Since the advent of functional magnetic resonance imaging cognitive science has experienced a turn towards neuroscience. Models of perceptual and cognitive functions can now be tested against patterns of human brain activity in anatomically well-defined regions of interest. Structural and functional connectivity analyses can inform us about how different brain regions are interconnected and interact in perceptual and cognitive tasks, as well as during resting states. In this study I review the results of a series of experiments that aimed to reveal the visual-vestibular sensory processing underlying self-motion perception. We (Frank, Baumann, Mattingley, & Greenlee, 2014; Frank, Wirth, & Greenlee, 2016) localized regions in the posterior insula using fMRI with visual and vestibular stimuli. The results suggest that two areas in this part of the brain are involved in self-motion perception: the parieto-insular vestibular cortex (PIVC) for the processing of vestibular information and posterior insular cortex (PIC) for the integration of visual and vestibular information. The results suggest that these two regions play different roles in the integration of visual and vestibular cues related to self-motion perception.
In this paper, the design and implementation of wireless data transmission and low power consumption of a low cost electroencephalogram (EEG) to monitor the brainwave signals for medical and non-medical applications is presented. It can be used in smart city applications such as for brain-computer interface in industrial and transportation applications or intelligent wireless wearable EEG solutions for daily life applications. The wireless EEG wearable system is designed, simulated, constructed and tested to monitor the brainwave signals. The Zigbee module was used to construct the wireless data transmission system. The experimental results show that the proposed EEG system was successfully developed and tested. Its total coast is cheaper compared to the commercial EEG system.