial and temporal information about the occurrence of past events. Although there has been significant progress toward understanding the neural circuits underlying the spatial dimension of episodic memory, the relevant circuits…
A simple algorithm to compute the peak power output of GaAs/Ge solar cells on the Martian surface
DOE Office of Scientific and Technical Information (OSTI.GOV)
Glueck, P.R.; Bahrami, K.A.
1995-12-31
The Jet Propulsion Laboratory`s (JPL`s) Mars Pathfinder Project will deploy a robotic ``microrover`` on the surface of Mars in the summer of 1997. This vehicle will derive primary power from a GaAs/Ge solar array during the day and will ``sleep`` at night. This strategy requires that the rover be able to (1) determine when it is necessary to save the contents of volatile memory late in the afternoon and (2) determine when sufficient power is available to resume operations in the morning. An algorithm was developed that estimates the peak power point of the solar array from the solar arraymore » short-circuit current and temperature telemetry, and provides functional redundancy for both measurements using the open-circuit voltage telemetry. The algorithm minimizes vehicle processing and memory utilization by using linear equations instead of look-up tables to estimate peak power with very little loss in accuracy. This paper describes the method used to obtain the algorithm and presents the detailed algorithm design.« less
Logistics and Operational Effectiveness of the P-3 Aircraft.
1977-03-01
Memory Module Tester for the AIMD at HAS Jacksonville Module Caddy utilization for the Position Indicator Failure rate and spares availability of the...into the P—3 aircraft • Investigated TRIAC failures in the AN/AQA-7(V) Sonar Computer Recorder Group • Identified and investigated incorrect use of...Magnetic Tape Transport: Replacement vacuum blower motors Piece parts for A7A1 circuit board • Investigated the availability of spare HI/LO Backward Wave
Time-scale invariance as an emergent property in a perceptron with realistic, noisy neurons
Buhusi, Catalin V.; Oprisan, Sorinel A.
2013-01-01
In most species, interval timing is time-scale invariant: errors in time estimation scale up linearly with the estimated duration. In mammals, time-scale invariance is ubiquitous over behavioral, lesion, and pharmacological manipulations. For example, dopaminergic drugs induce an immediate, whereas cholinergic drugs induce a gradual, scalar change in timing. Behavioral theories posit that time-scale invariance derives from particular computations, rules, or coding schemes. In contrast, we discuss a simple neural circuit, the perceptron, whose output neurons fire in a clockwise fashion (interval timing) based on the pattern of coincidental activation of its input neurons. We show numerically that time-scale invariance emerges spontaneously in a perceptron with realistic neurons, in the presence of noise. Under the assumption that dopaminergic drugs modulate the firing of input neurons, and that cholinergic drugs modulate the memory representation of the criterion time, we show that a perceptron with realistic neurons reproduces the pharmacological clock and memory patterns, and their time-scale invariance, in the presence of noise. These results suggest that rather than being a signature of higher-order cognitive processes or specific computations related to timing, time-scale invariance may spontaneously emerge in a massively-connected brain from the intrinsic noise of neurons and circuits, thus providing the simplest explanation for the ubiquity of scale invariance of interval timing. PMID:23518297
Li, Wenjun; Antuono, Piero G; Xie, Chunming; Chen, Gang; Jones, Jennifer L; Ward, B Douglas; Singh, Suraj P; Franczak, Malgorzata B; Goveas, Joseph S; Li, Shi-Jiang
2014-08-01
The main objective of this study is to detect the early changes in resting-state Papez circuit functional connectivity using the hippocampus as the seed, and to determine the associations between altered functional connectivity (FC) and the episodic memory performance in cognitively intact middle-aged apolipoprotein E4 (APOE4) carriers who are at risk of Alzheimer's disease (AD). Forty-six cognitively intact, middle-aged participants, including 20 APOE4 carriers and 26 age-, sex-, and education-matched noncarriers were studied. The resting-state FC of the hippocampus (HFC) was compared between APOE4 carriers and noncarriers. APOE4 carriers showed significantly decreased FC in brain areas that involve learning and memory functions, including the frontal, cingulate, thalamus and basal ganglia regions. Multiple linear regression analysis showed significant correlations between HFC and the episodic memory performance. Conjunction analysis between neural correlates of memory and altered HFC showed the overlapping regions, especially the subcortical regions such as thalamus, caudate nucleus, and cingulate cortices involved in the Papez circuit. Thus, changes in connectivity in the Papez circuit may be used as an early risk detection for AD. Copyright © 2014. Published by Elsevier Ltd.
Commentary: Elucidating the Neural Correlates of Early Childhood Memory
ERIC Educational Resources Information Center
Mullally, Sinead L.
2015-01-01
Both episodic memory and the key neural structure believed to support it, namely the hippocampus, are believed to undergo protracted periods of postnatal developmental. Critically however, the hippocampus is comprised of distinct subfields and circuits, and these circuits appear to mature at different rates (Lavenex and Banta Lavenex, 2013).…
Cell type-specific genetic and optogenetic tools reveal hippocampal CA2 circuits.
Kohara, Keigo; Pignatelli, Michele; Rivest, Alexander J; Jung, Hae-Yoon; Kitamura, Takashi; Suh, Junghyup; Frank, Dominic; Kajikawa, Koichiro; Mise, Nathan; Obata, Yuichi; Wickersham, Ian R; Tonegawa, Susumu
2014-02-01
The formation and recall of episodic memory requires precise information processing by the entorhinal-hippocampal network. For several decades, the trisynaptic circuit entorhinal cortex layer II (ECII)→dentate gyrus→CA3→CA1 and the monosynaptic circuit ECIII→CA1 have been considered the primary substrates of the network responsible for learning and memory. Circuits linked to another hippocampal region, CA2, have only recently come to light. Using highly cell type-specific transgenic mouse lines, optogenetics and patch-clamp recordings, we found that dentate gyrus cells, long believed to not project to CA2, send functional monosynaptic inputs to CA2 pyramidal cells through abundant longitudinal projections. CA2 innervated CA1 to complete an alternate trisynaptic circuit, but, unlike CA3, projected preferentially to the deep, rather than to the superficial, sublayer of CA1. Furthermore, contrary to existing knowledge, ECIII did not project to CA2. Our results allow a deeper understanding of the biology of learning and memory.
The declarative/procedural model of lexicon and grammar.
Ullman, M T
2001-01-01
Our use of language depends upon two capacities: a mental lexicon of memorized words and a mental grammar of rules that underlie the sequential and hierarchical composition of lexical forms into predictably structured larger words, phrases, and sentences. The declarative/procedural model posits that the lexicon/grammar distinction in language is tied to the distinction between two well-studied brain memory systems. On this view, the memorization and use of at least simple words (those with noncompositional, that is, arbitrary form-meaning pairings) depends upon an associative memory of distributed representations that is subserved by temporal-lobe circuits previously implicated in the learning and use of fact and event knowledge. This "declarative memory" system appears to be specialized for learning arbitrarily related information (i.e., for associative binding). In contrast, the acquisition and use of grammatical rules that underlie symbol manipulation is subserved by frontal/basal-ganglia circuits previously implicated in the implicit (nonconscious) learning and expression of motor and cognitive "skills" and "habits" (e.g., from simple motor acts to skilled game playing). This "procedural" system may be specialized for computing sequences. This novel view of lexicon and grammar offers an alternative to the two main competing theoretical frameworks. It shares the perspective of traditional dual-mechanism theories in positing that the mental lexicon and a symbol-manipulating mental grammar are subserved by distinct computational components that may be linked to distinct brain structures. However, it diverges from these theories where they assume components dedicated to each of the two language capacities (that is, domain-specific) and in their common assumption that lexical memory is a rote list of items. Conversely, while it shares with single-mechanism theories the perspective that the two capacities are subserved by domain-independent computational mechanisms, it diverges from them where they link both capacities to a single associative memory system with broad anatomic distribution. The declarative/procedural model, but neither traditional dual- nor single-mechanism models, predicts double dissociations between lexicon and grammar, with associations among associative memory properties, memorized words and facts, and temporal-lobe structures, and among symbol-manipulation properties, grammatical rule products, motor skills, and frontal/basal-ganglia structures. In order to contrast lexicon and grammar while holding other factors constant, we have focused our investigations of the declarative/procedural model on morphologically complex word forms. Morphological transformations that are (largely) unproductive (e.g., in go-went, solemn-solemnity) are hypothesized to depend upon declarative memory. These have been contrasted with morphological transformations that are fully productive (e.g., in walk-walked, happy-happiness), whose computation is posited to be solely dependent upon grammatical rules subserved by the procedural system. Here evidence is presented from studies that use a range of psycholinguistic and neurolinguistic approaches with children and adults. It is argued that converging evidence from these studies supports the declarative/procedural model of lexicon and grammar.
miR-150 Regulates Memory CD8 T Cell Differentiation via c-Myb.
Chen, Zeyu; Stelekati, Erietta; Kurachi, Makoto; Yu, Sixiang; Cai, Zhangying; Manne, Sasikanth; Khan, Omar; Yang, Xiaolu; Wherry, E John
2017-09-12
MicroRNAs play an important role in T cell responses. However, how microRNAs regulate CD8 T cell memory remains poorly defined. Here, we found that miR-150 negatively regulates CD8 T cell memory in vivo. Genetic deletion of miR-150 disrupted the balance between memory precursor and terminal effector CD8 T cells following acute viral infection. Moreover, miR-150-deficient memory CD8 T cells were more protective upon rechallenge. A key circuit whereby miR-150 repressed memory CD8 T cell development through the transcription factor c-Myb was identified. Without miR-150, c-Myb was upregulated and anti-apoptotic targets of c-Myb, such as Bcl-2 and Bcl-xL, were also increased, suggesting a miR-150-c-Myb survival circuit during memory CD8 T cell development. Indeed, overexpression of non-repressible c-Myb rescued the memory CD8 T cell defects caused by overexpression of miR-150. Overall, these results identify a key role for miR-150 in memory CD8 T cells through a c-Myb-controlled enhanced survival circuit. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Croitoru, Bogdan; Tulbure, Adrian; Abrudean, Mihail; Secara, Mihai
2015-02-01
The present paper describes a software method for creating / managing one type of Transducer Electronic Datasheet (TEDS) according to IEEE 1451.4 standard in order to develop a prototype of smart multi-sensor platform (with up to ten different analog sensors simultaneously connected) with Plug and Play capabilities over ETHERNET and Wi-Fi. In the experiments were used: one analog temperature sensor, one analog light sensor, one PIC32-based microcontroller development board with analog and digital I/O ports and other computing resources, one 24LC256 I2C (Inter Integrated Circuit standard) serial Electrically Erasable Programmable Read Only Memory (EEPROM) memory with 32KB available space and 3 bytes internal buffer for page writes (1 byte for data and 2 bytes for address). It was developed a prototype algorithm for writing and reading TEDS information to / from I2C EEPROM memories using the standard C language (up to ten different TEDS blocks coexisting in the same EEPROM device at once). The algorithm is able to write and read one type of TEDS: transducer information with standard TEDS content. A second software application, written in VB.NET platform, was developed in order to access the EEPROM sensor information from a computer through a serial interface (USB).
Asymmetric soft-error resistant memory
NASA Technical Reports Server (NTRS)
Buehler, Martin G. (Inventor); Perlman, Marvin (Inventor)
1991-01-01
A memory system is provided, of the type that includes an error-correcting circuit that detects and corrects, that more efficiently utilizes the capacity of a memory formed of groups of binary cells whose states can be inadvertently switched by ionizing radiation. Each memory cell has an asymmetric geometry, so that ionizing radiation causes a significantly greater probability of errors in one state than in the opposite state (e.g., an erroneous switch from '1' to '0' is far more likely than a switch from '0' to'1'. An asymmetric error correcting coding circuit can be used with the asymmetric memory cells, which requires fewer bits than an efficient symmetric error correcting code.
Energy efficient hybrid computing systems using spin devices
NASA Astrophysics Data System (ADS)
Sharad, Mrigank
Emerging spin-devices like magnetic tunnel junctions (MTJ's), spin-valves and domain wall magnets (DWM) have opened new avenues for spin-based logic design. This work explored potential computing applications which can exploit such devices for higher energy-efficiency and performance. The proposed applications involve hybrid design schemes, where charge-based devices supplement the spin-devices, to gain large benefits at the system level. As an example, lateral spin valves (LSV) involve switching of nanomagnets using spin-polarized current injection through a metallic channel such as Cu. Such spin-torque based devices possess several interesting properties that can be exploited for ultra-low power computation. Analog characteristic of spin current facilitate non-Boolean computation like majority evaluation that can be used to model a neuron. The magneto-metallic neurons can operate at ultra-low terminal voltage of ˜20mV, thereby resulting in small computation power. Moreover, since nano-magnets inherently act as memory elements, these devices can facilitate integration of logic and memory in interesting ways. The spin based neurons can be integrated with CMOS and other emerging devices leading to different classes of neuromorphic/non-Von-Neumann architectures. The spin-based designs involve `mixed-mode' processing and hence can provide very compact and ultra-low energy solutions for complex computation blocks, both digital as well as analog. Such low-power, hybrid designs can be suitable for various data processing applications like cognitive computing, associative memory, and currentmode on-chip global interconnects. Simulation results for these applications based on device-circuit co-simulation framework predict more than ˜100x improvement in computation energy as compared to state of the art CMOS design, for optimal spin-device parameters.
Optimization of a PCRAM Chip for high-speed read and highly reliable reset operations
NASA Astrophysics Data System (ADS)
Li, Xiaoyun; Chen, Houpeng; Li, Xi; Wang, Qian; Fan, Xi; Hu, Jiajun; Lei, Yu; Zhang, Qi; Tian, Zhen; Song, Zhitang
2016-10-01
The widely used traditional Flash memory suffers from its performance limits such as its serious crosstalk problems, and increasing complexity of floating gate scaling. Phase change random access memory (PCRAM) becomes one of the most potential nonvolatile memories among the new memory techniques. In this paper, a 1M-bit PCRAM chip is designed based on the SMIC 40nm CMOS technology. Focusing on the read and write performance, two new circuits with high-speed read operation and highly reliable reset operation are proposed. The high-speed read circuit effectively reduces the reading time from 74ns to 40ns. The double-mode reset circuit improves the chip yield. This 1M-bit PCRAM chip has been simulated on cadence. After layout design is completed, the chip will be taped out for post-test.
Wiring Together Synthetic Bacterial Consortia to Create a Biological Integrated Circuit.
Perry, Nicolas; Nelson, Edward M; Timp, Gregory
2016-12-16
The promise of adapting biology to information processing will not be realized until engineered gene circuits, operating in different cell populations, can be wired together to express a predictable function. Here, elementary biological integrated circuits (BICs), consisting of two sets of transmitter and receiver gene circuit modules with embedded memory placed in separate cell populations, were meticulously assembled using live cell lithography and wired together by the mass transport of quorum-sensing (QS) signal molecules to form two isolated communication links (comlinks). The comlink dynamics were tested by broadcasting "clock" pulses of inducers into the networks and measuring the responses of functionally linked fluorescent reporters, and then modeled through simulations that realistically captured the protein production and molecular transport. These results show that the comlinks were isolated and each mimicked aspects of the synchronous, sequential networks used in digital computing. The observations about the flow conditions, derived from numerical simulations, and the biofilm architectures that foster or silence cell-to-cell communications have implications for everything from decontamination of drinking water to bacterial virulence.
Filamentary model in resistive switching materials
NASA Astrophysics Data System (ADS)
Jasmin, Alladin C.
2017-12-01
The need for next generation computer devices is increasing as the demand for efficient data processing increases. The amount of data generated every second also increases which requires large data storage devices. Oxide-based memory devices are being studied to explore new research frontiers thanks to modern advances in nanofabrication. Various oxide materials are studied as active layers for non-volatile memory. This technology has potential application in resistive random-access-memory (ReRAM) and can be easily integrated in CMOS technologies. The long term perspective of this research field is to develop devices which mimic how the brain processes information. To realize such application, a thorough understanding of the charge transport and switching mechanism is important. A new perspective in the multistate resistive switching based on current-induced filament dynamics will be discussed. A simple equivalent circuit of the device gives quantitative information about the nature of the conducting filament at different resistance states.
Antiferromagnetic CuMnAs multi-level memory cell with microelectronic compatibility
NASA Astrophysics Data System (ADS)
Olejník, K.; Schuler, V.; Marti, X.; Novák, V.; Kašpar, Z.; Wadley, P.; Campion, R. P.; Edmonds, K. W.; Gallagher, B. L.; Garces, J.; Baumgartner, M.; Gambardella, P.; Jungwirth, T.
2017-05-01
Antiferromagnets offer a unique combination of properties including the radiation and magnetic field hardness, the absence of stray magnetic fields, and the spin-dynamics frequency scale in terahertz. Recent experiments have demonstrated that relativistic spin-orbit torques can provide the means for an efficient electric control of antiferromagnetic moments. Here we show that elementary-shape memory cells fabricated from a single-layer antiferromagnet CuMnAs deposited on a III-V or Si substrate have deterministic multi-level switching characteristics. They allow for counting and recording thousands of input pulses and responding to pulses of lengths downscaled to hundreds of picoseconds. To demonstrate the compatibility with common microelectronic circuitry, we implemented the antiferromagnetic bit cell in a standard printed circuit board managed and powered at ambient conditions by a computer via a USB interface. Our results open a path towards specialized embedded memory-logic applications and ultra-fast components based on antiferromagnets.
Early remodeling of the neocortex upon episodic memory encoding
Bero, Adam W.; Meng, Jia; Cho, Sukhee; Shen, Abra H.; Canter, Rebecca G.; Ericsson, Maria; Tsai, Li-Huei
2014-01-01
Understanding the mechanisms by which long-term memories are formed and stored in the brain represents a central aim of neuroscience. Prevailing theory suggests that long-term memory encoding involves early plasticity within hippocampal circuits, whereas reorganization of the neocortex is thought to occur weeks to months later to subserve remote memory storage. Here we report that long-term memory encoding can elicit early transcriptional, structural, and functional remodeling of the neocortex. Parallel studies using genome-wide RNA sequencing, ultrastructural imaging, and whole-cell recording in wild-type mice suggest that contextual fear conditioning initiates a transcriptional program in the medial prefrontal cortex (mPFC) that is accompanied by rapid expansion of the synaptic active zone and postsynaptic density, enhanced dendritic spine plasticity, and increased synaptic efficacy. To address the real-time contribution of the mPFC to long-term memory encoding, we performed temporally precise optogenetic inhibition of excitatory mPFC neurons during contextual fear conditioning. Using this approach, we found that real-time inhibition of the mPFC inhibited activation of the entorhinal–hippocampal circuit and impaired the formation of long-term associative memory. These findings suggest that encoding of long-term episodic memory is associated with early remodeling of neocortical circuits, identify the prefrontal cortex as a critical regulator of encoding-induced hippocampal activation and long-term memory formation, and have important implications for understanding memory processing in healthy and diseased brain states. PMID:25071187
MULTI-ELECTRODE TUBE PULSE MEMORY CIRCUIT
Gundlach, J.C.; Reeves, J.B.
1958-05-20
Control circuits are described for pulse memory devices for scalers and the like, and more particularly to a driving or energizing circuit for a polycathode gaseous discharge tube having an elongated anode and a successive series of cathodes spaced opposite the anode along its length. The circuit is so arranged as to utilize an arc discharge between the anode and a cathode to count a series of pulses. Upon application of an input pulse the discharge is made to occur between the anode and the next successive cathode, and an output pulse is produced when a particular subsequent cathode is reached. The circuit means for transfering the discharge by altering the anode potential and potential of the cathodes and interconnecting the cathodes constitutes the novel aspects of the invention. A low response time and reduced number of circuit components are the practical advantages of the described circuit.
Extinction Partially Reverts Structural Changes Associated with Remote Fear Memory
ERIC Educational Resources Information Center
Vetere, Gisella; Restivo, Leonardo; Novembre, Giovanni; Aceti, Massimiliano; Lumaca, Massimo; Ammassari-Teule, Martine
2011-01-01
Structural synaptic changes occur in medial prefrontal cortex circuits during remote memory formation. Whether extinction reverts or further reshapes these circuits is, however, unknown. Here we show that the number and the size of spines were enhanced in anterior cingulate (aCC) and infralimbic (ILC) cortices 36 d following contextual fear…
1989-05-12
USA Resonant tunneling transistors and New III-V memory devices for new circuit architectures with reduced complexity F. Capasso, Bell. Murray Hill...the evaporation, or by selective oxidation of As, leaving metallic Ga clusters and b) the interdiffusive deterioration of metal contacts on GaAs...VEB (My) Resonant Tunneling Transistors and New III-V Memory Devices for New Circuit Architectures with Reduced Complexity . Invited: F. Capasso
Characteristics of a Nonvolatile SRAM Memory Cell Utilizing a Ferroelectric Transistor
NASA Technical Reports Server (NTRS)
Mitchell, Cody; Laws, Crystal; MacLeod, Todd C.; Ho, Fat D.
2011-01-01
The SRAM cell circuit is a standard for volatile data storage. When utilizing one or more ferroelectric transistors, the hysteresis characteristics give unique properties to the SRAM circuit, providing for investigation into the development of a nonvolatile memory cell. This paper discusses various formations of the SRAM circuit, using ferroelectric transistors, n-channel and p-channel MOSFETs, and resistive loads. With varied source and supply voltages, the effects on the timing and retention characteristics are investigated, including retention times of up to 24 hours.
Tagawa, Koichi; Tokida, Haruki
2017-06-01
Pure amnesia (amnesic syndrome) is an organic brain syndrome characterized by impairment in episodic memory, with either an anterograde or sometimes retrograde loss of memories. Although episodic memory is impaired, semantic memory, immediate memory, and procedural memory are preserved. The Papez circuit is a network of nerve fibers and nerve centers that starts and ends in the hippocampus travelling by way of the fornix, mammillary bodies, anterior thalamic nuclei, cingulate gyrus, and parahippocampal gyrus. A lesion restricted to this circuit often produces pure amnesia. Regions concerned with the Yakovlev circuit also have an important role in memory. Clinical cases of pure amnesia caused by cerebrovascular disease presented following brain imaging and resulted from various different lesions. The cases identified were predominantly thalamic amnesia and hippocampal amnesia. Thalamic amnesia often resulted from an infarction in the territory of the thalamotuberal artery and paramedian thalamic artery although thalamic hemorrhage in medial portion of thalamus also produced pure amnesia. Hippocampal amnesia usually occurred following an infarction in the temporal branches of posterior cerebral artery. Cases of retrosplenial amnesia caused by subcortical hematoma and infarction in the retrosplenial region are also described. In addition, cases of pure amnesia resulting from an infarction in the fornix, mammillary body hemorrhage, and caudate hemorrhage are also shown.
Qualitative-Modeling-Based Silicon Neurons and Their Networks
Kohno, Takashi; Sekikawa, Munehisa; Li, Jing; Nanami, Takuya; Aihara, Kazuyuki
2016-01-01
The ionic conductance models of neuronal cells can finely reproduce a wide variety of complex neuronal activities. However, the complexity of these models has prompted the development of qualitative neuron models. They are described by differential equations with a reduced number of variables and their low-dimensional polynomials, which retain the core mathematical structures. Such simple models form the foundation of a bottom-up approach in computational and theoretical neuroscience. We proposed a qualitative-modeling-based approach for designing silicon neuron circuits, in which the mathematical structures in the polynomial-based qualitative models are reproduced by differential equations with silicon-native expressions. This approach can realize low-power-consuming circuits that can be configured to realize various classes of neuronal cells. In this article, our qualitative-modeling-based silicon neuron circuits for analog and digital implementations are quickly reviewed. One of our CMOS analog silicon neuron circuits can realize a variety of neuronal activities with a power consumption less than 72 nW. The square-wave bursting mode of this circuit is explained. Another circuit can realize Class I and II neuronal activities with about 3 nW. Our digital silicon neuron circuit can also realize these classes. An auto-associative memory realized on an all-to-all connected network of these silicon neurons is also reviewed, in which the neuron class plays important roles in its performance. PMID:27378842
Neuromorphic computing enabled by physics of electron spins: Prospects and perspectives
NASA Astrophysics Data System (ADS)
Sengupta, Abhronil; Roy, Kaushik
2018-03-01
“Spintronics” refers to the understanding of the physics of electron spin-related phenomena. While most of the significant advancements in this field has been driven primarily by memory, recent research has demonstrated that various facets of the underlying physics of spin transport and manipulation can directly mimic the functionalities of the computational primitives in neuromorphic computation, i.e., the neurons and synapses. Given the potential of these spintronic devices to implement bio-mimetic computations at very low terminal voltages, several spin-device structures have been proposed as the core building blocks of neuromorphic circuits and systems to implement brain-inspired computing. Such an approach is expected to play a key role in circumventing the problems of ever-increasing power dissipation and hardware requirements for implementing neuro-inspired algorithms in conventional digital CMOS technology. Perspectives on spin-enabled neuromorphic computing, its status, and challenges and future prospects are outlined in this review article.
NASA Technical Reports Server (NTRS)
Leibfritz, Gilbert H.; Larson, Howard K.
1987-01-01
Compact speech synthesizer useful traveling companion to speech-handicapped. User simply enters statement on board, and synthesizer converts statement into spoken words. Battery-powered and housed in briefcase, easily carried on trips. Unit used on telephones and face-to-face communication. Synthesizer consists of micro-computer with memory-expansion module, speech-synthesizer circuit, batteries, recharger, dc-to-dc converter, and telephone amplifier. Components, commercially available, fit neatly in 17-by 13-by 5-in. briefcase. Weighs about 20 lb (9 kg) and operates and recharges from ac receptable.
Nga Ng, Tse; Schwartz, David E.; Mei, Ping; Krusor, Brent; Kor, Sivkheng; Veres, Janos; Bröms, Per; Eriksson, Torbjörn; Wang, Yong; Hagel, Olle; Karlsson, Christer
2015-01-01
We have demonstrated a printed electronic tag that monitors time-integrated sensor signals and writes to nonvolatile memories for later readout. The tag is additively fabricated on flexible plastic foil and comprises a thermistor divider, complementary organic circuits, and two nonvolatile memory cells. With a supply voltage below 30 V, the threshold temperatures can be tuned between 0 °C and 80 °C. The time-temperature dose measurement is calibrated for minute-scale integration. The two memory bits are sequentially written in a thermometer code to provide an accumulated dose record. PMID:26307438
A role for CA3 in social recognition memory.
Chiang, Ming-Ching; Huang, Arthur J Y; Wintzer, Marie E; Ohshima, Toshio; McHugh, Thomas J
2018-02-02
Social recognition memory is crucial for survival across species, underlying the need to correctly identify conspecifics, mates and potential enemies. In humans the hippocampus is engaged in social and episodic memory, however the circuit mechanisms of social memory in rodent models has only recently come under scrutiny. Work in mice has established that the dorsal CA2 and ventral CA1 regions play critical roles, however a more comprehensive comparative analyses of the circuits and mechanisms required has not been reported. Here we employ conditional genetics to examine the differential contributions of the hippocampal subfields to social memory. We find that the deletion of NMDA receptor subunit 1 gene (NR1), which abolishes NMDA receptor synaptic plasticity, in CA3 pyramidal cells led to deficits in social memory; however, mice lacking the same gene in DG granule cells performed indistinguishable from controls. Further, we use conditional pharmacogenetic inhibition to demonstrate that activity in ventral, but not dorsal, CA3 is necessary for the encoding of a social memory. These findings demonstrated CA3 pyramidal cell plasticity and transmission contribute to the encoding of social stimuli and help further identify the distinct circuits underlying the role of the hippocampus in social memory. Copyright © 2018 Elsevier B.V. All rights reserved.
You, Hongzhi; Wang, Da-Hui
2017-01-01
Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems. PMID:28223913
You, Hongzhi; Wang, Da-Hui
2017-01-01
Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.
Final report for CCS cross-layer reliability visioning study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Quinn, Heather M; Dehon, Andre; Carter, Nicj
The geometric rate of improvement of transistor size and integrated circuit performance known as Moore's Law has been an engine of growth for our economy, enabling new products and services, creating new value and wealth, increasing safety, and removing menial tasks from our daily lives. Affordable, highly integrated components have enabled both life-saving technologies and rich entertainment applications. Anti-lock brakes, insulin monitors, and GPS-enabled emergency response systems save lives. Cell phones, internet appliances, virtual worlds, realistic video games, and mp3 players enrich our lives and connect us together. Over the past 40 years of silicon scaling, the increasing capabilities ofmore » inexpensive computation have transformed our society through automation and ubiquitous communications. Looking forward, increasing unpredictability threatens our ability to continue scaling integrated circuits at Moore's Law rates. As the transistors and wires that make up integrated circuits become smaller, they display both greater differences in behavior among devices designed to be identical and greater vulnerability to transient and permanent faults. Conventional design techniques expend energy to tolerate this unpredictability by adding safety margins to a circuit's operating voltage, clock frequency or charge stored per bit. However, the rising energy costs needed to compensate for increasing unpredictability are rapidly becoming unacceptable in today's environment where power consumption is often the limiting factor on integrated circuit performance and energy efficiency is a national concern. Reliability and energy consumption are both reaching key inflection points that, together, threaten to reduce or end the benefits of feature size reduction. To continue beneficial scaling, we must use a cross-layer, Jull-system-design approach to reliability. Unlike current systems, which charge every device a substantial energy tax in order to guarantee correct operation in spite of rare events, such as one high-threshold transistor in a billion or one erroneous gate evaluation in an hour of computation, cross-layer reliability schemes make reliability management a cooperative effort across the system stack, sharing information across layers so that they only expend energy on reliability when an error actually occurs. Figure 1 illustrates an example of such a system that uses a combination of information from the application and cheap architecture-level techniques to detect errors. When an error occurs, mechanisms at higher levels in the stack correct the error, efficiently delivering correct operation to the user in spite of errors at the device or circuit levels. In the realms of memory and communication, engineers have a long history of success in tolerating unpredictable effects such as fabrication variability, transient upsets, and lifetime wear using information sharing, limited redundancy, and cross-layer approaches that anticipate, accommodate, and suppress errors. Networks use a combination of hardware and software to guarantee end-toend correctness. Error-detection and correction codes use additional information to correct the most common errors, single-bit transmission errors. When errors occur that cannot be corrected by these codes, the network protocol requests re-transmission of one or more packets until the correct data is received. Similarly, computer memory systems exploit a cross-layer division of labor to achieve high performance with modest hardware. Rather than demanding that hardware alone provide the virtual memory abstraction, software page-fault and TLB-miss handlers allow a modest piece of hardware, the TLB, to handle the common-case operations on a cyc1e-by-cycle basis while infrequent misses are handled in system software. Unfortunately, mitigating logic errors is not as simple or as well researched as memory or communication systems. This lack of understanding has led to very expensive solutions. For example, triple-modular redundancy masks errors by triplicating computations in either time or area. This mitigation methods imposes a 200% increase in energy consumption for every operation, not just the uncommon failure cases. At a time when computation is rapidly becoming part of our critical civilian and military infrastructure and decreasing costsfor computation are fueling our economy and our well being, we cannot afford increasingly unreliable electronics or a stagnation in capabilities per dollar, watt, or cubic meter. If researchers are able to develop techniques that tolerate the growing unpredictability of silicon devices, Moore's Law scaling should continue until at least 2022. During this 12-year time period, transistors, which are the building blocks of electronic devices, will scale their dimensions (feature sizes) from 45nm to 4.5nm.« less
Realisation of all 16 Boolean logic functions in a single magnetoresistance memory cell
NASA Astrophysics Data System (ADS)
Gao, Shuang; Yang, Guang; Cui, Bin; Wang, Shouguo; Zeng, Fei; Song, Cheng; Pan, Feng
2016-06-01
Stateful logic circuits based on next-generation nonvolatile memories, such as magnetoresistance random access memory (MRAM), promise to break the long-standing von Neumann bottleneck in state-of-the-art data processing devices. For the successful commercialisation of stateful logic circuits, a critical step is realizing the best use of a single memory cell to perform logic functions. In this work, we propose a method for implementing all 16 Boolean logic functions in a single MRAM cell, namely a magnetoresistance (MR) unit. Based on our experimental results, we conclude that this method is applicable to any MR unit with a double-hump-like hysteresis loop, especially pseudo-spin-valve magnetic tunnel junctions with a high MR ratio. Moreover, after simply reversing the correspondence between voltage signals and output logic values, this method could also be applicable to any MR unit with a double-pit-like hysteresis loop. These results may provide a helpful solution for the final commercialisation of MRAM-based stateful logic circuits in the near future.Stateful logic circuits based on next-generation nonvolatile memories, such as magnetoresistance random access memory (MRAM), promise to break the long-standing von Neumann bottleneck in state-of-the-art data processing devices. For the successful commercialisation of stateful logic circuits, a critical step is realizing the best use of a single memory cell to perform logic functions. In this work, we propose a method for implementing all 16 Boolean logic functions in a single MRAM cell, namely a magnetoresistance (MR) unit. Based on our experimental results, we conclude that this method is applicable to any MR unit with a double-hump-like hysteresis loop, especially pseudo-spin-valve magnetic tunnel junctions with a high MR ratio. Moreover, after simply reversing the correspondence between voltage signals and output logic values, this method could also be applicable to any MR unit with a double-pit-like hysteresis loop. These results may provide a helpful solution for the final commercialisation of MRAM-based stateful logic circuits in the near future. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03169b
Japanese project aims at supercomputer that executes 10 gflops
DOE Office of Scientific and Technical Information (OSTI.GOV)
Burskey, D.
1984-05-03
Dubbed supercom by its multicompany design team, the decade-long project's goal is an engineering supercomputer that can execute 10 billion floating-point operations/s-about 20 times faster than today's supercomputers. The project, guided by Japan's Ministry of International Trade and Industry (MITI) and the Agency of Industrial Science and Technology encompasses three parallel research programs, all aimed at some angle of the superconductor. One program should lead to superfast logic and memory circuits, another to a system architecture that will afford the best performance, and the last to the software that will ultimately control the computer. The work on logic and memorymore » chips is based on: GAAS circuit; Josephson junction devices; and high electron mobility transistor structures. The architecture will involve parallel processing.« less
Zhu, Yuan-Gui; Cao, He-Qi; Dong, Er-Dan
2013-02-01
During recent years, major advances have been made in neuroscience, i.e., asynchronous release, three-dimensional structural data sets, saliency maps, magnesium in brain research, and new functional roles of long non-coding RNAs. Especially, the development of optogenetic technology provides access to important information about relevant neural circuits by allowing the activation of specific neurons in awake mammals and directly observing the resulting behavior. The Grand Research Plan for Neural Circuits of Emotion and Memory was launched by the National Natural Science Foundation of China. It takes emotion and memory as its main objects, making the best use of cutting-edge technologies from medical science, life science and information science. In this paper, we outline the current status of neural circuit studies in China and the technologies and methodologies being applied, as well as studies related to the impairments of emotion and memory. In this phase, we are making efforts to repair the current deficiencies by making adjustments, mainly involving four aspects of core scientific issues to investigate these circuits at multiple levels. Five research directions have been taken to solve important scientific problems while the Grand Research Plan is implemented. Future research into this area will be multimodal, incorporating a range of methods and sciences into each project. Addressing these issues will ensure a bright future, major discoveries, and a higher level of treatment for all affected by debilitating brain illnesses.
