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Harvard Scientist Creates Neural Lace That Fuses with Your Brain

January 22, 2018


The Elman Simple Recurrent Neural Network. The context layer (u1. ul) provides a temporal memory to the network, allowing it to "remember" previous hidden layer states. Generated in LaTeX via PGF/Tikz.
Graphic credit: Fyedernoggersnodden - Own work, CC BY 3.0,

Connectionism is a set of approaches in the fields of artificial 1) ___, cognitive psychology, cognitive science, neuroscience, and philosophy of mind, that models mental or behavioral phenomena as the emergent processes of interconnected networks of simple units. The term was introduced by Donald Hebb in the 1940s. There are many forms of connectionism, but the most common forms use neural network models. Connectionism can be traced to ideas more than a century old, which were little more than speculation until the mid-to-late 20th century. Through his work on the structure of the nervous system for which he won the Nobel Prize in 1906, the Spanish physician, Santiago Ramon y Cajal established the basis for studies of neural networks, but it wasn't until the 1980s that connectionism became a popular perspective.

A neural network (also called an ANN or an artificial neural 2) ___) is a sort of computer software, inspired by biological neurons. Biological brains are capable of solving complex problems, but each individual neuron is only responsible for solving a very small part of the problem. Similarly, a neural network is made up of interconnected cells that work together to produce a desired result, although each individual cell is only responsible for solving a small part of the problem. This is one method for creating artificially intelligent programs. There are two ways to think of a neural network. First is like a human brain. Second is like a mathematical equation. Neural networks are also an example of machine learning, where the output of the program can change as it learns. A 3) ___ network can be trained and improves with each example, but the larger the neural network, the more examples it needs to perform well - often needing millions or billions of examples in the case of deep learning.

In a world where in only a few decades we went from clunky phones to wireless satellite-connected devices that allow us to be anywhere and do anything on the internet, it's natural that scientists went to the next level - to your 4) ___. A fine nano-mesh (also referred to as neural lace), created by Dr. Charles M. Lieber, fits inside a syringe and unfurls on the brain to monitor its activity, creating a bio-technological interface. A recent paper was published in Nature Nanotechnology where a new ultra-fine mesh that merges with the brain and creates a machine-biological functionality is described. For now, the mice with this electronic 5) ___ are connected by a wire to a computer ? but in the future, this connection could become wireless. Called "mesh electronics," the device is so thin that it can be directly injected to the brain, where it attaches to the brain. The technology was already successfully tested on mice, who not only survived the implantation, but seem to have no negative side 6) ___. This could have a lot of potential applications, including monitoring brain activity and delivering treatment for degenerative diseases such as Parkinson's. It might even be used to artificially boost brain capacity. The mesh was injected into a region of the brain called the lateral ventricle. "This could make some inroads to a brain interface for consumers," says Jacob Robinson, who develops technologies that interface with the brain at Rice University. "Plugging your 7) ___ into your brain becomes a lot more palatable if all you need to do is inject something."

The mesh also gives scientists access to previously inaccessible areas of the brain; when researchers want to study some areas of the brain of a mouse, they have to actually cut a piece from it, but this technology might change that, allowing remote research. Further down the line, delivering treatment directly to the brain could be the way to go. Neural electronics are already a reality for some people. Patients suffering from severe epilepsy or tremors can find relief via electric shocks, which are delivered by long wires threaded deep into the brain. Also, quadriplegics have learned to control prosthetic limbs using chips embedded in the brain. But we're still far from actually implementing the mesh in 8) ___. For starters, researchers need to ensure a longer mesh lifespan. Previous neural meshes have suffered from stability problems either with the signal they output or their own structure. But the team is optimistic that this time, the mesh will blend in with the brain and quietly fit in the empty gaps. 

We are now poised at a time in history when brain-computer interfaces (BCI) are the obvious next step. Now in the automation age, humans face the daunting prospect of 9) ___ intelligence (AI) becoming more capable than ourselves. Now that touchscreens and voice recognition are part of our everyday devices, it's time for us to be able to control our electronics with our minds. In this electronic age, we are edging closer to the elimination of various diseases, hoping for life without dementia, brain damage, and neurological diseases. The BCI provides us with a way to maintain control of our world and our electronics, to heal ourselves - and maybe even allow humanity itself to level up. Caleb Sharf, director of Astrobiology at Columbia University in New York City, has predicted that we may well witness a "first new origin event" in the process of 10) ___. Bionics and the brain computer interfaces that are already in development may change the human species forever.

Journal Reference: Jia Liu, Tian-Ming Fu, Zengguang Cheng, Guosong Hong, Tao Zhou, Lihua Jin, Madhavi Duvvuri, Zhe Jiang, Peter Kruskal, Chong Xie, Zhigang Suo, Ying Fang & Charles M. Lieber. Syringe-injectable electronics. Nature Nanotechnology (2015) doi:10.1038/nnano.2015.115; References: Tech Insider; Aeon; Inverse; DARPA; ScienceDaily: Wikipedia;

ANSWERS: 1) intelligence; 2) network; 3) neural; 4) brain; 5) mesh; 6) effects; 7) computer; 8) humans; 9) artificial; 10) evolution

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