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Journal ArticleDOI

In-materio neuromimetic devices: dynamics, information processing and pattern recognition

TL;DR: This feature article is devoted to various in materio implementation of neuromimetic processes, including neuronal dynamics, synaptic plasticity, and higher-level signal and information processing, along with more sophisticated implementations, including signal processing, speech recognition and data security.
Abstract: The story of information processing is a story of great success. Todays' microprocessors are devices of unprecedented complexity and MOSFET transistors are considered as the most widely produced artifact in the history of mankind. The current miniaturization of electronic circuits is pushed almost to the physical limit and begins to suffer from various parasitic effects. These facts stimulate intense research on neuromimetic devices. This feature article is devoted to various in materio implementation of neuromimetic processes, including neuronal dynamics, synaptic plasticity, and higher-level signal and information processing, along with more sophisticated implementations, including signal processing, speech recognition and data security. Due to vast number of papers in the field, only a subjective selection of topics is presented in this review.
Citations
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Journal ArticleDOI
TL;DR: SNESM could prove to be a useful time series signal processing system designed to improve accuracy in classification tasks and there are more differences in the correlation of complexity parameters between the transformed signal and the input signal, which may explain the improvement in the classification scores.
Abstract: ABSTRACT Nanodevices that show the potential for non-linear transformation of electrical signals and various forms of memory can be successfully used in new computational paradigms, such as neuromorphic or reservoir computing. In this work, we present single-node Echo State Machine (SNESM) RC system based on bridge synapse as a computational substrate (consisting of 4 memristors and a differential amplifier) used for epileptic seizure detection. The results show that the evolution of the signal in a feedback loop helps improve the classification accuracy of the system for that task. The transformation in SNESM changes the correlation and distribution of the complexity parameters of the input signal. In general, there are more differences in the correlation of complexity parameters between the transformed signal and the input signal, which may explain the improvement in the classification scores. SNESM could prove to be a useful time series signal processing system designed to improve accuracy in classification tasks.

9 citations

Journal ArticleDOI
TL;DR: In this article , photochromic and luminescent materials contribute to processing Fuzzy logic, which is a good model of human power to compute by using words, and perspectives on how photoswitchable materials will be employed in further developments of CAI are outlined.

6 citations

Journal ArticleDOI
TL;DR: The global challenges of the XXI century require a more in-depth analysis and investigation of complex systems, according to a new report by the International Institute for Strategic Studies.
Abstract: The global challenges of the XXI century require a more in-depth analysis and investigation of complex systems [...]

5 citations

Journal ArticleDOI
TL;DR: The road-map of the inspiration from wave-based computing on chemical media towards the implementation of equivalent systems on oscillating memristive circuits was studied here and the most straightforward example was demonstrated, namely the approximation of Boolean gates.
Abstract: Unconventional and, specifically, wave computing has been repeatedly studied in laboratory based experiments by utilizing chemical systems like a thin film of Belousov–Zhabotinsky (BZ) reactions. Nonetheless, the principles demonstrated by this chemical computer were mimicked by mathematical models to enhance the understanding of these systems and enable a more detailed investigation of their capacity. As expected, the computerized counterparts of the laboratory based experiments are faster and less expensive. A further step of acceleration in wave-based computing is the development of electrical circuits that imitate the dynamics of chemical computers. A key component of the electrical circuits is the memristor which facilitates the non-linear behavior of the chemical systems. As part of this concept, the road-map of the inspiration from wave-based computing on chemical media towards the implementation of equivalent systems on oscillating memristive circuits was studied here. For illustration reasons, the most straightforward example was demonstrated, namely the approximation of Boolean gates.

4 citations

Journal ArticleDOI
TL;DR: In this article, the capacity of concrete-based information processing substrate in signal classification task in accordance with in materio computing paradigm has been demonstrated, where the reservoir computing is used as a source for reservoir of states necessary for simple tuning of the readout layer.
Abstract: We present results showing the capability of concrete-based information processing substrate in the signal classification task in accordance with in materio computing paradigm. As the Reservoir Computing is a suitable model for describing embedded in materio computation, we propose that this type of presented basic construction unit can be used as a source for “reservoir of states” necessary for simple tuning of the readout layer. We present an electrical characterization of the set of samples with different additive concentrations followed by a dynamical analysis of selected specimens showing fingerprints of memfractive properties. As part of dynamic analysis, several fractal dimensions and entropy parameters for the output signal were analyzed to explore the richness of the reservoir configuration space. In addition, to investigate the chaotic nature and self-affinity of the signal, Lyapunov exponents and Detrended Fluctuation Analysis exponents were calculated. Moreover, on the basis of obtained parameters, classification of the signal waveform shapes can be performed in scenarios explicitly tuned for a given device terminal.