A neuromorphic circuit mimicking biological short-term memory.
Barzegarjalali, Saeid; Parker, Alice C
2016-08-01
Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).
Chemically programmed ink-jet printed resistive WORM memory array and readout circuit
NASA Astrophysics Data System (ADS)
Andersson, H.; Manuilskiy, A.; Sidén, J.; Gao, J.; Hummelgård, M.; Kunninmel, G. V.; Nilsson, H.-E.
2014-09-01
In this paper an ink-jet printed write once read many (WORM) resistive memory fabricated on paper substrate is presented. The memory elements are programmed for different resistance states by printing triethylene glycol monoethyl ether on the substrate before the actual memory element is printed using silver nano particle ink. The resistance is thus able to be set to a broad range of values without changing the geometry of the elements. A memory card consisting of 16 elements is manufactured for which the elements are each programmed to one of four defined logic levels, providing a total of 4294 967 296 unique possible combinations. Using a readout circuit, originally developed for resistive sensors to avoid crosstalk between elements, a memory card reader is manufactured that is able to read the values of the memory card and transfer the data to a PC. Such printed memory cards can be used in various applications.
Spintronic Nanodevices for Bioinspired Computing
Grollier, Julie; Querlioz, Damien; Stiles, Mark D.
2016-01-01
Bioinspired hardware holds the promise of low-energy, intelligent, and highly adaptable computing systems. Applications span from automatic classification for big data management, through unmanned vehicle control, to control for biomedical prosthesis. However, one of the major challenges of fabricating bioinspired hardware is building ultra-high-density networks out of complex processing units interlinked by tunable connections. Nanometer-scale devices exploiting spin electronics (or spintronics) can be a key technology in this context. In particular, magnetic tunnel junctions (MTJs) are well suited for this purpose because of their multiple tunable functionalities. One such functionality, non-volatile memory, can provide massive embedded memory in unconventional circuits, thus escaping the von-Neumann bottleneck arising when memory and processors are located separately. Other features of spintronic devices that could be beneficial for bioinspired computing include tunable fast nonlinear dynamics, controlled stochasticity, and the ability of single devices to change functions in different operating conditions. Large networks of interacting spintronic nanodevices can have their interactions tuned to induce complex dynamics such as synchronization, chaos, soliton diffusion, phase transitions, criticality, and convergence to multiple metastable states. A number of groups have recently proposed bioinspired architectures that include one or several types of spintronic nanodevices. In this paper, we show how spintronics can be used for bioinspired computing. We review the different approaches that have been proposed, the recent advances in this direction, and the challenges toward fully integrated spintronics complementary metal–oxide–semiconductor (CMOS) bioinspired hardware. PMID:27881881
Li, Y; Ge, S; Li, N; Chen, L; Zhang, S; Wang, J; Wu, H; Wang, X; Wang, X
2016-02-19
Reactivation of consolidated memory initiates a memory reconsolidation process, during which the reactivated memory is susceptible to strengthening, weakening or updating. Therefore, effective interference with the memory reconsolidation process is expected to be an important treatment for drug addiction. The nucleus accumbens (NAc) has been well recognized as a pathway component that can prevent drug relapse, although the mechanism underlying this function is poorly understood. We aimed to clarify the regulatory role of the NAc in the cocaine memory reconsolidation process, by examining the effect of applying different pharmacological interventions to the NAc on Zif 268 and Fos B expression in the entire reward circuit after cocaine memory reactivation. Through the cocaine-induced conditioned place preference (CPP) model, immunohistochemical and immunofluorescence staining for Zif 268 and Fos B were used to explore the functional activated brain nuclei after cocaine memory reactivation. Our results showed that the expression of Zif 268 and Fos B was commonly increased in the medial prefrontal cortex (mPFC), the infralimbic cortex (IL), the NAc-core, the NAc-shell, the hippocampus (CA1, CA2, and CA3 subregions), the amygdala, the ventral tegmental area (VTA), and the supramammillary nucleus (SuM) following memory reconsolidation, and Zif 268/Fos B co-expression was commonly observed (for Zif 268: 51-68%; for Fos B: 52-66%). Further, bilateral NAc-shell infusion of MK 801 and SCH 23390, but not raclopride or propranolol, prior to addictive memory reconsolidation, decreased Zif 268 and Fos B expression in the entire reward circuit, except for the amygdala, and effectively disturbed subsequent CPP-related behavior. In summary, N-methyl-d-aspartate (NMDA) and dopamine D1 receptors, but not dopamine D2 or β adrenergic receptors, within the NAc-shell, may regulate Zif 268 and Fos B expression in most brain nuclei of the reward circuit after cocaine memory reactivation. These findings indicated that the NAc played a key role in regulating addictive memory reconsolidation by influencing the function of the entire addictive memory network. Copyright © 2016. Published by Elsevier Ltd.
Evaluation of 1.5-T Cell Flash Memory Total Ionizing Dose Response
NASA Astrophysics Data System (ADS)
Clark, Lawrence T.; Holbert, Keith E.; Adams, James W.; Navale, Harshad; Anderson, Blake C.
2015-12-01
Flash memory is an essential part of systems used in harsh environments, experienced by both terrestrial and aerospace TID applications. This paper presents studies of COTS flash memory TID hardness. While there is substantial literature on flash memory TID response, this work focuses for the first time on 1.5 transistor per cell flash memory. The experimental results show hardness varying from about 100 krad(Si) to over 250 krad(Si) depending on the usage model. We explore the circuit and device aspects of the results, based on the extensive reliability literature for this flash memory type. Failure modes indicate both device damage and circuit marginalities. Sector erase failure limits, but read only operation allows TID exceeding 200 krad(Si). The failures are analyzed by type.
de Souza Silva, Maria A; Huston, Joseph P; Wang, An-Li; Petri, David; Chao, Owen Yuan-Hsin
2016-07-01
We asked whether episodic-like memory requires neural mechanisms independent of those that mediate its component memories for "what," "when," and "where," and if neuronal connectivity between the medial prefrontal cortex (mPFC) and the hippocampus (HPC) CA3 subregion is essential for episodic-like memory. Unilateral lesion of the mPFC was combined with unilateral lesion of the CA3 in the ipsi- or contralateral hemispheres in rats. Episodic-like memory was tested using a task, which assesses the integration of memories for "what, where, and when" concomitantly. Tests for novel object recognition (what), object place (where), and temporal order memory (when) were also applied. Bilateral disconnection of the mPFC-CA3 circuit by N-methyl-d-aspartate (NMDA) lesions disrupted episodic-like memory, but left the component memories for object, place, and temporal order, per se, intact. Furthermore, unilateral NMDA lesion of the CA3 plus injection of (6-cyano-7-nitroquinoxaline-2,3-dione) (CNQX) (AMPA/kainate receptor antagonist), but not AP-5 (NMDA receptor antagonist), into the contralateral mPFC also disrupted episodic-like memory, indicating the mPFC AMPA/kainate receptors as critical for this circuit. These results argue for a selective neural system that specifically subserves episodic memory, as it is not critically involved in the control of its component memories for object, place, and time. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
A Method for Growing Bio-memristors from Slime Mold
Miranda, Eduardo Reck; Braund, Edward
2017-01-01
Our research is aimed at gaining a better understanding of the electronic properties of organisms in order to engineer novel bioelectronic systems and computing architectures based on biology. This specific paper focuses on harnessing the unicellular slime mold Physarum polycephalum to develop bio-memristors (or biological memristors) and bio-computing devices. The memristor is a resistor that possesses memory. It is the 4th fundamental passive circuit element (the other three are the resistor, the capacitor, and the inductor), which is paving the way for the design of new kinds of computing systems; e.g., computers that might relinquish the distinction between storage and a central processing unit. When applied with an AC voltage, the current vs. voltage characteristic of a memristor is a pinched hysteresis loop. It has been shown that P. polycephalum produces pinched hysteresis loops under AC voltages and displays adaptive behavior that is comparable with the functioning of a memristor. This paper presents the method that we developed for implementing bio-memristors with P. polycephalum and introduces the development of a receptacle to culture the organism, which facilitates its deployment as an electronic circuit component. Our method has proven to decrease growth time, increase component lifespan, and standardize electrical observations. PMID:29155754
Data storage technology comparisons
NASA Technical Reports Server (NTRS)
Katti, Romney R.
1990-01-01
The role of data storage and data storage technology is an integral, though conceptually often underestimated, portion of data processing technology. Data storage is important in the mass storage mode in which generated data is buffered for later use. But data storage technology is also important in the data flow mode when data are manipulated and hence required to flow between databases, datasets and processors. This latter mode is commonly associated with memory hierarchies which support computation. VLSI devices can reasonably be defined as electronic circuit devices such as channel and control electronics as well as highly integrated, solid-state devices that are fabricated using thin film deposition technology. VLSI devices in both capacities play an important role in data storage technology. In addition to random access memories (RAM), read-only memories (ROM), and other silicon-based variations such as PROM's, EPROM's, and EEPROM's, integrated devices find their way into a variety of memory technologies which offer significant performance advantages. These memory technologies include magnetic tape, magnetic disk, magneto-optic disk, and vertical Bloch line memory. In this paper, some comparison between selected technologies will be made to demonstrate why more than one memory technology exists today, based for example on access time and storage density at the active bit and system levels.
Hybrid quantum processors: molecular ensembles as quantum memory for solid state circuits.
Rabl, P; DeMille, D; Doyle, J M; Lukin, M D; Schoelkopf, R J; Zoller, P
2006-07-21
We investigate a hybrid quantum circuit where ensembles of cold polar molecules serve as long-lived quantum memories and optical interfaces for solid state quantum processors. The quantum memory realized by collective spin states (ensemble qubit) is coupled to a high-Q stripline cavity via microwave Raman processes. We show that, for convenient trap-surface distances of a few microm, strong coupling between the cavity and ensemble qubit can be achieved. We discuss basic quantum information protocols, including a swap from the cavity photon bus to the molecular quantum memory, and a deterministic two qubit gate. Finally, we investigate coherence properties of molecular ensemble quantum bits.
Mizuhara, Hiroaki; Sato, Naoyuki; Yamaguchi, Yoko
2015-05-01
Neural oscillations are crucial for revealing dynamic cortical networks and for serving as a possible mechanism of inter-cortical communication, especially in association with mnemonic function. The interplay of the slow and fast oscillations might dynamically coordinate the mnemonic cortical circuits to rehearse stored items during working memory retention. We recorded simultaneous EEG-fMRI during a working memory task involving a natural scene to verify whether the cortical networks emerge with the neural oscillations for memory of the natural scene. The slow EEG power was enhanced in association with the better accuracy of working memory retention, and accompanied cortical activities in the mnemonic circuits for the natural scene. Fast oscillation showed a phase-amplitude coupling to the slow oscillation, and its power was tightly coupled with the cortical activities for representing the visual images of natural scenes. The mnemonic cortical circuit with the slow neural oscillations would rehearse the distributed natural scene representations with the fast oscillation for working memory retention. The coincidence of the natural scene representations could be obtained by the slow oscillation phase to create a coherent whole of the natural scene in the working memory. Copyright © 2015 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Secondo, R.; Alía, R. Garcia; Peronnard, P.; Brugger, M.; Masi, A.; Danzeca, S.; Merlenghi, A.; Vaillé, J.-R.; Dusseau, L.
2017-08-01
A single event latchup (SEL) experiment based on commercial static random access memory (SRAM) memories has recently been proposed in the framework of the European Organization for Nuclear Research (CERN) Latchup Experiment and Student Satellite nanosatellite low Earth orbit (LEO) space mission. SEL characterization of three commercial SRAM memories has been carried out at the Paul Scherrer Institut (PSI) facility, using monoenergetic focused proton beams and different acquisition setups. The best target candidate was selected and a circuit for SEL detection has been proposed and tested at CERN, in the CERN High Energy AcceleRator Mixed-field facility (CHARM). Experimental results were carried out at test locations representative of the LEO environment, thus providing a full characterization of the SRAM cross sections, together with the analysis of the single-event effect and total ionizing dose of the latchup detection circuit in relation to the particle spectra expected during mission. The setups used for SEL monitoring are described, and details of the proposed circuit components and topology are presented. Experimental results obtained both at PSI and at CHARM facilities are discussed.
Takeda, Masaki; Koyano, Kenji W; Hirabayashi, Toshiyuki; Adachi, Yusuke; Miyashita, Yasushi
2015-05-06
Memory retrieval in primates is orchestrated by a brain-wide neuronal circuit. To elucidate the operation of this circuit, it is imperative to comprehend neuronal mechanisms of coordination between area-to-area interaction and information processing within individual areas. By simultaneous recording from area 36 (A36) and area TE (TE) of the temporal cortex while monkeys performed a pair-association memory task, we found two distinct inter-area signal flows during memory retrieval: A36 spiking activity exhibited coherence with low-frequency field activity in either the supragranular or infragranular layer of TE. Of these two flows, only signal flow targeting the infragranular layer of TE was further translaminarly coupled with gamma activity in the supragranular layer of TE. Moreover, this coupling was observed when monkeys succeeded in the retrieval of the sought object but not when they failed. The results suggest that local translaminar processing can be recruited via a layer-specific inter-area network for memory retrieval. Copyright © 2015 Elsevier Inc. All rights reserved.
Li, Dong; Chen, Mingyuan; Zong, Qijun; Zhang, Zengxing
2017-10-11
The Schottky junction is an important unit in electronics and optoelectronics. However, its properties greatly degrade with device miniaturization. The fast development of circuits has fueled a rapid growth in the study of two-dimensional (2D) crystals, which may lead to breakthroughs in the semiconductor industry. Here we report a floating-gate manipulated nonvolatile ambipolar Schottky junction memory from stacked all-2D layers of graphene-BP/h-BN/graphene (BP, black phosphorus; h-BN, hexagonal boron nitride) in a designed floating-gate field-effect Schottky barrier transistor configuration. By manipulating the voltage pulse applied to the control gate, the device exhibits ambipolar characteristics and can be tuned to act as graphene-p-BP or graphene-n-BP junctions with reverse rectification behavior. Moreover, the junction exhibits good storability properties of more than 10 years and is also programmable. On the basis of these characteristics, we further demonstrate the application of the device to dual-mode nonvolatile Schottky junction memories, memory inverter circuits, and logic rectifiers.
A nanocryotron comparator can connect single-flux-quantum circuits to conventional electronics
NASA Astrophysics Data System (ADS)
Zhao, Qing-Yuan; McCaughan, Adam N.; Dane, Andrew E.; Berggren, Karl K.; Ortlepp, Thomas
2017-04-01
Integration with conventional electronics offers a straightforward and economical approach to upgrading existing superconducting technologies, such as scaling up superconducting detectors into large arrays and combining single flux quantum (SFQ) digital circuits with semiconductor logic gates and memories. However, direct output signals from superconducting devices (e.g., Josephson junctions) are usually not compatible with the input requirements of conventional devices (e.g., transistors). Here, we demonstrate the use of a single three-terminal superconducting-nanowire device, called the nanocryotron (nTron), as a digital comparator to combine SFQ circuits with mature semiconductor circuits such as complementary metal oxide semiconductor (CMOS) circuits. Since SFQ circuits can digitize output signals from general superconducting devices and CMOS circuits can interface existing CMOS-compatible electronics, our results demonstrate the feasibility of a general architecture that uses an nTron as an interface to realize a ‘super-hybrid’ system consisting of superconducting detectors, superconducting quantum electronics, CMOS logic gates and memories, and other conventional electronics.
Coupled circuit numerical analysis of eddy currents in an open MRI system.
Akram, Md Shahadat Hossain; Terada, Yasuhiko; Keiichiro, Ishi; Kose, Katsumi
2014-08-01
We performed a new coupled circuit numerical simulation of eddy currents in an open compact magnetic resonance imaging (MRI) system. Following the coupled circuit approach, the conducting structures were divided into subdomains along the length (or width) and the thickness, and by implementing coupled circuit concepts we have simulated transient responses of eddy currents for subdomains in different locations. We implemented the Eigen matrix technique to solve the network of coupled differential equations to speed up our simulation program. On the other hand, to compute the coupling relations between the biplanar gradient coil and any other conducting structure, we implemented the solid angle form of Ampere's law. We have also calculated the solid angle for three dimensions to compute inductive couplings in any subdomain of the conducting structures. Details of the temporal and spatial distribution of the eddy currents were then implemented in the secondary magnetic field calculation by the Biot-Savart law. In a desktop computer (Programming platform: Wolfram Mathematica 8.0®, Processor: Intel(R) Core(TM)2 Duo E7500 @ 2.93GHz; OS: Windows 7 Professional; Memory (RAM): 4.00GB), it took less than 3min to simulate the entire calculation of eddy currents and fields, and approximately 6min for X-gradient coil. The results are given in the time-space domain for both the direct and the cross-terms of the eddy current magnetic fields generated by the Z-gradient coil. We have also conducted free induction decay (FID) experiments of eddy fields using a nuclear magnetic resonance (NMR) probe to verify our simulation results. The simulation results were found to be in good agreement with the experimental results. In this study we have also conducted simulations for transient and spatial responses of secondary magnetic field induced by X-gradient coil. Our approach is fast and has much less computational complexity than the conventional electromagnetic numerical simulation methods. Copyright © 2014 Elsevier Inc. All rights reserved.
Improved Writing-Conductor Designs For Magnetic Memory
NASA Technical Reports Server (NTRS)
Wu, Jiin-Chuan; Stadler, Henry L.; Katti, Romney R.
1994-01-01
Writing currents reduced to practical levels. Improved conceptual designs for writing conductors in micromagnet/Hall-effect random-access integrated-circuit memory reduces electrical current needed to magnetize micromagnet in each memory cell. Basic concept of micromagnet/Hall-effect random-access memory presented in "Magnetic Analog Random-Access Memory" (NPO-17999).
Memory Applications Using Resonant Tunneling Diodes
NASA Astrophysics Data System (ADS)
Shieh, Ming-Huei
Resonant tunneling diodes (RTDs) producing unique folding current-voltage (I-V) characteristics have attracted considerable research attention due to their promising application in signal processing and multi-valued logic. The negative differential resistance of RTDs renders the operating points self-latching and stable. We have proposed a multiple -dimensional multiple-state RTD-based static random-access memory (SRAM) cell in which the number of stable states can significantly be increased to (N + 1)^ m or more for m number of N-peak RTDs connected in series. The proposed cells take advantage of the hysteresis and folding I-V characteristics of RTD. Several cell designs are presented and evaluated. A two-dimensional nine-state memory cell has been implemented and demonstrated by a breadboard circuit using two 2-peak RTDs. The hysteresis phenomenon in a series of RTDs is also further analyzed. The switch model provided in SPICE 3 can be utilized to simulate the hysteretic I-V characteristics of RTDs. A simple macro-circuit is described to model the hysteretic I-V characteristic of RTD for circuit simulation. A new scheme for storing word-wide multiple-bit information very efficiently in a single memory cell using RTDs is proposed. An efficient and inexpensive periphery circuit to read from and write into the cell is also described. Simulation results on the design of a 3-bit memory cell scheme using one-peak RTDs are also presented. Finally, a binary transistor-less memory cell which is only composed of a pair of RTDs and an ordinary rectifier diode is presented and investigated. A simple means for reading and writing information from or into the memory cell is also discussed.
NASA Astrophysics Data System (ADS)
Jiang, Yuning; Kang, Jinfeng; Wang, Xinan
2017-03-01
Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today’s electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance.
Biologically based neural circuit modelling for the study of fear learning and extinction
NASA Astrophysics Data System (ADS)
Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra
2016-11-01
The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.
Three-dimensional crossbar arrays of self-rectifying Si/SiO 2/Si memristors
Li, Can; Han, Lili; Jiang, Hao; ...
2017-06-05
Memristors are promising building blocks for the next generation memory, unconventional computing systems and beyond. Currently common materials used to build memristors are not necessarily compatible with the silicon dominant complementary metal-oxide-semiconductor (CMOS) technology. Furthermore, external selector devices or circuits are usually required in order for large memristor arrays to function properly, resulting in increased circuit complexity. Here we demonstrate fully CMOS-compatible, all-silicon based and self-rectifying memristors that negate the need for external selectors in large arrays. It consists of p- and n-type doped single crystalline silicon electrodes and a thin chemically produced silicon oxide switching layer. The device exhibitsmore » repeatable resistance switching behavior with high rectifying ratio (10 5), high ON/OFF conductance ratio (10 4) and attractive retention at 300 °C. We further build a 5-layer 3-dimensional (3D) crossbar array of 100 nm memristors by stacking fluid supported silicon membranes. The CMOS compatibility and self-rectifying behavior open up opportunities for mass production of memristor arrays and 3D hybrid circuits on full-wafer scale silicon and flexible substrates without increasing circuit complexity.« less
A 16X16 Discrete Cosine Transform Chip
NASA Astrophysics Data System (ADS)
Sun, M. T.; Chen, T. C.; Gottlieb, A.; Wu, L.; Liou, M. L.
1987-10-01
Among various transform coding techniques for image compression the Discrete Cosine Transform (DCT) is considered to be the most effective method and has been widely used in the laboratory as well as in the market, place. DCT is computationally intensive. For video application at 14.3 MHz sample rate, a direct implementation of a 16x16 DCT requires a throughput, rate of approximately half a billion multiplications per second. In order to reduce the cost of hardware implementation, a single chip DCT implementation is highly desirable. In this paper, the implementation of a 16x16 DCT chip using a concurrent architecture will be presented. The chip is designed for real-time processing of 14.3 MHz sampled video data. It uses row-column decomposition to implement the two-dimensional transform. Distributed arithmetic combined with hit-serial and hit-parallel structures is used to implement the required vector inner products concurrently. Several schemes are utilized to reduce the size of required memory. The resultant circuit only uses memory, shift registers, and adders. No multipliers are required. It achieves high speed performance with a very regular and efficient integrated circuit realization. The chip accepts 0-bit input and produces 14-bit DCT coefficients. 12 bits are maintained after the first one-dimensional transform. The circuit has been laid out using a 2-μm CMOS technology with a symbolic design tool MULGA. The core contains approximately 73,000 transistors in an area of 7.2 x 7.0
Realisation of all 16 Boolean logic functions in a single magnetoresistance memory cell.
Gao, Shuang; Yang, Guang; Cui, Bin; Wang, Shouguo; Zeng, Fei; Song, Cheng; Pan, Feng
2016-07-07
Stateful logic circuits based on next-generation nonvolatile memories, such as magnetoresistance random access memory (MRAM), promise to break the long-standing von Neumann bottleneck in state-of-the-art data processing devices. For the successful commercialisation of stateful logic circuits, a critical step is realizing the best use of a single memory cell to perform logic functions. In this work, we propose a method for implementing all 16 Boolean logic functions in a single MRAM cell, namely a magnetoresistance (MR) unit. Based on our experimental results, we conclude that this method is applicable to any MR unit with a double-hump-like hysteresis loop, especially pseudo-spin-valve magnetic tunnel junctions with a high MR ratio. Moreover, after simply reversing the correspondence between voltage signals and output logic values, this method could also be applicable to any MR unit with a double-pit-like hysteresis loop. These results may provide a helpful solution for the final commercialisation of MRAM-based stateful logic circuits in the near future.
SVGA and XGA active matrix microdisplays for head-mounted applications
NASA Astrophysics Data System (ADS)
Alvelda, Phillip; Bolotski, Michael; Brown, Imani L.
2000-03-01
The MicroDisplay Corporation's liquid crystal on silicon (LCOS) display devices are based on the union of several technologies with the extreme integration capability of conventionally fabricated CMOS substrates. The fast liquid crystal operation modes and new scalable high-performance pixel addressing architectures presented in this paper enable substantially improved color, contrast, and brightness while still satisfying the optical, packaging, and power requirements of portable applications. The entire suite of MicroDisplay's technologies was devised to create a line of mixed-signal application-specific integrated circuits (ASICs) in single-chip display systems. Mixed-signal circuits can integrate computing, memory, and communication circuitry on the same substrate as the display drivers and pixel array for a multifunctional complete system-on-a-chip. System-on-a-chip benefits also include reduced head supported weight requirements through the elimination of off-chip drive electronics.
Selective alterations of neurons and circuits related to early memory loss in Alzheimer’s disease
Llorens-Martín, Maria; Blazquez-Llorca, Lidia; Benavides-Piccione, Ruth; Rabano, Alberto; Hernandez, Felix; Avila, Jesus; DeFelipe, Javier
2014-01-01
A progressive loss of episodic memory is a well-known clinical symptom that characterizes Alzheimer’s disease (AD). The beginning of this loss of memory has been associated with the very early, pathological accumulation of tau and neuronal degeneration observed in the entorhinal cortex (EC). Tau-related pathology is thought to then spread progressively to the hippocampal formation and other brain areas as the disease progresses. The major cortical afferent source of the hippocampus and dentate gyrus is the EC through the perforant pathway. At least two main circuits participate in the connection between EC and the hippocampus; one originating in layer II and the other in layer III of the EC giving rise to the classical trisynaptic (ECII → dentate gyrus → CA3 → CA1) and monosynaptic (ECIII → CA1) circuits. Thus, the study of the early pathological changes in these circuits is of great interest. In this review, we will discuss mainly the alterations of the granule cell neurons of the dentate gyrus and the atrophy of CA1 pyramidal neurons that occur in AD in relation to the possible differential alterations of these two main circuits. PMID:24904307
Selective alterations of neurons and circuits related to early memory loss in Alzheimer's disease.
Llorens-Martín, Maria; Blazquez-Llorca, Lidia; Benavides-Piccione, Ruth; Rabano, Alberto; Hernandez, Felix; Avila, Jesus; DeFelipe, Javier
2014-01-01
A progressive loss of episodic memory is a well-known clinical symptom that characterizes Alzheimer's disease (AD). The beginning of this loss of memory has been associated with the very early, pathological accumulation of tau and neuronal degeneration observed in the entorhinal cortex (EC). Tau-related pathology is thought to then spread progressively to the hippocampal formation and other brain areas as the disease progresses. The major cortical afferent source of the hippocampus and dentate gyrus is the EC through the perforant pathway. At least two main circuits participate in the connection between EC and the hippocampus; one originating in layer II and the other in layer III of the EC giving rise to the classical trisynaptic (ECII → dentate gyrus → CA3 → CA1) and monosynaptic (ECIII → CA1) circuits. Thus, the study of the early pathological changes in these circuits is of great interest. In this review, we will discuss mainly the alterations of the granule cell neurons of the dentate gyrus and the atrophy of CA1 pyramidal neurons that occur in AD in relation to the possible differential alterations of these two main circuits.
Semantic memory retrieval circuit: role of pre-SMA, caudate, and thalamus.
Hart, John; Maguire, Mandy J; Motes, Michael; Mudar, Raksha Anand; Chiang, Hsueh-Sheng; Womack, Kyle B; Kraut, Michael A
2013-07-01
We propose that pre-supplementary motor area (pre-SMA)-thalamic interactions govern processes fundamental to semantic retrieval of an integrated object memory. At the onset of semantic retrieval, pre-SMA initiates electrical interactions between multiple cortical regions associated with semantic memory subsystems encodings as indexed by an increase in theta-band EEG power. This starts between 100-150 ms after stimulus presentation and is sustained throughout the task. We posit that this activity represents initiation of the object memory search, which continues in searching for an object memory. When the correct memory is retrieved, there is a high beta-band EEG power increase, which reflects communication between pre-SMA and thalamus, designates the end of the search process and resultant in object retrieval from multiple semantic memory subsystems. This high beta signal is also detected in cortical regions. This circuit is modulated by the caudate nuclei to facilitate correct and suppress incorrect target memories. Copyright © 2012 Elsevier Inc. All rights reserved.
Tirone, Felice; Farioli-Vecchioli, Stefano; Micheli, Laura; Ceccarelli, Manuela; Leonardi, Luca
2013-01-01
Within the hippocampal circuitry, the basic function of the dentate gyrus is to transform the memory input coming from the enthorinal cortex into sparse and categorized outputs to CA3, in this way separating related memory information. New neurons generated in the dentate gyrus during adulthood appear to facilitate this process, allowing a better separation between closely spaced memories (pattern separation). The evidence underlying this model has been gathered essentially by ablating the newly adult-generated neurons. This approach, however, does not allow monitoring of the integration of new neurons into memory circuits and is likely to set in motion compensatory circuits, possibly leading to an underestimation of the role of new neurons. Here we review the background of the basic function of the hippocampus and of the known properties of new adult-generated neurons. In this context, we analyze the cognitive performance in mouse models generated by us and others, with modified expression of the genes Btg2 (PC3/Tis21), Btg1, Pten, BMP4, etc., where new neurons underwent a change in their differentiation rate or a partial decrease of their proliferation or survival rate rather than ablation. The effects of these modifications are equal or greater than full ablation, suggesting that the architecture of circuits, as it unfolds from the interaction between existing and new neurons, can have a greater functional impact than the sheer number of new neurons. We propose a model which attempts to measure and correlate the set of cellular changes in the process of neurogenesis with the memory function. PMID:23734097
NASA Astrophysics Data System (ADS)
Campagne-Ibarcq, P.; Zalys-Geller, E.; Narla, A.; Shankar, S.; Reinhold, P.; Burkhart, L.; Axline, C.; Pfaff, W.; Frunzio, L.; Schoelkopf, R. J.; Devoret, M. H.
2018-05-01
Large-scale quantum information processing networks will most probably require the entanglement of distant systems that do not interact directly. This can be done by performing entangling gates between standing information carriers, used as memories or local computational resources, and flying ones, acting as quantum buses. We report the deterministic entanglement of two remote transmon qubits by Raman stimulated emission and absorption of a traveling photon wave packet. We achieve a Bell state fidelity of 73%, well explained by losses in the transmission line and decoherence of each qubit.
Campagne-Ibarcq, P; Zalys-Geller, E; Narla, A; Shankar, S; Reinhold, P; Burkhart, L; Axline, C; Pfaff, W; Frunzio, L; Schoelkopf, R J; Devoret, M H
2018-05-18
Large-scale quantum information processing networks will most probably require the entanglement of distant systems that do not interact directly. This can be done by performing entangling gates between standing information carriers, used as memories or local computational resources, and flying ones, acting as quantum buses. We report the deterministic entanglement of two remote transmon qubits by Raman stimulated emission and absorption of a traveling photon wave packet. We achieve a Bell state fidelity of 73%, well explained by losses in the transmission line and decoherence of each qubit.
Fault-tolerant building-block computer study
NASA Technical Reports Server (NTRS)
Rennels, D. A.
1978-01-01
Ultra-reliable core computers are required for improving the reliability of complex military systems. Such computers can provide reliable fault diagnosis, failure circumvention, and, in some cases serve as an automated repairman for their host systems. A small set of building-block circuits which can be implemented as single very large integration devices, and which can be used with off-the-shelf microprocessors and memories to build self checking computer modules (SCCM) is described. Each SCCM is a microcomputer which is capable of detecting its own faults during normal operation and is described to communicate with other identical modules over one or more Mil Standard 1553A buses. Several SCCMs can be connected into a network with backup spares to provide fault-tolerant operation, i.e. automated recovery from faults. Alternative fault-tolerant SCCM configurations are discussed along with the cost and reliability associated with their implementation.
Microbial Genetic Memory to Study Heterogeneous Soil Processes
NASA Astrophysics Data System (ADS)
Fulk, E. M.; Silberg, J. J.; Masiello, C. A.
2017-12-01
Microbes can be engineered to sense environmental conditions and produce a detectable output. These microbial biosensors have traditionally used visual outputs that are difficult to detect in soil. However, recently developed gas-producing biosensors can be used to noninvasively monitor complex soil processes such as horizontal gene transfer or cell-cell signaling. While these biosensors report on the fraction of a microbial population exposed to a process or chemical signal at the time of measurement, they do not record a "memory" of past exposure. Synthetic biologists have recently developed a suite of genetically encoded memory circuits capable of reporting on historical exposure to the signal rather than just the current state. We will provide an overview of the microbial memory systems that may prove useful to studying microbial decision-making in response to environmental conditions. Simple memory circuits can give a yes/no report of any past exposure to the signal (for example anaerobic conditions, osmotic stress, or high nitrate concentrations). More complicated systems can report on the order of exposure of a population to multiple signals or the experiences of spatially distinct populations, such as those in root vs. bulk soil. We will report on proof-of-concept experiments showing the function of a simple permanent memory system in soil-cultured microbes, and we will highlight additional applications. Finally, we will discuss challenges still to be addressed in applying these memory circuits for biogeochemical studies.
Haldane, Morgan; Jogia, Jigar; Cobb, Annabel; Kozuch, Eliza; Kumari, Veena; Frangou, Sophia
2008-01-01
Verbal working memory and emotional self-regulation are impaired in Bipolar Disorder (BD). Our aim was to investigate the effect of Lamotrigine (LTG), which is effective in the clinical management of BD, on the neural circuits subserving working memory and emotional processing. Functional Magnetic Resonance Imaging data from 12 stable BD patients was used to detect LTG-induced changes as the differences in brain activity between drug-free and post-LTG monotherapy conditions during a verbal working memory (N-back sequential letter task) and an angry facial affect recognition task. For both tasks, LGT monotherapy compared to baseline was associated with increased activation mostly within the prefrontal cortex and cingulate gyrus, in regions normally engaged in verbal working memory and emotional processing. Therefore, LTG monotherapy in BD patients may enhance cortical function within neural circuits involved in memory and emotional self-regulation.
Integrated Circuit For Simulation Of Neural Network
NASA Technical Reports Server (NTRS)
Thakoor, Anilkumar P.; Moopenn, Alexander W.; Khanna, Satish K.
1988-01-01
Ballast resistors deposited on top of circuit structure. Cascadable, programmable binary connection matrix fabricated in VLSI form as basic building block for assembly of like units into content-addressable electronic memory matrices operating somewhat like networks of neurons. Connections formed during storage of data, and data recalled from memory by prompting matrix with approximate or partly erroneous signals. Redundancy in pattern of connections causes matrix to respond with correct stored data.
