Appetitive reversal learning differences of two honey bee subspecies with different foraging behaviors by Eddie Pérez Claudio, Yoselyn Rodriguez-Cruz, Okan Can Arslan, Tugrul Giray, José Luis Agosto Rivera, Meral Kence, Harrington Wells, Charles I. Abramson

“…In the initial or Acquisition phase of the test we examined specifically discrimination learning, where bees were trained to respond to a paired conditioned stimulus with an unconditioned stimulus and not to respond to a second conditioned stimulus that is not followed by an unconditioned stimulus. …”
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Genetic Perturbation of TIA1 Reveals a Physiological Role in Fear Memory by Joseph B. Rayman, Joud Hijazi, Xiang Li, Nancy Kedersha, Paul J. Anderson, Eric R. Kandel

“…Here, we show that TIA1 bidirectionally modulates stress-dependent synaptic plasticity in the hippocampus, a brain region involved in fear memory and olfactory discrimination learning. At the behavioral level, conditioned odor avoidance is potentiated by TIA1 deletion, whereas overexpression of TIA1 in the ventral hippocampus inhibits both contextual fear memory and avoidance. …”
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Do cows see the forest or the trees? A preliminary investigation of attentional scope as a potential indicator of emotional state in dairy cows housed with their calves by Heather W. Neave, Jean-Loup Rault, Melissa Bateson, Emma Hvidtfeldt Jensen, Margit Bak Jensen

“…Cows were trained to approach or avoid hierarchical images on a screen that were consistent in local and global elements (i.e., 13 small circles or crosses arranged in an overall circle or cross). After discrimination learning (>80% correct, over two consecutive days), 14 cows proceeded to test (n = 6 each full-and part-time; n = 2 no-contact, not analyzed). …”
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Reversibility of n-3 fatty acid deficiency-induced alterations of learning behavior in the rat: level of n-6 fatty acids as another critical factor by Atsushi Ikemoto, Masayo Ohishi, Yosuke Sato, Noriaki Hata, Yoshihisa Misawa, Yoichi Fujii, Harumi Okuyama

“…Rats fed a semipurified diet supplemented with 3% (w/w) safflower oil [Saf, n-3 fatty acid deficient, high linoleic acid (18:2n-6)] through two generations exhibit decreased correct response ratios in a brightness-discrimination learning test compared with rats fed 3% perilla oil [Per, high α-linolenic acid (18:3n-3)]. …”
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Mice carrying a schizophrenia-associated mutation of the Arhgap10 gene are vulnerable to the effects of methamphetamine treatment on cognitive function: association with morphologi... by Kazuhiro Hada, Bolati Wulaer, Taku Nagai, Norimichi Itoh, Masahito Sawahata, Akira Sobue, Hiroyuki Mizoguchi, Daisuke Mori, Itaru Kushima, Toshitaka Nabeshima, Norio Ozaki, Kiyofumi Yamada

“…There was no difference in touchscreen-based visual discrimination learning between Arhgap10 S490P/NHEJ and wild-type mice, but a significant impairment of visual discrimination was evident in Arhgap10 S490P/NHEJ mice but not wild-type mice when they were treated with methamphetamine. …”
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Static internal representation of dynamic situations reveals time compaction in human cognition by José Antonio Villacorta-Atienza, Carlos Calvo Tapia, Sergio Díez-Hermano, Abel Sánchez-Jiménez, Sergey Lobov, Nadia Krilova, Antonio Murciano, Gabriela E. López-Tolsa, Ricardo Pellón, Valeri A. Makarov

“…Methods: We engaged human subjects in a discrimination-learning task consisting in the classification of static and dynamic visual stimuli. …”
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Inhibitory effect of tDCS on auditory evoked response: Simultaneous MEG-tDCS reveals causal role of right auditory cortex in pitch learning by Reiko Matsushita, Sebastian Puschmann, Sylvain Baillet, Robert J. Zatorre

“…Our data show that anodal tDCS of the right AC disrupted pitch discrimination learning up to two days after its application, whereas learning was unaffected by left-AC or sham tDCS. …”
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Reconsidering repurposing: long-term metformin treatment impairs cognition in Alzheimer’s model mice by So Yeon Cho, Eun Woo Kim, Soo Jin Park, Benjamin U. Phillips, Jihyeon Jeong, Hyunjeong Kim, Christopher J. Heath, Daehwan Kim, Yurim Jang, Laura López-Cruz, Lisa M. Saksida, Timothy J. Bussey, Do Yup Lee, Eosu Kim

