List of emerging technologies
Agriculture[edit] Biomedical[edit] Displays[edit] Electronics[edit] Energy[edit] IT and communications[edit] Manufacturing[edit] Materials science[edit] Military[edit] Neuroscience[edit] Robotics[edit] Transport[edit] Other[edit] See also[edit] General Disruptive innovation, Industrial Ecology, List of inventors, List of inventions, Sustainable development, Technology readiness level Nano- Molecular manufacturing, Neurotechnology Bioscience Human Connectome Project Ethics Casuistry, Computer ethics, Engineering ethics, Nanoethics, Bioethics, Neuroethics, Roboethics Other Anthropogenics, Machine guidance, Radio frequency identification, National Science Foundation, Virtual reality Transport List of proposed future transport Further reading[edit] IEEE International Conference on Emerging Technologies and Factory Automation, & Fuertes, J. References[edit] External links[edit]
Mind melds move from science fiction to science in rats
Neuroinformatics
Neuroinformatics is a research field concerned with the organization of neuroscience data by the application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly large-volume, high-dimensional, and fine-grain experimental data. Neuroinformaticians provide computational tools, mathematical models, and create interoperable databases for clinicians and research scientists. Neuroscience is a heterogeneous field, consisting of many and various sub-disciplines (e.g., Cognitive Psychology, Behavioral Neuroscience, and Behavioral Genetics). In order for our understanding of the brain to continue to deepen, it is necessary that these sub-disciplines are able to share data and findings in a meaningful way; Neuroinformaticians facilitate this.[1] Neuroinformatics stands at the intersection of neuroscience and information science. There are three main directions where neuroinformatics has to be applied:[2] History[edit]
A Brain-to-Brain Interface for Real-Time Sharing of Sensorimotor Information : Scientific Reports
In our training paradigm, animals learned basic elements of the tasks prior to participating in any BTBI experiments. First, prospective encoder rats were trained to respond to either tactile or visual stimuli until they reached 95% correct trials accuracy. Meanwhile, decoder rats were trained to become proficient while receiving ICMS as a stimulus. A train of ICMS pulses instructed the animal to select one of the levers/nose pokes, whereas a single ICMS pulse instructed a response to the other option. Decoder rats reached a 78.77% ± 2.1 correct trials performance level. The next phase of training began with the encoder rat performing ~10 trials of the motor or tactile task, which were used to construct a cortical ensemble template, i.e. the mean cortical neuronal activity for one of the responses. In experiment 1 (Figure 1), encoder rats (N = 3) pressed one of two levers after an LED on top of the lever was turned on. Full size image (222 KB) Full size image (314 KB)
Brain-Computer Music Interface - Hacked Gadgets - DIY Tech Blog
It is hard to imagine what will be possible with direct mind control in the next dozen years. Will we be driving cars with no steering wheel? Read the research paper (warning it is a PDF). “Researchers at the University of Plymouth created this “Brain-Computer Music Interface”, which uses two laptops to analyze brain waves and composes music based on the results. The BCMI-Piano (Figure 1) falls into the category of BCI computer-oriented systems. Via: TechEBlog
Earthquake algorithm picks up the brain's vibrations
There are better ways to shake up your brain (Image: Federica Rainò/Getty) Your brain is buzzing. Analysing those natural vibrations might help spot tumours and other abnormalities, and now an algorithm normally used to study earthquakes has been adapted to do just that. The elasticity of different parts of the body is a useful way to tell if something is wrong. It is more difficult to measure the elasticity of the brain. Catheline’s team, and others around the world, have been working on a way to use modified MRI scanners to measure brain elasticity. Shake it up But such devices haven’t made it to the clinic yet, in part because they aren’t very comfortable to use, says Catheline. Now Catheline is trying another approach. The idea came to Catheline after he spent time working with seismologists, who study how to extract information from the seismic waves created by earthquakes. The body’s noise
Biological neural network
In neuroscience, a biological neural network (sometimes called a neural pathway) is a series of interconnected neurons whose activation defines a recognizable linear pathway. The interface through which neurons interact with their neighbors usually consists of several axon terminals connected via synapses to dendrites on other neurons. If the sum of the input signals into one neuron surpasses a certain threshold, the neuron sends an action potential (AP) at the axon hillock and transmits this electrical signal along the axon. In contrast, a neural circuit is a functional entity of interconnected neurons that is able to regulate its own activity using a feedback loop (similar to a control loop in cybernetics). Early study[edit] Connections between neurons[edit] The connections between neurons are much more complex than those implemented in neural computing architectures. Connections display temporal and spatial characteristics. Representations in neural networks[edit] Study methods[edit]
Applications: Neural Interface » The neurophotonic interface: stimulating neurons with light
Applications » Neural Interface The neurophotonic interface: stimulating neurons with light PDF version | Permalink Nir Grossman, Konstantin Nikolic, and Patrick Degenaar 28 February 2008 Remote neural control is performed with single-cell single-action-potential resolution. At the end of the 18th century, Luigi Galvani demonstrated that nerves could be excited with electrical stimuli. In 1971 Richard Fork showed that a high power laser can stimulate neurons by physically punching temporarily holes in their membranes. The neurophotonics interface Our group is mainly interested in using this ion channel as a novel type of neurointerface based on light instead of electricity. Figure 1. Light from a micro-LED stripe triggers action potentials in a ChR2-transfected neuron with single-cell single-spike resolution. Figure 2. Microscope image of a blue 64 by 64 matrix light emitting diode where 2 rows of LEDs are turned on. The future There are many advantages in using light to interface with neurons.