MPEG-1 low-cost encoder solution
NASA Astrophysics Data System (ADS)
Grueger, Klaus; Schirrmeister, Frank; Filor, Lutz; von Reventlow, Christian; Schneider, Ulrich; Mueller, Gerriet; Sefzik, Nicolai; Fiedrich, Sven
1995-02-01
A solution for real-time compression of digital YCRCB video data to an MPEG-1 video data stream has been developed. As an additional option, motion JPEG and video telephone streams (H.261) can be generated. For MPEG-1, up to two bidirectional predicted images are supported. The required computational power for motion estimation and DCT/IDCT, memory size and memory bandwidth have been the main challenges. The design uses fast-page-mode memory accesses and requires only one single 80 ns EDO-DRAM with 256 X 16 organization for video encoding. This can be achieved only by using adequate access and coding strategies. The architecture consists of an input processing and filter unit, a memory interface, a motion estimation unit, a motion compensation unit, a DCT unit, a quantization control, a VLC unit and a bus interface. For using the available memory bandwidth by the processing tasks, a fixed schedule for memory accesses has been applied, that can be interrupted for asynchronous events. The motion estimation unit implements a highly sophisticated hierarchical search strategy based on block matching. The DCT unit uses a separated fast-DCT flowgraph realized by a switchable hardware unit for both DCT and IDCT operation. By appropriate multiplexing, only one multiplier is required for: DCT, quantization, inverse quantization, and IDCT. The VLC unit generates the video-stream up to the video sequence layer and is directly coupled with an intelligent bus-interface. Thus, the assembly of video, audio and system data can easily be performed by the host computer. Having a relatively low complexity and only small requirements for DRAM circuits, the developed solution can be applied to low-cost encoding products for consumer electronics.
The misnomer of attention-deficit hyperactivity disorder.
Wasserman, Theodore; Wasserman, Lori Drucker
2015-01-01
We propose that attention-deficit disorder represents an inefficiency of an integrated system designed to allocate working memory to designated tasks rather than the absence or dysfunction of a particular form of attention. A significant portion of this inefficiency in the allocation of working memory represents poor engagement of the reward circuit with distinct circuits of learning and performance that control instrumental conditioning (learning). Efficient attention requires the interaction of these circuits. For a significant percentage of individuals who present with attention-deficit disorder, their problems represent the engagement, or lack thereof, of the motivational and reward circuit as opposed to problems, or disorders of attention traditionally defined as problems with orienting, focusing, and sustaining. We demonstrate that there is an integrated system of working-memory allocation that responds by recruiting relevant aspects of both cortex and subcortex to the demands of the task being encountered. In this model, attention is viewed as a gating function determined by novelty, flight-or-fight response, and reward history/valence affecting motivation. We view the traditional models of attention, rather than describe specific types of attention per se, as representing the description of the behavioral output of this integrated orienting and engagement system designed to allocate working memory to task-specific stimuli.
Electronic Circuit Analysis Language (ECAL)
NASA Astrophysics Data System (ADS)
Chenghang, C.
1983-03-01
The computer aided design technique is an important development in computer applications and it is an important component of computer science. The special language for electronic circuit analysis is the foundation of computer aided design or computer aided circuit analysis (abbreviated as CACD and CACA) of simulated circuits. Electronic circuit analysis language (ECAL) is a comparatively simple and easy to use circuit analysis special language which uses the FORTRAN language to carry out the explanatory executions. It is capable of conducting dc analysis, ac analysis, and transient analysis of a circuit. Futhermore, the results of the dc analysis can be used directly as the initial conditions for the ac and transient analyses.
ERIC Educational Resources Information Center
Fox, Jeffrey L.
1983-01-01
Provides comments on research studies related to memory systems, considering those exploring the nature of memory traces. One researcher suggests that memory trace circuits are extremely localized (as opposed to being diffuse), such that a lesion in a rabbit's brain can completely destroy the trace for a particular learned response. (JN)
[Memory engram of brain circuit].
Kojima, Hiroto; Sakaguchi, Tetsuya; Ikegaya, Yuji
2015-05-01
How are memories stored in the brain and retrieved on demand? This is a frequently asked question. Indeed, we acquire new memories daily and remember old ones. However, how we can memorize one-time experiences is yet to be investigated. Here, we review possible mechanisms by which memories are maintained in neural networks.
Insights on consciousness from taste memory research.
Gallo, Milagros
2016-01-01
Taste research in rodents supports the relevance of memory in order to determine the content of consciousness by modifying both taste perception and later action. Associated with this issue is the fact that taste and visual modalities share anatomical circuits traditionally related to conscious memory. This challenges the view of taste memory as a type of non-declarative unconscious memory.
Energy-efficient STDP-based learning circuits with memristor synapses
NASA Astrophysics Data System (ADS)
Wu, Xinyu; Saxena, Vishal; Campbell, Kristy A.
2014-05-01
It is now accepted that the traditional von Neumann architecture, with processor and memory separation, is ill suited to process parallel data streams which a mammalian brain can efficiently handle. Moreover, researchers now envision computing architectures which enable cognitive processing of massive amounts of data by identifying spatio-temporal relationships in real-time and solving complex pattern recognition problems. Memristor cross-point arrays, integrated with standard CMOS technology, are expected to result in massively parallel and low-power Neuromorphic computing architectures. Recently, significant progress has been made in spiking neural networks (SNN) which emulate data processing in the cortical brain. These architectures comprise of a dense network of neurons and the synapses formed between the axons and dendrites. Further, unsupervised or supervised competitive learning schemes are being investigated for global training of the network. In contrast to a software implementation, hardware realization of these networks requires massive circuit overhead for addressing and individually updating network weights. Instead, we employ bio-inspired learning rules such as the spike-timing-dependent plasticity (STDP) to efficiently update the network weights locally. To realize SNNs on a chip, we propose to use densely integrating mixed-signal integrate-andfire neurons (IFNs) and cross-point arrays of memristors in back-end-of-the-line (BEOL) of CMOS chips. Novel IFN circuits have been designed to drive memristive synapses in parallel while maintaining overall power efficiency (<1 pJ/spike/synapse), even at spike rate greater than 10 MHz. We present circuit design details and simulation results of the IFN with memristor synapses, its response to incoming spike trains and STDP learning characterization.
Topological order and memory time in marginally-self-correcting quantum memory
NASA Astrophysics Data System (ADS)
Siva, Karthik; Yoshida, Beni
2017-03-01
We examine two proposals for marginally-self-correcting quantum memory: the cubic code by Haah and the welded code by Michnicki. In particular, we prove explicitly that they are absent of topological order above zero temperature, as their Gibbs ensembles can be prepared via a short-depth quantum circuit from classical ensembles. Our proof technique naturally gives rise to the notion of free energy associated with excitations. Further, we develop a framework for an ergodic decomposition of Davies generators in CSS codes which enables formal reduction to simpler classical memory problems. We then show that memory time in the welded code is doubly exponential in inverse temperature via the Peierls argument. These results introduce further connections between thermal topological order and self-correction from the viewpoint of free energy and quantum circuit depth.
Potential roles of cholinergic modulation in the neural coding of location and movement speed
Dannenberg, Holger; Hinman, James R.; Hasselmo, Michael E.
2016-01-01
Behavioral data suggest that cholinergic modulation may play a role in certain aspects of spatial memory, and neurophysiological data demonstrate neurons that fire in response to spatial dimensions, including grid cells and place cells that respond on the basis of location and running speed. These neurons show firing responses that depend upon the visual configuration of the environment, due to coding in visually-responsive regions of the neocortex. This review focuses on the physiological effects of acetylcholine that may influence the sensory coding of spatial dimensions relevant to behavior. In particular, the local circuit effects of acetylcholine within the cortex regulate the influence of sensory input relative to internal memory representations, via presynaptic inhibition of excitatory and inhibitory synaptic transmission, and the modulation of intrinsic currents in cortical excitatory and inhibitory neurons. In addition, circuit effects of acetylcholine regulate the dynamics of cortical circuits including oscillations at theta and gamma frequencies. These effects of acetylcholine on local circuits and network dynamics could underlie the role of acetylcholine in coding of spatial information for the performance of spatial memory tasks. PMID:27677935
Synthesis of energy-efficient FSMs implemented in PLD circuits
NASA Astrophysics Data System (ADS)
Nawrot, Radosław; Kulisz, Józef; Kania, Dariusz
2017-11-01
The paper presents an outline of a simple synthesis method of energy-efficient FSMs. The idea consists in using local clock gating to selectively block the clock signal, if no transition of a state of a memory element is required. The research was dedicated to logic circuits using Programmable Logic Devices as the implementation platform, but the conclusions can be applied to any synchronous circuit. The experimental section reports a comparison of three methods of implementing sequential circuits in PLDs with respect to clock distribution: the classical fully synchronous structure, the structure exploiting the Enable Clock inputs of memory elements, and the structure using clock gating. The results show that the approach based on clock gating is the most efficient one, and it leads to significant reduction of dynamic power consumed by the FSM.
The Neurobiology of Learning and Memory.
ERIC Educational Resources Information Center
Thompson, Rihard F.
1986-01-01
Describes recent research findings in the area of neurobiology and its relationship to learning and memory. The article provides definitions of associative and nonassociative learning, identifies essential memory trace circuits of the mammalian brain, and discusses some neural mechanisms of learning. (TW)
The Corticohippocampal Circuit, Synaptic Plasticity, and Memory
Basu, Jayeeta; Siegelbaum, Steven A.
2015-01-01
Synaptic plasticity serves as a cellular substrate for information storage in the central nervous system. The entorhinal cortex (EC) and hippocampus are interconnected brain areas supporting basic cognitive functions important for the formation and retrieval of declarative memories. Here, we discuss how information flow in the EC–hippocampal loop is organized through circuit design. We highlight recently identified corticohippocampal and intrahippocampal connections and how these long-range and local microcircuits contribute to learning. This review also describes various forms of activity-dependent mechanisms that change the strength of corticohippocampal synaptic transmission. A key point to emerge from these studies is that patterned activity and interaction of coincident inputs gives rise to associational plasticity and long-term regulation of information flow. Finally, we offer insights about how learning-related synaptic plasticity within the corticohippocampal circuit during sensory experiences may enable adaptive behaviors for encoding spatial, episodic, social, and contextual memories. PMID:26525152
Kim, Gyungock; Park, Hyundai; Joo, Jiho; Jang, Ki-Seok; Kwack, Myung-Joon; Kim, Sanghoon; Kim, In Gyoo; Oh, Jin Hyuk; Kim, Sun Ae; Park, Jaegyu; Kim, Sanggi
2015-06-10
When silicon photonic integrated circuits (PICs), defined for transmitting and receiving optical data, are successfully monolithic-integrated into major silicon electronic chips as chip-level optical I/Os (inputs/outputs), it will bring innovative changes in data computing and communications. Here, we propose new photonic integration scheme, a single-chip optical transceiver based on a monolithic-integrated vertical photonic I/O device set including light source on bulk-silicon. This scheme can solve the major issues which impede practical implementation of silicon-based chip-level optical interconnects. We demonstrated a prototype of a single-chip photonic transceiver with monolithic-integrated vertical-illumination type Ge-on-Si photodetectors and VCSELs-on-Si on the same bulk-silicon substrate operating up to 50 Gb/s and 20 Gb/s, respectively. The prototype realized 20 Gb/s low-power chip-level optical interconnects for λ ~ 850 nm between fabricated chips. This approach can have a significant impact on practical electronic-photonic integration in high performance computers (HPC), cpu-memory interface, hybrid memory cube, and LAN, SAN, data center and network applications.
Postirradiation Effects In Integrated Circuits
NASA Technical Reports Server (NTRS)
Shaw, David C.; Barnes, Charles E.
1993-01-01
Two reports discuss postirradiation effects in integrated circuits. Presents examples of postirradiation measurements of performances of integrated circuits of five different types: dual complementary metal oxide/semiconductor (CMOS) flip-flop; CMOS analog multiplier; two CMOS multiplying digital-to-analog converters; electrically erasable programmable read-only memory; and semiconductor/oxide/semiconductor octal buffer driver.
Low-power integrated-circuit driver for ferrite-memory word lines
NASA Technical Reports Server (NTRS)
Katz, S.
1970-01-01
Composite circuit uses both n-p-n bipolar and p-channel MOS transistors /BIMOS/. The BIMOS driver provides 1/ ease of integrated circuit construction, 2/ low standby power consumption, 3/ bidirectional current pulses, and 4/ current-pulse amplitudes and rise times independent of active device parameters.
Perspective: Memcomputing: Leveraging memory and physics to compute efficiently
NASA Astrophysics Data System (ADS)
Di Ventra, Massimiliano; Traversa, Fabio L.
2018-05-01
It is well known that physical phenomena may be of great help in computing some difficult problems efficiently. A typical example is prime factorization that may be solved in polynomial time by exploiting quantum entanglement on a quantum computer. There are, however, other types of (non-quantum) physical properties that one may leverage to compute efficiently a wide range of hard problems. In this perspective, we discuss how to employ one such property, memory (time non-locality), in a novel physics-based approach to computation: Memcomputing. In particular, we focus on digital memcomputing machines (DMMs) that are scalable. DMMs can be realized with non-linear dynamical systems with memory. The latter property allows the realization of a new type of Boolean logic, one that is self-organizing. Self-organizing logic gates are "terminal-agnostic," namely, they do not distinguish between the input and output terminals. When appropriately assembled to represent a given combinatorial/optimization problem, the corresponding self-organizing circuit converges to the equilibrium points that express the solutions of the problem at hand. In doing so, DMMs take advantage of the long-range order that develops during the transient dynamics. This collective dynamical behavior, reminiscent of a phase transition, or even the "edge of chaos," is mediated by families of classical trajectories (instantons) that connect critical points of increasing stability in the system's phase space. The topological character of the solution search renders DMMs robust against noise and structural disorder. Since DMMs are non-quantum systems described by ordinary differential equations, not only can they be built in hardware with the available technology, they can also be simulated efficiently on modern classical computers. As an example, we will show the polynomial-time solution of the subset-sum problem for the worst cases, and point to other types of hard problems where simulations of DMMs' equations of motion on classical computers have already demonstrated substantial advantages over traditional approaches. We conclude this article by outlining further directions of study.
Updated Electronic Testbed System
NASA Technical Reports Server (NTRS)
Brewer, Kevin L.
2001-01-01
As we continue to advance in exploring space frontiers, technology must also advance. The need for faster data recovery and data processing is crucial. In this, the less equipment used, and lighter that equipment is, the better. Because integrated circuits become more sensitive in high altitude, experimental verification and quantification is required. The Center for Applied Radiation Research (CARR) at Prairie View A&M University was awarded a grant by NASA to participate in the NASA ER-2 Flight Program, the APEX balloon flight program, and the Student Launch Program. These programs are to test anomalous errors in integrated circuits due to single event effects (SEE). CARR had already begun experiments characterizing the SEE behavior of high speed and high density SRAM's. The research center built a error testing system using a PC-104 computer unit, an Iomega Zip drive for storage, a test board with the components under test, and a latchup detection and reset unit. A test program was written to continuously monitor a stored data pattern in the SRAM chip and record errors. The devices under test were eight 4Mbit memory chips totaling 4Mbytes of memory. CARR was successful at obtaining data using the Electronic TestBed System (EBS) in various NASA ER-2 test flights. These series of high altitude flights of up to 70,000 feet, were effective at yielding the conditions which single event effects usually occur. However, the data received from the series of flights indicated one error per twenty-four hours. Because flight test time is very expensive, the initial design proved not to be cost effective. The need for orders of magnitude with more memory became essential. Therefore, a project which could test more memory within a given time was created. The goal of this project was not only to test more memory within a given time, but also to have a system with a faster processing speed, and which used less peripherals. This paper will describe procedures used to build an updated Electronic Testbed System.
A hybrid nanomemristor/transistor logic circuit capable of self-programming
Borghetti, Julien; Li, Zhiyong; Straznicky, Joseph; Li, Xuema; Ohlberg, Douglas A. A.; Wu, Wei; Stewart, Duncan R.; Williams, R. Stanley
2009-01-01
Memristor crossbars were fabricated at 40 nm half-pitch, using nanoimprint lithography on the same substrate with Si metal-oxide-semiconductor field effect transistor (MOS FET) arrays to form fully integrated hybrid memory resistor (memristor)/transistor circuits. The digitally configured memristor crossbars were used to perform logic functions, to serve as a routing fabric for interconnecting the FETs and as the target for storing information. As an illustrative demonstration, the compound Boolean logic operation (A AND B) OR (C AND D) was performed with kilohertz frequency inputs, using resistor-based logic in a memristor crossbar with FET inverter/amplifier outputs. By routing the output signal of a logic operation back onto a target memristor inside the array, the crossbar was conditionally configured by setting the state of a nonvolatile switch. Such conditional programming illuminates the way for a variety of self-programmed logic arrays, and for electronic synaptic computing. PMID:19171903
A hybrid nanomemristor/transistor logic circuit capable of self-programming.
Borghetti, Julien; Li, Zhiyong; Straznicky, Joseph; Li, Xuema; Ohlberg, Douglas A A; Wu, Wei; Stewart, Duncan R; Williams, R Stanley
2009-02-10
Memristor crossbars were fabricated at 40 nm half-pitch, using nanoimprint lithography on the same substrate with Si metal-oxide-semiconductor field effect transistor (MOS FET) arrays to form fully integrated hybrid memory resistor (memristor)/transistor circuits. The digitally configured memristor crossbars were used to perform logic functions, to serve as a routing fabric for interconnecting the FETs and as the target for storing information. As an illustrative demonstration, the compound Boolean logic operation (A AND B) OR (C AND D) was performed with kilohertz frequency inputs, using resistor-based logic in a memristor crossbar with FET inverter/amplifier outputs. By routing the output signal of a logic operation back onto a target memristor inside the array, the crossbar was conditionally configured by setting the state of a nonvolatile switch. Such conditional programming illuminates the way for a variety of self-programmed logic arrays, and for electronic synaptic computing.
NASA Astrophysics Data System (ADS)
di Ventra, Massimiliano; Peotta, Sebastiano
2014-03-01
In his original work Josephson [Phys. Lett. 1, 251 (1962)] predicted that a phase-dependent conductance should be present in superconductor tunnel junctions. This effect attracted considerable attention in the past but is difficult to detect, mainly because it is hard to single it out from the background pair current. Here, we propose to isolate it by using a two-junction interferometer where the junctions have the same critical currents but different conductances. The pair current is completely suppressed when the magnetic flux in the loop is half of a flux quantum and the device is characterized by a pure phase-dependent conductance. According to the theory of nonlinear circuit elements this is in fact an ideal voltage-controlled memristor. Possible applications of this memristive device are memories and neuromorphic computing within the framework of ultrafast and low-energy superconducting digital circuits. This work has been supported by DOE under Grant No. DE-FG02-05ER46204.
PWM Inverter control and the application thereof within electric vehicles
Geppert, Steven
1982-01-01
An inverter (34) which provides power to an A.C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A.C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A.C. machine is optimized. The control circuit includes a micro-computer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).
NASA Astrophysics Data System (ADS)
Saint-Jalmes, Hervé; Barjhoux, Yves
1982-01-01
We present a 10 line-7 MHz timing generator built on a single board around two LSI timer chips interfaced to a 16-bit microcomputer. Once programmed from the host computer, this device is able to generate elaborate logic sequences on its 10 output lines without further interventions from the CPU. Powerful architecture introduces new possibilities over conventional memory-based timing simulators and word generators. Loop control on a given sequence of events, loop nesting, and various logic combinations can easily be implemented through a software interface, using a symbolic command language. Typical applications of such a device range from development, emulation, and test of integrated circuits, circuit boards, and communication systems to pulse-controlled instrumentation (radar, ultrasonic systems). A particular application to a pulsed Nuclear Magnetic Resonance (NMR) spectrometer is presented, along with customization of the device for generating four-channel radio-frequency pulses and the necessary sequence for subsequent data acquisition.
Constraints on the synchronization of entorhinal cortex stellate cells
NASA Astrophysics Data System (ADS)
Crotty, Patrick; Lasker, Eric; Cheng, Sen
2012-07-01
Synchronized oscillations of large numbers of central neurons are believed to be important for a wide variety of cognitive functions, including long-term memory recall and spatial navigation. It is therefore plausible that evolution has optimized the biophysical properties of central neurons in some way for synchronized oscillations to occur. Here, we use computational models to investigate the relationships between the presumably genetically determined parameters of stellate cells in layer II of the entorhinal cortex and the ability of coupled populations of these cells to synchronize their intrinsic oscillations: in particular, we calculate the time it takes circuits of two or three cells with initially randomly distributed phases to synchronize their oscillations to within one action potential width, and the metabolic energy they consume in doing so. For recurrent circuit topologies, we find that parameters giving low intrinsic firing frequencies close to those actually observed are strongly advantageous for both synchronization time and metabolic energy consumption.
ERIC Educational Resources Information Center
Xie, Zhiyong; Huang, Cheng; Ci, Bo; Lianzhang, Wang; Zhong, Yi
2013-01-01
Extensive studies of "Drosophila" mushroom body in formation and retrieval of olfactory memories allow us to delineate the functional logic for memory storage and retrieval. Currently, there is a questionable disassociation of circuits for memory storage and retrieval during "Drosophila" olfactory memory processing. Formation…
The neuroscience of positive memory deficits in depression
Dillon, Daniel G.
2015-01-01
Adults with unipolar depression typically show poor episodic memory for positive material, but the neuroscientific mechanisms responsible for this deficit have not been characterized. I suggest a simple hypothesis: weak memory for positive material in depression reflects disrupted communication between the mesolimbic dopamine pathway and medial temporal lobe (MTL) memory systems during encoding. This proposal draws on basic research showing that dopamine release in the hippocampus is critical for the transition from early- to late-phase long-term potentiation (LTP) that marks the conversion of labile, short-term memories into stable, long-term memories. Neuroimaging and pharmacological data from healthy humans paint a similar picture: activation of the mesolimbic reward circuit enhances encoding and boosts retention. Unipolar depression is characterized by anhedonia–loss of pleasure–and reward circuit dysfunction, which is believed to reflect negative effects of stress on the mesolimbic dopamine pathway. Thus, I propose that the MTL is deprived of strengthening reward signals in depressed adults and memory for positive events suffers accordingly. Although other mechanisms are important, this hypothesis holds promise as an explanation for positive memory deficits in depression. PMID:26441703
Schlichting, Margaret L.; Preston, Alison R.
2015-01-01
Learning occurs in the context of existing memories. Encountering new information that relates to prior knowledge may trigger integration, whereby established memories are updated to incorporate new content. Here, we provide a critical test of recent theories suggesting hippocampal (HPC) and medial prefrontal (MPFC) involvement in integration, both during and immediately following encoding. Human participants with established memories for a set of initial (AB) associations underwent fMRI scanning during passive rest and encoding of new related (BC) and unrelated (XY) pairs. We show that HPC-MPFC functional coupling during learning was more predictive of trial-by-trial memory for associations related to prior knowledge relative to unrelated associations. Moreover, the degree to which HPC-MPFC functional coupling was enhanced following overlapping encoding was related to memory integration behavior across participants. We observed a dissociation between anterior and posterior MPFC, with integration signatures during post-encoding rest specifically in the posterior subregion. These results highlight the persistence of integration signatures into post-encoding periods, indicating continued processing of interrelated memories during rest. We also interrogated the coherence of white matter tracts to assess the hypothesis that integration behavior would be related to the integrity of the underlying anatomical pathways. Consistent with our predictions, more coherent HPC-MPFC white matter structure was associated with better performance across participants. This HPC-MPFC circuit also interacted with content-sensitive visual cortex during learning and rest, consistent with reinstatement of prior knowledge to enable updating. These results show that the HPC-MPFC circuit supports on- and offline integration of new content into memory. PMID:26608407
Radiation-Tolerant Intelligent Memory Stack - RTIMS
NASA Technical Reports Server (NTRS)
Ng, Tak-kwong; Herath, Jeffrey A.
2011-01-01
This innovation provides reconfigurable circuitry and 2-Gb of error-corrected or 1-Gb of triple-redundant digital memory in a small package. RTIMS uses circuit stacking of heterogeneous components and radiation shielding technologies. A reprogrammable field-programmable gate array (FPGA), six synchronous dynamic random access memories, linear regulator, and the radiation mitigation circuits are stacked into a module of 42.7 42.7 13 mm. Triple module redundancy, current limiting, configuration scrubbing, and single- event function interrupt detection are employed to mitigate radiation effects. The novel self-scrubbing and single event functional interrupt (SEFI) detection allows a relatively soft FPGA to become radiation tolerant without external scrubbing and monitoring hardware
Optimizing TLB entries for mixed page size storage in contiguous memory
Chen, Dong; Gara, Alan; Giampapa, Mark E.; Heidelberger, Philip; Kriegel, Jon K.; Ohmacht, Martin; Steinmacher-Burow, Burkhard
2013-04-30
A system and method for accessing memory are provided. The system comprises a lookup buffer for storing one or more page table entries, wherein each of the one or more page table entries comprises at least a virtual page number and a physical page number; a logic circuit for receiving a virtual address from said processor, said logic circuit for matching the virtual address to the virtual page number in one of the page table entries to select the physical page number in the same page table entry, said page table entry having one or more bits set to exclude a memory range from a page.
Biological Signal Processing with a Genetic Toggle Switch
Hillenbrand, Patrick; Fritz, Georg; Gerland, Ulrich
2013-01-01
Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems. PMID:23874595
NASA Astrophysics Data System (ADS)
Di Pendina, G.; Zianbetov, E.; Beigne, E.
2015-05-01
Micro and nano electronic integrated circuit domain is today mainly driven by the advent of the Internet of Things for which the constraints are strong, especially in terms of power consumption and autonomy, not only during the computing phases but also during the standby or idle phases. In such ultra-low power applications, the circuit has to meet new constraints mainly linked to its changing energetic environment: long idle phases, automatic wake up, data back-up when the circuit is sporadically turned off, and ultra-low voltage power supply operation. Such circuits have to be completely autonomous regarding their unstable environment, while remaining in an optimum energetic configuration. Therefore, we propose in this paper the first MRAM-based non-volatile asynchronous Muller cell. This cell has been simulated and characterized in a very advanced 28 nm CMOS fully depleted silicon-on-insulator technology, presenting good power performance results due to an extremely efficient body biasing control together with ultra-wide supply voltage range from 160 mV up to 920 mV. The leakage current can be reduced to 154 pA thanks to reverse body biasing. We also propose an efficient standard CMOS bulk version of this cell in order to be compatible with different fabrication processes.
Wang, Xiao-Jing
2016-01-01
The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied. PMID:26928718
Recycling of WEEE: Characterization of spent printed circuit boards from mobile phones and computers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yamane, Luciana Harue, E-mail: lucianayamane@uol.com.br; Tavares de Moraes, Viviane, E-mail: tavares.vivi@gmail.com; Crocce Romano Espinosa, Denise, E-mail: espinosa@usp.br
Highlights: > This paper presents new and important data on characterization of wastes of electric and electronic equipments. > Copper concentration is increasing in mobile phones and remaining constant in personal computers. > Printed circuit boards from mobile phones and computers would not be mixed prior treatment. - Abstract: This paper presents a comparison between printed circuit boards from computers and mobile phones. Since printed circuits boards are becoming more complex and smaller, the amount of materials is constantly changing. The main objective of this work was to characterize spent printed circuit boards from computers and mobile phones applying mineralmore » processing technique to separate the metal, ceramic, and polymer fractions. The processing was performed by comminution in a hammer mill, followed by particle size analysis, and by magnetic and electrostatic separation. Aqua regia leaching, loss-on-ignition and chemical analysis (inductively coupled plasma atomic emission spectroscopy - ICP-OES) were carried out to determine the composition of printed circuit boards and the metal rich fraction. The composition of the studied mobile phones printed circuit boards (PCB-MP) was 63 wt.% metals; 24 wt.% ceramics and 13 wt.% polymers; and of the printed circuit boards from studied personal computers (PCB-PC) was 45 wt.% metals; 27 wt.% polymers and ceramics 28 wt.% ceramics. The chemical analysis showed that copper concentration in printed circuit boards from personal computers was 20 wt.% and in printed circuit boards from mobile phones was 34.5 wt.%. According to the characteristics of each type of printed circuit board, the recovery of precious metals may be the main goal of the recycling process of printed circuit boards from personal computers and the recovery of copper should be the main goal of the recycling process of printed circuit boards from mobile phones. Hence, these printed circuit boards would not be mixed prior treatment. The results of this paper show that copper concentration is increasing in mobile phones and remaining constant in personal computers.« less
Leung, Celeste; Cao, Feng; Nguyen, Robin; Joshi, Krutika; Aqrabawi, Afif J; Xia, Shuting; Cortez, Miguel A; Snead, O Carter; Kim, Jun Chul; Jia, Zhengping
2018-05-22
Social interactions are essential to our mental health, and a deficit in social interactions is a hallmark characteristic of numerous brain disorders. Various subregions within the medial temporal lobe have been implicated in social memory, but the underlying mechanisms that tune these neural circuits remain unclear. Here, we demonstrate that optical activation of excitatory entorhinal cortical perforant projections to the dentate gyrus (EC-DG) is necessary and sufficient for social memory retrieval. We further show that inducible disruption of p21-activated kinase (PAK) signaling, a key pathway important for cytoskeletal reorganization, in the EC-DG circuit leads to impairments in synaptic function and social recognition memory, and, importantly, optogenetic activation of the EC-DG terminals reverses the social memory deficits in the transgenic mice. These results provide compelling evidence that activation of the EC-DG pathway underlies social recognition memory recall and that PAK signaling may play a critical role in modulating this process. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
Field-Sequential Color Converter
NASA Technical Reports Server (NTRS)
Studer, Victor J.
1989-01-01
Electronic conversion circuit enables display of signals from field-sequential color-television camera on color video camera. Designed for incorporation into color-television monitor on Space Shuttle, circuit weighs less, takes up less space, and consumes less power than previous conversion equipment. Incorporates state-of-art memory devices, also used in terrestrial stationary or portable closed-circuit television systems.
Sitaraman, Divya; Kramer, Elizabeth F.; Kahsai, Lily; Ostrowski, Daniela; Zars, Troy
2017-01-01
Feedback mechanisms in operant learning are critical for animals to increase reward or reduce punishment. However, not all conditions have a behavior that can readily resolve an event. Animals must then try out different behaviors to better their situation through outcome learning. This form of learning allows for novel solutions and with positive experience can lead to unexpected behavioral routines. Learned helplessness, as a type of outcome learning, manifests in part as increases in escape latency in the face of repeated unpredicted shocks. Little is known about the mechanisms of outcome learning. When fruit fly Drosophila melanogaster are exposed to unpredicted high temperatures in a place learning paradigm, flies both increase escape latencies and have a higher memory when given control of a place/temperature contingency. Here we describe discrete serotonin neuronal circuits that mediate aversive reinforcement, escape latencies, and memory levels after place learning in the presence and absence of unexpected aversive events. The results show that two features of learned helplessness depend on the same modulatory system as aversive reinforcement. Moreover, changes in aversive reinforcement and escape latency depend on local neural circuit modulation, while memory enhancement requires larger modulation of multiple behavioral control circuits. PMID:29321732
Transfer Functions Via Laplace- And Fourier-Borel Transforms
NASA Technical Reports Server (NTRS)
Can, Sumer; Unal, Aynur
1991-01-01
Approach to solution of nonlinear ordinary differential equations involves transfer functions based on recently-introduced Laplace-Borel and Fourier-Borel transforms. Main theorem gives transform of response of nonlinear system as Cauchy product of transfer function and transform of input function of system, together with memory effects. Used to determine responses of electrical circuits containing variable inductances or resistances. Also possibility of doing all noncommutative algebra on computers in such symbolic programming languages as Macsyma, Reduce, PL1, or Lisp. Process of solution organized and possibly simplified by algebraic manipulations reducing integrals in solutions to known or tabulated forms.
Compact, high-speed algorithm for laying out printed circuit board runs
NASA Astrophysics Data System (ADS)
Zapolotskiy, D. Y.
1985-09-01
A high speed printed circuit connection layout algorithm is described which was developed within the framework of an interactive system for designing two-sided printed circuit broads. For this reason, algorithm speed was considered, a priori, as a requirement equally as important as the inherent demand for minimizing circuit run lengths and the number of junction openings. This resulted from the fact that, in order to provide psychological man/machine compatibility in the design process, real-time dialog during the layout phase is possible only within limited time frames (on the order of several seconds) for each circuit run. The work was carried out for use on an ARM-R automated work site complex based on an SM-4 minicomputer with a 32K-word memory. This limited memory capacity heightened the demand for algorithm speed and also tightened data file structure and size requirements. The layout algorithm's design logic is analyzed. The structure and organization of the data files are described.
NASA Technical Reports Server (NTRS)
Seefeldt, James (Inventor); Feng, Xiaoxin (Inventor); Roper, Weston (Inventor)
2013-01-01
A process, voltage, and temperature (PVT) compensation circuit and a method of continuously generating a delay measure are provided. The compensation circuit includes two delay lines, each delay line providing a delay output. The two delay lines may each include a number of delay elements, which in turn may include one or more current-starved inverters. The number of delay lines may differ between the two delay lines. The delay outputs are provided to a combining circuit that determines an offset pulse based on the two delay outputs and then averages the voltage of the offset pulse to determine a delay measure. The delay measure may be one or more currents or voltages indicating an amount of PVT compensation to apply to input or output signals of an application circuit, such as a memory-bus driver, dynamic random access memory (DRAM), a synchronous DRAM, a processor or other clocked circuit.
Long sequence correlation coprocessor
NASA Astrophysics Data System (ADS)
Gage, Douglas W.
1994-09-01
A long sequence correlation coprocessor (LSCC) accelerates the bitwise correlation of arbitrarily long digital sequences by calculating in parallel the correlation score for 16, for example, adjacent bit alignments between two binary sequences. The LSCC integrated circuit is incorporated into a computer system with memory storage buffers and a separate general purpose computer processor which serves as its controller. Each of the LSCC's set of sequential counters simultaneously tallies a separate correlation coefficient. During each LSCC clock cycle, computer enable logic associated with each counter compares one bit of a first sequence with one bit of a second sequence to increment the counter if the bits are the same. A shift register assures that the same bit of the first sequence is simultaneously compared to different bits of the second sequence to simultaneously calculate the correlation coefficient by the different counters to represent different alignments of the two sequences.
