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The Potential of Cognitive Neuroimaging: a Way Forward to the Mind-Machine Interface

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The Potential of Cognitive Neuroimaging: a Way Forward to the Mind-Machine Interface Journal of Imaging Review The Potential of Cognitive Neuroimaging: A Way Forward to the Mind-Machine Interface Ganesh Pandarinathan, Sachin Mishra, Anu Maashaa Nedumaran, Parasuraman Padmanabhan * ID and Balázs Gulyás * Lee Kong Chian School of Medicine, Experimental Medicine Building, Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore; [email protected] (G.P.); [email protected] (S.M.); [email protected] (A.M.N.) * Correspondence: [email protected] (P.P.); [email protected] (B.G.); Tel.: +65-6904-1186 (P.P.); +65-6904-1184 (B.G.) Received: 23 March 2018; Accepted: 10 May 2018; Published: 14 May 2018 Abstract: Bridging the human mind with an external system implicitly or explicitly has been the aspiration of researchers working in the field of cognitive neuroimaging. Identifying the potential of various imaging techniques in identifying and mapping different regions of the brain in relation to their functions is the key to eliminating the difficulties in developing a mind-machine interface (MMI). Communication technology has flourished to the extent that wireless MMI applications can be designed to virtually control machines like wheelchairs, artificial limbs, etc. A cornucopia of diversified works on cognitive imaging is required to move the preliminary MMI models forward, thus engendering a technologically advanced system which can be operated directly by the brain. This article provides an overview of various aspects of cognitive neuroimaging and its potential applications in the development of a mind-machine interface. Keywords: functional imaging; mind-machine interface; cognitive neuroimaging; brain-computer interface 1. Introduction Functional neuroimaging portrays the regions of the brain that are responsible for specific cognitive functions. The basic reason for this imaging approach is to understand the relation between various activities of the brain with respect to its cohorts. Neuroimaging has helped us comprehend the fundamental concept that intricate mental functions are best expressed as a blend of different rudimentary operations. This may not be restricted to a single region of the brain but can be a result of the combined work of various regions and neuronal networks. Matching these basic operations with the locations of the brain is a significant objective of advanced cognitive imaging research. The development of several cognitive imaging modalities such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), electrocorticography (ECoG), near-infrared spectroscopy (NIRS), magnetoencephalography (MEG), and positron emission tomography (PET), as well as hybrid modalities [1] (refer to Figure1), has paved a way forward for the mind-machine interface (MMI). The roots of cognitive neuroimaging lie within the work of Angelo Mosso (a 19th century Italian physiologist) and his experiment monitoring of the pulsations of the brain in human subjects while conducting a defined task, during which he noticed an increase in the circulation locally in the brain [2]. Later, in 1890, Charles Roy and Charles Sherrington confirmed the relationship between blood flow and brain function [3]. Further, in 1924 the first human electroencephalography (EEG) which recorded the electrical activity of brain, opened the window to harness brain signals as carriers J. Imaging 2018, 4, 70; doi:10.3390/jimaging4050070 www.mdpi.com/journal/jimaging J. Imaging 2018, 4, 70 2 of 17 of information for direct brain-computer communication [4,5]. Cognitive neuroimaging, together with J. Imaging 2018, 4, x FOR PEER REVIEW 2 of 17 various other inter-disciplinary approaches of mechatronics, communication, cybernetics, etc. helped inin thethe developmentdevelopment ofof aa communicationcommunication pathwaypathway betweenbetween brainbrain andand anan externalexternal device.device. SinceSince thethe 1970s,1970s, researchresearch andand developmentdevelopment onon MMIMMI havehave influencedinfluenced neuroprosthetics,neuroprosthetics, cyberphysicalcyberphysical systems, neurogaming,neurogaming, andand severalseveral otherother cognitivecognitive disciplines.disciplines. FigureFigure 1.1. DifferentDifferent imagingimaging modalitiesmodalities contributingcontributing towardstowards thethe developmentdevelopment ofof thethe mind-machinemind-machine interfaceinterface in in a a clockwise clockwise direction direction from from the thetop topright rightcorner corner:: near-infrared near-infrared spectroscopy spectroscopy (NIRS), (NIRS),functional functional magnetic magnetic resonance resonance imaging imaging (fMRI), (fMRI), positron positron emission emission tomography tomography (PET),(PET), magnetoencephalographymagnetoencephalography (MEG), (MEG), electroencephalography electroencephalography (EEG), (EEG), and electroencephalography and electroencephalography (ECoG). (ECoG). 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Various experiments invasive, to be partially performed invasive, to understand and non-invasive better the techniquesbrain as a haveprocessing been widely organ usedand its to clearlyneuronal define setup. various Various cognitive invasive, concepts partially and theirinvasive localization, and non in- theinvasive brain. techniques have been widely used to clearly define various cognitive concepts and their localizationA prospective in the brain. application of cognitive neuroimaging will be its use in designing a mind-machine interfaceA prospective [7]. This imaging application technique of cognitive can potentially neuroimaging identify will variousbe its use regions in designing of cognition a mind which-machine can beinterface used to[7] control. This imaging an external technique system. can potentially For example, identify Ludovico various et regions al. used of functionalcognition which magnetic can resonancebe used to imaging control (fMRI)an external to control system. a For robotic example, arm basedLudovico on theet al. imagination used functional of subjects magnetic [8]. Aresonance junction imaging between (fMRI) neuron to andcontrol silicon a robotic in the arm leech based Retizus on the cell imagination for stimulation of subjects was developed[8]. A junction by Fromherzbetween neuron et al. [9 and]. This silicon cellular in the level leech interface Retizus entails cell for the stimulation potential for was making developed some by well-advanced Fromherz et complexal. [9]. 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Functional Neuroimaging—The Concept Functional neuroimaging relies on a blood oxygen level-dependent (BOLD) signal [10]. The principle is that the consumption of oxygen by neurons in the regions of brain involved in an activity is high when compared to other neurons not involved in the activity. This leads to a regional increase in blood flow in the oxygen-depleted region. The increase is not to equalize the oxygen concentration J. Imaging 2018, 4, 70 3 of 17
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