Neural Mechanisms for Information Compression by Multiple Alignment, Unification and Search

This article describes how an abstract framework for perception and cognition may be realised in terms of neural mechanisms and neural processing. This framework — called information compression by multiple alignment, unification and search (ICMAUS) — has been developed in previous research as a generalized model of any system for processing information, either natural or artificial. It has a range of applications including the analysis and production of natural language, unsupervised inductive learning, recognition of objects and patterns, probabilistic reasoning, and others. The proposals in this article may be seen as an extension and development of Hebb’s (1949) concept of a ‘cell assembly’. The article describes how the concept of ‘pattern’ in the ICMAUS framework may be mapped onto a version of the cell assembly concept and the way in which neural mechanisms may achieve the effect of ‘multiple alignment’ in the ICMAUS framework. By contrast with the Hebbian concept of a cell assembly, it is proposed here that any one neuron can belong in one assembly and only one assembly. A key feature of present proposals, which is not part of the Hebbian concept, is that any cell assembly may contain ‘references’ or ‘codes’ that serve to identify one or more other cell assemblies. This mechanism allows information to be stored in a compressed form, it provides a robust mechanism by which assemblies may be connected to form hierarchies and other kinds of structure, it means that assemblies can express abstract concepts, and it provides solutions to some of the other problems associated with cell assemblies. Drawing on insights derived from the ICMAUS framework, the article also describes how learning may be achieved with neural mechanisms. This concept of learning is significantly different from the Hebbian concept and appears to provide a better account of what we know about human learning

Information Compression, Intelligence, Computing, and Mathematics

This paper presents evidence for the idea that much of artificial intelligence, human perception and cognition, mainstream computing, and mathematics, may be understood as compression of information via the matching and unification of patterns. This is the basis for the "SP theory of intelligence", outlined in the paper and fully described elsewhere. Relevant evidence may be seen: in empirical support for the SP theory; in some advantages of information compression (IC) in terms of biology and engineering; in our use of shorthands and ordinary words in language; in how we merge successive views of any one thing; in visual recognition; in binocular vision; in visual adaptation; in how we learn lexical and grammatical structures in language; and in perceptual constancies. IC via the matching and unification of patterns may be seen in both computing and mathematics: in IC via equations; in the matching and unification of names; in the reduction or removal of redundancy from unary numbers; in the workings of Post's Canonical System and the transition function in the Universal Turing Machine; in the way computers retrieve information from memory; in systems like Prolog; and in the query-by-example technique for information retrieval. The chunking-with-codes technique for IC may be seen in the use of named functions to avoid repetition of computer code. The schema-plus-correction technique may be seen in functions with parameters and in the use of classes in object-oriented programming. And the run-length coding technique may be seen in multiplication, in division, and in several other devices in mathematics and computing. The SP theory resolves the apparent paradox of "decompression by compression". And computing and cognition as IC is compatible with the uses of redundancy in such things as backup copies to safeguard data and understanding speech in a noisy environment

Nanoscale all-oxide-heterostructured bio-inspired optoresponsive nociceptor

Retina nociceptor, as a key sensory receptor, not only enables the transport of warning signals to the human central nervous system upon its exposure to noxious stimuli, but also triggers the motor response that minimizes potential sensitization. In this study, the capability of two-dimensional all-oxide-heterostructured artificial nociceptor as a single device with tunable properties was confirmed. Newly designed nociceptors utilize ultra-thin sub-stoichiometric TiO2-Ga2O3 heterostructures, where the thermally annealed Ga2O3 films play the role of charge transfer controlling component. It is discovered that the phase transformation in Ga2O3 is accompanied by substantial jump in conductivity, induced by thermally assisted internal redox reaction of Ga2O3 nanostructure during annealing. It is also experimentally confirmed that the charge transfer in all-oxide heterostructures can be tuned and controlled by the heterointerfaces manipulation. Results demonstrate that the engineering of heterointerfaces of two-dimensional (2D) films enables the fabrication of either high-sensitive TiO2-Ga2O3 (Ar) or high-threshold TiO2-Ga2O3 (N-2) nociceptors. The hypersensitive nociceptor mimics the functionalities of corneal nociceptors of human eye, whereas the delayed reaction of nociceptor is similar to high-threshold nociceptive characteristics of human sensory system. The long-term stability of 2D nociceptors demonstrates the capability of heterointerfaces engineering for effective control of charge transfer at 2D heterostructured devices

Stereo Matching in Address-Event-Representation (AER) Bio-Inspired Binocular Systems in a Field-Programmable Gate Array (FPGA)

In stereo-vision processing, the image-matching step is essential for results, although it involves a very high computational cost. Moreover, the more information is processed, the more time is spent by the matching algorithm, and the more ine cient it is. Spike-based processing is a relatively new approach that implements processing methods by manipulating spikes one by one at the time they are transmitted, like a human brain. The mammal nervous system can solve much more complex problems, such as visual recognition by manipulating neuron spikes. The spike-based philosophy for visual information processing based on the neuro-inspired address-event-representation (AER) is currently achieving very high performance. The aim of this work was to study the viability of a matching mechanism in stereo-vision systems, using AER codification and its implementation in a field-programmable gate array (FPGA). Some studies have been done before in an AER system with monitored data using a computer; however, this kind of mechanism has not been implemented directly on hardware. To this end, an epipolar geometry basis applied to AER systems was studied and implemented, with other restrictions, in order to achieve good results in a real-time scenario. The results and conclusions are shown, and the viability of its implementation is proven.Ministerio de Economía y Competitividad TEC2016-77785-

Integrated Circuitry to Detect Slippage Inspired by Human Skin and Artificial Retinas

This paper presents a bioinspired integrated tactile coprocessor that is able to generate a warning in the case of slippage via the data provided by a tactile sensor. Some implementations use different layers of piezoresistive and piezoelectric materials to build upon the raw sensor and obtain the static (pressure) as well as the dynamic (slippage) information. In this paper, a simple raw sensor is used, and a circuitry is implemented, which is able to extract the dynamic information from a single piezoresistive layer. The circuitry was inspired by structures found in human skin and retina, as they are biological systems made up of a dense network of receptors. It is largely based on an artificial retina , which is able to detect motion by using relatively simple spatial temporal dynamics. The circuitry was adapted to respond in the bandwidth of microvibrations produced by early slippage, resembling human skin. Experimental measurements from a chip implemented in a 0.35-mum four-metal two-poly standard CMOS process are presented to show both the performance of the building blocks included in each processing node and the operation of the whole system as a detector of early slippage.Ministerio de Economía y Competitividad TEC2006-12376-C02-01Gobierno de España TEC2006- 1572

Response for light scattered in the ocular fundus from double-pass and Hartmann–Shack estimations

Double-pass (DP) and Hartmann--Shack (HS) are complementary techniques based on reflections of light in the ocular fundus that may be used to estimate the optical properties of the human eye. Under conventional data processing, both of these assessment modes provide information on aberrations. In addition, DP data contain the effects of scattering. In the ocular fundus, this phenomenon may arise from the interaction of light with not only the retina, but also deeper layers up to which certain wavelengths may penetrate. In this work, we estimate the response of the ocular fundus to incident light by fitting the deviations between DP and HS estimations using an exponential model. In measurements with negligible intraocular scattering, such differences may be related to the lateral spreading of light that occurs in the ocular fundus due to the diffusive properties of the media at the working wavelength. The proposed model was applied in young healthy eyes to evaluate the performance of scattering in such a population. Besides giving a parameter with information on the ocular fundus, the model contributes to the understanding of the differences between DP and HS estimations.Postprint (author's final draft