Recall and recognition memory in concept identification
Recall and recognition memory in concept identification, discussing presentation time /PT/
Calfee, R. C.↗
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Consolidation and retroactive interference in short-term recognition memory for pitch.
Consolidation and retroactive interference in short-term recognition memory for pitch
MASKING↗
Retroactive interference in short-term recognition memory for pitch
Retroactive interference stimuli effects on pitch discrimination in short term recognition memory task
Massaro, D. W.↗
Exponential decay and independence from irrelevant associations in short-term recognition memory for serial order.
Exponential decay and independence from irrelevant associations in short-term recognition memory for digits presented in serial order
TIME FACTOR↗
Working and strategic memory deficits in schizophrenia
Working memory and its contribution to performance on strategic memory tests in schizophrenia were studied. Patients (n = 18) and control participants (n = 15), all men, received tests of immediate memory (forward digit span), working memory (listening, computation, and backward digit span), and long-term strategic (free recall, temporal order, and self-ordered pointing) and nonstrategic (recognition) memory. Schizophrenia patients performed worse on all tests. Education, verbal intelligence, and immediate memory capacity did not account for deficits in working memory in schizophrenia patients. Reduced working memory capacity accounted for group differences in strategic memory but not in recognition memory. Working memory impairment may be central to the profile of impaired cognitive performance in schizophrenia and is consistent with hypothesized frontal lobe dysfunction associated with this disease. Additional medial-temporal dysfunction may account for the recognition memory deficit.
Memory Disorders/etiology/physiopathology↗
Examining the Effects of 4He Exposure on the Gut-Brain Axis
Beyond low earth orbit, space radiation poses significant risks to astronaut health. Previous studies have shown that the microbial composition of the gastrointestinal (GI) microbiome changes upon exposure to high linear energy transfer radiation. Interestingly, radiation-induced shifts in GI microbiota composition are linked to various neuropsychological disorders. Herein, we aimed to study changes in GI microbiota and behaviors of rats exposed to whole-body radiation (0, 5, or 25 cGy 4 He, 250 MeV/n) at approximately 6 months of age. Fecal samples were collected 24 hours prior to 4 He radiation and 24 hours and 7 days post-exposure for quantitative PCR analyses to assess fecal levels of spore-forming bacteria (SFB), Bifidobacterium, Lactobacillus, and Akkermansia. Rats were also tested in the social odor recognition memory (SORM) test at 7 days following 4 He exposure. A subset of rats was euthanized 90 minutes following completion of the SORM test, and GI tissue from small intestine to colon were prepared for examining overall histological changes and immunohistochemical staining for serotonin (5-HT). No notable pathological changes were observed in GI tissues. Akkermansia spp. and SFB were significantly decreased the 25 cGy group at 24 hours and 7 days post-exposure compared to pre-exposure, respectively. Bifidobacterium and Lactobacillus spp. showed no significant changes. 5-HT production was significantly higher in the proximal small intestine and the cecum in the 25 cGy group compared to the sham group. The 25 cGy group exhibited deficits in recognition in SORM testing at 7 days post-exposure. Taken together, these results suggest a connection between GI microbiome 3 composition, serotonin production, and neurobehavioral performance, and that this connection may be disrupted upon exposure to 25 cGy of 4 He ions
Carli B Jones↗
High speed optical object recognition processor with massive holographic memory
Real-time object recognition using a compact grayscale optical correlator will be introduced. A holographic memory module for storing a large bank of optimum correlation filters, to accommodate the large data throughput rate needed for many real-world applications, has also been developed. System architecture of the optical processor and the holographic memory will be presented. Application examples of this object recognition technology will also be demonstrated.
512 X 512 grayscale optical correlator holographic↗
An empirical investigation of sparse distributed memory using discrete speech recognition
Presented here is a step by step analysis of how the basic Sparse Distributed Memory (SDM) model can be modified to enhance its generalization capabilities for classification tasks. Data is taken from speech generated by a single talker. Experiments are used to investigate the theory of associative memories and the question of generalization from specific instances.
Danforth, Douglas G.↗
Two-dimensional shape recognition using sparse distributed memory
Researchers propose a method for recognizing two-dimensional shapes (hand-drawn characters, for example) with an associative memory. The method consists of two stages: first, the image is preprocessed to extract tangents to the contour of the shape; second, the set of tangents is converted to a long bit string for recognition with sparse distributed memory (SDM). SDM provides a simple, massively parallel architecture for an associative memory. Long bit vectors (256 to 1000 bits, for example) serve as both data and addresses to the memory, and patterns are grouped or classified according to similarity in Hamming distance. At the moment, tangents are extracted in a simple manner by progressively blurring the image and then using a Canny-type edge detector (Canny, 1986) to find edges at each stage of blurring. This results in a grid of tangents. While the technique used for obtaining the tangents is at present rather ad hoc, researchers plan to adopt an existing framework for extracting edge orientation information over a variety of resolutions, such as suggested by Watson (1987, 1983), Marr and Hildreth (1980), or Canny (1986).
