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In addition, simulation data are also used to analyze the relationship between spike correlations and synchronous spike events. Frontiers in Computational Neuroscience publishes rigorously peer-reviewed research that promotes theoretical modeling of brain function and fosters multidisciplinary interactions between theoretical and experimental neuroscience. Frontiers in Computational Neuroscience, 8 (MAY). Frontiers in Computational Neuroscience, Volume 14; doi:10.3389/fncom.2020.563439.s001, Frontiers in Computational Neuroscience, Volume 14; doi:10.3389/fncom.2020.578158.s001. doi: 10.1371/journal.pcbi.1003376. Two sets of simulation data are used to test the effectiveness of the estimation algorithm and the model goodness-of-fit. However, despite its transparent definition, careless use of the Fano factor can easily lead to distorted or even wrong results. Please enable Cookies and reload the page. Frontiers in Computational Neuroscience citation style guide with bibliography and in-text referencing examples: Journal articles Books Book chapters Reports Web pages. Please check back frequently for updates. Journal info (provided by editor) The editor of Frontiers in Computational Neuroscience has not yet provided information for this page. If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. Author; Title; Issue year; Journal title; Type; References of "Frontiers in computational neuroscience" Finally, we use this method to identify network spike correlations evoked by four different acupuncture manipulations. Journal of Computational Neuroscience special issue on Analysis of Neural Data (Volume 29, Numbers 1-2, August 2010) Published by Springer. Frontiers in Computational Neuroscience, Volume 14; doi:10.3389/fncom.2020.578158. Read also provides personalized recommendations to keep you up to date in your field. The scientific journal Frontiers in Computational Neuroscience is included in the Scopus database. IF. When they were first launched, I, like many people, was suspicious. Journal ISSN: 1662-5188. Journal of Computational Neuroscience special issue on Analysis of Neuronal Excitability (Volume 18, Number 3, June 2005) Published by Springer. The best quartile for this journal is Q2. Xiayu Chen, Ming Zhou, Zhengxin Gong, Wei Xu, Xingyu Liu, Taicheng Huang, Frontiers in Computational Neuroscience, Volume 14; doi:10.3389/fncom.2020.580632. In order to identify these network collaborative activities, we analyze the underlying spike correlation in the synchronous spike event. For questions or feedback, please reach us at. Results show that reinforcing manipulations (twirling reinforcing and lifting-thrusting reinforcing) can evoke the third-order spike correlation but reducing manipulations (twirling reducing and lifting-thrusting reducing) does not. Although general deep learning frameworks, such as PyTorch and TensorFlow, could be used to allow such cross-disciplinary investigations, the use of these frameworks typically requires high-level programming expertise and comprehensive mathematical knowledge. • Muscle synergy analysis (MSA) is a dimensionality reduction approach that decomposes a large number of muscle excitations into a small number of time-varying synergy excitations along with time-invariant synergy weights that define the contribution of each synergy excitation to all muscle excitations. Multiple Sclerosis Journal. These include extracting DNN activation, probing and visualizing DNN representations, and mapping DNN representations onto the brain. (2016) Parasuram et al. Your IP: 200.111.112.34 You may need to download version 2.0 now from the Chrome Web Store. Statistically significant clusters were finally mapped to a structural atlas to provide anatomic localization of their location. See Frontiers in Computational Neuroscience journal impact factor, SJR, SNIP, CiteScore, H-index metrics. First, enhancing lesion on Gd-T1w MRI and peri-lesional hyperintensities on T2w/FLAIR were segmented by experts and then registered to a brain atlas. However, it remains unclear how objects are represented in DCNNs with an overwhelming number of features and non-linear operations. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. Search for Library Items Search for Lists ... Internet Resource, Computer File, Journal / Magazine / Newspaper: All Authors / Contributors: Frontiers Research Foundation. Sign In. Year. Based on 2018, SJR is 1.315. Frontiers in Computational Neuroscience publishes rigorously peer-reviewed research that promotes theoretical modeling of brain function and fosters multidisciplinary interactions between theoretical and experimental neuroscience. In this paper, we adopt a log-linear model to describe network response activities evoked by different acupuncture manipulations. Using patients from the two phenotypes, we construct two atlases by quantifying frequency of occurrence of enhancing lesion and peri-lesion hyperintensities, by averaging voxel intensities across the population. Frontiers in Computational Neuroscience. Deep learning allows data representations that have multiple levels of abstraction; however, it does not explicitly provide any insights into the internal operations of DNNs. Comprehending how the brain functions requires an understanding of the