A space-efficient quantum computer simulator suitable for high-speed FPGA implementation
NASA Astrophysics Data System (ADS)
Frank, Michael P.; Oniciuc, Liviu; Meyer-Baese, Uwe H.; Chiorescu, Irinel
2009-05-01
Conventional vector-based simulators for quantum computers are quite limited in the size of the quantum circuits they can handle, due to the worst-case exponential growth of even sparse representations of the full quantum state vector as a function of the number of quantum operations applied. However, this exponential-space requirement can be avoided by using general space-time tradeoffs long known to complexity theorists, which can be appropriately optimized for this particular problem in a way that also illustrates some interesting reformulations of quantum mechanics. In this paper, we describe the design and empirical space/time complexity measurements of a working software prototype of a quantum computer simulator that avoids excessive space requirements. Due to its space-efficiency, this design is well-suited to embedding in single-chip environments, permitting especially fast execution that avoids access latencies to main memory. We plan to prototype our design on a standard FPGA development board.
NASA Astrophysics Data System (ADS)
Baviere, Ph.
Tests which have proven effective for evaluating VLSI circuits for space applications are described. It is recommended that circuits be examined after each manfacturing step to gain fast feedback on inadequacies in the production system. Data from failure modes which occur during operational lifetimes of circuits also permit redefinition of the manufacturing and quality control process to eliminate the defects identified. Other tests include determination of the operational envelope of the circuits, examination of the circuit response to controlled inputs, and the performance and functional speeds of ROM and RAM memories. Finally, it is desirable that all new circuits be designed with testing in mind.
Barker, Jacqueline M.; Taylor, Jane R.; De Vries, Taco J.; Peters, Jamie
2015-01-01
Many abused drugs lead to changes in endogenous brain-derived neurotrophic factor (BDNF) expression in neural circuits responsible for addictive behaviors. BDNF is a known molecular mediator of memory consolidation processes, evident at both behavioral and neurophysiological levels. Specific neural circuits are responsible for storing and executing drug-procuring motor programs, whereas other neural circuits are responsible for the active suppression of these “seeking” systems. These seeking-circuits are established as associations are formed between drug-associated cues and the conditioned responses they elicit. Such conditioned responses (e.g. drug seeking) can be diminished either through a passive weakening of seeking-circuits or an active suppression of those circuits through extinction. Extinction learning occurs when the association between cues and drug are violated, for example, by cue exposure without the drug present. Cue exposure therapy has been proposed as a therapeutic avenue for the treatment of addictions. Here we explore the role of BDNF in extinction circuits, compared to seeking-circuits that “incubate” over prolonged withdrawal periods. We begin by discussing the role of BDNF in extinction memory for fear and cocaine-seeking behaviors, where extinction circuits overlap in infralimbic prefrontal cortex (PFC). We highlight the ability of estrogen to promote BDNF-like effects in hippocampal–prefrontal circuits and consider the role of sex differences in extinction and incubation of drug-seeking behaviors. Finally, we examine how opiates and alcohol “break the mold” in terms of BDNF function in extinction circuits. PMID:25451116
A Design Methodology for Optoelectronic VLSI
2007-01-01
current gets converted to a CMOS voltage level through a transimpedance amplifier circuit called a receiver. The output of the receiver is then...change the current flowing from the diode to a voltage that the logic inputs can use. That circuit is called a receiver. It is a transimpedance amplifier ...incorpo- rate random access memory circuits, SRAM or dynamic RAM (DRAM). These circuits use weak internal analog signals that are amplified by sense
Fredkin and Toffoli Gates Implemented in Oregonator Model of Belousov-Zhabotinsky Medium
NASA Astrophysics Data System (ADS)
Adamatzky, Andrew
A thin-layer Belousov-Zhabotinsky (BZ) medium is a powerful computing device capable for implementing logical circuits, memory, image processors, robot controllers, and neuromorphic architectures. We design the reversible logical gates — Fredkin gate and Toffoli gate — in a BZ medium network of excitable channels with subexcitable junctions. Local control of the BZ medium excitability is an important feature of the gates’ design. An excitable thin-layer BZ medium responds to a localized perturbation with omnidirectional target or spiral excitation waves. A subexcitable BZ medium responds to an asymmetric perturbation by producing traveling localized excitation wave-fragments similar to dissipative solitons. We employ interactions between excitation wave-fragments to perform the computation. We interpret the wave-fragments as values of Boolean variables. The presence of a wave-fragment at a given site of a circuit represents the logical truth, absence of the wave-fragment — logically false. Fredkin gate consists of ten excitable channels intersecting at 11 junctions, eight of which are subexcitable. Toffoli gate consists of six excitable channels intersecting at six junctions, four of which are subexcitable. The designs of the gates are verified using numerical integration of two-variable Oregonator equations.
New ultraportable display technology and applications
NASA Astrophysics Data System (ADS)
Alvelda, Phillip; Lewis, Nancy D.
1998-08-01
MicroDisplay devices are based on a combination of technologies rooted in the extreme integration capability of conventionally fabricated CMOS active-matrix liquid crystal display substrates. Customized diffraction grating and optical distortion correction technology for lens-system compensation allow the elimination of many lenses and systems-level components. The MicroDisplay Corporation's miniature integrated information display technology is rapidly leading to many new defense and commercial applications. There are no moving parts in MicroDisplay substrates, and the fabrication of the color generating gratings, already part of the CMOS circuit fabrication process, is effectively cost and manufacturing process-free. The entire suite of the MicroDisplay Corporation's technologies was devised to create a line of application- specific integrated circuit single-chip display systems with integrated computing, memory, and communication circuitry. Next-generation portable communication, computer, and consumer electronic devices such as truly portable monitor and TV projectors, eyeglass and head mounted displays, pagers and Personal Communication Services hand-sets, and wristwatch-mounted video phones are among the may target commercial markets for MicroDisplay technology. Defense applications range from Maintenance and Repair support, to night-vision systems, to portable projectors for mobile command and control centers.
A novel mechanism of toxic injury to the Papez circuit from chemotherapy.
Kwan, Benjamin Yin Ming; Krings, Timo; Bernstein, Mark; Mandell, Daniel M
2015-04-01
Toxic effects of chemotherapy delivered via Ommaya reservoir include pericatheter necrosis and toxic leukoencephalopathy. Imaging evidence of toxicity is often asymptomatic, but can be clinically consequential. A young patient, treated for cerebrospinal fluid relapse of acute lymphoblastic leukemia with methotrexate and cytarabine via Ommaya reservoir, presented with acute deterioration of short-term memory. MRI demonstrated extra-ventricular Ommaya catheter position and typical methotrexate-induced changes in the deep white matter, but also signal alteration in the forniceal columns and mammillary bodies, components of the Papez circuit. This case presents a novel mechanism of chemotherapy-induced neurotoxicity associated with extra-ventricular Ommaya catheter position. Specifically, the clinical and imaging findings suggest that extra-ventricular Ommaya catheter position may lead to a direct methotrexate-induced toxicity to the Papez circuit. This provides further clinical evidence of the function of the circuit. The possibility that this patient received a supratherapeutic dose of methotrexate may explain why this presentation with profound memory impairment is not more common. However, this case also provides a potential explanation for patients who receive standard dose chemotherapy via extra-ventricular Ommaya catheter and develop milder memory loss. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ma, J.; Liu, Q.
2018-02-01
This paper presents an improved short circuit calculation method, based on pre-computed surface to determine the short circuit current of a distribution system with multiple doubly fed induction generators (DFIGs). The short circuit current, injected into power grid by DFIG, is determined by low voltage ride through (LVRT) control and protection under grid fault. However, the existing methods are difficult to calculate the short circuit current of DFIG in engineering practice due to its complexity. A short circuit calculation method, based on pre-computed surface, was proposed by developing the surface of short circuit current changing with the calculating impedance and the open circuit voltage. And the short circuit currents were derived by taking into account the rotor excitation and crowbar activation time. Finally, the pre-computed surfaces of short circuit current at different time were established, and the procedure of DFIG short circuit calculation considering its LVRT was designed. The correctness of proposed method was verified by simulation.
Automatic weld torch guidance control system
NASA Technical Reports Server (NTRS)
Smaith, H. E.; Wall, W. A.; Burns, M. R., Jr.
1982-01-01
A highly reliable, fully digital, closed circuit television optical, type automatic weld seam tracking control system was developed. This automatic tracking equipment is used to reduce weld tooling costs and increase overall automatic welding reliability. The system utilizes a charge injection device digital camera which as 60,512 inidividual pixels as the light sensing elements. Through conventional scanning means, each pixel in the focal plane is sequentially scanned, the light level signal digitized, and an 8-bit word transmitted to scratch pad memory. From memory, the microprocessor performs an analysis of the digital signal and computes the tracking error. Lastly, the corrective signal is transmitted to a cross seam actuator digital drive motor controller to complete the closed loop, feedback, tracking system. This weld seam tracking control system is capable of a tracking accuracy of + or - 0.2 mm, or better. As configured, the system is applicable to square butt, V-groove, and lap joint weldments.
NASA Technical Reports Server (NTRS)
Wilson, William C.
1999-01-01
The NASA Langley Research Center's Wind Tunnel Reinvestment project plans to shrink the existing data acquisition electronics to fit inside a wind tunnel model. Space limitations within a model necessitate a distributed system of Application Specific Integrated Circuits (ASICs) rather than a centralized system based on PC boards. This thesis will focus on the design of the prototype of the communication Controller board. A portion of the communication Controller board is to be used as the basis of an ASIC design. The communication Controller board will communicate between the internal model modules and the external data acquisition computer. This board is based around an Field Programmable Gate Array (FPGA), to allow for reconfigurability. In addition to the FPGA, this board contains buffer Random Access Memory (RAM), configuration memory (EEPROM), drivers for the communications ports, and passive components.
Liang, Jiajie; Chen, Yongsheng; Xu, Yanfei; Liu, Zhibo; Zhang, Long; Zhao, Xin; Zhang, Xiaoliang; Tian, Jianguo; Huang, Yi; Ma, Yanfeng; Li, Feifei
2010-11-01
Owing to its extraordinary electronic property, chemical stability, and unique two-dimensional nanostructure, graphene is being considered as an ideal material for the highly expected all-carbon-based micro/nanoscale electronics. Herein, we present a simple yet versatile approach to constructing all-carbon micro/nanoelectronics using solution-processing graphene films directly. From these graphene films, various graphene-based microcosmic patterns and structures have been fabricated using maskless computer-controlled laser cutting. Furthermore, a complete system involving a prototype of a flexible write-once-read-many-times memory card and a fast data-reading system has been demonstrated, with infinite data retention time and high reliability. These results indicate that graphene could be the ideal material for fabricating the highly demanded all-carbon and flexible devices and electronics using the simple and efficient roll-to-roll printing process when combined with maskless direct data writing.
Gómez, Rebecca L.; Edgin, Jamie O.
2015-01-01
Hippocampus has an extended developmental trajectory, with refinements occurring in the trisynaptic circuit until adolescence. While structural change should suggest a protracted course in behavior, some studies find evidence of precocious hippocampal development in the first postnatal year and continuity in memory processes beyond. However, a number of memory functions, including binding and relational inference, can be cortically supported. Evidence from the animal literature suggests that tasks often associated with hippocampus (Visual Paired Comparison, binding of a visuomotor response) can be mediated by structures external to hippocampus. Thus, a complete examination of memory development will have to rule out cortex as a source of early memory competency. We propose that early memory must show properties associated with full function of the trisynaptic circuit to reflect “adult-like” memory function, mainly 1) rapid encoding of contextual details of overlapping patterns, and 2) retention of these details over sleep-dependent delays. A wealth of evidence suggests that these functions are not apparent until 18–24 months, with behavioral discontinuities reflecting shifts in the neural structures subserving memory beginning approximately at this point in development. We discuss the implications of these observations for theories of memory and for identifying and measuring memory function in populations with typical and atypical hippocampal function. PMID:26437910
Thalamic abnormalities are a cardinal feature of alcohol-related brain dysfunction.
Pitel, Anne Lise; Segobin, Shailendra H; Ritz, Ludivine; Eustache, Francis; Beaunieux, Hélène
2015-07-01
Two brain networks are particularly affected by the harmful effect of chronic and excessive alcohol consumption: the circuit of Papez and the frontocerebellar circuit, in both of which the thalamus plays a key role. Shrinkage of the thalamus is more severe in alcoholics with Korsakoff's syndrome (KS) than in those without neurological complication (AL). In accordance with the gradient effect of thalamic abnormalities between AL and KS, the pattern of brain dysfunction in the Papez's circuit results in anterograde amnesia in KS and only mild-to-moderate episodic memory disorders in AL. On the opposite, dysfunction of the frontocerebellar circuit results in a similar pattern of working memory and executive deficits in the AL and KS. Several hypotheses, mutually compatible, can be drawn to explain that the severe thalamic shrinkage observed in KS has different consequences in the neuropsychological profile associated with the two brain networks. Copyright © 2014. Published by Elsevier Ltd.
Sornborger, Andrew T.; Wang, Zhuo; Tao, Louis
2015-01-01
Neural oscillations can enhance feature recognition [1], modulate interactions between neurons [2], and improve learning and memory [3]. Numerical studies have shown that coherent spiking can give rise to windows in time during which information transfer can be enhanced in neuronal networks [4–6]. Unanswered questions are: 1) What is the transfer mechanism? And 2) how well can a transfer be executed? Here, we present a pulse-based mechanism by which a graded current amplitude may be exactly propagated from one neuronal population to another. The mechanism relies on the downstream gating of mean synaptic current amplitude from one population of neurons to another via a pulse. Because transfer is pulse-based, information may be dynamically routed through a neural circuit with fixed connectivity. We demonstrate the transfer mechanism in a realistic network of spiking neurons and show that it is robust to noise in the form of pulse timing inaccuracies, random synaptic strengths and finite size effects. We also show that the mechanism is structurally robust in that it may be implemented using biologically realistic pulses. The transfer mechanism may be used as a building block for fast, complex information processing in neural circuits. We show that the mechanism naturally leads to a framework wherein neural information coding and processing can be considered as a product of linear maps under the active control of a pulse generator. Distinct control and processing components combine to form the basis for the binding, propagation, and processing of dynamically routed information within neural pathways. Using our framework, we construct example neural circuits to 1) maintain a short-term memory, 2) compute time-windowed Fourier transforms, and 3) perform spatial rotations. We postulate that such circuits, with automatic and stereotyped control and processing of information, are the neural correlates of Crick and Koch’s zombie modes. PMID:26227067
ERIC Educational Resources Information Center
Schacher, Samuel; Hu, Jiang-Yuan
2014-01-01
An important cellular mechanism contributing to the strength and duration of memories is activity-dependent alterations in the strength of synaptic connections within the neural circuit encoding the memory. Reversal of the memory is typically correlated with a reversal of the cellular changes to levels expressed prior to the stimulation. Thus, for…
Chao, Owen Y; Huston, Joseph P; Li, Jay-Shake; Wang, An-Li; de Souza Silva, Maria A
2016-05-01
The prefrontal cortex directly projects to the lateral entorhinal cortex (LEC), an important substrate for engaging item-associated information and relaying the information to the hippocampus. Here we ask to what extent the communication between the prefrontal cortex and LEC is critically involved in the processing of episodic-like memory. We applied a disconnection procedure to test whether the interaction between the medial prefrontal cortex (mPFC) and LEC is essential for the expression of recognition memory. It was found that male rats that received unilateral NMDA lesions of the mPFC and LEC in the same hemisphere, exhibited intact episodic-like (what-where-when) and object-recognition memories. When these lesions were placed in the opposite hemispheres (disconnection), episodic-like and associative memories for object identity, location and context were impaired. However, the disconnection did not impair the components of episodic memory, namely memory for novel object (what), object place (where) and temporal order (when), per se. Thus, the present findings suggest that the mPFC and LEC are a critical part of a neural circuit that underlies episodic-like and associative object-recognition memory. © 2015 Wiley Periodicals, Inc.
Yamane, Luciana Harue; de Moraes, Viviane Tavares; Espinosa, Denise Crocce Romano; Tenório, Jorge Alberto Soares
2011-12-01
This paper presents a comparison between printed circuit boards from computers and mobile phones. Since printed circuits boards are becoming more complex and smaller, the amount of materials is constantly changing. The main objective of this work was to characterize spent printed circuit boards from computers and mobile phones applying mineral processing technique to separate the metal, ceramic, and polymer fractions. The processing was performed by comminution in a hammer mill, followed by particle size analysis, and by magnetic and electrostatic separation. Aqua regia leaching, loss-on-ignition and chemical analysis (inductively coupled plasma atomic emission spectroscopy - ICP-OES) were carried out to determine the composition of printed circuit boards and the metal rich fraction. The composition of the studied mobile phones printed circuit boards (PCB-MP) was 63 wt.% metals; 24 wt.% ceramics and 13 wt.% polymers; and of the printed circuit boards from studied personal computers (PCB-PC) was 45 wt.% metals; 27 wt.% polymers and ceramics 28 wt.% ceramics. The chemical analysis showed that copper concentration in printed circuit boards from personal computers was 20 wt.% and in printed circuit boards from mobile phones was 34.5 wt.%. According to the characteristics of each type of printed circuit board, the recovery of precious metals may be the main goal of the recycling process of printed circuit boards from personal computers and the recovery of copper should be the main goal of the recycling process of printed circuit boards from mobile phones. Hence, these printed circuit boards would not be mixed prior treatment. The results of this paper show that copper concentration is increasing in mobile phones and remaining constant in personal computers. Copyright © 2011 Elsevier Ltd. All rights reserved.
Somatostatin-Expressing Inhibitory Interneurons in Cortical Circuits
Yavorska, Iryna; Wehr, Michael
2016-01-01
Cortical inhibitory neurons exhibit remarkable diversity in their morphology, connectivity, and synaptic properties. Here, we review the function of somatostatin-expressing (SOM) inhibitory interneurons, focusing largely on sensory cortex. SOM neurons also comprise a number of subpopulations that can be distinguished by their morphology, input and output connectivity, laminar location, firing properties, and expression of molecular markers. Several of these classes of SOM neurons show unique dynamics and characteristics, such as facilitating synapses, specific axonal projections, intralaminar input, and top-down modulation, which suggest possible computational roles. SOM cells can be differentially modulated by behavioral state depending on their class, sensory system, and behavioral paradigm. The functional effects of such modulation have been studied with optogenetic manipulation of SOM cells, which produces effects on learning and memory, task performance, and the integration of cortical activity. Different classes of SOM cells participate in distinct disinhibitory circuits with different inhibitory partners and in different cortical layers. Through these disinhibitory circuits, SOM cells help encode the behavioral relevance of sensory stimuli by regulating the activity of cortical neurons based on subcortical and intracortical modulatory input. Associative learning leads to long-term changes in the strength of connectivity of SOM cells with other neurons, often influencing the strength of inhibitory input they receive. Thus despite their heterogeneity and variability across cortical areas, current evidence shows that SOM neurons perform unique neural computations, forming not only distinct molecular but also functional subclasses of cortical inhibitory interneurons. PMID:27746722
Integrated-Circuit Pseudorandom-Number Generator
NASA Technical Reports Server (NTRS)
Steelman, James E.; Beasley, Jeff; Aragon, Michael; Ramirez, Francisco; Summers, Kenneth L.; Knoebel, Arthur
1992-01-01
Integrated circuit produces 8-bit pseudorandom numbers from specified probability distribution, at rate of 10 MHz. Use of Boolean logic, circuit implements pseudorandom-number-generating algorithm. Circuit includes eight 12-bit pseudorandom-number generators, outputs are uniformly distributed. 8-bit pseudorandom numbers satisfying specified nonuniform probability distribution are generated by processing uniformly distributed outputs of eight 12-bit pseudorandom-number generators through "pipeline" of D flip-flops, comparators, and memories implementing conditional probabilities on zeros and ones.
Simulated mossy fiber associated feedforward circuit functioning as a highpass filter.
Zalay, Osbert C; Bardakjian, Berj L
2006-01-01
Learning and memory rely on the strict regulation of communication between neurons in the hippocampus. The mossy fiber (MF) pathway connects the dentate gyrus to the auto-associative CA3 network, and the information it carries is controlled by a feedforward circuit combining disynaptic inhibition with monosynaptic excitation. Analysis of the MF associated circuit using a mapped clock oscillator (MCO) model reveals the circuit to be a highpass filter.
Wei, Wei; Wang, Xiao-Jing
2016-12-07
We developed a circuit model of spiking neurons that includes multiple pathways in the basal ganglia (BG) and is endowed with feedback mechanisms at three levels: cortical microcircuit, corticothalamic loop, and cortico-BG-thalamocortical system. We focused on executive control in a stop signal task, which is known to depend on BG across species. The model reproduces a range of experimental observations and shows that the newly discovered feedback projection from external globus pallidus to striatum is crucial for inhibitory control. Moreover, stopping process is enhanced by the cortico-subcortical reverberatory dynamics underlying persistent activity, establishing interdependence between working memory and inhibitory control. Surprisingly, the stop signal reaction time (SSRT) can be adjusted by weights of certain connections but is insensitive to other connections in this complex circuit, suggesting novel circuit-based intervention for inhibitory control deficits associated with mental illness. Our model provides a unified framework for inhibitory control, decision making, and working memory. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Baek, Burm
Superconducting-ferromagnetic hybrid devices have potential for a practical memory technology compatible with superconducting logic circuits and may help realize energy-efficient, high-performance superconducting computers. We have developed Josephson junction devices with pseudo-spin-valve barriers. We observed changes in Josephson critical current depending on the magnetization state of the barrier (parallel or anti-parallel) through the superconductor-ferromagnet proximity effect. This effect persists to nanoscale devices in contrast to the remanent field effect. In nanopillar devices, the magnetization states of the pseudo-spin-valve barriers could also be switched with applied bias currents at 4 K, which is consistent with the spin-transfer torque effect in analogous room-temperature spin valve devices. These results demonstrate devices that combine major superconducting and spintronic effects for scalable read and write of memory states, respectively. Further challenges and proposals towards practical devices will also be discussed.In collaboration with: William Rippard, NIST - Boulder, Matthew Pufall, NIST - Boulder, Stephen Russek, NIST-Boulder, Michael Schneider, NIST - Boulder, Samuel Benz, NIST - Boulder, Horst Rogalla, NIST-Boulder, Paul Dresselhaus, NIST - Boulder
Pulvermüller, Friedemann; Garagnani, Max
2014-08-01
Memory cells, the ultimate neurobiological substrates of working memory, remain active for several seconds and are most commonly found in prefrontal cortex and higher multisensory areas. However, if correlated activity in "embodied" sensorimotor systems underlies the formation of memory traces, why should memory cells emerge in areas distant from their antecedent activations in sensorimotor areas, thus leading to "disembodiment" (movement away from sensorimotor systems) of memory mechanisms? We modelled the formation of memory circuits in six-area neurocomputational architectures, implementing motor and sensory primary, secondary and higher association areas in frontotemporal cortices along with known between-area neuroanatomical connections. Sensorimotor learning driven by Hebbian neuroplasticity led to formation of cell assemblies distributed across the different areas of the network. These action-perception circuits (APCs) ignited fully when stimulated, thus providing a neural basis for long-term memory (LTM) of sensorimotor information linked by learning. Subsequent to ignition, activity vanished rapidly from APC neurons in sensorimotor areas but persisted in those in multimodal prefrontal and temporal areas. Such persistent activity provides a mechanism for working memory for actions, perceptions and symbols, including short-term phonological and semantic storage. Cell assembly ignition and "disembodied" working memory retreat of activity to multimodal areas are documented in the neurocomputational models' activity dynamics, at the level of single cells, circuits, and cortical areas. Memory disembodiment is explained neuromechanistically by APC formation and structural neuroanatomical features of the model networks, especially the central role of multimodal prefrontal and temporal cortices in bridging between sensory and motor areas. These simulations answer the "where" question of cortical working memory in terms of distributed APCs and their inner structure, which is, in part, determined by neuroanatomical structure. As the neurocomputational model provides a mechanistic explanation of how memory-related "disembodied" neuronal activity emerges in "embodied" APCs, it may be key to solving aspects of the embodiment debate and eventually to a better understanding of cognitive brain functions. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
CMOS-compatible spintronic devices: a review
NASA Astrophysics Data System (ADS)
Makarov, Alexander; Windbacher, Thomas; Sverdlov, Viktor; Selberherr, Siegfried
2016-11-01
For many decades CMOS devices have been successfully scaled down to achieve higher speed and increased performance of integrated circuits at lower cost. Today’s charge-based CMOS electronics encounters two major challenges: power dissipation and variability. Spintronics is a rapidly evolving research and development field, which offers a potential solution to these issues by introducing novel ‘more than Moore’ devices. Spin-based magnetoresistive random-access memory (MRAM) is already recognized as one of the most promising candidates for future universal memory. Magnetic tunnel junctions, the main elements of MRAM cells, can also be used to build logic-in-memory circuits with non-volatile storage elements on top of CMOS logic circuits, as well as versatile compact on-chip oscillators with low power consumption. We give an overview of CMOS-compatible spintronics applications. First, we present a brief introduction to the physical background considering such effects as magnetoresistance, spin-transfer torque (STT), spin Hall effect, and magnetoelectric effects. We continue with a comprehensive review of the state-of-the-art spintronic devices for memory applications (STT-MRAM, domain wall-motion MRAM, and spin-orbit torque MRAM), oscillators (spin torque oscillators and spin Hall nano-oscillators), logic (logic-in-memory, all-spin logic, and buffered magnetic logic gate grid), sensors, and random number generators. Devices with different types of resistivity switching are analyzed and compared, with their advantages highlighted and challenges revealed. CMOS-compatible spintronic devices are demonstrated beginning with predictive simulations, proceeding to their experimental confirmation and realization, and finalized by the current status of application in modern integrated systems and circuits. We conclude the review with an outlook, where we share our vision on the future applications of the prospective devices in the area.
Cardoso-Cruz, Helder; Sousa, Mafalda; Vieira, Joana B; Lima, Deolinda; Galhardo, Vasco
2013-11-01
The medial prefrontal cortex (mPFC) and the mediodorsal thalamus (MD) form interconnected neural circuits that are important for spatial cognition and memory, but it is not known whether the functional connectivity between these areas is affected by the onset of an animal model of inflammatory pain. To address this issue, we implanted 2 multichannel arrays of electrodes in the mPFC and MD of adult rats and recorded local field potential activity during a food-reinforced spatial working memory task. Recordings were performed for 3weeks, before and after the establishment of the pain model. Our results show that inflammatory pain caused an impairment of spatial working memory performance that is associated with changes in the activity of the mPFC-MD circuit; an analysis of partial directed coherence between the areas revealed a global decrease in the connectivity of the circuit. This decrease was observed over a wide frequency range in both the frontothalamic and thalamofrontal directions of the circuit, but was more evident from MD to mPFC. In addition, spectral analysis revealed significant oscillations of power across frequency bands, namely with a strong theta component that oscillated after the onset of the painful condition. Finally, our data revealed that chronic pain induces an increase in theta/gamma phase coherence and a higher level of mPFC-MD coherence, which is partially conserved across frequency bands. The present results demonstrate that functional disturbances in mPFC-MD connectivity are a relevant cause of deficits in pain-related working memory. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.
Neural Representation of a Target Auditory Memory in a Cortico-Basal Ganglia Pathway
Bottjer, Sarah W.
2013-01-01
Vocal learning in songbirds, like speech acquisition in humans, entails a period of sensorimotor integration during which vocalizations are evaluated via auditory feedback and progressively refined to achieve an imitation of memorized vocal sounds. This process requires the brain to compare feedback of current vocal behavior to a memory of target vocal sounds. We report the discovery of two distinct populations of neurons in a cortico-basal ganglia circuit of juvenile songbirds (zebra finches, Taeniopygia guttata) during vocal learning: (1) one in which neurons are selectively tuned to memorized sounds and (2) another in which neurons are selectively tuned to self-produced vocalizations. These results suggest that neurons tuned to learned vocal sounds encode a memory of those target sounds, whereas neurons tuned to self-produced vocalizations encode a representation of current vocal sounds. The presence of neurons tuned to memorized sounds is limited to early stages of sensorimotor integration: after learning, the incidence of neurons encoding memorized vocal sounds was greatly diminished. In contrast to this circuit, neurons known to drive vocal behavior through a parallel cortico-basal ganglia pathway show little selective tuning until late in learning. One interpretation of these data is that representations of current and target vocal sounds in the shell circuit are used to compare ongoing patterns of vocal feedback to memorized sounds, whereas the parallel core circuit has a motor-related role in learning. Such a functional subdivision is similar to mammalian cortico-basal ganglia pathways in which associative-limbic circuits mediate goal-directed responses, whereas sensorimotor circuits support motor aspects of learning. PMID:24005299
Heavy-ion induced single-event upset in integrated circuits
NASA Technical Reports Server (NTRS)
Zoutendyk, J. A.
1991-01-01
The cosmic ray environment in space can affect the operation of Integrated Circuit (IC) devices via the phenomenon of Single Event Upset (SEU). In particular, heavy ions passing through an IC can induce sufficient integrated current (charge) to alter the state of a bistable circuit, for example a memory cell. The SEU effect is studied in great detail in both static and dynamic memory devices, as well as microprocessors fabricated from bipolar, Complementary Metal Oxide Semiconductor (CMOS) and N channel Metal Oxide Semiconductor (NMOS) technologies. Each device/process reflects its individual characteristics (minimum scale geometry/process parameters) via a unique response to the direct ionization of electron hole pairs by heavy ion tracks. A summary of these analytical and experimental SEU investigations is presented.
Configurable test bed design for nanosats to qualify commercial and customized integrated circuits
NASA Astrophysics Data System (ADS)
Guareschi, W.; Azambuja, J.; Kastensmidt, F.; Reis, R.; Durao, O.; Schuch, N.; Dessbesel, G.
The use of small satellites has increased substantially in recent years due to the reduced cost of their development and launch, as well to the flexibility offered by commercial components. The test bed is a platform that allows components to be evaluated and tested in space. It is a flexible platform, which can be adjusted to a wide quantity of components and interfaces. This work proposes the design and implementation of a test bed suitable for test and evaluation of commercial circuits used in nanosatellites. The development of such a platform allows developers to reduce the efforts in the integration of components and therefore speed up the overall system development time. The proposed test bed is a configurable platform implemented using a Field Programmable Gate Array (FPGA) that controls the communication protocols and connections to the devices under test. The Flash-based ProASIC3E FPGA from Microsemi is used as a control system. This adaptive system enables the control of new payloads and softcores for test and validation in space. Thus, the integration can be easily performed through configuration parameters. It is intended for modularity. Each component connected to the test bed can have a specific interface programmed using a hardware description language (HDL). The data of each component is stored in embedded memories. Each component has its own memory space. The size of the allocated memory can be also configured. The data transfer priority can be set and packaging can be added to the logic, when needed. Communication with peripheral devices and with the Onboard Computer (OBC) is done through the pre-implemented protocols, such as I2C (Inter-Integrated Circuit), SPI (Serial Peripheral Interface) and external memory control. In loco primary tests demonstrated the control system's functionality. The commercial ProASIC3E FPGA family is not space-flight qualified, but tests have been made under Total Ionizing Dose (TID) showing its robustness up to 25 kr- ds (Si). When considering proton and heavy ions, flash-based FPGAs provide immunity to configuration loss and low bit-flips susceptibility in flash memory. In this first version of the test bed two components are connected to the controller FPGA: a commercial magnetometer and a hardened test chip. The embedded FPGA implements a Single Event Effects (SEE) hardened microprocessor and few other soft-cores to be used in space. This test bed will be used in the NanoSatC-BR1, the first Brazilian Cubesat scheduled to be launched in mid-2013.
Blanket Gate Would Address Blocks Of Memory
NASA Technical Reports Server (NTRS)
Lambe, John; Moopenn, Alexander; Thakoor, Anilkumar P.
1988-01-01
Circuit-chip area used more efficiently. Proposed gate structure selectively allows and restricts access to blocks of memory in electronic neural-type network. By breaking memory into independent blocks, gate greatly simplifies problem of reading from and writing to memory. Since blocks not used simultaneously, share operational amplifiers that prompt and read information stored in memory cells. Fewer operational amplifiers needed, and chip area occupied reduced correspondingly. Cost per bit drops as result.
Cognitive Consilience: Primate Non-Primary Neuroanatomical Circuits Underlying Cognition
Solari, Soren Van Hout; Stoner, Rich
2011-01-01
Interactions between the cerebral cortex, thalamus, and basal ganglia form the basis of cognitive information processing in the mammalian brain. Understanding the principles of neuroanatomical organization in these structures is critical to understanding the functions they perform and ultimately how the human brain works. We have manually distilled and synthesized hundreds of primate neuroanatomy facts into a single interactive visualization. The resulting picture represents the fundamental neuroanatomical blueprint upon which cognitive functions must be implemented. Within this framework we hypothesize and detail 7 functional circuits corresponding to psychological perspectives on the brain: consolidated long-term declarative memory, short-term declarative memory, working memory/information processing, behavioral memory selection, behavioral memory output, cognitive control, and cortical information flow regulation. Each circuit is described in terms of distinguishable neuronal groups including the cerebral isocortex (9 pyramidal neuronal groups), parahippocampal gyrus and hippocampus, thalamus (4 neuronal groups), basal ganglia (7 neuronal groups), metencephalon, basal forebrain, and other subcortical nuclei. We focus on neuroanatomy related to primate non-primary cortical systems to elucidate the basis underlying the distinct homotypical cognitive architecture. To display the breadth of this review, we introduce a novel method of integrating and presenting data in multiple independent visualizations: an interactive website (http://www.frontiersin.org/files/cognitiveconsilience/index.html) and standalone iPhone and iPad applications. With these tools we present a unique, annotated view of neuroanatomical consilience (integration of knowledge). PMID:22194717
Analog hardware for delta-backpropagation neural networks
NASA Technical Reports Server (NTRS)
Eberhardt, Silvio P. (Inventor)
1992-01-01
This is a fully parallel analog backpropagation learning processor which comprises a plurality of programmable resistive memory elements serving as synapse connections whose values can be weighted during learning with buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in a plurality of neuron layers in accordance with delta-backpropagation algorithms modified so as to control weight changes due to circuit drift.
