It was proposed that the human visual system analyzes images into square wavelets. To test this view, comparisons were made between the perceived similarity-dissimilarity of alphabet letters and the wavelet analyses of those same letters. For the proposal to be considered tenable, the coefficients of the wavelet analysis of similar letters must be similar, and the coefficients of the wavelet analysis of dissimilar letters must be dissimilar. From a selection of 12 letters, four pairs of letters had been reported by Van der Heijden, Mathas, and Van den Roovaart as very similar, and four other pairs of letters dissimilar. Each of the 12 letters was separately depicted in 8 x 8 matrices, and the signal represented by each of the matrices was analyzed into square wavelets using a new and original procedure which yielded a single set of coefficients for each matrix. Correlations between sets of coefficients were high (r ranged from .88 to .58) for those letter pairs judged high in similarity; correlations were low (r ranged from -.02 to .29) for those letter pairs judged low in similarity. When the correlations between the coefficients of wavelets of all eight-letter pairs were compared with the judged similarity-dissimilarity of all eight-letter pairs, the linear agreement was statistically significant. Agreement was found between the neurophysiological mapping of receptive fields of visual cortical neurons and the vectors or the pattern of pluses and minuses which characterized the wavelet analysis. Furthermore, regeneration of the visual image, or the pattern of neural activity representing the image, could be described by a tree-like flow of information among visual cortical neurons which received response data from visual receptive fields, the response data being wavelet coefficients. Results indicate the analysis accurately produces reliable transformations of visual patterns and may be a process used by the visual system.
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http://dx.doi.org/10.2466/pms.2003.97.2.407 | DOI Listing |
J Med Internet Res
January 2025
Knight Foundation of Computing & Information Sciences, Florida International University, Miami, FL, United States.
Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.
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Department of Materials Physics, Graduate School of Engineering, Nagoya University, Chikusa-ku, Nagoya 464-8603, Japan.
The distribution of dopants in host crystals significantly influences the chemical and electronic properties of materials. Therefore, determining this distribution is crucial for optimizing material performance. The previously developed statistical ALCHEMI (St-ALCHEMI), an extension of the atom-location by channeling-enhanced microanalysis (ALCHEMI) technique, utilizes variations in electron channeling based on the beam direction relative to the crystal orientation.
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Department of Chemistry, North Tehran Branch, Islamic Azad University, Tehran, Iran. Electronic address:
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View Article and Find Full Text PDFSensors (Basel)
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School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
This study aimed to predict and fit the nonlinear dynamic grip force of the human upper limb using surface electromyographic (sEMG) signals. The research employed a time-series-based neural network, NARX, to establish a mapping relationship between the electromyographic signals of the forearm muscle groups and dynamic grip force. Three-channel electromyographic signal acquisition equipment and a grip force sensor were used to record muscle signals and grip force data of the subjects under specific dynamic force conditions.
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