4 citations

References
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Journal ArticleDOI
01 May 2008-Nature
TL;DR: It is shown, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage.
Abstract: Anyone who ever took an electronics laboratory class will be familiar with the fundamental passive circuit elements: the resistor, the capacitor and the inductor. However, in 1971 Leon Chua reasoned from symmetry arguments that there should be a fourth fundamental element, which he called a memristor (short for memory resistor). Although he showed that such an element has many interesting and valuable circuit properties, until now no one has presented either a useful physical model or an example of a memristor. Here we show, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage. These results serve as the foundation for understanding a wide range of hysteretic current-voltage behaviour observed in many nanoscale electronic devices that involve the motion of charged atomic or molecular species, in particular certain titanium dioxide cross-point switches.

8,971 citations

Journal ArticleDOI
TL;DR: In situ click chemistry is used to develop COX-2 specific inhibitors with high in vivo anti-inflammatory activity, significantly higher than that of widely used selective cyclooxygenase-2 inhibitors.
Abstract: Cyclooxygenase-2 isozyme is a promising anti-inflammatory drug target, and overexpression of this enzyme is also associated with several cancers and neurodegenerative diseases. The amino-acid sequence and structural similarity between inducible cyclooxygenase-2 and housekeeping cyclooxygenase-1 isoforms present a significant challenge to design selective cyclooxygenase-2 inhibitors. Herein, we describe the use of the cyclooxygenase-2 active site as a reaction vessel for the in situ generation of its own highly specific inhibitors. Multi-component competitive-binding studies confirmed that the cyclooxygenase-2 isozyme can judiciously select most appropriate chemical building blocks from a pool of chemicals to build its own highly potent inhibitor. Herein, with the use of kinetic target-guided synthesis, also termed as in situ click chemistry, we describe the discovery of two highly potent and selective cyclooxygenase-2 isozyme inhibitors. The in vivo anti-inflammatory activity of these two novel small molecules is significantly higher than that of widely used selective cyclooxygenase-2 inhibitors. Traditional inflammation and pain relief drugs target both cyclooxygenase 1 and 2 (COX-1 and COX-2), causing severe side effects. Here, the authors use in situ click chemistry to develop COX-2 specific inhibitors with high in vivo anti-inflammatory activity.

6,061 citations

Book
D. O. Hebb1
01 Jan 1949
TL;DR: In this paper, the authors discuss the first stage of perception: growth of the assembly, the phase sequence, and the problem of Motivational Drift, which is the line of attack.
Abstract: Contents: Introduction. The Problem and the Line of Attack. Summation and Learning in Perception. Field Theory and Equipotentiality. The First Stage of Perception: Growth of the Assembly. Perception of a Complex: The Phase Sequence. Development of the Learning Capacity. Higher and Lower Processes Related to Learning. Problems of Motivation: Pain and Hunger. The Problem of Motivational Drift. Emotional Disturbances. The Growth and Decline of Intelligence.

5,038 citations

Journal ArticleDOI
TL;DR: The results underscore the importance of precise spike timing, synaptic strength, and postsynaptic cell type in the activity-induced modification of central synapses and suggest that Hebb’s rule may need to incorporate a quantitative consideration of spike timing that reflects the narrow and asymmetric window for the induction of synaptic modification.
Abstract: In cultures of dissociated rat hippocampal neurons, persistent potentiation and depression of glutamatergic synapses were induced by correlated spiking of presynaptic and postsynaptic neurons. The relative timing between the presynaptic and postsynaptic spiking determined the direction and the extent of synaptic changes. Repetitive postsynaptic spiking within a time window of 20 msec after presynaptic activation resulted in long-term potentiation (LTP), whereas postsynaptic spiking within a window of 20 msec before the repetitive presynaptic activation led to long-term depression (LTD). Significant LTP occurred only at synapses with relatively low initial strength, whereas the extent of LTD did not show obvious dependence on the initial synaptic strength. Both LTP and LTD depended on the activation of NMDA receptors and were absent in cases in which the postsynaptic neurons were GABAergic in nature. Blockade of L-type calcium channels with nimodipine abolished the induction of LTD and reduced the extent of LTP. These results underscore the importance of precise spike timing, synaptic strength, and postsynaptic cell type in the activity-induced modification of central synapses and suggest that Hebb’s rule may need to incorporate a quantitative consideration of spike timing that reflects the narrow and asymmetric window for the induction of synaptic modification.

4,382 citations

Journal ArticleDOI
02 Apr 2004-Science
TL;DR: A method for learning nonlinear systems, echo state networks (ESNs), which employ artificial recurrent neural networks in a way that has recently been proposed independently as a learning mechanism in biological brains is presented.
Abstract: We present a method for learning nonlinear systems, echo state networks (ESNs). ESNs employ artificial recurrent neural networks in a way that has recently been proposed independently as a learning mechanism in biological brains. The learning method is computationally efficient and easy to use. On a benchmark task of predicting a chaotic time series, accuracy is improved by a factor of 2400 over previous techniques. The potential for engineering applications is illustrated by equalizing a communication channel, where the signal error rate is improved by two orders of magnitude.

3,122 citations