or other smart material actuators-based stages, such as neural network-based iterative learning control [21,22], Pi-sigma fuzzy neural network-based self-adaption compensation control [23], adaptive neural control [24], and adaptive Takagi-Sugeno fuzzy model-based model predictive control [25]. ...
We implemented a post-processing data extraction and analysis pipeline that is almost completely automated. A convolutional neural network estimates the locations of the nose, neck, and the base of the tail of the rat from the video stream, inferring head and body directions (Fig.3d (1), Addi...
B. Energy as a constraint on the coding and processing of sensory information. Curr. Opin. Neurobiol. 11, 475–480 (2001). Article PubMed CAS Google Scholar Balasubramanian, V. & Berry, M. J. A test of metabolically efficient coding in the retina. Network 13, 531–552 (2002). ...
However, it should be noted that there is no one-to-one mapping between computational processes and brain regions, suggesting that multivoxel pattern analysis and brain network analysis should be utilized in future studies to reveal how different computational processes are implemented in large-scale ...
Over the last several years, the study of working memory (WM) for simple visual features (e.g., colors, orientations) has been dominated by perspectives that assume items in WM are stored independently of one another. Evidence has revealed, however, syst
AdaLearner: An Adaptive Distributed Mobile Learning System for Neural Networks. (Duke) MeDNN: A Distributed Mobile System with Enhanced Partition and Deployment for Large-Scale DNNs. (Duke) TraNNsformer: Neural Network Transformation for Memristive Crossbar based Neuromorphic System Design. (Purdue)....
79 Interestingly, deletion of Lrp1 from astrocytes in a hippocampal neuron co-culture model decreased neuronal network activity and influenced the proportion of pre- and postsynaptic structures.80 In summary, we noted an extensive ECM remodeling and synaptic imbalance in quadruple mutant mice, which ...
We built a recurrent neural network modelling these first stages of visual processing in the optic lobe based on the connectome for the right eye. Each neuron in this DMN corresponds to a real neuron in the fly visual system, belonging to an identified cell type, and is connected to other ...
The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various b
1. This approach enables compatibility of the same network structure with different data formats. Examples of direct coding can be found in SI Appendix, Fig. S2. 直接编码将网络的第一层视为编码层。这种方法显著减少了模拟长度同时保持准确性。对于归一化的图像 x\in [0,1]^{W\times H\times3},...