Matching tutors and students: effective strategies for information transfer between circuits
NASA Astrophysics Data System (ADS)
Tesileanu, Tiberiu; Balasubramanian, Vijay; Olveczky, Bence
Many neural circuits transfer learned information to downstream circuits: hippocampal-dependent memories are consolidated into long-term memories elsewhere; motor cortex is essential for skill learning but dispensable for execution; anterior forebrain pathway (AFP) in songbirds drives short-term improvements in song that are later consolidated in pre-motor area RA. We show how to match instructive signals from tutor circuits to synaptic plasticity rules in student circuits to achieve effective two-stage learning. We focus on learning sequential patterns where a timebase is transformed into motor commands by connectivity with a `student' area. If the sign of the synaptic change is given by the magnitude of tutor input, a good teaching strategy uses a strong (weak) tutor signal if student output is below (above) its target. If instead timing of tutor input relative to the timebase determines the sign of synaptic modifications, a good instructive signal accumulates the errors in student output as the motor program progresses. We demonstrate song learning in a biologically-plausible model of the songbird circuit given diverse plasticity rules interpolating between those described above. The model also reproduces qualitative firing statistics of RA neurons in juveniles and adults. Also affiliated to CUNY - Graduate Center.
Xyce Parallel Electronic Simulator Users' Guide Version 6.7.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keiter, Eric R.; Aadithya, Karthik Venkatraman; Mei, Ting
This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel com- puting platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one tomore » develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase -- a message passing parallel implementation -- which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The information herein is subject to change without notice. Copyright c 2002-2017 Sandia Corporation. All rights reserved. Trademarks Xyce TM Electronic Simulator and Xyce TM are trademarks of Sandia Corporation. Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence Design Systems, Inc. Microsoft, Windows and Windows 7 are registered trademarks of Microsoft Corporation. Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation. Amtec and TecPlot are trademarks of Amtec Engineering, Inc. All other trademarks are property of their respective owners. Contacts World Wide Web http://xyce.sandia.gov https://info.sandia.gov/xyce (Sandia only) Email xyce@sandia.gov (outside Sandia) xyce-sandia@sandia.gov (Sandia only) Bug Reports (Sandia only) http://joseki-vm.sandia.gov/bugzilla http://morannon.sandia.gov/bugzilla« less
Radiation Effects of Commercial Resistive Random Access Memories
NASA Technical Reports Server (NTRS)
Chen, Dakai; LaBel, Kenneth A.; Berg, Melanie; Wilcox, Edward; Kim, Hak; Phan, Anthony; Figueiredo, Marco; Buchner, Stephen; Khachatrian, Ani; Roche, Nicolas
2014-01-01
We present results for the single-event effect response of commercial production-level resistive random access memories. We found that the resistive memory arrays are immune to heavy ion-induced upsets. However, the devices were susceptible to single-event functional interrupts, due to upsets from the control circuits. The intrinsic radiation tolerant nature of resistive memory makes the technology an attractive consideration for future space applications.
New dynamic FET logic and serial memory circuits for VLSI GaAs technology
NASA Technical Reports Server (NTRS)
Eldin, A. G.
1991-01-01
The complexity of GaAs field effect transistor (FET) very large scale integration (VLSI) circuits is limited by the maximum power dissipation while the uniformity of the device parameters determines the functional yield. In this work, digital GaAs FET circuits are presented that eliminate the DC power dissipation and reduce the area to 50% of that of the conventional static circuits. Its larger tolerance to device parameter variations results in higher functional yield.
Arithmetic Circuit Verification Based on Symbolic Computer Algebra
NASA Astrophysics Data System (ADS)
Watanabe, Yuki; Homma, Naofumi; Aoki, Takafumi; Higuchi, Tatsuo
This paper presents a formal approach to verify arithmetic circuits using symbolic computer algebra. Our method describes arithmetic circuits directly with high-level mathematical objects based on weighted number systems and arithmetic formulae. Such circuit description can be effectively verified by polynomial reduction techniques using Gröbner Bases. In this paper, we describe how the symbolic computer algebra can be used to describe and verify arithmetic circuits. The advantageous effects of the proposed approach are demonstrated through experimental verification of some arithmetic circuits such as multiply-accumulator and FIR filter. The result shows that the proposed approach has a definite possibility of verifying practical arithmetic circuits.
A Unified Dynamic Model for Learning, Replay, and Sharp-Wave/Ripples.
Jahnke, Sven; Timme, Marc; Memmesheimer, Raoul-Martin
2015-12-09
Hippocampal activity is fundamental for episodic memory formation and consolidation. During phases of rest and sleep, it exhibits sharp-wave/ripple (SPW/R) complexes, which are short episodes of increased activity with superimposed high-frequency oscillations. Simultaneously, spike sequences reflecting previous behavior, such as traversed trajectories in space, are replayed. Whereas these phenomena are thought to be crucial for the formation and consolidation of episodic memory, their neurophysiological mechanisms are not well understood. Here we present a unified model showing how experience may be stored and thereafter replayed in association with SPW/Rs. We propose that replay and SPW/Rs are tightly interconnected as they mutually generate and support each other. The underlying mechanism is based on the nonlinear dendritic computation attributable to dendritic sodium spikes that have been prominently found in the hippocampal regions CA1 and CA3, where SPW/Rs and replay are also generated. Besides assigning SPW/Rs a crucial role for replay and thus memory processing, the proposed mechanism also explains their characteristic features, such as the oscillation frequency and the overall wave form. The results shed a new light on the dynamical aspects of hippocampal circuit learning. During phases of rest and sleep, the hippocampus, the "memory center" of the brain, generates intermittent patterns of strongly increased overall activity with high-frequency oscillations, the so-called sharp-wave/ripples. We investigate their role in learning and memory processing. They occur together with replay of activity sequences reflecting previous behavior. Developing a unifying computational model, we propose that both phenomena are tightly linked, by mutually generating and supporting each other. The underlying mechanism depends on nonlinear amplification of synchronous inputs that has been prominently found in the hippocampus. Besides assigning sharp-wave/ripples a crucial role for replay generation and thus memory processing, the proposed mechanism also explains their characteristic features, such as the oscillation frequency and the overall wave form. Copyright © 2015 the authors 0270-6474/15/3516236-23$15.00/0.
Kim, Gyungock; Park, Hyundai; Joo, Jiho; Jang, Ki-Seok; Kwack, Myung-Joon; Kim, Sanghoon; Gyoo Kim, In; Hyuk Oh, Jin; Ae Kim, Sun; Park, Jaegyu; Kim, Sanggi
2015-01-01
When silicon photonic integrated circuits (PICs), defined for transmitting and receiving optical data, are successfully monolithic-integrated into major silicon electronic chips as chip-level optical I/Os (inputs/outputs), it will bring innovative changes in data computing and communications. Here, we propose new photonic integration scheme, a single-chip optical transceiver based on a monolithic-integrated vertical photonic I/O device set including light source on bulk-silicon. This scheme can solve the major issues which impede practical implementation of silicon-based chip-level optical interconnects. We demonstrated a prototype of a single-chip photonic transceiver with monolithic-integrated vertical-illumination type Ge-on-Si photodetectors and VCSELs-on-Si on the same bulk-silicon substrate operating up to 50 Gb/s and 20 Gb/s, respectively. The prototype realized 20 Gb/s low-power chip-level optical interconnects for λ ~ 850 nm between fabricated chips. This approach can have a significant impact on practical electronic-photonic integration in high performance computers (HPC), cpu-memory interface, hybrid memory cube, and LAN, SAN, data center and network applications. PMID:26061463
Night-day-night sleep-wakefulness monitoring by ambulatory integrated circuit memories.
Yamamoto, M; Nakao, M; Katayama, N; Waku, M; Suzuki, K; Irokawa, K; Abe, M; Ueno, T
1999-04-01
A medium-sized portable digital recorder with fully integrated circuit (IC) memories for sleep monitoring has been developed. It has five amplifiers for EEG, EMG, EOG, ECG, and a signal of body acceleration or respiration sound, four event markers, an 8 ch A/D converter, a digital signal processor (DSP), 192 Mbytes IC flash memories, and batteries. The whole system weighs 1200 g including batteries and is put into a small bag worn on the subject's waist or carried in their hand. The sampling rate for each input channel is programmable through the DSP. This apparatus is valuable for continuously monitoring the states of sleep-wakefulness over 24 h, making a night-day-night recording possible in a hospital, home, or car.
Multi-variants synthesis of Petri nets for FPGA devices
NASA Astrophysics Data System (ADS)
Bukowiec, Arkadiusz; Doligalski, Michał
2015-09-01
There is presented new method of synthesis of application specific logic controllers for FPGA devices. The specification of control algorithm is made with use of control interpreted Petri net (PT type). It allows specifying parallel processes in easy way. The Petri net is decomposed into state-machine type subnets. In this case, each subnet represents one parallel process. For this purpose there are applied algorithms of coloring of Petri nets. There are presented two approaches of such decomposition: with doublers of macroplaces or with one global wait place. Next, subnets are implemented into two-level logic circuit of the controller. The levels of logic circuit are obtained as a result of its architectural decomposition. The first level combinational circuit is responsible for generation of next places and second level decoder is responsible for generation output symbols. There are worked out two variants of such circuits: with one shared operational memory or with many flexible distributed memories as a decoder. Variants of Petri net decomposition and structures of logic circuits can be combined together without any restrictions. It leads to existence of four variants of multi-variants synthesis.
Gallium arsenide pilot line for high performance components
NASA Astrophysics Data System (ADS)
1990-01-01
The Gallium Arsenide Pilot Line for High Performance Components (Pilot Line III) is to develop a facility for the fabrication of GaAs logic and memory chips. The first thirty months of this contract are now complete, and this report covers the period from March 27 through September 24, 1989. Similar to the PT-2M SRAM function for memories, the six logic circuits of PT-2L and PT-2M have served their functions as stepping stones toward the custom, standard cell, and cell array logic circuits. All but one of these circuits was right first time; the remaining circuit had a layout error due to a bug in the design rule checker that has since been fixed. The working devices all function over the full temperature range from -55 to 125 C. They all comfortably meet the 200 MHz requirement. They do not solidly conform to the required input and output voltage levels, particularly Vih. It is known that these circuits were designed with the older design models and that they came from an era where the DFET thresholds were often not on target.
Characterization of an Autonomous Non-Volatile Ferroelectric Memory Latch
NASA Technical Reports Server (NTRS)
John, Caroline S.; MacLeod, Todd C.; Evans, Joe; Ho, Fat D.
2011-01-01
We present the electrical characterization of an autonomous non-volatile ferroelectric memory latch using the principle that when an electric field is applied to a ferroelectriccapacitor,the positive and negative remnant polarization charge states of the capacitor are denoted as either data 0 or data 1. The properties of the ferroelectric material to store an electric polarization in the absence of an electric field make the device non-volatile. Further the memory latch is autonomous as it operates with the ground, power and output node connections, without any externally clocked control line. The unique quality of this latch circuit is that it can be written when powered off. The advantages of this latch over flash memories are: a) It offers unlimited reads/writes b) works on symmetrical read/write cycles. c) The latch is asynchronous. The circuit was initially developed by Radiant Technologies Inc., Albuquerque, New Mexico.
A fast low-power optical memory based on coupled micro-ring lasers
NASA Astrophysics Data System (ADS)
Hill, Martin T.; Dorren, Harmen J. S.; de Vries, Tjibbe; Leijtens, Xaveer J. M.; den Besten, Jan Hendrik; Smalbrugge, Barry; Oei, Yok-Siang; Binsma, Hans; Khoe, Giok-Djan; Smit, Meint K.
2004-11-01
The increasing speed of fibre-optic-based telecommunications has focused attention on high-speed optical processing of digital information. Complex optical processing requires a high-density, high-speed, low-power optical memory that can be integrated with planar semiconductor technology for buffering of decisions and telecommunication data. Recently, ring lasers with extremely small size and low operating power have been made, and we demonstrate here a memory element constructed by interconnecting these microscopic lasers. Our device occupies an area of 18 × 40µm2 on an InP/InGaAsP photonic integrated circuit, and switches within 20ps with 5.5fJ optical switching energy. Simulations show that the element has the potential for much smaller dimensions and switching times. Large numbers of such memory elements can be densely integrated and interconnected on a photonic integrated circuit: fast digital optical information processing systems employing large-scale integration should now be viable.
Circuit Analysis of a Drosophila Dopamine Type 2 Receptor That Supports Anesthesia-Resistant Memory.
Scholz-Kornehl, Sabrina; Schwärzel, Martin
2016-07-27
Dopamine is central to reinforcement processing and exerts this function in species ranging from humans to fruit flies. It can do so via two different types of receptors (i.e., D1 or D2) that mediate either augmentation or abatement of cellular cAMP levels. Whereas D1 receptors are known to contribute to Drosophila aversive odor learning per se, we here show that D2 receptors are specific for support of a consolidated form of odor memory known as anesthesia-resistant memory. By means of genetic mosaicism, we localize this function to Kenyon cells, the mushroom body intrinsic neurons, as well as GABAergic APL neurons and local interneurons of the antennal lobes, suggesting that consolidated anesthesia-resistant memory requires widespread dopaminergic modulation within the olfactory circuit. Additionally, dopaminergic neurons themselves require D2R, suggesting a critical role in dopamine release via its recognized autoreceptor function. Considering the dual role of dopamine in balancing memory acquisition (proactive function of dopamine) and its "forgetting" (retroactive function of dopamine), our analysis suggests D2R as central player of either process. Dopamine provides different information; while it mediates reinforcement during the learning act (proactive function), it balances memory performance between two antithetic processes thereafter (retroactive function) (i.e., forgetting and augmentation). Such bidirectional design can also be found at level of dopamine receptors, where augmenting D1 and abating D2 receptors are engaged to balance cellular cAMP levels. Here, we report that consolidated anesthesia-resistant memory (ARM), but not other concomitant memory phases, are sensitive to bidirectional dopaminergic signals. By means of genetic mosaicism, we identified widespread dopaminergic modulation within the olfactory circuit that suggests nonredundant and reiterating functions of D2R in support of ARM. Our results oppose ARM to its concomitant memory phases that localize to mushroom bodies and propose a decentralized organization of consolidated ARM. Copyright © 2016 the authors 0270-6474/16/367936-10$15.00/0.
Place Cells, Grid Cells, and Memory
Moser, May-Britt; Rowland, David C.; Moser, Edvard I.
2015-01-01
The hippocampal system is critical for storage and retrieval of declarative memories, including memories for locations and events that take place at those locations. Spatial memories place high demands on capacity. Memories must be distinct to be recalled without interference and encoding must be fast. Recent studies have indicated that hippocampal networks allow for fast storage of large quantities of uncorrelated spatial information. The aim of the this article is to review and discuss some of this work, taking as a starting point the discovery of multiple functionally specialized cell types of the hippocampal–entorhinal circuit, such as place, grid, and border cells. We will show that grid cells provide the hippocampus with a metric, as well as a putative mechanism for decorrelation of representations, that the formation of environment-specific place maps depends on mechanisms for long-term plasticity in the hippocampus, and that long-term spatiotemporal memory storage may depend on offline consolidation processes related to sharp-wave ripple activity in the hippocampus. The multitude of representations generated through interactions between a variety of functionally specialized cell types in the entorhinal–hippocampal circuit may be at the heart of the mechanism for declarative memory formation. PMID:25646382
AHaH computing-from metastable switches to attractors to machine learning.
Nugent, Michael Alexander; Molter, Timothy Wesley
2014-01-01
Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures-all key capabilities of biological nervous systems and modern machine learning algorithms with real world application.
Built-in self-repair of VLSI memories employing neural nets
NASA Astrophysics Data System (ADS)
Mazumder, Pinaki
1998-10-01
The decades of the Eighties and the Nineties have witnessed the spectacular growth of VLSI technology, when the chip size has increased from a few hundred devices to a staggering multi-millon transistors. This trend is expected to continue as the CMOS feature size progresses towards the nanometric dimension of 100 nm and less. SIA roadmap projects that, where as the DRAM chips will integrate over 20 billion devices in the next millennium, the future microprocessors may incorporate over 100 million transistors on a single chip. As the VLSI chip size increase, the limited accessibility of circuit components poses great difficulty for external diagnosis and replacement in the presence of faulty components. For this reason, extensive work has been done in built-in self-test techniques, but little research is known concerning built-in self-repair. Moreover, the extra hardware introduced by conventional fault-tolerance techniques is also likely to become faulty, therefore causing the circuit to be useless. This research demonstrates the feasibility of implementing electronic neural networks as intelligent hardware for memory array repair. Most importantly, we show that the neural network control possesses a robust and degradable computing capability under various fault conditions. Overall, a yield analysis performed on 64K DRAM's shows that the yield can be improved from as low as 20 percent to near 99 percent due to the self-repair design, with overhead no more than 7 percent.
Beyond the bolus: transgenic tools for investigating the neurophysiology of learning and memory.
Lykken, Christine; Kentros, Clifford G
2014-10-01
Understanding the neural mechanisms underlying learning and memory in the entorhinal-hippocampal circuit is a central challenge of systems neuroscience. For more than 40 years, electrophysiological recordings in awake, behaving animals have been used to relate the receptive fields of neurons in this circuit to learning and memory. However, the vast majority of such studies are purely observational, as electrical, surgical, and pharmacological circuit manipulations are both challenging and relatively coarse, being unable to distinguish between specific classes of neurons. Recent advances in molecular genetic tools can overcome many of these limitations, enabling unprecedented control over neural activity in behaving animals. Expression of pharmaco- or optogenetic transgenes in cell-type-specific "driver" lines provides unparalleled anatomical and cell-type specificity, especially when delivered by viral complementation. Pharmacogenetic transgenes are specially designed neurotransmitter receptors exclusively activated by otherwise inactive synthetic ligands and have kinetics similar to traditional pharmacology. Optogenetic transgenes use light to control the membrane potential, and thereby operate at the millisecond timescale. Thus, activation of pharmacogenetic transgenes in specific neuronal cell types while recording from other parts of the circuit allows investigation of the role of those neurons in the steady state, whereas optogenetic transgenes allow one to determine the immediate network response. © 2014 Lykken and Kentros; Published by Cold Spring Harbor Laboratory Press.
Gómez, Rebecca L; Edgin, Jamie O
2016-04-01
Hippocampus has an extended developmental trajectory, with refinements occurring in the trisynaptic circuit until adolescence. While structural change should suggest a protracted course in behavior, some studies find evidence of precocious hippocampal development in the first postnatal year and continuity in memory processes beyond. However, a number of memory functions, including binding and relational inference, can be cortically supported. Evidence from the animal literature suggests that tasks often associated with hippocampus (visual paired comparison, binding of a visuomotor response) can be mediated by structures external to hippocampus. Thus, a complete examination of memory development will have to rule out cortex as a source of early memory competency. We propose that early memory must show properties associated with full function of the trisynaptic circuit to reflect "adult-like" memory function, mainly (1) rapid encoding of contextual details of overlapping patterns, and (2) retention of these details over sleep-dependent delays. A wealth of evidence suggests that these functions are not apparent until 18-24 months, with behavioral discontinuities reflecting shifts in the neural structures subserving memory beginning approximately at this point in development. We discuss the implications of these observations for theories of memory and for identifying and measuring memory function in populations with typical and atypical hippocampal function. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Integrated plasticity at inhibitory and excitatory synapses in the cerebellar circuit.
Mapelli, Lisa; Pagani, Martina; Garrido, Jesus A; D'Angelo, Egidio
2015-01-01
The way long-term potentiation (LTP) and depression (LTD) are integrated within the different synapses of brain neuronal circuits is poorly understood. In order to progress beyond the identification of specific molecular mechanisms, a system in which multiple forms of plasticity can be correlated with large-scale neural processing is required. In this paper we take as an example the cerebellar network, in which extensive investigations have revealed LTP and LTD at several excitatory and inhibitory synapses. Cerebellar LTP and LTD occur in all three main cerebellar subcircuits (granular layer, molecular layer, deep cerebellar nuclei) and correspondingly regulate the function of their three main neurons: granule cells (GrCs), Purkinje cells (PCs) and deep cerebellar nuclear (DCN) cells. All these neurons, in addition to be excited, are reached by feed-forward and feed-back inhibitory connections, in which LTP and LTD may either operate synergistically or homeostatically in order to control information flow through the circuit. Although the investigation of individual synaptic plasticities in vitro is essential to prove their existence and mechanisms, it is insufficient to generate a coherent view of their impact on network functioning in vivo. Recent computational models and cell-specific genetic mutations in mice are shedding light on how plasticity at multiple excitatory and inhibitory synapses might regulate neuronal activities in the cerebellar circuit and contribute to learning and memory and behavioral control.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Di Pendina, G., E-mail: gregory.dipendina@cea.fr, E-mail: eldar.zianbetov@cea.fr, E-mail: edith.beigne@cea.fr; Zianbetov, E., E-mail: gregory.dipendina@cea.fr, E-mail: eldar.zianbetov@cea.fr, E-mail: edith.beigne@cea.fr; CNRS, SPINTEC, F-38000 Grenoble
2015-05-07
Micro and nano electronic integrated circuit domain is today mainly driven by the advent of the Internet of Things for which the constraints are strong, especially in terms of power consumption and autonomy, not only during the computing phases but also during the standby or idle phases. In such ultra-low power applications, the circuit has to meet new constraints mainly linked to its changing energetic environment: long idle phases, automatic wake up, data back-up when the circuit is sporadically turned off, and ultra-low voltage power supply operation. Such circuits have to be completely autonomous regarding their unstable environment, while remainingmore » in an optimum energetic configuration. Therefore, we propose in this paper the first MRAM-based non-volatile asynchronous Muller cell. This cell has been simulated and characterized in a very advanced 28 nm CMOS fully depleted silicon-on-insulator technology, presenting good power performance results due to an extremely efficient body biasing control together with ultra-wide supply voltage range from 160 mV up to 920 mV. The leakage current can be reduced to 154 pA thanks to reverse body biasing. We also propose an efficient standard CMOS bulk version of this cell in order to be compatible with different fabrication processes.« less
Difference-Equation/Flow-Graph Circuit Analysis
NASA Technical Reports Server (NTRS)
Mcvey, I. M.
1988-01-01
Numerical technique enables rapid, approximate analyses of electronic circuits containing linear and nonlinear elements. Practiced in variety of computer languages on large and small computers; for circuits simple enough, programmable hand calculators used. Although some combinations of circuit elements make numerical solutions diverge, enables quick identification of divergence and correction of circuit models to make solutions converge.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salmilehto, J.; Deppe, F.; Di Ventra, M.
Memristors are resistive elements retaining information of their past dynamics. They have garnered substantial interest due to their potential for representing a paradigm change in electronics, information processing and unconventional computing. Given the advent of quantum technologies, a design for a quantum memristor with superconducting circuits may be envisaged. Along these lines, we introduce such a quantum device whose memristive behavior arises from quasiparticle-induced tunneling when supercurrents are cancelled. Here in this paper, for realistic parameters, we find that the relevant hysteretic behavior may be observed using current state-of-the-art measurements of the phase-driven tunneling current. Finally, we develop suitable methodsmore » to quantify memory retention in the system.« less
Ophir, Alexander G
2017-01-01
The role of memory in mating systems is often neglected despite the fact that most mating systems are defined in part by how animals use space. Monogamy, for example, is usually characterized by affiliative (e.g., pairbonding) and defensive (e.g., mate guarding) behaviors, but a high degree of spatial overlap in home range use is the easiest defining feature of monogamous animals in the wild. The nonapeptides vasopressin and oxytocin have been the focus of much attention for their importance in modulating social behavior, however this work has largely overshadowed their roles in learning and memory. To date, the understanding of memory systems and mechanisms governing social behavior have progressed relatively independently. Bridging these two areas will provide a deeper appreciation for understanding behavior, and in particular the mechanisms that mediate reproductive decision-making. Here, I argue that the ability to mate effectively as monogamous individuals is linked to the ability to track conspecifics in space. I discuss the connectivity across some well-known social and spatial memory nuclei, and propose that the nonapeptide receptors within these structures form a putative "socio-spatial memory neural circuit." This purported circuit may function to integrate social and spatial information to shape mating decisions in a context-dependent fashion. The lateral septum and/or the nucleus accumbens, and neuromodulation therein, may act as an intermediary to relate socio-spatial information with social behavior. Identifying mechanisms responsible for relating information about the social world with mechanisms mediating mating tactics is crucial to fully appreciate the suite of factors driving reproductive decisions and social decision-making.
A set-associative, fault-tolerant cache design
NASA Technical Reports Server (NTRS)
Lamet, Dan; Frenzel, James F.
1992-01-01
The design of a defect-tolerant control circuit for a set-associative cache memory is presented. The circuit maintains the stack ordering necessary for implementing the Least Recently Used (LRU) replacement algorithm. A discussion of programming techniques for bypassing defective blocks is included.
Multiple channel programmable coincidence counter
Arnone, Gaetano J.
1990-01-01
A programmable digital coincidence counter having multiple channels and featuring minimal dead time. Neutron detectors supply electrical pulses to a synchronizing circuit which in turn inputs derandomized pulses to an adding circuit. A random access memory circuit connected as a programmable length shift register receives and shifts the sum of the pulses, and outputs to a serializer. A counter is input by the adding circuit and downcounted by the seralizer, one pulse at a time. The decoded contents of the counter after each decrement is output to scalers.
John, Rohit Abraham; Ko, Jieun; Kulkarni, Mohit R; Tiwari, Naveen; Chien, Nguyen Anh; Ing, Ng Geok; Leong, Wei Lin; Mathews, Nripan
2017-08-01
Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm 2 V -1 s -1 with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time-dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation transparent neural circuits. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Watson, Bobby L.; Aeby, Ian
1982-01-01
An adaptive data compression device for compressing data having variable frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.
HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.
James, Alex Pappachen; Fedorova, Irina; Ibrayev, Timur; Kudithipudi, Dhireesha
2017-06-01
Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and temporal memory. In this work, we propose a new Spatial Pooler circuit design with parallel memristive crossbar arrays for the 2D columns. The proposed design was validated on two different benchmark datasets, face recognition, and speech recognition. The circuits are simulated and analyzed using a practical memristor device model and 0.18 μm IBM CMOS technology model. The databases AR, YALE, ORL, and UFI, are used to test the performance of the design in face recognition. TIMIT dataset is used for the speech recognition.
The Infrared Automatic Mass Screening (IRAMS) System For Printed Circuit Board Fault Detection
NASA Astrophysics Data System (ADS)
Hugo, Perry W.
1987-05-01
Office of the Program Manager for TMDE (OPM TMDE) has initiated a program to develop techniques for evaluating the performance of printed circuit boards (PCB's) using infrared thermal imaging. It is OPM TMDE's expectation that the standard thermal profile (STP) will become the basis for the future rapid automatic detection and isolation of gross failure mechanisms on units under test (UUT's). To accomplish this OPM TMDE has purchased two Infrared Automatic Mass Screening ( I RAMS) systems which are scheduled for delivery in 1987. The IRAMS system combines a high resolution infrared thermal imager with a test bench and diagnostic computer hardware and software. Its purpose is to rapidly and automatically compare the thermal profiles of a UUT with the STP of that unit, recalled from memory, in order to detect thermally responsive failure mechanisms in PCB's. This paper will review the IRAMS performance requirements, outline the plan for implementing the two systems and report on progress to date.
Cerebellar supervised learning revisited: biophysical modeling and degrees-of-freedom control.
Kawato, Mitsuo; Kuroda, Shinya; Schweighofer, Nicolas
2011-10-01
The biophysical models of spike-timing-dependent plasticity have explored dynamics with molecular basis for such computational concepts as coincidence detection, synaptic eligibility trace, and Hebbian learning. They overall support different learning algorithms in different brain areas, especially supervised learning in the cerebellum. Because a single spine is physically very small, chemical reactions at it are essentially stochastic, and thus sensitivity-longevity dilemma exists in the synaptic memory. Here, the cascade of excitable and bistable dynamics is proposed to overcome this difficulty. All kinds of learning algorithms in different brain regions confront with difficult generalization problems. For resolution of this issue, the control of the degrees-of-freedom can be realized by changing synchronicity of neural firing. Especially, for cerebellar supervised learning, the triangle closed-loop circuit consisting of Purkinje cells, the inferior olive nucleus, and the cerebellar nucleus is proposed as a circuit to optimally control synchronous firing and degrees-of-freedom in learning. Copyright © 2011 Elsevier Ltd. All rights reserved.
Anatomy of filamentary threshold switching in amorphous niobium oxide.
Li, Shuai; Liu, Xinjun; Nandi, Sanjoy Kumar; Elliman, Robert Glen
2018-06-25
The threshold switching behaviour of Pt/NbOx/TiN devices is investigated as a function device area and NbOx film thickness and shown to reveal important insight into the structure of the self-assembled switching region. The devices exhibit combined selector-memory (1S1R) behavior after an initial voltage-controlled forming process, but exhibit symmetric threshold switching when the RESET and SET currents are kept below a critical value. In this mode, the threshold and hold voltages are independent of the device area and film thickness but the threshold current (power), while independent of device area, decreases with increasing film thickness. These results are shown to be consistent with a structure in which the threshold switching volume is confined, both laterally and vertically, to the region between the residual memory filament and the TiN electrode, and where the memory filament has a core-shell structure comprising a metallic core and a semiconducting shell. The veracity of this structure is demonstrated by comparing experimental results with the predictions of a simple circuit model, and more detailed finite element simulations. These results provide further insight into the structure and operation of NbOx threshold switching devices that have application in emerging memory and neuromorphic computing fields. © 2018 IOP Publishing Ltd.
Long-Term Memory Shapes the Primary Olfactory Center of an Insect Brain
ERIC Educational Resources Information Center
Hourcade, Benoit; Perisse, Emmanuel; Devaud, Jean-Marc; Sandoz, Jean-Christophe
2009-01-01
The storage of stable memories is generally considered to rely on changes in the functional properties and/or the synaptic connectivity of neural networks. However, these changes are not easily tractable given the complexity of the learning procedures and brain circuits studied. Such a search can be narrowed down by studying memories of specific…
NASA Technical Reports Server (NTRS)
Horst, R. L.; Nordstrom, M. J.
1972-01-01
An operation manual is presented for the oligatomic mass memory feasibility model. It includes a brief description of the memory and exerciser units, a description of the controls and their functions, the operating procedures, the test points and adjustments, and the circuit diagram.
Notes on implementation of sparsely distributed memory
NASA Technical Reports Server (NTRS)
Keeler, J. D.; Denning, P. J.
1986-01-01
The Sparsely Distributed Memory (SDM) developed by Kanerva is an unconventional memory design with very interesting and desirable properties. The memory works in a manner that is closely related to modern theories of human memory. The SDM model is discussed in terms of its implementation in hardware. Two appendices discuss the unconventional approaches of the SDM: Appendix A treats a resistive circuit for fast, parallel address decoding; and Appendix B treats a systolic array for high throughput read and write operations.
Jiang, Li; Kundu, Srikanya; Lederman, James D.; López-Hernández, Gretchen Y.; Ballinger, Elizabeth C.; Wang, Shaohua; Talmage, David A.; Role, Lorna W.
2016-01-01
Summary We examined the contribution of endogenous cholinergic signaling to the acquisition and extinction of fear- related memory by optogenetic regulation of cholinergic input to the basal lateral amygdala (BLA). Stimulation of cholinergic terminal fields within the BLA in awake-behaving mice during training in a cued fear-conditioning paradigm slowed the extinction of learned fear as assayed by multi-day retention of extinction learning. Inhibition of cholinergic activity during training reduced the acquisition of learned fear behaviors. Circuit mechanisms underlying the behavioral effects of cholinergic signaling in the BLA were assessed by in vivo and ex vivo electrophysiological recording. Photo-stimulation of endogenous cholinergic input: (1) enhances firing of putative BLA principal neurons through activation of acetylcholine receptors (AChRs); (2) enhances glutamatergic synaptic transmission in the BLA and (3) induces LTP of cortical-amygdala circuits. These studies support an essential role of cholinergic modulation of BLA circuits in the inscription and retention of fear memories. PMID:27161525
Emotion and the motivational brain
Lang, Peter J.; Bradley, Margaret M.
2013-01-01
Psychophysiological and neuroscience studies of emotional processing undertaken by investigators at the University of Florida Laboratory of the Center for the Study of Emotion and Attention (CSEA) are reviewed, with a focus on reflex reactions, neural structures and functional circuits that mediate emotional expression. The theoretical view shared among the investigators is that expressed emotions are founded on motivational circuits in the brain that developed early in evolutionary history to ensure the survival of individuals and their progeny. These circuits react to appetitive and aversive environmental and memorial cues, mediating appetitive and defensive reflexes that tune sensory systems and mobilize the organism for action and underly negative and positive affects. The research reviewed here assesses the reflex physiology of emotion, both autonomic and somatic, studying affects evoked in picture perception, memory imagery, and in the context of tangible reward and punishment, and using the electroencephalograph (EEG) and functional magnetic resonance imaging (fMRI), explores the brain’s motivational circuits that determine human emotion. PMID:19879918
Maximum Acceleration Recording Circuit
NASA Technical Reports Server (NTRS)
Bozeman, Richard J., Jr.
1995-01-01
Coarsely digitized maximum levels recorded in blown fuses. Circuit feeds power to accelerometer and makes nonvolatile record of maximum level to which output of accelerometer rises during measurement interval. In comparison with inertia-type single-preset-trip-point mechanical maximum-acceleration-recording devices, circuit weighs less, occupies less space, and records accelerations within narrower bands of uncertainty. In comparison with prior electronic data-acquisition systems designed for same purpose, circuit simpler, less bulky, consumes less power, costs and analysis of data recorded in magnetic or electronic memory devices. Circuit used, for example, to record accelerations to which commodities subjected during transportation on trucks.
Using New Approaches in Neurobiology to Rethink Stress-Induced Amnesia
2018-01-01
Purpose of Review Psychological stress can impact memory systems in several different ways. In individuals with healthy defense and coping systems, stress results in the formation of negatively valenced memories whose ability to induce emotional and somatic distress subsides with time. Vulnerable individuals, however, go on to develop stress-related disorders such as post-traumatic stress disorder (PTSD) and suffer from significant memory abnormalities. Whether expressed as intrusive trauma memories, partial amnesia, or dissociative amnesia, such abnormalities are thought to be the core source of patients’ symptoms, which are often debilitating and implicate an entire socio-cognitive-affective spectrum. Recent Findings With this in mind, and focusing on stress-responsive hippocampal microcircuits, this article highlights recent advances in the neurobiology of memory that allow us to (1) isolate and visualize memory circuits, (2) change their activity using genetic tools and state-dependent manipulations, and (3) directly examine their impact on socio-affective circuits and global network connectivity. By integrating these approaches, we are now in a position to address important questions that have troubled psychiatry for a long time—questions such as are traumatic memories special, and why are stress effects on memory diverse. Summary Furthering our fundamental understanding of memory in the framework of adaptive and maladaptive stress responses has the potential to boost the development of new treatments that can benefit patients suffering from psychological trauma. PMID:29657916
Using New Approaches in Neurobiology to Rethink Stress-Induced Amnesia.
