Interneurons in leech ganglia receive multiple sensory inputs and make synaptic contacts with many motor neurons. These "hidden" units coordinate several different behaviors. We used physiological and anatomical constraints to construct a model of the local bending reflex. Dynamical networks were trained on experimentally derived input-output patterns using recurrent back-propagation. Units in the model were modified to include electrical synapses and multiple synaptic time constants.

Based on the intricacies of origami -- and inspired by the movements of nature's leeches -- his research is advancing how robots could carry out basic health care tasks in certain conditions, including in remote regions, or where minimal personal contact is needed, such as during pandemics. The research is published in the journal npj Flexible Electronics from Nature Publishing Group. Together with PhD student Tae-Ho Kim and a team in SFU's Additive Manufacturing Lab, Kim and researchers have replaced the traditional blood pressure procedure by replicated the folding mechanisms of the leech in their design of 3-D printable origami sensors. The leech-inspired origami (LIO) sensors can be integrated onto the fingertips of a humanoid-sensing robot. "Our origami-inspired dry electrode has unique characteristics such as suction for grasping and foldability inspired by nature," says Kim, a professor and associate director of SFU's School of Mechatronic Systems Engineering.

The Bank of England has revealed the design for the UK's new £50 note featuring computer scientist and codebreaker Alan Turing. Turing was selected to appear on the note in July 2019 in recognition of his groundbreaking work in mathematics and computer science, as well as his role in cracking the Enigma code used by Germany in World War II. The polymer note will enter circulation from June 23 this year, and incorporates a number of designs linked to Turing's life and legacy. These include technical drawings for the bombe, a decryption device used during WWII; a string of ticker tape with Turing's birthday rendered in binary (23 June 1912); a green and gold security foil resembling a microchip; and a table and mathematical formulae taken from one of Turing's most famous papers. As well as honoring his scientific achievements, Turing was also selected to appear on the bank note in recognition of his persecution by the UK government for homosexuality.

When Lorenz and Leech met her second supervisor, neuroscientist Aldo Faisal, in January, they needed to discuss how best to proceed. It's trivial for humans to figure out the combinations of sight and sounds needed to activate the auditory cortex and not the visual cortex, and vice versa - the latter can be done by pairing a blank screen with the vocal acrobatics of an opera singer, the latter by pairing video of the hurly burly of Tokyo's Shibuya crossing with the drone of a test tone. In March 2015, with the help of a statistician from King's College London, Giovanni Montana, and aided by his PhD student Ricardo Pio Monti, Lorenz and Leech created an AI algorithm based on Bayesian Optimisation, a method named after the 18th-century Presbyterian minister Thomas Bayes. When Lorenz first suggested using artificial intelligence to study the human brain, Leech was immediately struck by its implications for dealing with this looming crisis.

Take part in the first online AI study of human intelligence Put your intelligence to the ultimate test and see how you fare compared with other people. In around half an hour, the artificial intelligence developed by a team at Imperial College London – nicknamed Cognitron - will put you through a series of a dozen customised tests and, after you have supplied a few details, tell you how well you did.The online study uses web-based AI developed by neuroscientists Romy Lorenz, Rob Leech, Pete Hellyer and Adam Hampshire at Imperial's Computational, Cognitive and Clinical Neuroimaging Laboratory, 'C3NL'. The AI will harvest information from thousands of people and dozens of tests, enabling it to explore hundreds of different measures of cognitive ability.The subject of intelligence remains contentious, not least because there is still no agreement on precisely what the word means. Tthe AI will tinker with the tests to find out if intelligence can be divided into different types of cognitive ability like verbal reasoning and focused attention, or if such cognitive skills are all interdependent. Ultimately, Cognitron aims to understand if AI is the key to understanding human intelligence.

Robotic surgery and computer-assisted medicine are already doing amazing things right now -- just look at the da Vinci Surgical System! Are you ready to ditch the hospital and buy a robot surgeon for the home? Let's say you have to have a dangerous surgical procedure. Let us know your decision and why in the comments below! Alright, medical technology is getting weirder by the day.

In weighted voting games, each agent has a weight, and a coalition of players is deemed to be winning if its weight meets or exceeds the given quota. An agent's power in such games is usually measured by her Shapley value, which depends both on the agent's weight and the quota. [Zuckerman et. al., 2008] show that one can alter a player's power significantly by modifying the quota, and investigate some of the related algorithmic issues. In this paper, we answer a number of questions that were left open by [Zuckerman et. al., 2008]: we show that, even though deciding whether a quota maximizes or minimizes an agent's Shapley value is coNP-hard, finding a Shapley value-maximizing quota is easy. Minimizing a player's power appears to be more difficult. However, we propose and evaluate a heuristic for this problem, which takes into account the voter's rank and the overall weight distribution. We also explore a number of other algorithmic issues related to quota manipulation.

The biological network is small and relatively well understood, and the silicon model can therefore span three levels of organization in the leech nervous system (neuron, ganglion, system); it represents one of the first comprehensive models of leech swimming operating in real-time. The circuit employs biophysically motivated analog neurons networked to form multiple biologically inspired silicon ganglia. These ganglia are coupled using known interganglionic connections. Thus the model retains the flavor of its biological counterpart, and though simplified, the output of the silicon circuit is similar to the output of the leech swim central pattern generator. The model operates on the same time-and spatial-scale as the leech nervous system and will provide an excellent platform with which to explore real-time adaptive locomotion in the leech and other "simple" invertebrate nervous systems.

The biological network is small and relatively well understood, and the silicon model can therefore span three levels of organization in the leech nervous system (neuron, ganglion, system); it represents one of the first comprehensive models of leech swimming operating in real-time. The circuit employs biophysically motivated analog neurons networked to form multiple biologically inspired silicon ganglia. These ganglia are coupled using known interganglionic connections. Thus the model retains the flavor of its biological counterpart, and though simplified, the output of the silicon circuit is similar to the output of the leech swim central pattern generator. The model operates on the same time-and spatial-scale as the leech nervous system and will provide an excellent platform with which to explore real-time adaptive locomotion in the leech and other "simple" invertebrate nervous systems.

The biological network is small and relatively well understood, and the silicon model can therefore span three levels of organization in the leech nervous system (neuron, ganglion, system); it represents one of the first comprehensive models of leech swimming operating in real-time. The circuit employs biophysically motivated analog neurons networked to form multiple biologically inspired silicon ganglia. These ganglia are coupled using known interganglionic connections. Thus the model retains the flavor of its biological counterpart, and though simplified, the output of the silicon circuit is similar to the output of the leech swim central pattern generator. The model operates on the same time-and spatial-scale as the leech nervous system and will provide an excellent platform with which to explore real-time adaptive locomotion in the leech and other "simple" invertebrate nervous systems.