Compared with event-related potential(ERP)which is widely used in psychology research,functional near-infrared imaging(fNIRI)is a new technique providing hemodynamic information related to brain activity,except for electrophysiological signals.Here,we use both these techniques to study ocular attention.We conducted a series of experiments with a classic paradigm of ocular nonselective attention,and monitored responses with fNIRI and ERP respectively.The results showed that fNIRI measured brain activations in the left prefrontal lobe,while ERPs showed activation in frontal lobe.More importantly,only with the combination measurements of fNIRI and ERP,we were then able to find the pinpoint source of ocular nonselective attention,which is in the left and upper corner in Brodmann area 10.These results demonstrated that fNIRI is a reliable technique in psychology,and the combination of fNIRI and ERP can be promising to reveal more information in the research of brain mechanism.
Working memory is one of the most important functions in our brain,which has been widely studied with unreal-life measured technologies.A functional near-infrared spectroscopy(fNIRS)instrument with a portable and low-cost design is developed,which is capable of providing hemodynamic measurement associated with brain function in real-life situations.Using this instrument,we performed working memory studies involved in Chinese words encoding,verbal,and spatial stem recognition,which are mainly studied with other technologies.Our results show that fNIRS can well assess working memory activities,in comparison with the reported results mainly using other methodologies.Furthermore,we find that hemodynamic change in the prefrontal cortex during all working memory tasks is highly associated with subjects’behavioral data.fNIRS is shown to be a promising alternative to the current methodologies for studying or assessing functional brain activities in natural condition.
Three-dimensional image reconstruction with Feldkamp,Davis,and Kress(FDK)algorithm is the most time consuming part in Micro-CT.The parallel algorithm based on the computer cluster is capable of accelerating image reconstruction speed;however,the hardware is very expensive.In this paper,using the most current graphics processing units(GPU),we present a method based on common unified device architecture(CUDA)for speeding up the Micro-CT image reconstruction process.The most time consuming filtering and back-projection parts of the FDK algorithm are parallelized for the CUDA architecture.The CUDA-based reconstruction speed and image qualities are compared with CPU results for the projecting data of the Micro-CT system.The results show that the 3D image reconstruction speed based on CUDA is ten times faster than the speed with CPU.In conclusion the FDK algorithm based on CUDA for Micro-CT can reconstruct the 3D image right after the end of data acquisition.