dynamics of neuronal assemblies. ISSN 1662-5188 Want full text access to this journal? Analysis of differential involvement was then performed to compute voxel-wise significant differences (p-value < 0.05) across the atlases. Cloudflare Ray ID: 605e4ac708e62875 This is the main reason why synchronous spikes evoked by reinforcing manipulations are more abundant than reducing manipulations. Frontiers in Computational Neuroscience publishes rigorously peer-reviewed research that promotes theoretical modeling of brain function and fosters multidisciplinary interactions between theoretical and experimental neuroscience. The method was evaluated using a gait data set collected from a stroke survivor walking on an instrumented treadmill at self-selected and fastest-comfortable speeds. One of the problems is the unclear dependence of the Fano factor on the spiking rate, which is often neglected or handled insufficiently. More information will be made available shortly. Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma?—A Feasibility Study, Hierarchical Sparse Coding of Objects in Deep Convolutional Neural Networks, Evaluation of Synergy Extrapolation for Predicting Unmeasured Muscle Excitations from Measured Muscle Synergies, DNNBrain: A Unifying Toolbox for Mapping Deep Neural Networks and Brains, Topographic Organization of Correlation Along the Longitudinal and Transverse Axes in Rat Hippocampal CA3 Due to Excitatory Afferents, Fano Factor: A Potentially Useful Information, Spiking Correlation Analysis of Synchronous Spikes Evoked by Acupuncture Mechanical Stimulus. ;] Home. Published: (2017) Frontiers in neuroinformatics Published: (2007) Neuroscience … Journal list; Help; Journal List; Front Comput Neurosci; Frontiers in Computational Neuroscience Vols. Previous studies have linked tumor lobar presence and laterality to GBM outcomes, suggesting that disease etiology and progression in GBM may be impacted by tumor location. In this paper we aim to explore this problem in more detail and to study the possible solution, which is to evaluate the Fano factor in the operational time. Performance & security by Cloudflare, Please complete the security check to access. SynX performance was most influenced by the choice of synergy analysis algorithm and number of synergies. Previous work used a mean-field reduction method to determine the collective dynamics of a large heterogeneous network of uniformly and globally coupled theta neurons, which are a canonical formulation of Type I neurons. Existing User. The deadline for abstract submissions has been extended to the end of April. Frontiers in Computational Neuroscience is a first-tier electronic journal devoted to promoting theoretical modeling of brain function and fostering interdisciplinary interactions between theoretical and experimental neuroscience. Specifically, we used the population sparseness index, which is widely-used in neurophysiological studies on primates' brain, to characterize the degree of sparseness at each layer in representative DCNNs pretrained for object categorization. 【Frontiers in Computational Neuroscience】CiteScore Trend Comments from Authors * All review process metrics, such as acceptance rate and review speed, are limited to … Click on a pathway for a more detailed view. Frontiers is based in Lausanne, Switzerland, with other offices in London, Madrid, Seattle and Brussels. Hence, in this feasibility study, we seek to investigate the following question: Can tumor location on treatment-naïve MRI provide early cues regarding likelihood of a patient developing pseudo-progression vs. tumor recurrence? Recently, deep convolutional neural networks (DCNNs) have attained human-level performances on challenging object recognition tasks owing to their complex internal representation. The resulting gradients may provide a basis for the known functional organization observed in hippocampus. Frontiers in Computational Neuroscience, Volume 14; doi:10.3389/fncom.2020.569049. 7 - ?. We use equilibrium renewal and Markov renewal processes as spike train models to describe the method in detail, and we provide an illustration on experimental data. The evaluation process started with full calibration of a lower-body EMG-driven model using 16 measured EMG channels (collected using surface and fine wire electrodes) per leg. Gene J. Yu, Jean-Marie C. Bouteiller, Theodore W. Berger, Frontiers in Computational Neuroscience, Volume 14; doi:10.3389/fncom.2020.588881. Neural Regeneration Research Use Read by QxMD to access full text via your institution or open access sources. The topographic organization of the associational system gave rise to changes in the spatial correlation structure along the longitudinal and transverse axes of the CA3. Frontiers in Computational Neuroscience, Volume 14; doi:10.3389/fncom.2020.563439. Review this journal Show reviews. Frontiers in Computational Neuroscience. Di Ao, Mohammad S. Shourijeh, Carolynn Patten, Benjamin J. Fregly, Frontiers in Computational Neuroscience, Volume 14; doi:10.3389/fncom.2020.588943.s001. One fine wire EMG channel (either iliopsoas or adductor longus) was then treated as unmeasured. Frontiers in Neuroinformatics. PLUS: Download citation style files for your favorite reference manager. 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