Acupuncture in the Treatment of a Female Patient Suffering from Chronic Schizophrenia and Sleep Disorders by Peggy Bosch, Sabina Lim, Sujung Yeo, Sook-Hyun Lee, Heike Staudte, Maurits van den Noort

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The MMP-1/PAR-1 Axis Enhances Proliferation and Neuronal Differentiation of Adult Hippocampal Neural Progenitor Cells by Maria Maddalena Valente, Megan Allen, Valeria Bortolotto, Seung T. Lim, Katherine Conant, Mariagrazia Grilli

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Research on the robustness of convolutional neural networks in image recognition by Dian LIN, Li PAN, Ping YI

“…Convolutional neural network is one of the key technologies in the application of image recognition and processing in artificial intelligence.Its wide application makes researches on its robustness more and more important.Previous researches on robustness of neural networks were too sweeping and most of them focused on adversarial robustness, which causes difficulty in further study in the mechanism of neural network robustness.The related researches of neuroscience were introduced and the concept of visual robustness was put forward.By studying the similarity and difference between neural network models and human visual system, the internal mechanism and faults of neural network robustness were revealed.The researches of neural network robustness in recent years were reviewed, and the reasons for the lack of robustness of neural network models were analyzed.The lack of robustness of neural networks is reflected in their sensitivity to small perturbations.The reason is that neural networks tend to learn high-frequency information for calculation and inference, which is difficult for humans to recognize.High-frequency information is easily affected by perturbations, and eventually causes mistakes of models.Previous researches on robustness mostly focused on mathematical properties of models, and were limited in the natural faults of neural networks.Visual robustness extends the traditional concept of robustness.The traditional concept of robustness measures the discrimination ability of models for distorted image examples.Distorted examples and clean examples can get correct outputs through robust models.Visual robustness measures the consistency between models and humans in discrimination ability.Visual robustness combines the research methods and achievements of neuroscience and psychology with artificial intelligence.The development of neuroscience in the field of vision were reviewed, and the application of research methods of cognitive psychology in neural network robustness were discussed.Human visual system has advantages in learning and abstract ability, whill neural network models have better performance in calculation speed and memory.The difference between the physiological structure of human brain and the logical structure of neural network models is the key factor leading to the problem of robustness of neural networks.The research of visual robustness requires deeper understanding of human visual system.Revealing the differences in cognitive mechanism between human visual system and neural network models and effectively improving the algorithm are the development trends of neural network robustness and even artificial intelligence.…”
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Functional Autonomy Affects Elderly Spatial Perception in Body-Centered Coordinates by Giorgia Committeri, Valentina Sebastiani, Francesco de Pasquale, Massimiliano Stocchi, Chiara Fini

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The R18 Polyarginine Peptide Is More Effective Than the TAT-NR2B9c (NA-1) Peptide When Administered 60 Minutes after Permanent Middle Cerebral Artery Occlusion in the Rat by D. Milani, N. W. Knuckey, R. S. Anderton, J. L. Cross, B. P. Meloni

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A Novel Nitronyl Nitroxide with Salicylic Acid Framework Attenuates Pain Hypersensitivity and Ectopic Neuronal Discharges in Radicular Low Back Pain by Wen-Juan Han, Lei Chen, Hai-Bo Wang, Xiang-Zeng Liu, San-Jue Hu, Xiao-Li Sun, Ceng Luo

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Sleep in Genetically Confirmed Pantothenate Kinase-Associated Neurodegeneration: A Video-Polysomnographic Study by Maria Livia Fantini, Giovanni Cossu, Andrea Molari, Monia Cabinio, Ozlem Uyanik, Roberto Cilia, Maurizio Melis, Angelo Antonini, Luigi Ferini-Strambi

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Human Transcriptome and Chromatin Modifications: An ENCODE Perspective by Li Shen, Inchan Choi, Eric J. Nestler, Kyoung-Jae Won

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Astrocytes Control Neuronal Excitability in the Nucleus Accumbens by Tommaso Fellin, Marcello D'Ascenzo, Philip G. Haydon

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Emerging Roles of Synapse Organizers in the Regulation of Critical Periods by Adema Ribic, Thomas Biederer

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GABAergic Neuron Specification in the Spinal Cord, the Cerebellum, and the Cochlear Nucleus by Kei Hori, Mikio Hoshino

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Stress Effects on Multiple Memory System Interactions by Deborah Ness, Pasquale Calabrese

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Correction: Inflammasomes in neurodegenerative diseases by Qianchen Wang, Songwei Yang, Xuan Zhang, Shanshan Zhang, Liping Chen, Wanxue Wang, Naihong Chen, Jiaqing Yan

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The Enigma of the Tinnitus-Free Dream State in a Bayesian World by Dirk De Ridder, Kathleen Joos, Sven Vanneste

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Genetic Rat Models of Parkinson's Disease by Ryan M. Welchko, Xavier T. Lévêque, Gary L. Dunbar

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Serotonergic Dysfunction in Parkinson's Disease and Its Relevance to Disability by Marios Politis, Clare Loane

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Pharmacological management of gambling disorder: A systematic review and network meta-analysis by Konstantinos Ioannidis, Cinzia Del Giovane, Charidimos Tzagarakis, Jeremy E. Solly, Samuel J. Westwood, Valeria Parlatini, Henrietta Bowden-Jones, Jon E. Grant, Samuele Cortese, Samuel R. Chamberlain

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Feedback of aggregate patient-reported outcomes (PROs) data to clinicians and hospital end users: findings from an Australian codesign workshop process by Monique F Kilkenny, Dominique A Cadilhac, Shaun L Hancock, Violet Marion, Paulette Kelly, Sibilah Breen, Benjamin Clissold, Lauren Sanders, Olivia Francis Ryan, Penina Gunzburg, Shae Cooke, Lauren Guy

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TAS2R38 genotype and CRS severity in children with cystic fibrosis by Elena Cantone, Antonella Tosco, Angela Sepe, Valeria Raia, Rossella Negri, Alice Castaldo, Chiara Cimbalo, Paolo Pezzella, Mario Brandon Russo, Giusi Grimaldi, Claudio Di Nola, Luigi Greco

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Genomic evolution of SARS-CoV-2 in Morocco: Insights from whole genome sequences collected from 2020 to 2024 by Hamza GHAMMAZ, Marouane MELLOUL, Ahlam MBARKI, Mouhssine HEMLALI, Taha CHOUATI, Hicham EL ANNAZ, Nadia TOUIL, Mostafa ELOUENNASS, Khalid ENNIBI, Elmostafa EL FAHIME

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