Computational and Mathematical Methods for Neuroscience
This reprint immerses readers in the latest advancements in the computational and mathematical modeling of neural systems, with a focus on brain functionality. It explores foundational principles, established models, and emerging technologies that are shaping the future of computational neuroscience...
-д хадгалсан:
| Формат: | Online |
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| Хэл сонгох: | англи |
| Хэвлэсэн: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Нөхцлүүд: | |
| Онлайн хандалт: | ONIX_20250812T110751_9783725834938_41 |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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| _version_ | 1869530860305252352 |
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| collection | Directory of Open Access Books |
| description | This reprint immerses readers in the latest advancements in the computational and mathematical modeling of neural systems, with a focus on brain functionality. It explores foundational principles, established models, and emerging technologies that are shaping the future of computational neuroscience. By integrating theoretical foundations with empirical data, the approaches presented not only enhance our understanding of neural dynamics but also pave the way for transformative applications in clinical practice and therapeutic innovation. This special issue underscores the pivotal role of computational methodologies—including machine learning, network analysis, brain–computer interfaces, and predictive modeling—in unraveling the complexities of brain function, cognition, and behavior. Addressing key challenges in data integration and model validation, the methods described in this reprint demonstrate the vast potential of these techniques to drive groundbreaking discoveries with far-reaching implications for medicine, technology, and neuroscience. From improving medical diagnostics to refining cognitive models and developing innovative statistical frameworks, this edition strengthens our ability to analyze, predict, and interpret brain activity with unprecedented precision. By showcasing cutting-edge methodologies and their real-world impact, we aim to inspire further research and push the boundaries of neuroscience, unlocking new horizons in our understanding of the human mind. |
| format | Online |
| id | doab-20.500.12854ir-165285 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1652852025-08-12T09:17:34Z Computational and Mathematical Methods for Neuroscience Pisarchik, Alexander N. brain–machine interface brain–computer interface embodiment sensorial feedback Alzheimer’s disease image processing deep learning transfer learning classification BCI SSVEP CNN EEG data augmentation transfer-learning parallelism biomarker laboratory test graphical statistics mismatch negativity somatosensory stimuli cerebral palsy cognitive enhancement vigilance inertial measurement units psychomotor vigilance task head micromovements body posture brain magnetoencephalography (MEG) network hypergraph coherence visual perception emotion recognition complex network ordinal patterns tacrine radiopharmaceuticals molecular modeling PET SPECT medical image-to-image translation generative adversarial networks dMRI data augmentation macaque brain image feature extraction transformer LeViT hyperparameter tuning model optimization neuroimaging neurodegenerative diseases ionic channels random process psychometric function geometric distribution Gaussian distribution threshold exhausting exercise maximal oxygen consumption fatigue central governor endurance cycling diffusion tensor imaging whole-brain tractography biomarkers neural networks multilayer perceptron compressed weight matrix weight density sparsity stereoelectroencephalography focal epilepsy hyperventilation brain dynamics network analysis phase transfer entropy n/a thema EDItEUR::M Medicine and Nursing thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences This reprint immerses readers in the latest advancements in the computational and mathematical modeling of neural systems, with a focus on brain functionality. It explores foundational principles, established models, and emerging technologies that are shaping the future of computational neuroscience. By integrating theoretical foundations with empirical data, the approaches presented not only enhance our understanding of neural dynamics but also pave the way for transformative applications in clinical practice and therapeutic innovation. This special issue underscores the pivotal role of computational methodologies—including machine learning, network analysis, brain–computer interfaces, and predictive modeling—in unraveling the complexities of brain function, cognition, and behavior. Addressing key challenges in data integration and model validation, the methods described in this reprint demonstrate the vast potential of these techniques to drive groundbreaking discoveries with far-reaching implications for medicine, technology, and neuroscience. From improving medical diagnostics to refining cognitive models and developing innovative statistical frameworks, this edition strengthens our ability to analyze, predict, and interpret brain activity with unprecedented precision. By showcasing cutting-edge methodologies and their real-world impact, we aim to inspire further research and push the boundaries of neuroscience, unlocking new horizons in our understanding of the human mind. 2025-08-12T09:17:31Z 2025-08-12T09:17:31Z 2025 book ONIX_20250812T110751_9783725834938_41 9783725834938 9783725834945 https://directory.doabooks.org/handle/20.500.12854/165285 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10662 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-3494-5 10.3390/books978-3-7258-3494-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725834938 9783725834945 294 open access |
