The metabolic profiles of brain biopsies obtained at surgery were recorded using capillary gas chromatography (GC). About 160 peaks were seen, of which 105 were used for data analysis. Three classes of brain tissue were examined: normal cerebral cortex, pituitary tumours and " brain" tumours. Pattern recognition analyses of the GC profiles using the SIMCA multivariate programme clearly resolved normal brain tissue from the tumours. Subclassification of the different tumours was more difficult, probable because the number of samples in each tumour class was too small. High-resolution two-dimensional electrophoresis separated the brain biopsies into several hundred different proteins. The combined use of the latter technique and capillary GC-mass spectrometry and pattern recognition analyses gives the possibility of the classification of diseased cells based solely on differences in their biochemical compositions.
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http://dx.doi.org/10.1016/s0021-9673(00)88077-2 | DOI Listing |
J Exp Psychol Gen
January 2025
Department of Psychology, University of Freiburg.
It has long been debated whether latent memory signals determine recognition judgments directly or through a small number of discrete states. Often, signal detection theory (SDT) models instantiate the former perspective, whereas the two-high-threshold (2HT) model instantiates the latter. Kellen and Klauer (2014) conducted a critical test using a ranking paradigm that yielded results in line with common SDT models and incompatible with the 2HT model.
View Article and Find Full Text PDFEfficient visual word recognition presumably relies on orthographic prediction error (oPE) representations. On the basis of a transparent neurocognitive computational model rooted in the principles of the predictive coding framework, we postulated that readers optimize their percept by removing redundant visual signals, allowing them to focus on the informative aspects of the sensory input (i.e.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Department of Psychiatry, University of Oxford, Warneford Ln, Headington, Oxford OX3 7JX, United Kingdom; Oxford Health NHS Foundation Trust, Warneford Ln, Headington, Oxford OX3 7JX, United Kingdom. Electronic address:
Background: The renin angiotensin system (RAS) is implicated in various cognitive processes relevant to anxiety. However, the role of the RAS in pattern separation, a hippocampal memory mechanism that enables discrete encoding of similar stimuli, is unclear. Given the proposed role of this mechanism in overgeneralization and the maintenance of anxiety, we explored the influence of the RAS on mnemonic discrimination i.
View Article and Find Full Text PDFComput Biol Med
January 2025
School of Computer Science, Chungbuk National University, Cheongju 28644, Republic of Korea. Electronic address:
The fusion index is a critical metric for quantitatively assessing the transformation of in vitro muscle cells into myotubes in the biological and medical fields. Traditional methods for calculating this index manually involve the labor-intensive counting of numerous muscle cell nuclei in images, which necessitates determining whether each nucleus is located inside or outside the myotubes, leading to significant inter-observer variation. To address these challenges, this study proposes a three-stage process that integrates the strengths of pattern recognition and deep-learning to automatically calculate the fusion index.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Cognitive Systems Lab, University of Bremen, 28359 Bremen, Germany.
This paper presents an approach for event recognition in sequential images using human body part features and their surrounding context. Key body points were approximated to track and monitor their presence in complex scenarios. Various feature descriptors, including MSER (Maximally Stable Extremal Regions), SURF (Speeded-Up Robust Features), distance transform, and DOF (Degrees of Freedom), were applied to skeleton points, while BRIEF (Binary Robust Independent Elementary Features), HOG (Histogram of Oriented Gradients), FAST (Features from Accelerated Segment Test), and Optical Flow were used on silhouettes or full-body points to capture both geometric and motion-based features.
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