Introduction
In the recent years, technological advancement has made an explosive move in the field of neuroscience. This has presented the engineers with notable milestone in the development of flexible and adaptive brain-based technologies. Cognitive science which is a multidisciplinary branch of artificial intelligence emulates how human brain gathers raw facts and analyzes it to process information in the reasoning activity. Artificial intelligence has further contributed to natural interfaces such as voice recognition, image processing and brain interfaces being the latest technologies. According to Kerick et al. (2012), brain interface technologies can broadly be classified into invasive computer interfaces and partial invasive computer interfaces. The invasive interfaces involve implantation of electrodes into the brain and which can be used to track movements of objects and communication. On the other hand, partial interface comprise of recorders that can detect signal directly from superficially implanted devices. A good example of such a device is electrocorticography that has been used to record activity of the brain via an electrode grid that was implanted surgically. Various research initiatives provide potential insights into the state of the brain and how human mental processes could be expanded. This could potentially open the doors for more advanced approaches to human and computer interactions 1,2. This essay presents some good examples which would showcase the worthiness of investing efforts in the development of brain interface technologies despite its challenging implementation.

To begin with, in the recent study at Stanford University it has proved why brain interface technology is relevant in the medical advancement. This study describes how the application of brain computer interfaces could improve the lives of three paralytic patients of which two suffered amyotrophic lateral sclerosis and one with a spinal cord injury 3,4. In this experiment, the patients could effectively move an onscreen cursor by a way of imagining the appropriate arm movements. This historic move was made possible by implanting electrodes in the motor cortex of each patient which recorded signalling of the brain and transmitted signals to the computer. According to Kaufmann et al (2015), brain computer interface has been used in visually and auditory impaired patients to enable them navigate their environment by use of neural prosthetic devices such as cochlea implant. In this medical context, brain computer interface has been extended to assist the amyotrophic lateral sclerosis patients to provide them with means to communicate using humanoid robots. The humanoid robots can perform tasks like bringing plate since their construct resemble human beings. This has eliminated the necessity of human care givers who to some extent had their productivity under-utilized (Hong et al., 2014).
Additionally brain interface technologies have been used in mental state detection. A number of algorithms have been developed to detect mental states. Using brain computer interfaces to analyze level of attentiveness, affective and arousal levels could allow environment to be familiar with the state of the user scaling joint user-performance system on a broader range of tasks. Also there is an ongoing research on fatigue based performance during driving (Käthner et al 2014). The integration of predictors on mitigation of fatigue could be lifesaving where brain computer interface are envisioned to reduce catastrophic driver errors. Similarly, fatigue and or attention based brain interface technologies could be escalated in critical mission activities where vigilant attention is required especially in surgical rooms and warfare scenes. Training system is another potential field where mental state is being monitored. Brain computer interface has been used to come up with intelligent and adaptive tutoring systems that have replaced the human tutor. This has provided personalized coaching and feedback mechanism to develop proficiency and skills in a particular field of study. These intelligent coaching systems could benefit from state detection systems that identify the indicative state of the brain on the lack of learning such as frustration, fatigue and strong negative attitude. In the near future such indicative states of the mental on learning process could be combined with other pedagogical theories to measure potential influences on learning progress of an individual (Käthner et al 2014).
Moreover, communication is another aspect of human life where brain interface technologies find their massive investment. In the previous years, human-computer communication was in the form of mouse and keyboard. According to Chaudhary, Birbaumer & Ramos-Murguialday (2016), these interfaces are not inclusive in the fact that they could not effectively allow the mentally and physically challenged members of the society communicate with the computers. However, the brain computer interfaces have solved this challenge by developing intuitive interfaces where users can issue command. This has given the visually impaired members of community retrieve contacts from their phonebooks and makes phone calls. Voice recognition systems have also been used for security measures through identification. Recently, people are able to interact with the computers by use of activity of the brain by aid of implanted electrodes. In this context movement of the mouse pointer to the left could be a brain activity thinking of blue colour and its right movement is associated with thinking of red colour. This has also been escalated in the entertainment industry where movie watchers can participate in an immersive simulated environment by use of head mounted devices. Sub-marine divers also use head mounted devices with sensors that could detect and analyze position and of an object while underwater.
In conclusion, the ongoing breakthrough in neuroscience research and neurotechnological interfaces provides brain computer interactions that could predict human emotion and mental states. The medical field has for instance benefitted from the advancement in brain computer interfaces; restoring states of amyotrophic lateral sclerosis patients to normal with the use of neural prosthetic devices. Human-computer interaction will not be limited to use of mouse and keyboards as the only means for data input and monitors, printers and speakers as the only means for information output. In my opinion the future of brain interface technologies however, calls for massive investment and comprehensive research to reap the maximum benefit. This is because the brain interface signals are mathematically complicated and that the cortex folding of human differs in every two people, brain dynamics differs under conditions and behave differently under experimental tests.

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