Radulovic, Jelena
2017-03-01
Psychological stress can impact memory systems in several different ways. In individuals with healthy defense and coping systems, stress results in the formation of negatively valenced memories whose ability to induce emotional and somatic distress subsides with time. Vulnerable individuals, however, go on to develop stress-related disorders such as post-traumatic stress disorder (PTSD) and suffer from significant memory abnormalities. Whether expressed as intrusive trauma memories, partial amnesia, or dissociative amnesia, such abnormalities are thought to be the core source of patients' symptoms, which are often debilitating and implicate an entire socio-cognitive-affective spectrum. With this in mind, and focusing on stress-responsive hippocampal microcircuits, this article highlights recent advances in the neurobiology of memory that allow us to (1) isolate and visualize memory circuits, (2) change their activity using genetic tools and state-dependent manipulations, and (3) directly examine their impact on socio-affective circuits and global network connectivity. By integrating these approaches, we are now in a position to address important questions that have troubled psychiatry for a long time-questions such as are traumatic memories special, and why are stress effects on memory diverse. Furthering our fundamental understanding of memory in the framework of adaptive and maladaptive stress responses has the potential to boost the development of new treatments that can benefit patients suffering from psychological trauma.
Meeting the memory challenges of brain-scale network simulation.
Kunkel, Susanne; Potjans, Tobias C; Eppler, Jochen M; Plesser, Hans Ekkehard; Morrison, Abigail; Diesmann, Markus
2011-01-01
The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity, and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10(5) neurons with up to 10(9) synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been investigated in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Blue Gene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of neuronal simulators as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place. As a consequence, development cycles can be shorter and less expensive. Applying the model to our freely available Neural Simulation Tool (NEST), we identify the software components dominant at different scales, and develop general strategies for reducing the memory consumption, in particular by using data structures that exploit the sparseness of the local representation of the network. We show that these adaptations enable our simulation software to scale up to the order of 10,000 processors and beyond. As memory consumption issues are likely to be relevant for any software dealing with complex connectome data on such architectures, our approach and our findings should be useful for researchers developing novel neuroinformatics solutions to the challenges posed by the connectome project.
Pralus, Agathe; Nelson, Andrew J. D.; Hornberger, Michael
2016-01-01
Abstract It is widely assumed that incipient protein pathology in the medial temporal lobe instigates the loss of episodic memory in Alzheimer’s disease, one of the earliest cognitive deficits in this type of dementia. Within this region, the hippocampus is seen as the most vital for episodic memory. Consequently, research into the causes of memory loss in Alzheimer’s disease continues to centre on hippocampal dysfunction and how disease-modifying therapies in this region can potentially alleviate memory symptomology. The present review questions this entrenched notion by bringing together findings from post-mortem studies, non-invasive imaging (including studies of presymptomatic, at-risk cases) and genetically modified animal models. The combined evidence indicates that the loss of episodic memory in early Alzheimer’s disease reflects much wider neurodegeneration in an extended mnemonic system (Papez circuit), which critically involves the limbic thalamus. Within this system, the anterior thalamic nuclei are prominent, both for their vital contributions to episodic memory and for how these same nuclei appear vulnerable in prodromal Alzheimer’s disease. As thalamic abnormalities occur in some of the earliest stages of the disease, the idea that such changes are merely secondary to medial temporal lobe dysfunctions is challenged. This alternate view is further strengthened by the interdependent relationship between the anterior thalamic nuclei and retrosplenial cortex, given how dysfunctions in the latter cortical area provide some of the earliest in vivo imaging evidence of prodromal Alzheimer’s disease. Appreciating the importance of the anterior thalamic nuclei for memory and attention provides a more balanced understanding of Alzheimer’s disease. Furthermore, this refocus on the limbic thalamus, as well as the rest of Papez circuit, would have significant implications for the diagnostics, modelling, and experimental treatment of cognitive symptoms in Alzheimer’s disease. PMID:27190025
Watson, B.L.; Aeby, I.
1980-08-26
An adaptive data compression device for compressing data is described. The device has a frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.
Memory-Based Structured Application Specific Integrated Circuit (ASIC) Study
2008-10-01
memory interface, arbiter/ schedulers for rescheduling the memory requests according to some schedule policy, and memory channels for communicating...between the power-savings and the wakeup overhead with respect to both wakeup power and wakeup delay. For example, dream mode can save 50% more static...power than sleep mode, but at the expense of twice the wake delay and three times the wakeup energy. The user can specify power-gating modes for various components.
AHaH Computing–From Metastable Switches to Attractors to Machine Learning
Nugent, Michael Alexander; Molter, Timothy Wesley
2014-01-01
Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures–all key capabilities of biological nervous systems and modern machine learning algorithms with real world application. PMID:24520315
Electronics. Module 3: Digital Logic Application. Instructor's Guide.
ERIC Educational Resources Information Center
Carter, Ed; Murphy, Mark
This guide contains instructor's materials for a 10-unit secondary school course on digital logic application. The units are introduction to digital, logic gates, digital integrated circuits, combination logic, flip-flops, counters and shift registers, encoders and decoders, arithmetic circuits, memory, and analog/digital and digital/analog…
3D Printing of Shape Memory Polymers for Flexible Electronic Devices.
Zarek, Matt; Layani, Michael; Cooperstein, Ido; Sachyani, Ela; Cohn, Daniel; Magdassi, Shlomo
2016-06-01
The formation of 3D objects composed of shape memory polymers for flexible electronics is described. Layer-by-layer photopolymerization of methacrylated semicrystalline molten macromonomers by a 3D digital light processing printer enables rapid fabrication of complex objects and imparts shape memory functionality for electrical circuits. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
D’Esposito, Mark
2017-01-01
Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic “activity-silent” synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior. PMID:29244810
NASA Technical Reports Server (NTRS)
Hall, William A. (Inventor)
1993-01-01
A bus programmable slave module card for use in a computer control system is disclosed which comprises a master computer and one or more slave computer modules interfacing by means of a bus. Each slave module includes its own microprocessor, memory, and control program for acting as a single loop controller. The slave card includes a plurality of memory means (S1, S2...) corresponding to a like plurality of memory devices (C1, C2...) in the master computer, for each slave memory means its own communication lines connectable through the bus with memory communication lines of an associated memory device in the master computer, and a one-way electronic door which is switchable to either a closed condition or a one-way open condition. With the door closed, communication lines between master computer memory (C1, C2...) and slave memory (S1, S2...) are blocked. In the one-way open condition invention, the memory communication lines or each slave memory means (S1, S2...) connect with the memory communication lines of its associated memory device (C1, C2...) in the master computer, and the memory devices (C1, C2...) of the master computer and slave card are electrically parallel such that information seen by the master's memory is also seen by the slave's memory. The slave card is also connectable to a switch for electronically removing the slave microprocessor from the system. With the master computer and the slave card in programming mode relationship, and the slave microprocessor electronically removed from the system, loading a program in the memory devices (C1, C2...) of the master accomplishes a parallel loading into the memory devices (S1, S2...) of the slave.
Characteristics of Radio-Frequency Circuits Utilizing Ferroelectric Capacitors
NASA Technical Reports Server (NTRS)
Eskridge, Michael; Gui, Xiao; MacLeod, Todd; Ho, Fat D.
2011-01-01
Ferroelectric capacitors, most commonly used in memory circuits and variable components, were studied in simple analog radio-frequency circuits such as the RLC resonator and Colpitts oscillator. The goal was to characterize the RF circuits in terms of frequency of oscillation, gain, etc, using ferroelectric capacitors. Frequencies of oscillation of both circuits were measured and studied a more accurate resonant frequency can be obtained using the ferroelectric capacitors. Many experiments were conducted and data collected. A model to simulate the experimental results will be developed. Discrepancies in gain and frequency in these RF circuits when conventional capacitors are replaced with ferroelectric ones were studied. These results will enable circuit designers to anticipate the effects of using ferroelectric components in their radio- frequency applications.
Song, Tianqi; Garg, Sudhanshu; Mokhtar, Reem; Bui, Hieu; Reif, John
2018-01-19
A main goal in DNA computing is to build DNA circuits to compute designated functions using a minimal number of DNA strands. Here, we propose a novel architecture to build compact DNA strand displacement circuits to compute a broad scope of functions in an analog fashion. A circuit by this architecture is composed of three autocatalytic amplifiers, and the amplifiers interact to perform computation. We show DNA circuits to compute functions sqrt(x), ln(x) and exp(x) for x in tunable ranges with simulation results. A key innovation in our architecture, inspired by Napier's use of logarithm transforms to compute square roots on a slide rule, is to make use of autocatalytic amplifiers to do logarithmic and exponential transforms in concentration and time. In particular, we convert from the input that is encoded by the initial concentration of the input DNA strand, to time, and then back again to the output encoded by the concentration of the output DNA strand at equilibrium. This combined use of strand-concentration and time encoding of computational values may have impact on other forms of molecular computation.
A Visual-Cue-Dependent Memory Circuit for Place Navigation.
Qin, Han; Fu, Ling; Hu, Bo; Liao, Xiang; Lu, Jian; He, Wenjing; Liang, Shanshan; Zhang, Kuan; Li, Ruijie; Yao, Jiwei; Yan, Junan; Chen, Hao; Jia, Hongbo; Zott, Benedikt; Konnerth, Arthur; Chen, Xiaowei
2018-06-05
The ability to remember and to navigate to safe places is necessary for survival. Place navigation is known to involve medial entorhinal cortex (MEC)-hippocampal connections. However, learning-dependent changes in neuronal activity in the distinct circuits remain unknown. Here, by using optic fiber photometry in freely behaving mice, we discovered the experience-dependent induction of a persistent-task-associated (PTA) activity. This PTA activity critically depends on learned visual cues and builds up selectively in the MEC layer II-dentate gyrus, but not in the MEC layer III-CA1 pathway, and its optogenetic suppression disrupts navigation to the target location. The findings suggest that the visual system, the MEC layer II, and the dentate gyrus are essential hubs of a memory circuit for visually guided navigation. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Suzuki, Daisuke; Hanyu, Takahiro
2018-04-01
A magnetic-tunnel-junction (MTJ)-oriented nonvolatile lookup table (LUT) circuit, in which a low-power data-shift function is performed by minimizing the number of write operations in MTJ devices is proposed. The permutation of the configuration memory cell for read/write access is performed as opposed to conventional direct data shifting to minimize the number of write operations, which results in significant write energy savings in the data-shift function. Moreover, the hardware cost of the proposed LUT circuit is small since the selector is shared between read access and write access. In fact, the power consumption in the data-shift function and the transistor count are reduced by 82 and 52%, respectively, compared with those in a conventional static random-access memory-based implementation using a 90 nm CMOS technology.
Ophir, Alexander G.
2017-01-01
The role of memory in mating systems is often neglected despite the fact that most mating systems are defined in part by how animals use space. Monogamy, for example, is usually characterized by affiliative (e.g., pairbonding) and defensive (e.g., mate guarding) behaviors, but a high degree of spatial overlap in home range use is the easiest defining feature of monogamous animals in the wild. The nonapeptides vasopressin and oxytocin have been the focus of much attention for their importance in modulating social behavior, however this work has largely overshadowed their roles in learning and memory. To date, the understanding of memory systems and mechanisms governing social behavior have progressed relatively independently. Bridging these two areas will provide a deeper appreciation for understanding behavior, and in particular the mechanisms that mediate reproductive decision-making. Here, I argue that the ability to mate effectively as monogamous individuals is linked to the ability to track conspecifics in space. I discuss the connectivity across some well-known social and spatial memory nuclei, and propose that the nonapeptide receptors within these structures form a putative “socio-spatial memory neural circuit.” This purported circuit may function to integrate social and spatial information to shape mating decisions in a context-dependent fashion. The lateral septum and/or the nucleus accumbens, and neuromodulation therein, may act as an intermediary to relate socio-spatial information with social behavior. Identifying mechanisms responsible for relating information about the social world with mechanisms mediating mating tactics is crucial to fully appreciate the suite of factors driving reproductive decisions and social decision-making. PMID:28744194
Grossberg, Stephen
2015-09-24
This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory. Copyright © 2014 Elsevier B.V. All rights reserved.
Fournier, Neil M; Botterill, Justin J; Marks, Wendie N; Guskjolen, Axel J; Kalynchuk, Lisa E
2013-06-01
Epileptic seizures increase the birth of new neurons in the adult hippocampus. Although the consequences of aberrant neurogenesis on behavior are not fully understood, one hypothesis is that seizure-generated neurons might form faulty circuits that disrupt hippocampal functions, such as learning and memory. In the present study, we employed long-term amygdala kindling (i.e., rats receive 99-electrical stimulations) to examine the effect of repeated seizures on hippocampal neurogenesis and behavior. We labeled seizure-generated cells with the proliferation marker BrdU after 30-stimulations and continued kindling for an additional 4weeks to allow newborn neurons to mature under conditions of repeated seizures. After kindling was complete, rats were tested in a trace fear conditioning task and sacrificed 2h later to examine if 4-week old newborn cells were recruited into circuits involved in the retrieval of emotional memory. Compared to non-kindled controls, long-term kindled rats showed significant impairments in fear memory reflected in a decrease in conditioned freezing to both tone and contextual cues during testing. Moreover, long-term kindling also prevented the activation of 4-week old newborn cells in response to fear memory retrieval. These results indicate that the presence of seizure activity during cell maturation impedes the ability of new neurons to integrate properly into circuits important in memory formation. Together, our findings suggest that aberrant seizure-induced neurogenesis might contribute to the development of learning impairments in chronic epilepsy and raise the possibility that targeting the reduced activation of adult born neurons could represent a beneficial strategy to reverse cognitive deficits in some epileptic patients. Copyright © 2012 Elsevier Inc. All rights reserved.
Ohki-Hamazaki, Hiroko
2012-06-01
Imprinting is an example of learning and memory acquisition in infancy. In the case of precocial birds, such as geese, ducks, and chickens, the baby birds learn the characteristics of the first moving object that they see within a critical period, and they imprint on it and follow it around. We analyzed the neural basis of this behavior in order to understand the neural mechanism of learning and memory in infancy. Information pertaining to a visual imprinting stimulus is recognized and processed in the visual Wulst, a region that corresponds to the mammalian visual cortex. It is then transmitted to the posterior region of the telencephalon, followed by the core region of the hyperpallium densocellulare (HDCo), periventricular region of the hyperpallium densocellulare (HDPe), and finally, the intermediate medial mesopallium (IMM), a region similar to the mammalian association cortex. Memory is stored in the IMM. After imprint training, plastic changes are observed in the visual Wulst as well as in the neurons of this circuit. HDCo cells, located at the center of this circuit, express N-methyl-D-aspartate (NMDA) receptors containing the NMDA receptor (NR) 2B subunit; the expression of this receptor increased after the imprint training. Inhibition of this receptor in the cells of the HDCo region leads to failure of imprinting and inactivation of this circuit. Thus, NMDA receptors bearing the NR2B subunit play a critical role in plastic changes in this circuit and in induction of imprinting.
Laviolette, Steven R
2007-07-01
The neural regulation of emotional perception, learning, and memory is essential for normal behavioral and cognitive functioning. Many of the symptoms displayed by individuals with schizophrenia may arise from fundamental disturbances in the ability to accurately process emotionally salient sensory information. The neurotransmitter dopamine (DA) and its ability to modulate neural regions involved in emotional learning, perception, and memory formation has received considerable research attention as a potential final common pathway to account for the aberrant emotional regulation and psychosis present in the schizophrenic syndrome. Evidence from both human neuroimaging studies and animal-based research using neurodevelopmental, behavioral, and electrophysiological techniques have implicated the mesocorticolimbic DA circuit as a crucial system for the encoding and expression of emotionally salient learning and memory formation. While many theories have examined the cortical-subcortical interactions between prefrontal cortical regions and subcortical DA substrates, many questions remain as to how DA may control emotional perception and learning and how disturbances linked to DA abnormalities may underlie the disturbed emotional processing in schizophrenia. Beyond the mesolimbic DA system, increasing evidence points to the amygdala-prefrontal cortical circuit as an important processor of emotionally salient information and how neurodevelopmental perturbances within this circuitry may lead to dysregulation of DAergic modulation of emotional processing and learning along this cortical-subcortical emotional processing circuit.
Spatial part-set cuing facilitation.
Kelley, Matthew R; Parasiuk, Yuri; Salgado-Benz, Jennifer; Crocco, Megan
2016-07-01
Cole, Reysen, and Kelley [2013. Part-set cuing facilitation for spatial information. Journal of Experimental Psychology: Learning, Memory, & Cognition, 39, 1615-1620] reported robust part-set cuing facilitation for spatial information using snap circuits (a colour-coded electronics kit designed for children to create rudimentary circuit boards). In contrast, Drinkwater, Dagnall, and Parker [2006. Effects of part-set cuing on experienced and novice chess players' reconstruction of a typical chess midgame position. Perceptual and Motor Skills, 102(3), 645-653] and Watkins, Schwartz, and Lane [1984. Does part-set cuing test for memory organization? Evidence from reconstructions of chess positions. Canadian Journal of Psychology/Revue Canadienne de Psychologie, 38(3), 498-503] showed no influence of part-set cuing for spatial information when using chess boards. One key difference between the two procedures was that the snap circuit stimuli were explicitly connected to one another, whereas chess pieces were not. Two experiments examined the effects of connection type (connected vs. unconnected) and cue type (cued vs. uncued) on memory for spatial information. Using chess boards (Experiment 1) and snap circuits (Experiment 2), part-set cuing facilitation only occurred when the stimuli were explicitly connected; there was no influence of cuing with unconnected stimuli. These results are potentially consistent with the retrieval strategy disruption hypothesis, as well as the two- and three-mechanism accounts of part-set cuing.
ERIC Educational Resources Information Center
Hochstadt, Jesse; Nakano, Hiroko; Lieberman, Philip; Friedman, Joseph
2006-01-01
Studies of sentence comprehension deficits in Parkinson's disease (PD) patients suggest that language processing involves circuits connecting subcortical and cortical regions. Anatomically segregated neural circuits appear to support different cognitive and motor functions. To investigate which functions are implicated in PD comprehension…
Universal programmable quantum circuit schemes to emulate an operator
DOE Office of Scientific and Technical Information (OSTI.GOV)
Daskin, Anmer; Grama, Ananth; Kollias, Giorgos
Unlike fixed designs, programmable circuit designs support an infinite number of operators. The functionality of a programmable circuit can be altered by simply changing the angle values of the rotation gates in the circuit. Here, we present a new quantum circuit design technique resulting in two general programmable circuit schemes. The circuit schemes can be used to simulate any given operator by setting the angle values in the circuit. This provides a fixed circuit design whose angles are determined from the elements of the given matrix-which can be non-unitary-in an efficient way. We also give both the classical and quantummore » complexity analysis for these circuits and show that the circuits require a few classical computations. For the electronic structure simulation on a quantum computer, one has to perform the following steps: prepare the initial wave function of the system; present the evolution operator U=e{sup -iHt} for a given atomic and molecular Hamiltonian H in terms of quantum gates array and apply the phase estimation algorithm to find the energy eigenvalues. Thus, in the circuit model of quantum computing for quantum chemistry, a crucial step is presenting the evolution operator for the atomic and molecular Hamiltonians in terms of quantum gate arrays. Since the presented circuit designs are independent from the matrix decomposition techniques and the global optimization processes used to find quantum circuits for a given operator, high accuracy simulations can be done for the unitary propagators of molecular Hamiltonians on quantum computers. As an example, we show how to build the circuit design for the hydrogen molecule.« less
Computer-aided engineering of semiconductor integrated circuits
NASA Astrophysics Data System (ADS)
Meindl, J. D.; Dutton, R. W.; Gibbons, J. F.; Helms, C. R.; Plummer, J. D.; Tiller, W. A.; Ho, C. P.; Saraswat, K. C.; Deal, B. E.; Kamins, T. I.
1980-07-01
Economical procurement of small quantities of high performance custom integrated circuits for military systems is impeded by inadequate process, device and circuit models that handicap low cost computer aided design. The principal objective of this program is to formulate physical models of fabrication processes, devices and circuits to allow total computer-aided design of custom large-scale integrated circuits. The basic areas under investigation are (1) thermal oxidation, (2) ion implantation and diffusion, (3) chemical vapor deposition of silicon and refractory metal silicides, (4) device simulation and analytic measurements. This report discusses the fourth year of the program.
Digital circuits for computer applications: A compilation
NASA Technical Reports Server (NTRS)
1972-01-01
The innovations in this updated series of compilations dealing with electronic technology represent a carefully selected collection of digital circuits which have direct application in computer oriented systems. In general, the circuits have been selected as representative items of each section and have been included on their merits of having universal applications in digital computers and digital data processing systems. As such, they should have wide appeal to the professional engineer and scientist who encounter the fundamentals of digital techniques in their daily activities. The circuits are grouped as digital logic circuits, analog to digital converters, and counters and shift registers.
Electromagnetic Compatibility Design of the Computer Circuits
NASA Astrophysics Data System (ADS)
Zitai, Hong
2018-02-01
Computers and the Internet have gradually penetrated into every aspect of people’s daily work. But with the improvement of electronic equipment as well as electrical system, the electromagnetic environment becomes much more complex. Electromagnetic interference has become an important factor to hinder the normal operation of electronic equipment. In order to analyse the computer circuit compatible with the electromagnetic compatibility, this paper starts from the computer electromagnetic and the conception of electromagnetic compatibility. And then, through the analysis of the main circuit and system of computer electromagnetic compatibility problems, we can design the computer circuits in term of electromagnetic compatibility. Finally, the basic contents and methods of EMC test are expounded in order to ensure the electromagnetic compatibility of equipment.
47 CFR 15.32 - Test procedures for CPU boards and computer power supplies.
Code of Federal Regulations, 2011 CFR
2011-10-01
... result in a complete personal computer system. If the oscillator and the microprocessor circuits are... microprocessor circuits are contained on separate circuit boards, both boards, typical of the combination that...
47 CFR 15.32 - Test procedures for CPU boards and computer power supplies.
Code of Federal Regulations, 2013 CFR
2013-10-01
... result in a complete personal computer system. If the oscillator and the microprocessor circuits are... microprocessor circuits are contained on separate circuit boards, both boards, typical of the combination that...
47 CFR 15.32 - Test procedures for CPU boards and computer power supplies.
Code of Federal Regulations, 2014 CFR
2014-10-01
... result in a complete personal computer system. If the oscillator and the microprocessor circuits are... microprocessor circuits are contained on separate circuit boards, both boards, typical of the combination that...
47 CFR 15.32 - Test procedures for CPU boards and computer power supplies.
Code of Federal Regulations, 2012 CFR
2012-10-01
... result in a complete personal computer system. If the oscillator and the microprocessor circuits are... microprocessor circuits are contained on separate circuit boards, both boards, typical of the combination that...
47 CFR 15.32 - Test procedures for CPU boards and computer power supplies.
Code of Federal Regulations, 2010 CFR
2010-10-01
... result in a complete personal computer system. If the oscillator and the microprocessor circuits are... microprocessor circuits are contained on separate circuit boards, both boards, typical of the combination that...
Method and apparatus for managing access to a memory
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeBenedictis, Erik
A method and apparatus for managing access to a memory of a computing system. A controller transforms a plurality of operations that represent a computing job into an operational memory layout that reduces a size of a selected portion of the memory that needs to be accessed to perform the computing job. The controller stores the operational memory layout in a plurality of memory cells within the selected portion of the memory. The controller controls a sequence by which a processor in the computing system accesses the memory to perform the computing job using the operational memory layout. The operationalmore » memory layout reduces an amount of energy consumed by the processor to perform the computing job.« less
A programming language for composable DNA circuits
Phillips, Andrew; Cardelli, Luca
2009-01-01
Recently, a range of information-processing circuits have been implemented in DNA by using strand displacement as their main computational mechanism. Examples include digital logic circuits and catalytic signal amplification circuits that function as efficient molecular detectors. As new paradigms for DNA computation emerge, the development of corresponding languages and tools for these paradigms will help to facilitate the design of DNA circuits and their automatic compilation to nucleotide sequences. We present a programming language for designing and simulating DNA circuits in which strand displacement is the main computational mechanism. The language includes basic elements of sequence domains, toeholds and branch migration, and assumes that strands do not possess any secondary structure. The language is used to model and simulate a variety of circuits, including an entropy-driven catalytic gate, a simple gate motif for synthesizing large-scale circuits and a scheme for implementing an arbitrary system of chemical reactions. The language is a first step towards the design of modelling and simulation tools for DNA strand displacement, which complements the emergence of novel implementation strategies for DNA computing. PMID:19535415
A programming language for composable DNA circuits.
Phillips, Andrew; Cardelli, Luca
2009-08-06
Recently, a range of information-processing circuits have been implemented in DNA by using strand displacement as their main computational mechanism. Examples include digital logic circuits and catalytic signal amplification circuits that function as efficient molecular detectors. As new paradigms for DNA computation emerge, the development of corresponding languages and tools for these paradigms will help to facilitate the design of DNA circuits and their automatic compilation to nucleotide sequences. We present a programming language for designing and simulating DNA circuits in which strand displacement is the main computational mechanism. The language includes basic elements of sequence domains, toeholds and branch migration, and assumes that strands do not possess any secondary structure. The language is used to model and simulate a variety of circuits, including an entropy-driven catalytic gate, a simple gate motif for synthesizing large-scale circuits and a scheme for implementing an arbitrary system of chemical reactions. The language is a first step towards the design of modelling and simulation tools for DNA strand displacement, which complements the emergence of novel implementation strategies for DNA computing.
Logic circuits based on molecular spider systems.
Mo, Dandan; Lakin, Matthew R; Stefanovic, Darko
2016-08-01
Spatial locality brings the advantages of computation speed-up and sequence reuse to molecular computing. In particular, molecular walkers that undergo localized reactions are of interest for implementing logic computations at the nanoscale. We use molecular spider walkers to implement logic circuits. We develop an extended multi-spider model with a dynamic environment wherein signal transmission is triggered via localized reactions, and use this model to implement three basic gates (AND, OR, NOT) and a cascading mechanism. We develop an algorithm to automatically generate the layout of the circuit. We use a kinetic Monte Carlo algorithm to simulate circuit computations, and we analyze circuit complexity: our design scales linearly with formula size and has a logarithmic time complexity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Analog Delta-Back-Propagation Neural-Network Circuitry
NASA Technical Reports Server (NTRS)
Eberhart, Silvio
1990-01-01
Changes in synapse weights due to circuit drifts suppressed. Proposed fully parallel analog version of electronic neural-network processor based on delta-back-propagation algorithm. Processor able to "learn" when provided with suitable combinations of inputs and enforced outputs. Includes programmable resistive memory elements (corresponding to synapses), conductances (synapse weights) adjusted during learning. Buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in layers of electronic neurons in accordance with delta-back-propagation algorithm.
Dissecting neural pathways for forgetting in Drosophila olfactory aversive memory
Shuai, Yichun; Hirokawa, Areekul; Ai, Yulian; Zhang, Min; Li, Wanhe; Zhong, Yi
2015-01-01
Recent studies have identified molecular pathways driving forgetting and supported the notion that forgetting is a biologically active process. The circuit mechanisms of forgetting, however, remain largely unknown. Here we report two sets of Drosophila neurons that account for the rapid forgetting of early olfactory aversive memory. We show that inactivating these neurons inhibits memory decay without altering learning, whereas activating them promotes forgetting. These neurons, including a cluster of dopaminergic neurons (PAM-β′1) and a pair of glutamatergic neurons (MBON-γ4>γ1γ2), terminate in distinct subdomains in the mushroom body and represent parallel neural pathways for regulating forgetting. Interestingly, although activity of these neurons is required for memory decay over time, they are not required for acute forgetting during reversal learning. Our results thus not only establish the presence of multiple neural pathways for forgetting in Drosophila but also suggest the existence of diverse circuit mechanisms of forgetting in different contexts. PMID:26627257
Large-area, flexible imaging arrays constructed by light-charge organic memories
Zhang, Lei; Wu, Ti; Guo, Yunlong; Zhao, Yan; Sun, Xiangnan; Wen, Yugeng; Yu, Gui; Liu, Yunqi
2013-01-01
Existing organic imaging circuits, which offer attractive benefits of light weight, low cost and flexibility, are exclusively based on phototransistor or photodiode arrays. One shortcoming of these photo-sensors is that the light signal should keep invariant throughout the whole pixel-addressing and reading process. As a feasible solution, we synthesized a new charge storage molecule and embedded it into a device, which we call light-charge organic memory (LCOM). In LCOM, the functionalities of photo-sensor and non-volatile memory are integrated. Thanks to the deliberate engineering of electronic structure and self-organization process at the interface, 92% of the stored charges, which are linearly controlled by the quantity of light, retain after 20000 s. The stored charges can also be non-destructively read and erased by a simple voltage program. These results pave the way to large-area, flexible imaging circuits and demonstrate a bright future of small molecular materials in non-volatile memory. PMID:23326636
Plasticity in single neuron and circuit computations
NASA Astrophysics Data System (ADS)
Destexhe, Alain; Marder, Eve
2004-10-01
Plasticity in neural circuits can result from alterations in synaptic strength or connectivity, as well as from changes in the excitability of the neurons themselves. To better understand the role of plasticity in the brain, we need to establish how brain circuits work and the kinds of computations that different circuit structures achieve. By linking theoretical and experimental studies, we are beginning to reveal the consequences of plasticity mechanisms for network dynamics, in both simple invertebrate circuits and the complex circuits of mammalian cerebral cortex.
Marvel, Cherie L; Faulkner, Monica L; Strain, Eric C; Mintzer, Miriam Z; Desmond, John E
2012-03-01
Working memory is impaired in opioid-dependent individuals, yet the neural underpinnings of working memory in this population are largely unknown. Previous studies in healthy adults have demonstrated that working memory is supported by a network of brain regions that includes a cerebro-cerebellar circuit. The cerebellum, in particular, may be important for inner speech mechanisms that assist verbal working memory. This study used functional magnetic resonance imaging to examine brain activity associated with working memory in five opioid-dependent, methadone-maintained patients and five matched, healthy controls. An item recognition task was administered in two conditions: (1) a low working memory load "match" condition in which participants determined whether target letters presented at the beginning of the trial matched a probe item, and (2) a high working memory load "manipulation" condition in which participants counted two alphabetical letters forward of each of the targets and determined whether either of these new items matched a probe item. Response times and accuracy scores were not significantly different between the groups. FMRI analyses indicated that, in association with higher working memory load ("manipulation" condition), the patient group exhibited hyperactivity in the superior and inferior cerebellum and amygdala relative to that of controls. At a more liberal statistical threshold, patients exhibited hypoactivity in the left prefrontal and medial frontal/pre-SMA regions. These results indicate that verbal working memory in opioid-dependent individuals involves a disrupted cerebro-cerebellar circuit and shed light on the neuroanatomical basis of working memory impairments in this population.
Marvel, Cherie L.; Faulkner, Monica L.; Strain, Eric C.; Mintzer, Miriam Z.; Desmond, John E.
2011-01-01
Working memory is impaired in opioid-dependent individuals, yet the neural underpinnings of working memory in this population are largely unknown. Previous studies in healthy adults have demonstrated that working memory is supported by a network of brain regions that includes a cerebro-cerebellar circuit. The cerebellum, in particular, may be important for inner speech mechanisms that assist verbal working memory. This study used functional magnetic resonance imaging (fMRI) to examine brain activity associated with working memory in 5 opioid-dependent, methadone-maintained patients and 5 matched, healthy controls. An item recognition task was administered in two conditions: 1) a low working memory load “match” condition in which participants determined whether target letters presented at the beginning of the trial matched a probe item, and 2) a high working memory load “manipulation” condition in which participants counted two alphabetical letters forward of each of the targets and determined whether either of these new items matched a probe item. Response times and accuracy scores were not significantly different between the groups. FMRI analyses indicated that, in association with higher working memory load (“manipulation” condition), the patient group exhibited hyperactivity in the superior and inferior cerebellum and amygdala relative to that of controls. At a more liberal statistical threshold, patients exhibited hypoactivity in the left prefrontal and medial frontal/pre-SMA regions. These results indicate that verbal working memory in opioid-dependent individuals involves a disrupted cerebro-cerebellar circuit, and shed light on the neuroanatomical basis of working memory impairments in this population. PMID:21892700
Winters, Boyer D; Tucci, Mark C; Jacklin, Derek L; Reid, James M; Newsome, James
2011-11-30
Research has implicated the perirhinal cortex (PRh) in several aspects of object recognition memory. The specific role of the hippocampus (HPC) remains controversial, but its involvement in object recognition may pertain to processing contextual information in relation to objects rather than object representation per se. Here we investigated the roles of the PRh and HPC in object memory reconsolidation using the spontaneous object recognition task for rats. Intra-PRh infusions of the protein synthesis inhibitor anisomycin immediately following memory reactivation prevented object memory reconsolidation. Similar deficits were observed when a novel object or a salient contextual change was introduced during the reactivation phase. Intra-HPC infusions of anisomycin, however, blocked object memory reconsolidation only when a contextual change was introduced during reactivation. Moreover, disrupting functional interaction between the HPC and PRh by infusing anisomycin unilaterally into each structure in opposite hemispheres also impaired reconsolidation when reactivation was done in an altered context. These results show for the first time that the PRh is critical for reconsolidation of object memory traces and provide insight into the dynamic process of object memory storage; the selective requirement for hippocampal involvement following reactivation in an altered context suggests a substantial circuit level object trace reorganization whereby an initially PRh-dependent object memory becomes reliant on both the HPC and PRh and their interaction. Such trace reorganization may play a central role in reconsolidation-mediated memory updating and could represent an important aspect of lingering consolidation processes proposed to underlie long-term memory modulation and stabilization.