Kanerva, Pentti↗
Automatic ground control point recognition with parallel associative memory
The basic principle of the associative memory is to match the unknown input pattern against a stored training set, and responding with the 'closest match' and the corresponding label. Generally, an associative memory system requires two preparatory steps: selecting attributes of the pattern class, and training the system by associating patterns with labels. Experimental results gained from using Parallel Associative Memory are presented. The primary concern is an automatic search for ground control points in aerial photographs. Synthetic patterns are tested followed by real data. The results are encouraging as a relatively high level of correct matches is reached.
Al-Tahir, Raid↗
Pattern recognition with parallel associative memory
An examination is conducted of the feasibility of searching targets in aerial photographs by means of a parallel associative memory (PAM) that is based on the nearest-neighbor algorithm; the Hamming distance is used as a measure of closeness, in order to discriminate patterns. Attention has been given to targets typically used for ground-control points. The method developed sorts out approximate target positions where precise localizations are needed, in the course of the data-acquisition process. The majority of control points in different images were correctly identified.
Toth, Charles K.↗
Machine parts recognition using a trinary associative memory
The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.
Awwal, Abdul Ahad S.↗
Some methods of encoding simple visual images for use with a sparse distributed memory, with applications to character recognition
To study the problems of encoding visual images for use with a Sparse Distributed Memory (SDM), I consider a specific class of images- those that consist of several pieces, each of which is a line segment or an arc of a circle. This class includes line drawings of characters such as letters of the alphabet. I give a method of representing a segment of an arc by five numbers in a continuous way; that is, similar arcs have similar representations. I also give methods for encoding these numbers as bit strings in an approximately continuous way. The set of possible segments and arcs may be viewed as a five-dimensional manifold M, whose structure is like a Mobious strip. An image, considered to be an unordered set of segments and arcs, is therefore represented by a set of points in M - one for each piece. I then discuss the problem of constructing a preprocessor to find the segments and arcs in these images, although a preprocessor has not been developed. I also describe a possible extension of the representation.
Jaeckel, Louis A.↗
Identification of aerospace acoustic sources using sparse distributed associative memory
A pattern recognition system has been developed to classify five different aerospace acoustic sources. In this paper the performance of two new classifiers, an associative memory classifier and a neural network classifier, is compared to the performance of a previously designed system. Sources are classified using features calculated from the time and frequency domain. Each classifier undergoes a training period where it learns to classify sources correctly based on a set of known sources. After training the classifier is tested with unknown sources. Results show that over 96 percent of sources were identified correctly with the new associative memory classifier. The neural network classifier identified over 81 percent of the sources correctly.
Scott, E. A.↗
Creative-Dynamics Approach To Neural Intelligence
Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.
Zak, Michail A.↗
Terminal attractors in neural networks
A new type of attractor (terminal attractors) for content-addressable memory, associative memory, and pattern recognition in artificial neural networks operating in continuous time is introduced. The idea of a terminal attractor is based upon a violation of the Lipschitz condition at a fixed point. As a result, the fixed point becomes a singular solution which envelopes the family of regular solutions, while each regular solution approaches such an attractor in finite time. It will be shown that terminal attractors can be incorporated into neural networks such that any desired set of these attractors with prescribed basins is provided by an appropriate selection of the synaptic weights. The applications of terminal attractors for content-addressable and associative memories, pattern recognition, self-organization, and for dynamical training are illustrated.
Zak, Michail↗
Long-term modifications of synaptic efficacy in the human inferior and middle temporal cortex
The primate temporal cortex has been demonstrated to play an important role in visual memory and pattern recognition. It is of particular interest to investigate whether activity-dependent modification of synaptic efficacy, a presumptive mechanism for learning and memory, is present in this cortical region. Here we address this issue by examining the induction of synaptic plasticity in surgically resected human inferior and middle temporal cortex. The results show that synaptic strength in the human temporal cortex could undergo bidirectional modifications, depending on the pattern of conditioning stimulation. High frequency stimulation (100 or 40 Hz) in layer IV induced long-term potentiation (LTP) of both intracellular excitatory postsynaptic potentials and evoked field potentials in layers II/III. The LTP induced by 100 Hz tetanus was blocked by 50-100 microM DL-2-amino-5-phosphonovaleric acid, suggesting that N-methyl-D-aspartate receptors were responsible for its induction. Long-term depression (LTD) was elicited by prolonged low frequency stimulation (1 Hz, 15 min). It was reduced, but not completely blocked, by DL-2-amino-5-phosphonovaleric acid, implying that some other mechanisms in addition to N-methyl-DL-aspartate receptors were involved in LTD induction. LTD was input-specific, i.e., low frequency stimulation of one pathway produced LTD of synaptic transmission in that pathway only. Finally, the LTP and LTD could reverse each other, suggesting that they can act cooperatively to modify the functional state of cortical network. These results suggest that LTP and LTD are possible mechanisms for the visual memory and pattern recognition functions performed in the human temporal cortex.
NASA Discipline Neuroscience↗