Optical Volumetric Brain Imaging: Speed, Depth, and Resolution Enhancement

Author(s):  
Shih-Huan Huang ◽  
Ninik Irawati ◽  
Yu-Feng Chien ◽  
Jyun-Yi Lin ◽  
Yu-Hsuan Tsai ◽  
...  
2020 ◽  
Vol 15 (1) ◽  
pp. 24-31
Author(s):  
Zeshan Shoaib ◽  
Junhyun Kim ◽  
M. Ahmad Kamran ◽  
Myung Yung Jeong

Optical brain imaging has the potential for a bright future thanks to its low cost and portability relative to other biomedical imaging modalities. Temporal and spatial resolutions are considered to be the discriminatory features for selection of biomedical imaging equipment. Optical brain imaging systems, however, still face the bottleneck of limited spatial resolution. In this study, a novel method for guiding near infrared light at one of two particular gaps spaced nanometers apart has been presented. It includes the design of a nanogap nano-antenna for measurement of overlapping information on vicinities of only nanoscale separation distance, which could result in enhancement of the spatial resolution of optical brain imaging systems. The design of the proposed nano-gap nano-antenna channels near-infrared light to a specific path among two gaps separated by a nanometer-scale distance. A supportive analysis of gap design also is presented in this study. Additionally, the results of a comprehensive analysis of the behavior of light through the designed nano-gap nano-antenna are provided. The proposed methodology is a practical substitute for a high-density probe arrangement as well as a possible means of spatial resolution enhancement.


Author(s):  
J.K. Weiss ◽  
M. Gajdardziska-Josifovska ◽  
M. R. McCartney ◽  
David J. Smith

Interfacial structure is a controlling parameter in the behavior of many materials. Electron microscopy methods are widely used for characterizing such features as interface abruptness and chemical segregation at interfaces. The problem for high resolution microscopy is to establish optimum imaging conditions for extracting this information. We have found that off-axis electron holography can provide useful information for the study of interfaces that is not easily obtained by other techniques.Electron holography permits the recovery of both the amplitude and the phase of the image wave. Recent studies have applied the information obtained from electron holograms to characterizing magnetic and electric fields in materials and also to atomic-scale resolution enhancement. The phase of an electron wave passing through a specimen is shifted by an amount which is proportional to the product of the specimen thickness and the projected electrostatic potential (ignoring magnetic fields and diffraction effects). If atomic-scale variations are ignored, the potential in the specimen is described by the mean inner potential, a bulk property sensitive to both composition and structure. For the study of interfaces, the specimen thickness is assumed to be approximately constant across the interface, so that the phase of the image wave will give a picture of mean inner potential across the interface.


2020 ◽  
Vol 36 (2) ◽  
pp. 296-302 ◽  
Author(s):  
Luke J. Hearne ◽  
Damian P. Birney ◽  
Luca Cocchi ◽  
Jason B. Mattingley

Abstract. The Latin Square Task (LST) is a relational reasoning paradigm developed by Birney, Halford, and Andrews (2006) . Previous work has shown that the LST elicits typical reasoning complexity effects, such that increases in complexity are associated with decrements in task accuracy and increases in response times. Here we modified the LST for use in functional brain imaging experiments, in which presentation durations must be strictly controlled, and assessed its validity and reliability. Modifications included presenting the components within each trial serially, such that the reasoning and response periods were separated. In addition, the inspection time for each LST problem was constrained to five seconds. We replicated previous findings of higher error rates and slower response times with increasing relational complexity and observed relatively large effect sizes (η2p > 0.70, r > .50). Moreover, measures of internal consistency and test-retest reliability confirmed the stability of the LST within and across separate testing sessions. Interestingly, we found that limiting the inspection time for individual problems in the LST had little effect on accuracy relative to the unconstrained times used in previous work, a finding that is important for future brain imaging experiments aimed at investigating the neural correlates of relational reasoning.


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