Cortical travelling waves: mechanisms and computational principles
Muller, Lyle; Chavane, Frédéric; Reynolds, John
2018-01-01
Multichannel recording technologies have revealed travelling waves of neural activity in multiple sensory, motor and cognitive systems. These waves can be spontaneously generated by recurrent circuits or evoked by external stimuli. They travel along brain networks at multiple scales, transiently modulating spiking and excitability as they pass. Here, we review recent experimental findings that have found evidence for travelling waves at single-area (mesoscopic) and whole-brain (macroscopic) scales. We place these findings in the context of the current theoretical understanding of wave generation and propagation in recurrent networks. During the large low-frequency rhythms of sleep or the relatively desynchronized state of the awake cortex, travelling waves may serve a variety of functions, from long-term memory consolidation to processing of dynamic visual stimuli. We explore new avenues for experimental and computational understanding of the role of spatiotemporal activity patterns in the cortex. PMID:29563572
Nanoelectronics: Opportunities for future space applications
NASA Technical Reports Server (NTRS)
Frazier, Gary
1995-01-01
Further improvements in the performance of integrated electronics will eventually halt due to practical fundamental limits on our ability to downsize transistors and interconnect wiring. Avoiding these limits requires a revolutionary approach to switching device technology and computing architecture. Nanoelectronics, the technology of exploiting physics on the nanometer scale for computation and communication, attempts to avoid conventional limits by developing new approaches to switching, circuitry, and system integration. This presentation overviews the basic principles that operate on the nanometer scale that can be assembled into practical devices and circuits. Quantum resonant tunneling (RT) is used as the center-piece of the overview since RT devices already operate at high temperature (120 degrees C) and can be scaled, in principle, to a few nanometers in semiconductors. Near- and long-term applications of GaAs and silicon quantum devices are suggested for signal and information processing, memory, optoelectronics, and radio frequency (RF) communication.
Method of pedestal and common-mode noise correction for switched-capacitor analog memories
Britton, Charles L.
1997-01-01
A method and apparatus for correcting common-mode noise and pedestal noise in a multichannel array of switched-capacitor analog memories wherein each analog memory is connected to an associated analog-to-digital converter. The apparatus comprises a single differential element in two different embodiments. In a first embodiment, the differential element is a reference analog memory connected to a buffer. In the second embodiment, the differential dement is a reference analog memory connected to a reference analog-to-digital connected to an array of digital summing circuits.
Method of pedestal and common-mode noise correction for switched-capacitor analog memories
Britton, Charles L.
1996-01-01
A method and apparatus for correcting common-mode noise and pedestal noise in a multichannel array of switched-capacitor analog memories wherein each analog memory is connected to an associated analog-to-digital converter. The apparatus comprises a single differential element in two different embodiments. In a first embodiment, the differential element is a reference analog memory connected to a buffer. In the second embodiment, the differential element is a reference analog memory connected to a reference analog-to-digital connected to an array of digital summing circuits.
Non-unitary probabilistic quantum computing circuit and method
NASA Technical Reports Server (NTRS)
Williams, Colin P. (Inventor); Gingrich, Robert M. (Inventor)
2009-01-01
A quantum circuit performing quantum computation in a quantum computer. A chosen transformation of an initial n-qubit state is probabilistically obtained. The circuit comprises a unitary quantum operator obtained from a non-unitary quantum operator, operating on an n-qubit state and an ancilla state. When operation on the ancilla state provides a success condition, computation is stopped. When operation on the ancilla state provides a failure condition, computation is performed again on the ancilla state and the n-qubit state obtained in the previous computation, until a success condition is obtained.
Memristor-based cellular nonlinear/neural network: design, analysis, and applications.
Duan, Shukai; Hu, Xiaofang; Dong, Zhekang; Wang, Lidan; Mazumder, Pinaki
2015-06-01
Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predicted in the late seventies, but it garnered nascent research interest due to the recent much-acclaimed discovery of nanocrossbar memories by engineers at the Hewlett-Packard Laboratory. The memristor is expected to be co-integrated with nanoscale CMOS technology to revolutionize conventional von Neumann as well as neuromorphic computing. In this paper, a compact CNN model based on memristors is presented along with its performance analysis and applications. In the new CNN design, the memristor bridge circuit acts as the synaptic circuit element and substitutes the complex multiplication circuit used in traditional CNN architectures. In addition, the negative differential resistance and nonlinear current-voltage characteristics of the memristor have been leveraged to replace the linear resistor in conventional CNNs. The proposed CNN design has several merits, for example, high density, nonvolatility, and programmability of synaptic weights. The proposed memristor-based CNN design operations for implementing several image processing functions are illustrated through simulation and contrasted with conventional CNNs. Monte-Carlo simulation has been used to demonstrate the behavior of the proposed CNN due to the variations in memristor synaptic weights.
Superior model for fault tolerance computation in designing nano-sized circuit systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Singh, N. S. S., E-mail: narinderjit@petronas.com.my; Muthuvalu, M. S., E-mail: msmuthuvalu@gmail.com; Asirvadam, V. S., E-mail: vijanth-sagayan@petronas.com.my
2014-10-24
As CMOS technology scales nano-metrically, reliability turns out to be a decisive subject in the design methodology of nano-sized circuit systems. As a result, several computational approaches have been developed to compute and evaluate reliability of desired nano-electronic circuits. The process of computing reliability becomes very troublesome and time consuming as the computational complexity build ups with the desired circuit size. Therefore, being able to measure reliability instantly and superiorly is fast becoming necessary in designing modern logic integrated circuits. For this purpose, the paper firstly looks into the development of an automated reliability evaluation tool based on the generalizationmore » of Probabilistic Gate Model (PGM) and Boolean Difference-based Error Calculator (BDEC) models. The Matlab-based tool allows users to significantly speed-up the task of reliability analysis for very large number of nano-electronic circuits. Secondly, by using the developed automated tool, the paper explores into a comparative study involving reliability computation and evaluation by PGM and, BDEC models for different implementations of same functionality circuits. Based on the reliability analysis, BDEC gives exact and transparent reliability measures, but as the complexity of the same functionality circuits with respect to gate error increases, reliability measure by BDEC tends to be lower than the reliability measure by PGM. The lesser reliability measure by BDEC is well explained in this paper using distribution of different signal input patterns overtime for same functionality circuits. Simulation results conclude that the reliability measure by BDEC depends not only on faulty gates but it also depends on circuit topology, probability of input signals being one or zero and also probability of error on signal lines.« less
Unifying Gate Synthesis and Magic State Distillation.
Campbell, Earl T; Howard, Mark
2017-02-10
The leading paradigm for performing a computation on quantum memories can be encapsulated as distill-then-synthesize. Initially, one performs several rounds of distillation to create high-fidelity magic states that provide one good T gate, an essential quantum logic gate. Subsequently, gate synthesis intersperses many T gates with Clifford gates to realize a desired circuit. We introduce a unified framework that implements one round of distillation and multiquibit gate synthesis in a single step. Typically, our method uses the same number of T gates as conventional synthesis but with the added benefit of quadratic error suppression. Because of this, one less round of magic state distillation needs to be performed, leading to significant resource savings.
Analog Computation by DNA Strand Displacement Circuits.
Song, Tianqi; Garg, Sudhanshu; Mokhtar, Reem; Bui, Hieu; Reif, John
2016-08-19
DNA circuits have been widely used to develop biological computing devices because of their high programmability and versatility. Here, we propose an architecture for the systematic construction of DNA circuits for analog computation based on DNA strand displacement. The elementary gates in our architecture include addition, subtraction, and multiplication gates. The input and output of these gates are analog, which means that they are directly represented by the concentrations of the input and output DNA strands, respectively, without requiring a threshold for converting to Boolean signals. We provide detailed domain designs and kinetic simulations of the gates to demonstrate their expected performance. On the basis of these gates, we describe how DNA circuits to compute polynomial functions of inputs can be built. Using Taylor Series and Newton Iteration methods, functions beyond the scope of polynomials can also be computed by DNA circuits built upon our architecture.
NASA Technical Reports Server (NTRS)
Egebrecht, R. A.; Thorbjornsen, A. R.
1967-01-01
Digital computer programs determine steady-state performance characteristics of active and passive linear circuits. The ac analysis program solves the basic circuit parameters. The compiler program solves these circuit parameters and in addition provides a more versatile program by allowing the user to perform mathematical and logical operations.
Demonstration of a neural circuit critical for imprinting behavior in chicks.
Nakamori, Tomoharu; Sato, Katsushige; Atoji, Yasuro; Kanamatsu, Tomoyuki; Tanaka, Kohichi; Ohki-Hamazaki, Hiroko
2010-03-24
Imprinting behavior in birds is elicited by visual and/or auditory cues. It has been demonstrated previously that visual cues are recognized and processed in the visual Wulst (VW), and imprinting memory is stored in the intermediate medial mesopallium (IMM) of the telencephalon. Alteration of neural responses in these two regions according to imprinting has been reported, yet direct evidence of the neural circuit linking these two regions is lacking. Thus, it remains unclear how memory is formed and expressed in this circuit. Here, we present anatomical as well as physiological evidence of the neural circuit connecting the VW and IMM and show that imprinting training during the critical period strengthens and refines this circuit. A functional connection established by imprint training resulted in an imprinting behavior. After the closure of the critical period, training could not activate this circuit nor induce the imprinting behavior. Glutamatergic neurons in the ventroposterior region of the VW, the core region of the hyperpallium densocellulare (HDCo), sent their axons to the periventricular part of the HD, just dorsal and afferent to the IMM. We found that the HDCo is important in imprinting behavior. The refinement and/or enhancement of this neural circuit are attributed to increased activity of HDCo cells, and the activity depended on NR2B-containing NMDA receptors. These findings show a neural connection in the telencephalon in Aves and demonstrate that NR2B function is indispensable for the plasticity of HDCo cells, which are key mediators of imprinting.
Parallel basal ganglia circuits for decision making.
Hikosaka, Okihide; Ghazizadeh, Ali; Griggs, Whitney; Amita, Hidetoshi
2018-03-01
The basal ganglia control body movements, mainly, based on their values. Critical for this mechanism is dopamine neurons, which sends unpredicted value signals, mainly, to the striatum. This mechanism enables animals to change their behaviors flexibly, eventually choosing a valuable behavior. However, this may not be the best behavior, because the flexible choice is focused on recent, and, therefore, limited, experiences (i.e., short-term memories). Our old and recent studies suggest that the basal ganglia contain separate circuits that process value signals in a completely different manner. They are insensitive to recent changes in value, yet gradually accumulate the value of each behavior (i.e., movement or object choice). These stable circuits eventually encode values of many behaviors and then retain the value signals for a long time (i.e., long-term memories). They are innervated by a separate group of dopamine neurons that retain value signals, even when no reward is predicted. Importantly, the stable circuits can control motor behaviors (e.g., hand or eye) quickly and precisely, which allows animals to automatically acquire valuable outcomes based on historical life experiences. These behaviors would be called 'skills', which are crucial for survival. The stable circuits are localized in the posterior part of the basal ganglia, separately from the flexible circuits located in the anterior part. To summarize, the flexible and stable circuits in the basal ganglia, working together but independently, enable animals (and humans) to reach valuable goals in various contexts.
The Science of Computing: Virtual Memory
NASA Technical Reports Server (NTRS)
Denning, Peter J.
1986-01-01
In the March-April issue, I described how a computer's storage system is organized as a hierarchy consisting of cache, main memory, and secondary memory (e.g., disk). The cache and main memory form a subsystem that functions like main memory but attains speeds approaching cache. What happens if a program and its data are too large for the main memory? This is not a frivolous question. Every generation of computer users has been frustrated by insufficient memory. A new line of computers may have sufficient storage for the computations of its predecessor, but new programs will soon exhaust its capacity. In 1960, a longrange planning committee at MIT dared to dream of a computer with 1 million words of main memory. In 1985, the Cray-2 was delivered with 256 million words. Computational physicists dream of computers with 1 billion words. Computer architects have done an outstanding job of enlarging main memories yet they have never kept up with demand. Only the shortsighted believe they can.
Electrically Variable Resistive Memory Devices
NASA Technical Reports Server (NTRS)
Liu, Shangqing; Wu, Nai-Juan; Ignatiev, Alex; Charlson, E. J.
2010-01-01
Nonvolatile electronic memory devices that store data in the form of electrical- resistance values, and memory circuits based on such devices, have been invented. These devices and circuits exploit an electrically-variable-resistance phenomenon that occurs in thin films of certain oxides that exhibit the colossal magnetoresistive (CMR) effect. It is worth emphasizing that, as stated in the immediately preceding article, these devices function at room temperature and do not depend on externally applied magnetic fields. A device of this type is basically a thin film resistor: it consists of a thin film of a CMR material located between, and in contact with, two electrical conductors. The application of a short-duration, low-voltage current pulse via the terminals changes the electrical resistance of the film. The amount of the change in resistance depends on the size of the pulse. The direction of change (increase or decrease of resistance) depends on the polarity of the pulse. Hence, a datum can be written (or a prior datum overwritten) in the memory device by applying a pulse of size and polarity tailored to set the resistance at a value that represents a specific numerical value. To read the datum, one applies a smaller pulse - one that is large enough to enable accurate measurement of resistance, but small enough so as not to change the resistance. In writing, the resistance can be set to any value within the dynamic range of the CMR film. Typically, the value would be one of several discrete resistance values that represent logic levels or digits. Because the number of levels can exceed 2, a memory device of this type is not limited to binary data. Like other memory devices, devices of this type can be incorporated into a memory integrated circuit by laying them out on a substrate in rows and columns, along with row and column conductors for electrically addressing them individually or collectively.
NASA Technical Reports Server (NTRS)
Carpenter, K. H.
1974-01-01
The design, construction, and test history of a 4096 word by 18 bit random access NDRO Plated Wire Memory for use in conjunction with a spacecraft input/output and central processing unit is reported. A technical and functional description is given along with diagrams illustrating layout and systems operation. Test data is shown on the procedures and results of system level and memory stack testing, and hybrid circuit screening. A comparison of the most significant physical and performance characteristics of the memory unit versus the specified requirements is also included.
Mixed-Mode Operation of Hybrid Phase-Change Nanophotonic Circuits.
Lu, Yegang; Stegmaier, Matthias; Nukala, Pavan; Giambra, Marco A; Ferrari, Simone; Busacca, Alessandro; Pernice, Wolfram H P; Agarwal, Ritesh
2017-01-11
Phase change materials (PCMs) are highly attractive for nonvolatile electrical and all-optical memory applications because of unique features such as ultrafast and reversible phase transitions, long-term endurance, and high scalability to nanoscale dimensions. Understanding their transient characteristics upon phase transition in both the electrical and the optical domains is essential for using PCMs in future multifunctional optoelectronic circuits. Here, we use a PCM nanowire embedded into a nanophotonic circuit to study switching dynamics in mixed-mode operation. Evanescent coupling between light traveling along waveguides and a phase-change nanowire enables reversible phase transition between amorphous and crystalline states. We perform time-resolved measurements of the transient change in both the optical transmission and resistance of the nanowire and show reversible switching operations in both the optical and the electrical domains. Our results pave the way toward on-chip multifunctional optoelectronic integrated devices, waveguide integrated memories, and hybrid processing applications.
Nanoelectronics from the bottom up.
Lu, Wei; Lieber, Charles M
2007-11-01
Electronics obtained through the bottom-up approach of molecular-level control of material composition and structure may lead to devices and fabrication strategies not possible with top-down methods. This review presents a brief summary of bottom-up and hybrid bottom-up/top-down strategies for nanoelectronics with an emphasis on memories based on the crossbar motif. First, we will discuss representative electromechanical and resistance-change memory devices based on carbon nanotube and core-shell nanowire structures, respectively. These device structures show robust switching, promising performance metrics and the potential for terabit-scale density. Second, we will review architectures being developed for circuit-level integration, hybrid crossbar/CMOS circuits and array-based systems, including experimental demonstrations of key concepts such lithography-independent, chemically coded stochastic demultipluxers. Finally, bottom-up fabrication approaches, including the opportunity for assembly of three-dimensional, vertically integrated multifunctional circuits, will be critically discussed.
Making A D-Latch Sensitive To Alpha Particles
NASA Technical Reports Server (NTRS)
Buehler, Martin G.; Blaes, Brent R.; Nixon, Robert H.
1994-01-01
Standard complementary metal oxide/semiconductor (CMOS) D-latch integrated circuit modified to increase susceptibility to single-event upsets (SEU's) (changes in logic state) caused by impacts of energetic alpha particles. Suitable for use in relatively inexpensive bench-scale SEU tests of itself and of related integrated circuits like static random-access memories.
Pavlovian Conditioning of "Hermissenda": Current Cellular, Molecular, and Circuit Perspectives
ERIC Educational Resources Information Center
Crow, Terry
2004-01-01
The less-complex central nervous system of many invertebrates make them attractive for not only the molecular analysis of the associative learning and memory, but also in determining how neural circuits are modified by learning to generate changes in behavior. The nudibranch mollusk "Hermissenda crassicornis" is a preparation that has contributed…
Montague, Shelby A; Baker, Bruce S
2016-01-01
An animal's ability to learn and to form memories is essential for its survival. The fruit fly has proven to be a valuable model system for studies of learning and memory. One learned behavior in fruit flies is courtship conditioning. In Drosophila courtship conditioning, male flies learn not to court females during training with an unreceptive female. He retains a memory of this training and for several hours decreases courtship when subsequently paired with any female. Courtship conditioning is a unique learning paradigm; it uses a positive-valence stimulus, a female fly, to teach a male to decrease an innate behavior, courtship of the female. As such, courtship conditioning is not clearly categorized as either appetitive or aversive conditioning. The mushroom body (MB) region in the fruit fly brain is important for several types of memory; however, the precise subsets of intrinsic and extrinsic MB neurons necessary for courtship conditioning are unknown. Here, we disrupted synaptic signaling by driving a shibirets effector in precise subsets of MB neurons, defined by a collection of split-GAL4 drivers. Out of 75 lines tested, 32 showed defects in courtship conditioning memory. Surprisingly, we did not have any hits in the γ lobe Kenyon cells, a region previously implicated in courtship conditioning memory. We did find that several γ lobe extrinsic neurons were necessary for courtship conditioning memory. Overall, our memory hits in the dopaminergic neurons (DANs) and the mushroom body output neurons were more consistent with results from appetitive memory assays than aversive memory assays. For example, protocerebral anterior medial DANs were necessary for courtship memory, similar to appetitive memory, while protocerebral posterior lateral 1 (PPL1) DANs, important for aversive memory, were not needed. Overall, our results indicate that the MB circuits necessary for courtship conditioning memory coincide with circuits necessary for appetitive memory.
Montague, Shelby A.; Baker, Bruce S.
2016-01-01
An animal’s ability to learn and to form memories is essential for its survival. The fruit fly has proven to be a valuable model system for studies of learning and memory. One learned behavior in fruit flies is courtship conditioning. In Drosophila courtship conditioning, male flies learn not to court females during training with an unreceptive female. He retains a memory of this training and for several hours decreases courtship when subsequently paired with any female. Courtship conditioning is a unique learning paradigm; it uses a positive-valence stimulus, a female fly, to teach a male to decrease an innate behavior, courtship of the female. As such, courtship conditioning is not clearly categorized as either appetitive or aversive conditioning. The mushroom body (MB) region in the fruit fly brain is important for several types of memory; however, the precise subsets of intrinsic and extrinsic MB neurons necessary for courtship conditioning are unknown. Here, we disrupted synaptic signaling by driving a shibirets effector in precise subsets of MB neurons, defined by a collection of split-GAL4 drivers. Out of 75 lines tested, 32 showed defects in courtship conditioning memory. Surprisingly, we did not have any hits in the γ lobe Kenyon cells, a region previously implicated in courtship conditioning memory. We did find that several γ lobe extrinsic neurons were necessary for courtship conditioning memory. Overall, our memory hits in the dopaminergic neurons (DANs) and the mushroom body output neurons were more consistent with results from appetitive memory assays than aversive memory assays. For example, protocerebral anterior medial DANs were necessary for courtship memory, similar to appetitive memory, while protocerebral posterior lateral 1 (PPL1) DANs, important for aversive memory, were not needed. Overall, our results indicate that the MB circuits necessary for courtship conditioning memory coincide with circuits necessary for appetitive memory. PMID:27764141
NASA Astrophysics Data System (ADS)
Jovanović, B.; Brum, R. M.; Torres, L.
2014-04-01
After decades of continued scaling to the beat of Moore's law, it now appears that conventional silicon based devices are approaching their physical limits. In today's deep-submicron nodes, a number of short-channel and quantum effects are emerging that affect the manufacturing process, as well as, the functionality of the microelectronic systems-on-chip. Spintronics devices that exploit both the intrinsic spin of the electron and its associated magnetic moment, in addition to its fundamental electronic charge, are promising solutions to circumvent these scaling threats. Being compatible with the CMOS technology, such devices offer a promising synergy of radiation immunity, infinite endurance, non-volatility, increased density, etc. In this paper, we present a hybrid (magnetic/CMOS) cell that is able to store and process data both electrically and magnetically. The cell is based on perpendicular spin-transfer torque magnetic tunnel junctions (STT-MTJs) and is suitable for use in magnetic random access memories and reprogrammable computing (non-volatile registers, processor cache memories, magnetic field-programmable gate arrays, etc). To demonstrate the potential our hybrid cell, we physically implemented a small hybrid memory block using 45 nm × 45 nm round MTJs for the magnetic part and 28 nm fully depleted silicon on insulator (FD-SOI) technology for the CMOS part. We also report the cells measured performances in terms of area, robustness, read/write speed and energy consumption.
ERIC Educational Resources Information Center
Slouzkey, Ilana; Maroun, Mouna
2016-01-01
The basolateral amygdala (BLA), medial prefrontal cortex (mPFC) circuit, plays a crucial role in acquisition and extinction of fear memory. Extinction of aversive memories is mediated, at least in part, by the phosphoinositide-3 kinase (P[subscript 3]K)/Akt pathway in adult rats. There is recent interest in the neural mechanisms that mediate fear…
On-chip photonic memory elements employing phase-change materials.
Rios, Carlos; Hosseini, Peiman; Wright, C David; Bhaskaran, Harish; Pernice, Wolfram H P
2014-03-05
Phase-change materials integrated into nanophotonic circuits provide a flexible way to realize tunable optical components. Relying on the enormous refractive-index contrast between the amorphous and crystalline states, such materials are promising candidates for on-chip photonic memories. Nonvolatile memory operation employing arrays of microring resonators is demonstrated as a route toward all-photonic chipscale information processing. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
2015-12-24
Signal to Noise Ratio SPICE Simulation Program with Integrated Circuit Emphasis TIFF Tagged Image File Format USC University of Southern California xvii...sources can create errors in digital circuits. These effects can be simulated using Simulation Program with Integrated Circuit Emphasis ( SPICE ) or...compute summary statistics. 4.1 Circuit Simulations Noisy analog circuits can be simulated in SPICE or Cadence SpectreTM software via noisy voltage
Ross, Erika K; Kim, Joo Pyung; Settell, Megan L; Han, Seong Rok; Blaha, Charles D; Min, Hoon-Ki; Lee, Kendall H
2016-03-01
Deep brain stimulation (DBS) is a circuit-based treatment shown to relieve symptoms from multiple neurologic and neuropsychiatric disorders. In order to treat the memory deficit associated with Alzheimer's disease (AD), several clinical trials have tested the efficacy of DBS near the fornix. Early results from these studies indicated that patients who received fornix DBS experienced an improvement in memory and quality of life, yet the mechanisms behind this effect remain controversial. It is known that transmission between the medial limbic and corticolimbic circuits plays an integral role in declarative memory, and dysfunction at the circuit level results in various forms of dementia, including AD. Here, we aimed to determine the potential underlying mechanism of fornix DBS by examining the functional circuitry and brain structures engaged by fornix DBS. A multimodal approach was employed to examine global and local temporal changes that occur in an anesthetized swine model of fornix DBS. Changes in global functional activity were measured by functional MRI (fMRI), and local neurochemical changes were monitored by fast scan cyclic voltammetry (FSCV) during electrical stimulation of the fornix. Additionally, intracranial microinfusions into the nucleus accumbens (NAc) were performed to investigate the global activity changes that occur with dopamine and glutamate receptor-specific antagonism. Hemodynamic responses in both medial limbic and corticolimbic circuits measured by fMRI were induced by fornix DBS. Additionally, fornix DBS resulted in increases in dopamine oxidation current (corresponding to dopamine efflux) monitored by FSCV in the NAc. Finally, fornix DBS-evoked hemodynamic responses in the amygdala and hippocampus decreased following dopamine and glutamate receptor antagonism in the NAc. The present findings suggest that fornix DBS modulates dopamine release on presynaptic dopaminergic terminals in the NAc, involving excitatory glutamatergic input, and that the medial limbic and corticolimbic circuits interact in a functional loop. Copyright © 2016 Elsevier Inc. All rights reserved.
Computer-aided design of large-scale integrated circuits - A concept
NASA Technical Reports Server (NTRS)
Schansman, T. T.
1971-01-01
Circuit design and mask development sequence are improved by using general purpose computer with interactive graphics capability establishing efficient two way communications link between design engineer and system. Interactive graphics capability places design engineer in direct control of circuit development.
Paging memory from random access memory to backing storage in a parallel computer
Archer, Charles J; Blocksome, Michael A; Inglett, Todd A; Ratterman, Joseph D; Smith, Brian E
2013-05-21
Paging memory from random access memory (`RAM`) to backing storage in a parallel computer that includes a plurality of compute nodes, including: executing a data processing application on a virtual machine operating system in a virtual machine on a first compute node; providing, by a second compute node, backing storage for the contents of RAM on the first compute node; and swapping, by the virtual machine operating system in the virtual machine on the first compute node, a page of memory from RAM on the first compute node to the backing storage on the second compute node.
A spatially localized architecture for fast and modular DNA computing
NASA Astrophysics Data System (ADS)
Chatterjee, Gourab; Dalchau, Neil; Muscat, Richard A.; Phillips, Andrew; Seelig, Georg
2017-09-01
Cells use spatial constraints to control and accelerate the flow of information in enzyme cascades and signalling networks. Synthetic silicon-based circuitry similarly relies on spatial constraints to process information. Here, we show that spatial organization can be a similarly powerful design principle for overcoming limitations of speed and modularity in engineered molecular circuits. We create logic gates and signal transmission lines by spatially arranging reactive DNA hairpins on a DNA origami. Signal propagation is demonstrated across transmission lines of different lengths and orientations and logic gates are modularly combined into circuits that establish the universality of our approach. Because reactions preferentially occur between neighbours, identical DNA hairpins can be reused across circuits. Co-localization of circuit elements decreases computation time from hours to minutes compared to circuits with diffusible components. Detailed computational models enable predictive circuit design. We anticipate our approach will motivate using spatial constraints for future molecular control circuit designs.
Petri-net-based 2D design of DNA walker circuits.
Gilbert, David; Heiner, Monika; Rohr, Christian
2018-01-01
We consider localised DNA computation, where a DNA strand walks along a binary decision graph to compute a binary function. One of the challenges for the design of reliable walker circuits consists in leakage transitions, which occur when a walker jumps into another branch of the decision graph. We automatically identify leakage transitions, which allows for a detailed qualitative and quantitative assessment of circuit designs, design comparison, and design optimisation. The ability to identify leakage transitions is an important step in the process of optimising DNA circuit layouts where the aim is to minimise the computational error inherent in a circuit while minimising the area of the circuit. Our 2D modelling approach of DNA walker circuits relies on coloured stochastic Petri nets which enable functionality, topology and dimensionality all to be integrated in one two-dimensional model. Our modelling and analysis approach can be easily extended to 3-dimensional walker systems.
VLSI circuits implementing computational models of neocortical circuits.
Wijekoon, Jayawan H B; Dudek, Piotr
2012-09-15
This paper overviews the design and implementation of three neuromorphic integrated circuits developed for the COLAMN ("Novel Computing Architecture for Cognitive Systems based on the Laminar Microcircuitry of the Neocortex") project. The circuits are implemented in a standard 0.35 μm CMOS technology and include spiking and bursting neuron models, and synapses with short-term (facilitating/depressing) and long-term (STDP and dopamine-modulated STDP) dynamics. They enable execution of complex nonlinear models in accelerated-time, as compared with biology, and with low power consumption. The neural dynamics are implemented using analogue circuit techniques, with digital asynchronous event-based input and output. The circuits provide configurable hardware blocks that can be used to simulate a variety of neural networks. The paper presents experimental results obtained from the fabricated devices, and discusses the advantages and disadvantages of the analogue circuit approach to computational neural modelling. Copyright © 2012 Elsevier B.V. All rights reserved.
An essential memory trace found.
Thompson, Richard F
2013-10-01
I argue here that we have succeeded in localizing an essential memory trace for a basic form of associative learning and memory--classical conditioning of discrete responses learned with an aversive stimulus--to the anterior interpositus nucleus of the cerebellum. We first identified the entire essential circuit, using eyelid conditioning as the model system, and used reversible inactivation, during training, of critical structures and pathways to localize definitively the essential memory trace. In recognition of the 30th anniversary of Behavioral Neuroscience, I highlight 1 paper (Tracy, Thompson, Krupa, & Thompson, 1998) that was particularly significant for the progress of this research program. In this review, I present definitive evidence that the essential memory trace for eyelid conditioning is localized to the cerebellum and to no other part of the essential circuit, using electrical stimulation of the pontine nuclei-mossy fibers projecting to the cerebellum as the conditional stimulus (CS; it proved to be a supernormal stimulus resulting in much faster learning than with any peripheral CS) and using an electrical stimulus to the output of the cerebellum as a test, which did not change. Pontine patterns of projection to the cerebellum were confirmed with retrograde labeling techniques. 2013 APA, all rights reserved
Remembering the past and imagining the future
Byrne, Patrick; Becker, Suzanna; Burgess, Neil
2009-01-01
The neural mechanisms underlying spatial cognition are modelled, integrating neuronal, systems and behavioural data, and addressing the relationships between long-term memory, short-term memory and imagery, and between egocentric and allocentric and visual and idiothetic representations. Long-term spatial memory is modeled as attractor dynamics within medial-temporal allocentric representations, and short-term memory as egocentric parietal representations driven by perception, retrieval and imagery, and modulated by directed attention. Both encoding and retrieval/ imagery require translation between egocentric and allocentric representations, mediated by posterior parietal and retrosplenial areas and utilizing head direction representations in Papez’s circuit. Thus hippocampus effectively indexes information by real or imagined location, while Papez’s circuit translates to imagery or from perception according to the direction of view. Modulation of this translation by motor efference allows “spatial updating” of representations, while prefrontal simulated motor efference allows mental exploration. The alternating temporo-parietal flows of information are organized by the theta rhythm. Simulations demonstrate the retrieval and updating of familiar spatial scenes, hemispatial neglect in memory, and the effects on hippocampal place cell firing of lesioned head direction representations and of conflicting visual and ideothetic inputs. PMID:17500630
NASA Astrophysics Data System (ADS)
Palade, C.; Lepadatu, A. M.; Slav, A.; Lazanu, S.; Teodorescu, V. S.; Stoica, T.; Ciurea, M. L.
2018-01-01
Trilayer memory capacitors with Ge nanocrystals (NCs) floating gate in HfO2 were obtained by magnetron sputtering deposition on p-type Si substrate followed by rapid thermal annealing at relatively low temperature of 600 °C. The frequency dispersion of capacitance and resistance was measured in accumulation regime of Al/HfO2 gate oxide/Ge NCs in HfO2 floating gate/HfO2 tunnel oxide/SiOx/p-Si/Al memory capacitors. For simulation of the frequency dispersion a complex circuit model was used considering an equivalent parallel RC circuit for each layer of the trilayer structure. A series resistance due to metallic contacts and Si substrate was necessary to be included in the model. A very good fit to the experimental data was obtained and the parameters of each layer in the memory capacitor, i.e. capacitances and resistances were determined and in turn the intrinsic material parameters, i.e. dielectric constants and resistivities of layers were evaluated. The results are very important for the study and optimization of the hysteresis behaviour of floating gate memories based on NCs embedded in oxide.
Marx, Svenja; Gruenhage, Gina; Walper, Daniel; Rutishauser, Ueli; Einhäuser, Wolfgang
2015-01-01
Competition is ubiquitous in perception. For example, items in the visual field compete for processing resources, and attention controls their priority (biased competition). The inevitable ambiguity in the interpretation of sensory signals yields another form of competition: distinct perceptual interpretations compete for access to awareness. Rivalry, where two equally likely percepts compete for dominance, explicates the latter form of competition. Building upon the similarity between attention and rivalry, we propose to model rivalry by a generic competitive circuit that is widely used in the attention literature—a winner-take-all (WTA) network. Specifically, we show that a network of two coupled WTA circuits replicates three common hallmarks of rivalry: the distribution of dominance durations, their dependence on input strength (“Levelt's propositions”), and the effects of stimulus removal (blanking). This model introduces a form of memory by forming discrete states and explains experimental data better than competitive models of rivalry without memory. This result supports the crucial role of memory in rivalry specifically and in competitive processes in general. Our approach unifies the seemingly distinct phenomena of rivalry, memory, and attention in a single model with competition as the common underlying principle. PMID:25581077
Balanced Cortical Microcircuitry for Spatial Working Memory Based on Corrective Feedback Control
2014-01-01
A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory–inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. PMID:24828633
Nanoscale superconducting memory based on the kinetic inductance of asymmetric nanowire loops
NASA Astrophysics Data System (ADS)
Murphy, Andrew; Averin, Dmitri V.; Bezryadin, Alexey
2017-06-01
The demand for low-dissipation nanoscale memory devices is as strong as ever. As Moore’s law is staggering, and the demand for a low-power-consuming supercomputer is high, the goal of making information processing circuits out of superconductors is one of the central goals of modern technology and physics. So far, digital superconducting circuits could not demonstrate their immense potential. One important reason for this is that a dense superconducting memory technology is not yet available. Miniaturization of traditional superconducting quantum interference devices is difficult below a few micrometers because their operation relies on the geometric inductance of the superconducting loop. Magnetic memories do allow nanometer-scale miniaturization, but they are not purely superconducting (Baek et al 2014 Nat. Commun. 5 3888). Our approach is to make nanometer scale memory cells based on the kinetic inductance (and not geometric inductance) of superconducting nanowire loops, which have already shown many fascinating properties (Aprili 2006 Nat. Nanotechnol. 1 15; Hopkins et al 2005 Science 308 1762). This allows much smaller devices and naturally eliminates magnetic-field cross-talk. We demonstrate that the vorticity, i.e., the winding number of the order parameter, of a closed superconducting loop can be used for realizing a nanoscale nonvolatile memory device. We demonstrate how to alter the vorticity in a controlled fashion by applying calibrated current pulses. A reliable read-out of the memory is also demonstrated. We present arguments that such memory can be developed to operate without energy dissipation.
Czerniawski, Jennifer; Miyashita, Teiko; Lewandowski, Gail; Guzowski, John F.