“…However, chronic treatment led to impairments in memory retention and discrimination learning at older age. Furthermore, metformin caused learning and memory impairment and increased levels of AMPKα1-subunit, β-amyloid oligomers, plaques, phosphorylated tau, and GSK3β expression in AD mice. …”
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Cognitive Performance during the Development of Diabetes in the Zucker Diabetic Fatty Rat by Marcia Spoelder, Yami Bright, Martine C. Morrison, Veerle van Kempen, Lilian de Groodt, Malvina Begalli, Nikita Schuijt, Eva Kruiger, Ronald Bulthuis, Gabriele Gross, Robert Kleemann, Janna A. van Diepen, Judith R. Homberg

“…This study aimed to gain more insight into whether cognition is already impacted during adolescence in a genetic rat model for obesity and type 2 diabetes. Visual discrimination learning throughout adolescence and the level of motivation during early adulthood were investigated in Zucker Diabetic Fatty (ZDF) obese and ZDF lean rats using operant touchscreens. …”
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Boosting visual perceptual learning by transcranial alternating current stimulation over the visual cortex at alpha frequency by Qing He, Xin-Yue Yang, Baoqi Gong, Keyan Bi, Fang Fang

“…Conclusion: TACS can facilitate orientation discrimination learning in a frequency- and location-specific manner. …”
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Video based object representation and classification using multiple covariance matrices. by Yurong Zhang, Quan Liu

“…In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. …”
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The role of prediction error in linguistic generalization and item learning: evidence from an online eye-tracking study by Zhou, H

“…The discriminative learning framework, grounded in principles of learning theory, was recently revitalized as a specific mechanism to carry out language acquisition within a domain-general, input-driven constructivist account. …”

The role of prediction error in linguistic generalization and item learning: evidence from an online eye-tracking study by Zhou, H

“…The discriminative learning framework, grounded in principles of learning theory, was recently revitalized as a specific mechanism to carry out language acquisition within a domain-general, input-driven constructivist account. …”

SUPERVISED OUTLIER DETECTION IN LARGE-SCALE MVS POINT CLOUDS FOR 3D CITY MODELING APPLICATIONS by C. Stucker, A. Richard, J. D. Wegner, K. Schindler

“…We thus propose to discriminatively learn class-specific distributions directly from the data to achieve high precision. …”
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Fine-tuning Strategies for Classifying Community-Engaged Research Studies Using Transformer-Based Models: Algorithm Development and Improvement Study by Brian J Ferrell

“…For the discriminative learning rate technique, we applied different learning rates to different layers of the model, with the aim of providing higher learning rates to layers that are more specialized to the task at hand. …”
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Naive Bayes vs Logistic Regression: Theory, Implementation and Experimental Validation by Tapan Kumar Bhowmik

“…A generative learning under Gaussian Naive Bayes assumption and two discriminative learning techniques based on gradient ascent and Newton-Raphson methods are described to estimate the parameters of LR. …”
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Enhanced dual branches network for arbitrary‐scale image super‐resolution by Guangping Li, Huanling Xiao, Dingkai Liang

“…The SGU module performs discriminant learning for each instance in the same batch. …”
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AUTOMATIC DETECTION AND RECOGNITION OF MAN-MADE OBJECTS IN HIGH RESOLUTION REMOTE SENSING IMAGES USING HIERARCHICAL SEMANTIC GRAPH MODEL by X. Sun, X. Sun, X. Sun, A. Thiele, S. Hinz, K. Fu

“…After training local classifiers to calculate parts properties, we use belief propagation to transmit messages quantitatively, which could enhance the utilization of spatial constrains existed in images. Besides, discriminative learning and generative learning are combined interleavely in the inference procedure, to improve the training error and recognition efficiency. …”
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Information Theoretic-Based Interpretation of a Deep Neural Network Approach in Diagnosing Psychogenic Non-Epileptic Seizures by Sara Gasparini, Maurizio Campolo, Cosimo Ieracitano, Nadia Mammone, Edoardo Ferlazzo, Chiara Sueri, Giovanbattista Gaspare Tripodi, Umberto Aguglia, Francesco Carlo Morabito

“…This deep model gives better classification performance than some other standard discriminative learning algorithms. As in clinical problems there is a need for explaining decisions, an effort has been carried out to qualitatively justify the classification results. …”
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A Data-Driven Regularization Model for Stereo and Flow by Freeman, William T., Wei, Donglai, Liu, Ce

“…We incorporate this data-driven regularization model into a standard Markov Random Field (MRF) model, inferred with a gradient descent algorithm and learned with a discriminative learning approach. Compared to prior state-of-the-art methods, our full model achieves comparable or better results on the KITTI stereo and flow datasets, and improves results on the Sintel Flow dataset under an online estimation setting.…”
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