Brain Mapping
Brain mapping is a set of neuroscience techniques based on the mapping of biological properties onto spatial representations of the human or non-human brain that result in information maps. Brain mapping is further defined as the study of the anatomy and function of the brain and spinal cord through the use of imaging. This also includes neurological imaging, which image the neurological structure, function and impacts of pharmacology or toxins upon the nervous system. Functional imaging of the neurological system and brain allow the processing of information in the brain to be visualized directly in images and mapped. Brain mapping can be read and analyzed directly by computerized systems, and extraterrestrial or military personnel that can directly see what areas of the brain are being activated and which centers "light up" on the scan. To read brain maps and neurological imaging allows the data to be loaded into computer for analysis, or for any entity to have access to another person’s thought identification or mind-reading. This can happen in real time, in the moment, and instantaneously, if the program has accessed the person’s brain and neurological system. Both the function and the structure, along with all data content of the brain and neurological system can be analyzed. Clearly this technology can be used for positive and negative effects. The current development of brain mapping technology is far more advanced than the current medical system and science has been allowed, and it has been reserved explicitly for military intelligence programs.[1]
=Artificial Intelligence
Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior. AI research is highly technical and specialized, and is deeply divided into subfields that often fail to communicate with each other. Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.