| ObjectiveThe thesis applies the likelihood synchronization methods (Synchronization likelihood, SL) to study the working memory process of rats on the prefrontal cortex multi-channel local field potentials (Local Field Potentials, LFPs) of θ functional connectivity features. Application of LFPs0synchronization between channels likelihood matrix, clustering coefficient Cp and characteristic path length Lp is used to quantitatively describe LFPs and band θ of functional connectivity features of rats in the process of working memory in order to provide the computing support of neural information in working memory connection mechanism.Methods1. An experimental data: the original data of16channel of SD rats in the Y-maze working memory processes and resting prefrontal cortex are provided by the Tianjin Medical University Neural Engineering Lab, including10times of the original data and10times of experiments data under the the experimental resting state.2. Data Pretreatment:16channel data underwent the low-pass filter (0.5-500Hz). The resultant low-communication channel number is16LFPs. After go-frequency interference and baseline drift, the zero-mean16-channel LFPs was obtained.3. STFT (Short Time Fourier Transform, STFT) is applied to analyze the16-channel LFPs time-frequency to calculate the energy of16-channel LFPs in different time distribution of the frequency domain. Moving window size and moving step are: window size100ms, moving step25ms.4.16-channel LFPs feature extraction band component:Ocomponent, synchronization likelihood of θ component was applied to analyze LFPs connection between working memory to get the resting state synchronization likelihood matrix.5. The experiments average clustering coefficient Cp and the average path length Lp were calculated10tomes on each rat, and were compared with the resting state average Cp, Lp.6. The likelihood synchronization matrix and Cp, Lp were used to study the functonal link between channels of LFPs θ in rats in working memory state.ResultsThe paper studies16-channel LFPs θ synchronization likelihood matrix and the function during the working memory in rats and also described LFPs connection parameters Cp, Lp. The research results are as follows:1. Time-frequency analysis: in working memory state LFPs mainly concentrated in the energy field0band (4-12Hz) and y band (30-OOHz). Whereas, there was no energy distribution when y band frequency was above70Hz. This band only had the functional connections when most of the channels were in working memory in the process. So this article will focus on the study of functional connectivity features of LFPs θ during working memory processes, and discuss the role of functional connection for y in working memory. According to synchronization likelihood analysis, four rats LFPs θ of the10experiments, the average MsL, that is an average of each rat synchronization likelihood matrix. The1st rat MsL matrix S of the average of working memory processes Sp=0.6675±0.0612, resting Sp=0.5243±0.0490. The2nd rat MsL matrix working memory processes Sp=0.6842±0.0596, resting Sp=0.5705±0.0443. The3rd rat MSL matrix working memory processes Sp=0.6529±0.0533, resting Sp=0.5003±0.0402. The4th rat MSL matrix working memory processes Sp=0.6324±0.0407, resting Sp=0.4465±0.0339. During the working memory synchronization process, the likelihood was significantly higher than the resting state synchronization likelihood values, which means the process of working memory functional link between LFPs channels are much closer.2. Cp comparison between working memory and resting state:The1st rat LFPs θ Cp=0.2293±0.0263during working memory, while Cp=0.1207±0.0288in the resting state,t-test for Cp (P<0.05). The2nd rat Cp=0.2305±0.0265during working memory, while Cp=0.1028+0.0228in the resting state (P<0.01). The3rd rat Cp=0.2179±0.0238during working memory, while Cp=0.1070±0.0173in the resting state (P<0.01). The4th rat Cp=0.2047±0.0235during working memory, while Cp=0.0956±0.0205in the resting state (P<0.05).4rats LFPs θ component average Cp=0.2206±0.0263during working memory, is significantly higher than average Cp=0.1065±0.0237in the resting state.3. Lp comparison between working memory and resting state:The1st rat LFPs θ Lp=1.3018+0.1414during working memory, while Lp=2.902610.1453in the resting state,t-test for Lp (P<0.05). The2nd rat Lp=1.261010.1311during working memory, while Lp=2.8782±0.1846in the resting state (P<0.01). The3rd rat Lp=1.320210.1277during working memory, while Lp= 2.9282±0.2223in the resting state (P<0.01). The4th rat Lp=1.3608±0.1268during working memory, while Lp=3.0226±0.4614in the resting state (P<0.05).4rats LFPs θ average Lp=1.3110±0.1318during working memory, is significantly lower than average Lp=2.9329±0.2763in the resting state.4. Comparing likelihood synchronization matrix during working memory and in the resting state, LFPs θ functional connection during working memory was significantly greater than the resting state.The1st rat S value higher than T value channels number during working memory is5, while in the resting state is1.The2nd rat S value higher than T value channels number during working memory is7, while in the resting state is2.The3rd rat S higher than T value channels number during working memory is4, while in the resting state is2.The4th rat S higher than T value channels number during working memory is4, while in the resting state is1.Conclusion1. LFPs energy distribution concentrated in0band during working memory in rats, which means that LFPs characteristic component during working memory is θ component.2. LFPs θ clustering coefficient Cp values during working memory significantly is significantly higher than that in the resting state and the channels aggregation was high during working memory. Characteristic path length Lp values during working memory is significantly lower than the resting state and during working memory, the channel connections between the shortest path length is shorter. |
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