The local field potential（LFP） is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are or...The local field potential（LFP） is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood（SL） is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas. One drawback of non-linear algorithms is the heavy computational burden. In the present study, we proposed a graphic processing unit（GPU）-accelerated implementation of an SL algorithm with optional 2-dimensional time-shifting. We tested the algorithm with both artificial data and raw LFP data. The results showed that this method revealed detailed information from original data with the synchronization values of two temporal axes,delay time and onset time, and thus can be used to reconstruct the temporal structure of a neural network. Our results suggest that this GPU-accelerated method can be extended to other algorithms for processing time-series signals（like EEG and f MRI） using similar recording techniques.展开更多
In this paper, a new approach to analyze synchronization of linearly coupled map lattices （LCMLs） is presented. A reference vector x（t） is introduced as the projection of the trajectory of the coupled system on th...In this paper, a new approach to analyze synchronization of linearly coupled map lattices （LCMLs） is presented. A reference vector x（t） is introduced as the projection of the trajectory of the coupled system on the synchronization manifold. The stability analysis of the synchronization manifold can be regarded as investigating the difference between the trajectory and the projection. By this method, some criteria are given for both local and global synchronization. These criteria indicate that the left and right eigenvectors corresponding to the eigenvalue ＂0＂ of the coupling matrix play key roles in the stability of synchronization manifold for the coupled system. Moreover, it is revealed that the stability of synchronization manifold for the coupled system is different from the stability for dynamical system in usual sense. That is, the solution of the coupled system does not converge to a certain knowable s（t） satisfying s（tT1） = f（s（t）） but to the reference vector on the synchronization manifold, which in fact is a certain weighted average of each x^i（t） for i=1,……, m, but not a solution s（t） satisfying s（t ＋ 1）=f（s（t））.展开更多
This paper describes a circular first in first out （FIFO） and its protocols which have a very low latency while still maintaining high throughput. Unlike the existing serial FIFOs based on asynchronous micropipeline...This paper describes a circular first in first out （FIFO） and its protocols which have a very low latency while still maintaining high throughput. Unlike the existing serial FIFOs based on asynchronous micropipelines, this FIFO＇s cells communicate directly with the input and output ports through a common bus, which effectively eliminates the data movement from the input port to the output port, thereby reducing the latency and the power consumption. Furthermore, the latency does not increase with the number of FIFO stages. Single-track asynchronous protocols are used to simplify the FIFO controller design, with only three C-gates needed in each cell controller, which substantially reduces the area. Simulations with the TSMC 0.25 μm CMOS logic process show that the latency of the 4-stage FIFO is less than 581 ps and the throughput is higher than 2.2 GHz.展开更多
基金supported by Grants from the National Natural Science Foundation of China(81230023,81571067,and 81521063)National Basic Research Development Program(973 Program)of China(2013CB531905)the‘‘111’’Project of China
文摘The local field potential（LFP） is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood（SL） is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas. One drawback of non-linear algorithms is the heavy computational burden. In the present study, we proposed a graphic processing unit（GPU）-accelerated implementation of an SL algorithm with optional 2-dimensional time-shifting. We tested the algorithm with both artificial data and raw LFP data. The results showed that this method revealed detailed information from original data with the synchronization values of two temporal axes,delay time and onset time, and thus can be used to reconstruct the temporal structure of a neural network. Our results suggest that this GPU-accelerated method can be extended to other algorithms for processing time-series signals（like EEG and f MRI） using similar recording techniques.
基金Project supported by the National Natural Science Foundation of China (No. 60374018, No. 60574044)the Graduate Student Innovation Foundation of Fudan University.
文摘In this paper, a new approach to analyze synchronization of linearly coupled map lattices （LCMLs） is presented. A reference vector x（t） is introduced as the projection of the trajectory of the coupled system on the synchronization manifold. The stability analysis of the synchronization manifold can be regarded as investigating the difference between the trajectory and the projection. By this method, some criteria are given for both local and global synchronization. These criteria indicate that the left and right eigenvectors corresponding to the eigenvalue ＂0＂ of the coupling matrix play key roles in the stability of synchronization manifold for the coupled system. Moreover, it is revealed that the stability of synchronization manifold for the coupled system is different from the stability for dynamical system in usual sense. That is, the solution of the coupled system does not converge to a certain knowable s（t） satisfying s（tT1） = f（s（t）） but to the reference vector on the synchronization manifold, which in fact is a certain weighted average of each x^i（t） for i=1,……, m, but not a solution s（t） satisfying s（t ＋ 1）=f（s（t））.
基金Supported by the National Key Basic Research and Development(973) Program of China (No. 2006CB302700)the National High-Tech Research and Development (863) Program of China (No.2007AA01Z2B3)
文摘This paper describes a circular first in first out （FIFO） and its protocols which have a very low latency while still maintaining high throughput. Unlike the existing serial FIFOs based on asynchronous micropipelines, this FIFO＇s cells communicate directly with the input and output ports through a common bus, which effectively eliminates the data movement from the input port to the output port, thereby reducing the latency and the power consumption. Furthermore, the latency does not increase with the number of FIFO stages. Single-track asynchronous protocols are used to simplify the FIFO controller design, with only three C-gates needed in each cell controller, which substantially reduces the area. Simulations with the TSMC 0.25 μm CMOS logic process show that the latency of the 4-stage FIFO is less than 581 ps and the throughput is higher than 2.2 GHz.