| spellingShingle | brain–machine interface brain–computer interface embodiment sensorial feedback Alzheimer’s disease image processing deep learning transfer learning classification BCI SSVEP CNN EEG data augmentation transfer-learning parallelism biomarker laboratory test graphical statistics mismatch negativity somatosensory stimuli cerebral palsy cognitive enhancement vigilance inertial measurement units psychomotor vigilance task head micromovements body posture brain magnetoencephalography (MEG) network hypergraph coherence visual perception emotion recognition complex network ordinal patterns tacrine radiopharmaceuticals molecular modeling PET SPECT medical image-to-image translation generative adversarial networks dMRI data augmentation macaque brain image feature extraction transformer LeViT hyperparameter tuning model optimization neuroimaging neurodegenerative diseases ionic channels random process psychometric function geometric distribution Gaussian distribution threshold exhausting exercise maximal oxygen consumption fatigue central governor endurance cycling diffusion tensor imaging whole-brain tractography biomarkers neural networks multilayer perceptron compressed weight matrix weight density sparsity stereoelectroencephalography focal epilepsy hyperventilation brain dynamics network analysis phase transfer entropy n/a thema EDItEUR::M Medicine and Nursing thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences Computational and Mathematical Methods for Neuroscience |
| title | Computational and Mathematical Methods for Neuroscience |
| title_full | Computational and Mathematical Methods for Neuroscience |
| title_fullStr | Computational and Mathematical Methods for Neuroscience |
| title_full_unstemmed | Computational and Mathematical Methods for Neuroscience |
| title_short | Computational and Mathematical Methods for Neuroscience |
| title_sort | computational and mathematical methods for neuroscience |
| topic | brain–machine interface brain–computer interface embodiment sensorial feedback Alzheimer’s disease image processing deep learning transfer learning classification BCI SSVEP CNN EEG data augmentation transfer-learning parallelism biomarker laboratory test graphical statistics mismatch negativity somatosensory stimuli cerebral palsy cognitive enhancement vigilance inertial measurement units psychomotor vigilance task head micromovements body posture brain magnetoencephalography (MEG) network hypergraph coherence visual perception emotion recognition complex network ordinal patterns tacrine radiopharmaceuticals molecular modeling PET SPECT medical image-to-image translation generative adversarial networks dMRI data augmentation macaque brain image feature extraction transformer LeViT hyperparameter tuning model optimization neuroimaging neurodegenerative diseases ionic channels random process psychometric function geometric distribution Gaussian distribution threshold exhausting exercise maximal oxygen consumption fatigue central governor endurance cycling diffusion tensor imaging whole-brain tractography biomarkers neural networks multilayer perceptron compressed weight matrix weight density sparsity stereoelectroencephalography focal epilepsy hyperventilation brain dynamics network analysis phase transfer entropy n/a thema EDItEUR::M Medicine and Nursing thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| topic_facet | brain–machine interface brain–computer interface embodiment sensorial feedback Alzheimer’s disease image processing deep learning transfer learning classification BCI SSVEP CNN EEG data augmentation transfer-learning parallelism biomarker laboratory test graphical statistics mismatch negativity somatosensory stimuli cerebral palsy cognitive enhancement vigilance inertial measurement units psychomotor vigilance task head micromovements body posture brain magnetoencephalography (MEG) network hypergraph coherence visual perception emotion recognition complex network ordinal patterns tacrine radiopharmaceuticals molecular modeling PET SPECT medical image-to-image translation generative adversarial networks dMRI data augmentation macaque brain image feature extraction transformer LeViT hyperparameter tuning model optimization neuroimaging neurodegenerative diseases ionic channels random process psychometric function geometric distribution Gaussian distribution threshold exhausting exercise maximal oxygen consumption fatigue central governor endurance cycling diffusion tensor imaging whole-brain tractography biomarkers neural networks multilayer perceptron compressed weight matrix weight density sparsity stereoelectroencephalography focal epilepsy hyperventilation brain dynamics network analysis phase transfer entropy n/a thema EDItEUR::M Medicine and Nursing thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| url | ONIX_20250812T110751_9783725834938_41 |