2014-01-01
Neuroinflammation is implicated in impairments in neuronal function and cognition that arise with aging, trauma, and/or disease. Therefore, understanding the underlying basis of the effect of immune system activation on neural function could lead to therapies for treating cognitive decline. Although neuroinflammation is widely thought to preferentially impair hippocampus-dependent memory, data on the effects of cytokines on cognition are mixed. One possible explanation for these inconsistent results is that cytokines may disrupt specific neural processes underlying some forms of memory but not others. In an earlier study, we tested the effect of systemic administration of bacterial lipopolysaccharide (LPS) on retrieval of hippocampus-dependent context memory and neural circuit function in CA3 and CA1 (Czerniawski and Guzowski, 2014). Paralleling impairment in context discrimination memory, we observed changes in neural circuit function consistent with disrupted pattern separation function. In the current study we tested the hypothesis that acute neuroinflammation selectively disrupts memory retrieval in tasks requiring hippocampal pattern separation processes. Male Sprague-Dawley rats given LPS systemically prior to testing exhibited intact performance in tasks that do not require hippocampal pattern separation processes: novel object recognition and spatial memory in the water maze. By contrast, memory retrieval in a task thought to require hippocampal pattern separation, context-object discrimination, was strongly impaired in LPS-treated rats in the absence of any gross effects on exploratory activity or motivation. These data show that LPS administration does not impair memory retrieval in all hippocampus-dependent tasks, and support the hypothesis that acute neuroinflammation impairs context discrimination memory via disruption of pattern separation processes in hippocampus. PMID:25451612
Czerniawski, Jennifer; Miyashita, Teiko; Lewandowski, Gail; Guzowski, John F
2015-02-01
Neuroinflammation is implicated in impairments in neuronal function and cognition that arise with aging, trauma, and/or disease. Therefore, understanding the underlying basis of the effect of immune system activation on neural function could lead to therapies for treating cognitive decline. Although neuroinflammation is widely thought to preferentially impair hippocampus-dependent memory, data on the effects of cytokines on cognition are mixed. One possible explanation for these inconsistent results is that cytokines may disrupt specific neural processes underlying some forms of memory but not others. In an earlier study, we tested the effect of systemic administration of bacterial lipopolysaccharide (LPS) on retrieval of hippocampus-dependent context memory and neural circuit function in CA3 and CA1 (Czerniawski and Guzowski, 2014). Paralleling impairment in context discrimination memory, we observed changes in neural circuit function consistent with disrupted pattern separation function. In the current study we tested the hypothesis that acute neuroinflammation selectively disrupts memory retrieval in tasks requiring hippocampal pattern separation processes. Male Sprague-Dawley rats given LPS systemically prior to testing exhibited intact performance in tasks that do not require hippocampal pattern separation processes: novel object recognition and spatial memory in the water maze. By contrast, memory retrieval in a task thought to require hippocampal pattern separation, context-object discrimination, was strongly impaired in LPS-treated rats in the absence of any gross effects on exploratory activity or motivation. These data show that LPS administration does not impair memory retrieval in all hippocampus-dependent tasks, and support the hypothesis that acute neuroinflammation impairs context discrimination memory via disruption of pattern separation processes in hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.
A Very Low Cost BCH Decoder for High Immunity of On-Chip Memories
NASA Astrophysics Data System (ADS)
Seo, Haejun; Han, Sehwan; Heo, Yoonseok; Cho, Taewon
BCH(Bose-Chaudhuri-Hoquenbhem) code, a type of block codes-cyclic codes, has very strong error-correcting ability which is vital for performing the error protection on the memory system. BCH code has many kinds of dual algorithms, PGZ(Pererson-Gorenstein-Zierler) algorithm out of them is advantageous in view of correcting the errors through the simple calculation in t value. However, this is problematic when this becomes 0 (divided by zero) in case ν ≠ t. In this paper, the circuit would be simplified by suggesting the multi-mode hardware architecture in preparation that v were 0~3. First, production cost would be less thanks to the smaller number of gates. Second, lessening power consumption could lengthen the recharging period. The very low cost and simple datapath make our design a good choice in small-footprint SoC(System on Chip) as ECC(Error Correction Code/Circuit) in memory system.
NASA Technical Reports Server (NTRS)
Gosney, W. M.
1977-01-01
Electrically alterable read-only memories (EAROM's) or reprogrammable read-only memories (RPROM's) can be fabricated using a single-level metal-gate p-channel MOS technology with all conventional processing steps. Given the acronym DIFMOS for dual-injector floating-gate MOS, this technology utilizes the floating-gate technique for nonvolatile storage of data. Avalanche injection of hot electrons through gate oxide from a special injector diode in each bit is used to charge the floating gates. A second injector structure included in each bit permits discharge of the floating gate by avalanche injection of holes through gate oxide. The overall design of the DIFMOS bit is dictated by the physical considerations required for each of the avalanche injector types. The end result is a circuit technology which can provide fully decoded bit-erasable EAROM-type circuits using conventional manufacturing techniques.
Direct neural pathways convey distinct visual information to Drosophila mushroom bodies
Vogt, Katrin; Aso, Yoshinori; Hige, Toshihide; Knapek, Stephan; Ichinose, Toshiharu; Friedrich, Anja B; Turner, Glenn C; Rubin, Gerald M; Tanimoto, Hiromu
2016-01-01
Previously, we demonstrated that visual and olfactory associative memories of Drosophila share mushroom body (MB) circuits (Vogt et al., 2014). Unlike for odor representation, the MB circuit for visual information has not been characterized. Here, we show that a small subset of MB Kenyon cells (KCs) selectively responds to visual but not olfactory stimulation. The dendrites of these atypical KCs form a ventral accessory calyx (vAC), distinct from the main calyx that receives olfactory input. We identified two types of visual projection neurons (VPNs) directly connecting the optic lobes and the vAC. Strikingly, these VPNs are differentially required for visual memories of color and brightness. The segregation of visual and olfactory domains in the MB allows independent processing of distinct sensory memories and may be a conserved form of sensory representations among insects. DOI: http://dx.doi.org/10.7554/eLife.14009.001 PMID:27083044
Synaptic plasticity functions in an organic electrochemical transistor
NASA Astrophysics Data System (ADS)
Gkoupidenis, Paschalis; Schaefer, Nathan; Strakosas, Xenofon; Fairfield, Jessamyn A.; Malliaras, George G.
2015-12-01
Synaptic plasticity functions play a crucial role in the transmission of neural signals in the brain. Short-term plasticity is required for the transmission, encoding, and filtering of the neural signal, whereas long-term plasticity establishes more permanent changes in neural microcircuitry and thus underlies memory and learning. The realization of bioinspired circuits that can actually mimic signal processing in the brain demands the reproduction of both short- and long-term aspects of synaptic plasticity in a single device. Here, we demonstrate the implementation of neuromorphic functions similar to biological memory, such as short- to long-term memory transition, in non-volatile organic electrochemical transistors (OECTs). Depending on the training of the OECT, the device displays either short- or long-term plasticity, therefore, exhibiting non von Neumann characteristics with merged processing and storing functionalities. These results are a first step towards the implementation of organic-based neuromorphic circuits.
Electric Circuit Theory--Computer Illustrated Text.
ERIC Educational Resources Information Center
Riches, Brian
1990-01-01
Discusses the use of a computer-illustrated text (CIT) with integrated software to teach electric circuit theory to college students. Examples of software use are given, including simple animation, graphical displays, and problem-solving programs. Issues affecting electric circuit theory instruction are also addressed, including mathematical…
Method of pedestal and common-mode noise correction for switched-capacitor analog memories
Britton, C.L.
1997-09-23
A method and apparatus are disclosed for correcting common-mode noise and pedestal noise in a multichannel array of switched-capacitor analog memories wherein each analog memory is connected to an associated analog-to-digital converter. The apparatus comprises a single differential element in two different embodiments. In a first embodiment, the differential element is a reference analog memory connected to a buffer. In the second embodiment, the differential dement is a reference analog memory connected to a reference analog-to-digital connected to an array of digital summing circuits. 4 figs.
Method of pedestal and common-mode noise correction for switched-capacitor analog memories
Britton, C.L.
1996-12-31
A method and apparatus are disclosed for correcting common-mode noise and pedestal noise in a multichannel array of switched-capacitor analog memories wherein each analog memory is connected to an associated analog-to-digital converter. The apparatus comprises a single differential element in two different embodiments. In a first embodiment, the differential element is a reference analog memory connected to a buffer. In the second embodiment, the differential element is a reference analog memory connected to a reference analog-to-digital connected to an array of digital summing circuits. 4 figs.
Radiation Issues and Applications of Floating Gate Memories
NASA Technical Reports Server (NTRS)
Scheick, L. Z.; Nguyen, D. N.
2000-01-01
The radiation effects that affect various systems that comprise floating gate memories are presented. The wear-out degradation results of unirradiated flash memories are compared to irradiated flash memories. The procedure analyzes the failure to write and erase caused by wear-out and degradation of internal charge pump circuits. A method is described for characterizing the radiation effects of the floating gate itself. The rate dependence, stopping power dependence, SEU susceptibility and applications of floating gate in radiation environment are presented. The ramifications for dosimetry and cell failure are discussed as well as for the long term use aspects of non-volatile memories.
NASA Technical Reports Server (NTRS)
2007-01-01
Topics include: Wearable Environmental and Physiological Sensing Unit; Broadband Phase Retrieval for Image-Based Wavefront Sensing; Filter Function for Wavefront Sensing Over a Field of View; Iterative-Transform Phase Retrieval Using Adaptive Diversity; Wavefront Sensing With Switched Lenses for Defocus Diversity; Smooth Phase Interpolated Keying; Maintaining Stability During a Conducted-Ripple EMC Test; Photodiode Preamplifier for Laser Ranging With Weak Signals; Advanced High-Definition Video Cameras; Circuit for Full Charging of Series Lithium-Ion Cells; Analog Nonvolatile Computer Memory Circuits; JavaGenes Molecular Evolution; World Wind 3D Earth Viewing; Lithium Dinitramide as an Additive in Lithium Power Cells; Accounting for Uncertainties in Strengths of SiC MEMS Parts; Ion-Conducting Organic/Inorganic Polymers; MoO3 Cathodes for High-Temperature Lithium Thin-Film Cells; Counterrotating-Shoulder Mechanism for Friction Stir Welding; Strain Gauges Indicate Differential-CTE-Induced Failures; Antibodies Against Three Forms of Urokinase; Understanding and Counteracting Fatigue in Flight Crews; Active Correction of Aberrations of Low-Quality Telescope Optics; Dual-Beam Atom Laser Driven by Spinor Dynamics; Rugged, Tunable Extended-Cavity Diode Laser; Balloon for Long-Duration, High-Altitude Flight at Venus; and Wide-Temperature-Range Integrated Operational Amplifier.
Simple proof of equivalence between adiabatic quantum computation and the circuit model.
Mizel, Ari; Lidar, Daniel A; Mitchell, Morgan
2007-08-17
We prove the equivalence between adiabatic quantum computation and quantum computation in the circuit model. An explicit adiabatic computation procedure is given that generates a ground state from which the answer can be extracted. The amount of time needed is evaluated by computing the gap. We show that the procedure is computationally efficient.
Laser Scanner Tests For Single-Event Upsets
NASA Technical Reports Server (NTRS)
Kim, Quiesup; Soli, George A.; Schwartz, Harvey R.
1992-01-01
Microelectronic advanced laser scanner (MEALS) is opto/electro/mechanical apparatus for nondestructive testing of integrated memory circuits, logic circuits, and other microelectronic devices. Multipurpose diagnostic system used to determine ultrafast time response, leakage, latchup, and electrical overstress. Used to simulate some of effects of heavy ions accelerated to high energies to determine susceptibility of digital device to single-event upsets.
The mysteries of remote memory.
Albo, Zimbul; Gräff, Johannes
2018-03-19
Long-lasting memories form the basis of our identity as individuals and lie central in shaping future behaviours that guide survival. Surprisingly, however, our current knowledge of how such memories are stored in the brain and retrieved, as well as the dynamics of the circuits involved, remains scarce despite seminal technical and experimental breakthroughs in recent years. Traditionally, it has been proposed that, over time, information initially learnt in the hippocampus is stored in distributed cortical networks. This process-the standard theory of memory consolidation-would stabilize the newly encoded information into a lasting memory, become independent of the hippocampus, and remain essentially unmodifiable throughout the lifetime of the individual. In recent years, several pieces of evidence have started to challenge this view and indicate that long-lasting memories might already ab ovo be encoded, and subsequently stored in distributed cortical networks, akin to the multiple trace theory of memory consolidation. In this review, we summarize these recent findings and attempt to identify the biologically plausible mechanisms based on which a contextual memory becomes remote by integrating different levels of analysis: from neural circuits to cell ensembles across synaptic remodelling and epigenetic modifications. From these studies, remote memory formation and maintenance appear to occur through a multi-trace, dynamic and integrative cellular process ranging from the synapse to the nucleus, and represent an exciting field of research primed to change quickly as new experimental evidence emerges.This article is part of a discussion meeting issue 'Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists'. © 2018 The Authors.
The mysteries of remote memory
2018-01-01
Long-lasting memories form the basis of our identity as individuals and lie central in shaping future behaviours that guide survival. Surprisingly, however, our current knowledge of how such memories are stored in the brain and retrieved, as well as the dynamics of the circuits involved, remains scarce despite seminal technical and experimental breakthroughs in recent years. Traditionally, it has been proposed that, over time, information initially learnt in the hippocampus is stored in distributed cortical networks. This process—the standard theory of memory consolidation—would stabilize the newly encoded information into a lasting memory, become independent of the hippocampus, and remain essentially unmodifiable throughout the lifetime of the individual. In recent years, several pieces of evidence have started to challenge this view and indicate that long-lasting memories might already ab ovo be encoded, and subsequently stored in distributed cortical networks, akin to the multiple trace theory of memory consolidation. In this review, we summarize these recent findings and attempt to identify the biologically plausible mechanisms based on which a contextual memory becomes remote by integrating different levels of analysis: from neural circuits to cell ensembles across synaptic remodelling and epigenetic modifications. From these studies, remote memory formation and maintenance appear to occur through a multi-trace, dynamic and integrative cellular process ranging from the synapse to the nucleus, and represent an exciting field of research primed to change quickly as new experimental evidence emerges. This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists’. PMID:29352028
CIRCUS--A digital computer program for transient analysis of electronic circuits
NASA Technical Reports Server (NTRS)
Moore, W. T.; Steinbert, L. L.
1968-01-01
Computer program simulates the time domain response of an electronic circuit to an arbitrary forcing function. CIRCUS uses a charge-control parameter model to represent each semiconductor device. Given the primary photocurrent, the transient behavior of a circuit in a radiation environment is determined.
NASA Astrophysics Data System (ADS)
Krishnamoorthy, Ashok Venketaraman
This thesis covers the design, analysis, optimization, and implementation of optoelectronic (N,M,F) networks. (N,M,F) networks are generic space-division networks that are well suited to implementation using optoelectronic integrated circuits and free-space optical interconnects. An (N,M,F) networks consists of N input channels each having a fanout F_{rm o}, M output channels each having a fanin F_{rm i}, and Log_{rm K}(N/F) stages of K x K switches. The functionality of the fanout, switching, and fanin stages depends on the specific application. Three applications of optoelectronic (N,M,F) networks are considered. The first is an optoelectronic (N,1,1) content -addressable memory system that achieves associative recall on two-dimensional images retrieved from a parallel-access optical memory. The design and simulation of the associative memory are discussed, and an experimental emulation of a prototype system using images from a parallel-readout optical disk is presented. The system design provides superior performance to existing electronic content-addressable memory chips in terms of capacity and search rate, and uses readily available optical disk and VLSI technologies. Next, a scalable optoelectronic (N,M,F) neural network that uses free-space holographic optical interconnects is presented. The neural architecture minimizes the number of optical transmitters needed, and provides accurate electronic fanin with low signal skew, and dendritic-type fan-in processing capability in a compact layout. Optimal data-encoding methods and circuit techniques are discussed. The implementation of an prototype optoelectronic neural system, and its application to a simple recognition task is demonstrated. Finally, the design, analysis, and optimization of a (N,N,F) self-routing, packet-switched multistage interconnection network is described. The network is suitable for parallel computing and broadband switching applications. The tradeoff between optical and electronic interconnects is examined quantitatively by varying the electronic switch size K. The performance of the (N,N,F) network versus the fanning parameter F, is also analyzed. It is shown that the optoelectronic (N,N,F) networks provide a range of performance-cost alternatives, and offer superior performance-per-cost to fully electronic switching networks and to previous networks designs.
Fabricating a Microcomputer on a Single Silicon Wafer
NASA Technical Reports Server (NTRS)
Evanchuk, V. L.
1983-01-01
Concept for "microcomputer on a slice" reduces microcomputer costs by eliminating scribing, wiring, and packaging of individual circuit chips. Low-cost microcomputer on silicon slice contains redundant components. All components-central processing unit, input/output circuitry, read-only memory, and random-access memory (CPU, I/O, ROM, and RAM) on placed on single silicon wafer.
Memory Processing: Ripples in the Resting Brain.
Walker, Matthew P; Robertson, Edwin M
2016-03-21
Recent work has shown that, during sleep, a functional circuit is created amidst a general breakdown in connectivity following fast-frequency bursts of brain activity. The findings question the unconscious nature of deep sleep, and provide an explanation for its contribution to memory processing. Copyright © 2016 Elsevier Ltd. All rights reserved.
Contributions of Memory Circuits to Language: The Declarative/Procedural Model
ERIC Educational Resources Information Center
Ullman, Michael T.
2004-01-01
The structure of the brain and the nature of evolution suggest that, despite its uniqueness, language likely depends on brain systems that also subserve other functions. The declarative/procedural (DP) model claims that the mental lexicon of memorized word-specific knowledge depends on the largely temporal-lobe substrates of declarative memory,…
The interhemispheric CA1 circuit governs rapid generalisation but not fear memory.
Zhou, Heng; Xiong, Gui-Jing; Jing, Liang; Song, Ning-Ning; Pu, De-Lin; Tang, Xun; He, Xiao-Bing; Xu, Fu-Qiang; Huang, Jing-Fei; Li, Ling-Jiang; Richter-Levin, Gal; Mao, Rong-Rong; Zhou, Qi-Xin; Ding, Yu-Qiang; Xu, Lin
2017-12-19
Encoding specificity theory predicts most effective recall by the original conditions at encoding, while generalization endows recall flexibly under circumstances which deviate from the originals. The CA1 regions have been implicated in memory and generalization but whether and which locally separated mechanisms are involved is not clear. We report here that fear memory is quickly formed, but generalization develops gradually over 24 h. Generalization but not fear memory is impaired by inhibiting ipsilateral (ips) or contralateral (con) CA1, and by optogenetic silencing of the ipsCA1 projections onto conCA1. By contrast, in vivo fEPSP recordings reveal that ipsCA1-conCA1 synaptic efficacy is increased with delay over 24 h when generalization is formed but it is unchanged if generalization is disrupted. Direct excitation of ipsCA1-conCA1 synapses using chemogenetic hM3Dq facilitates generalization formation. Thus, rapid generalization is an active process dependent on bilateral CA1 regions, and encoded by gradual synaptic learning in ipsCA1-conCA1 circuit.
Rapid and automatic speech-specific learning mechanism in human neocortex.
Kimppa, Lilli; Kujala, Teija; Leminen, Alina; Vainio, Martti; Shtyrov, Yury
2015-09-01
A unique feature of human communication system is our ability to rapidly acquire new words and build large vocabularies. However, its neurobiological foundations remain largely unknown. In an electrophysiological study optimally designed to probe this rapid formation of new word memory circuits, we employed acoustically controlled novel word-forms incorporating native and non-native speech sounds, while manipulating the subjects' attention on the input. We found a robust index of neurolexical memory-trace formation: a rapid enhancement of the brain's activation elicited by novel words during a short (~30min) perceptual exposure, underpinned by fronto-temporal cortical networks, and, importantly, correlated with behavioural learning outcomes. Crucially, this neural memory trace build-up took place regardless of focused attention on the input or any pre-existing or learnt semantics. Furthermore, it was found only for stimuli with native-language phonology, but not for acoustically closely matching non-native words. These findings demonstrate a specialised cortical mechanism for rapid, automatic and phonology-dependent formation of neural word memory circuits. Copyright © 2015. Published by Elsevier Inc.
Stafford, James M.; Maughan, DeeAnna K.; Ilioi, Elena C.; Lattal, K. Matthew
2013-01-01
An issue of increasing theoretical and translational importance is to understand the conditions under which learned fear can be suppressed, or even eliminated. Basic research has pointed to extinction, in which an organism is exposed to a fearful stimulus (such as a context) in the absence of an expected aversive outcome (such as a shock). This extinction process results in the suppression of fear responses, but is generally thought to leave the original fearful memory intact. Here, we investigate the effects of extinction during periods of memory lability on behavioral responses and on expression of the immediate–early gene c-Fos within fear conditioning and extinction circuits. Our results show that long-term extinction is impaired when it occurs during time periods during which the memory should be most vulnerable to disruption (soon after conditioning or retrieval). These behavioral effects are correlated with hyperactivation of medial prefrontal cortex and amygdala subregions associated with fear expression rather than fear extinction. These findings demonstrate that behavioral experiences during periods of heightened fear prevent extinction and prolong the conditioned fear response. PMID:23422280
NASA Technical Reports Server (NTRS)
Fijany, Amir; Toomarian, Benny N.
2000-01-01
There has been significant improvement in the performance of VLSI devices, in terms of size, power consumption, and speed, in recent years and this trend may also continue for some near future. However, it is a well known fact that there are major obstacles, i.e., physical limitation of feature size reduction and ever increasing cost of foundry, that would prevent the long term continuation of this trend. This has motivated the exploration of some fundamentally new technologies that are not dependent on the conventional feature size approach. Such technologies are expected to enable scaling to continue to the ultimate level, i.e., molecular and atomistic size. Quantum computing, quantum dot-based computing, DNA based computing, biologically inspired computing, etc., are examples of such new technologies. In particular, quantum-dots based computing by using Quantum-dot Cellular Automata (QCA) has recently been intensely investigated as a promising new technology capable of offering significant improvement over conventional VLSI in terms of reduction of feature size (and hence increase in integration level), reduction of power consumption, and increase of switching speed. Quantum dot-based computing and memory in general and QCA specifically, are intriguing to NASA due to their high packing density (10(exp 11) - 10(exp 12) per square cm ) and low power consumption (no transfer of current) and potentially higher radiation tolerant. Under Revolutionary Computing Technology (RTC) Program at the NASA/JPL Center for Integrated Space Microelectronics (CISM), we have been investigating the potential applications of QCA for the space program. To this end, exploiting the intrinsic features of QCA, we have designed novel QCA-based circuits for co-planner (i.e., single layer) and compact implementation of a class of data permutation matrices, a class of interconnection networks, and a bit-serial processor. Building upon these circuits, we have developed novel algorithms and QCA-based architectures for highly parallel and systolic computation of signal/image processing applications, such as FFT and Wavelet and Wlash-Hadamard Transforms.
GaAs Optoelectronic Integrated-Circuit Neurons
NASA Technical Reports Server (NTRS)
Lin, Steven H.; Kim, Jae H.; Psaltis, Demetri
1992-01-01
Monolithic GaAs optoelectronic integrated circuits developed for use as artificial neurons. Neural-network computer contains planar arrays of optoelectronic neurons, and variable synaptic connections between neurons effected by diffraction of light from volume hologram in photorefractive material. Basic principles of neural-network computers explained more fully in "Optoelectronic Integrated Circuits For Neural Networks" (NPO-17652). In present circuits, devices replaced by metal/semiconductor field effect transistors (MESFET's), which consume less power.
Computer-aided linear-circuit design.
NASA Technical Reports Server (NTRS)
Penfield, P.
1971-01-01
Usually computer-aided design (CAD) refers to programs that analyze circuits conceived by the circuit designer. Among the services such programs should perform are direct network synthesis, analysis, optimization of network parameters, formatting, storage of miscellaneous data, and related calculations. The program should be embedded in a general-purpose conversational language such as BASIC, JOSS, or APL. Such a program is MARTHA, a general-purpose linear-circuit analyzer embedded in APL.
The report gives results of a screening evaluation of volatile organic emissions from printed circuit board laminates and potential pollution prevention alternatives. In the evaluation, printed circuit board laminates, without circuitry, commonly found in personal computer (PC) m...
Synthetic analog computation in living cells.
Daniel, Ramiz; Rubens, Jacob R; Sarpeshkar, Rahul; Lu, Timothy K
2013-05-30
A central goal of synthetic biology is to achieve multi-signal integration and processing in living cells for diagnostic, therapeutic and biotechnology applications. Digital logic has been used to build small-scale circuits, but other frameworks may be needed for efficient computation in the resource-limited environments of cells. Here we demonstrate that synthetic analog gene circuits can be engineered to execute sophisticated computational functions in living cells using just three transcription factors. Such synthetic analog gene circuits exploit feedback to implement logarithmically linear sensing, addition, ratiometric and power-law computations. The circuits exhibit Weber's law behaviour as in natural biological systems, operate over a wide dynamic range of up to four orders of magnitude and can be designed to have tunable transfer functions. Our circuits can be composed to implement higher-order functions that are well described by both intricate biochemical models and simple mathematical functions. By exploiting analog building-block functions that are already naturally present in cells, this approach efficiently implements arithmetic operations and complex functions in the logarithmic domain. Such circuits may lead to new applications for synthetic biology and biotechnology that require complex computations with limited parts, need wide-dynamic-range biosensing or would benefit from the fine control of gene expression.
Synaptic plasticity and oscillation at zinc tin oxide/silver oxide interfaces
NASA Astrophysics Data System (ADS)
Murdoch, Billy J.; McCulloch, Dougal G.; Partridge, James G.
2017-02-01
Short-term plasticity, long-term potentiation, and pulse interval dependent plasticity learning/memory functions have been observed in junctions between amorphous zinc-tin-oxide and silver-oxide. The same junctions exhibited current-controlled negative differential resistance and when connected in an appropriate circuit, they behaved as relaxation oscillators. These oscillators produced voltage pulses suitable for device programming. Transmission electron microscopy, energy dispersive X-ray spectroscopy, and electrical measurements suggest that the characteristics of these junctions arise from Ag+/O- electromigration across a highly resistive interface layer. With memory/learning functions and programming spikes provided in a single device structure, arrays of similar devices could be used to form transistor-free neuromorphic circuits.
Optical memories in digital computing
NASA Technical Reports Server (NTRS)
Alford, C. O.; Gaylord, T. K.
1979-01-01
High capacity optical memories with relatively-high data-transfer rate and multiport simultaneous access capability may serve as basis for new computer architectures. Several computer structures that might profitably use memories are: a) simultaneous record-access system, b) simultaneously-shared memory computer system, and c) parallel digital processing structure.
The evolvability of programmable hardware.
Raman, Karthik; Wagner, Andreas
2011-02-06
In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected 'neutral networks' in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 10(45) logic circuits ('genotypes') and 10(19) logic functions ('phenotypes'). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry.
The evolvability of programmable hardware
Raman, Karthik; Wagner, Andreas
2011-01-01
In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected ‘neutral networks’ in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 1045 logic circuits (‘genotypes’) and 1019 logic functions (‘phenotypes’). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry. PMID:20534598
Wang, Yunpeng; Zhang, Hongying; Cui, Jingjing; Zhang, Jing; Yin, Fangyuan; Guo, Hao; Lai, Jianghua; Xing, Bo
2018-04-17
Contextual memory driven by abused drugs such as opiates has a central role in maintenance and relapse of drug-taking behaviors. Although dopamine (DA) signaling favors memory storage and retrieval via regulation of hippocampal-prefrontal connectivity, its role in modulating opiate-associated contextual memory is largely unknown. Here, we report roles of DA signaling within the hippocampal-prefrontal circuit for opiate-related memories. Combining-conditioned place preference (CPP) with molecular analyses, we investigated the DA D1 receptor (D1R) and extracellular signal-regulated kinase (ERK)-cAMP-response element binding protein (CREB) signaling, as well as DA D2 receptor (D2R) and protein kinase B (PKB or Akt)/glycogen synthase kinase 3 (GSK3) signaling in the ventral hippocampus (vHip) and medial prefrontal cortex (mPFC) during the formation of opiate-related associative memories. Morphine-CPP acquisition increased the activity of the D1R-ERK-CREB pathway in both the vHip and mPFC. Morphine-CPP reinstatement was associated with the D2R-mediated hyperactive GSK3 via Akt inhibition in the vHip and PFC. Furthermore, integrated D1R-ERK-CREB and D2R-Akt-GSK3 pathways in the vHip-mPFC circuit are required for the acquisition and retrieval of the morphine contextual memory, respectively. Moreover, blockage of D1R or D2R signaling could alleviate normal Hip-dependent spatial memory. These results suggest that D1R and D2R signaling are differentially involved in the acquisition and retrieval of morphine contextual memory, and DA signaling in the vHip-mPFC connection contributes to morphine-associated and normal memory, largely depending on opiate exposure states.
Four-Channel PC/104 MIL-STD-1553 Circuit Board
NASA Technical Reports Server (NTRS)
Cox, Gary L.
2004-01-01
The mini bus interface card (miniBIC) is the first four-channel electronic circuit board that conforms to MIL-STD-1553 and to the electrical-footprint portion of PC/104. [MIL-STD-1553 is a military standard that encompasses a method of communication and electrical- interface requirements for digital electronic subsystems connected to a data bus. PC/104 is an industry standard for compact, stackable modules that are fully compatible (in architecture, hardware, and software) with personal-computer data- and power-bus circuitry.] Prior to the development of the miniBIC, only one- and two-channel PC/104 MIL-STD-1553 boards were available. To obtain four channels, it was necessary to include at least two boards in a PC/104 stack. In comparison with such a two-board stack, the miniBIC takes up less space, consumes less power, and is more reliable. In addition, the miniBIC includes 32 digital input/output channels. The miniBIC (see figure) contains four MIL-STD-1553B hybrid integrated circuits (ICs), four transformers, a field-programmable gate array (FPGA), and an Industry Standard Architecture (ISA) interface. Each hybrid IC includes a MILSTD-1553 dual transceiver, memory-management circuitry, processor interface logic circuitry, and 64Kx16 bits of shared static random access memory. The memory is used to configure message and data blocks. In addition, 23 16-bit registers are available for (1) configuring the hybrid IC for, and starting it in, various modes of operation; (2) reading the status of the functionality of the hybrid IC; and (3) resetting the hybrid IC to a known state. The miniBIC can operate as a remote terminal, bus controller, or bus monitor. The FPGA provides the chip-select and data-strobe signals needed for operation of the hybrid ICs. The FPGA also receives interruption signals and forwards them to the ISA bus. The ISA interface connects the address, data, and control interfaces of the hybrid ICs to the ISA backplane. Each channel is, in effect, a MIL-STD-1553 interface that can operate either independently of the others or else as a redundant version of one of the others. The transformer in each channel provides electrical isolation between the rest of the miniBIC circuitry and the bus to which that channel is connected.
Oprisan, Sorinel A.; Buhusi, Catalin V.
2011-01-01
In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing) is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern), whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern). How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an striatal beat frequency (SBF) model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris–Lecar neurons (SBF–ML). Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF–ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise) – which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trials, and in the errors in recording/retrieving stored information related to criterion time – seems to be critical for the time-scale invariance of the clock and memory patterns. PMID:21977014
Hardware architecture design of a fast global motion estimation method
NASA Astrophysics Data System (ADS)
Liang, Chaobing; Sang, Hongshi; Shen, Xubang
2015-12-01
VLSI implementation of gradient-based global motion estimation (GME) faces two main challenges: irregular data access and high off-chip memory bandwidth requirement. We previously proposed a fast GME method that reduces computational complexity by choosing certain number of small patches containing corners and using them in a gradient-based framework. A hardware architecture is designed to implement this method and further reduce off-chip memory bandwidth requirement. On-chip memories are used to store coordinates of the corners and template patches, while the Gaussian pyramids of both the template and reference frame are stored in off-chip SDRAMs. By performing geometric transform only on the coordinates of the center pixel of a 3-by-3 patch in the template image, a 5-by-5 area containing the warped 3-by-3 patch in the reference image is extracted from the SDRAMs by burst read. Patched-based and burst mode data access helps to keep the off-chip memory bandwidth requirement at the minimum. Although patch size varies at different pyramid level, all patches are processed in term of 3x3 patches, so the utilization of the patch-processing circuit reaches 100%. FPGA implementation results show that the design utilizes 24,080 bits on-chip memory and for a sequence with resolution of 352x288 and frequency of 60Hz, the off-chip bandwidth requirement is only 3.96Mbyte/s, compared with 243.84Mbyte/s of the original gradient-based GME method. This design can be used in applications like video codec, video stabilization, and super-resolution, where real-time GME is a necessity and minimum memory bandwidth requirement is appreciated.
Strength of word-specific neural memory traces assessed electrophysiologically.
Alexandrov, Alexander A; Boricheva, Daria O; Pulvermüller, Friedemann; Shtyrov, Yury
2011-01-01
Memory traces for words are frequently conceptualized neurobiologically as networks of neurons interconnected via reciprocal links developed through associative learning in the process of language acquisition. Neurophysiological reflection of activation of such memory traces has been reported using the mismatch negativity brain potential (MMN), which demonstrates an enhanced response to meaningful words over meaningless items. This enhancement is believed to be generated by the activation of strongly intraconnected long-term memory circuits for words that can be automatically triggered by spoken linguistic input and that are absent for unfamiliar phonological stimuli. This conceptual framework critically predicts different amounts of activation depending on the strength of the word's lexical representation in the brain. The frequent use of words should lead to more strongly connected representations, whereas less frequent items would be associated with more weakly linked circuits. A word with higher frequency of occurrence in the subject's language should therefore lead to a more pronounced lexical MMN response than its low-frequency counterpart. We tested this prediction by comparing the event-related potentials elicited by low- and high-frequency words in a passive oddball paradigm; physical stimulus contrasts were kept identical. We found that, consistent with our prediction, presenting the high-frequency stimulus led to a significantly more pronounced MMN response relative to the low-frequency one, a finding that is highly similar to previously reported MMN enhancement to words over meaningless pseudowords. Furthermore, activation elicited by the higher-frequency word peaked earlier relative to low-frequency one, suggesting more rapid access to frequently used lexical entries. These results lend further support to the above view on word memory traces as strongly connected assemblies of neurons. The speed and magnitude of their activation appears to be linked to the strength of internal connections in a memory circuit, which is in turn determined by the everyday use of language elements.