It may seem absurd to compare a tiny fruit fly's brain to that of a majestic elephant. Yet it is the dream of many neuroscientists to find deep rules that very different brains share. As Gilles Laurent, a neuroscientist at the Max Planck Institute for Brain Research in Frankfurt, Germany, who has studied a variety of animals, from locusts to turtles, has said, "Neural responses can be described by the same mathematical operation … in completely different systems." Vivek Jayaraman, a researcher at the Howard Hughes Medical Institute's Janelia Research Campus, and a former student of Laurent's, believes that neuroscientists are on the verge of identifying some of these deep neural rules. Grasping them would advance another neuroscientific dream: to be able to predict animal behavior as easily as Newton could predict the behavior of a moving object. Jayaraman and a small number of researchers studying the brain's GPS have, in fact, already experienced the thrill of discovering one such rule.

It may seem absurd to compare a tiny fruit fly's brain to that of a majestic elephant. Yet it is the dream of many neuroscientists to find deep rules that very different brains share. As Gilles Laurent, a neuroscientist at the Max Planck Institute for Brain Research in Frankfurt, Germany, who has studied a variety of animals, from locusts to turtles, has said, "Neural responses can be described by the same mathematical operation…in completely different systems." Vivek Jayaraman, a researcher at the Howard Hughes Medical Institute's Janelia Research Campus, and a student of Laurent's, believes that neuroscientists are on the verge of identifying some of these deep neural rules. Grasping them would advance another neuroscientific dream: to be able to predict animal behavior as easily as Newton could predict the behavior of a moving object.

Call it an a-MAZE-ing development: A U.K.-based team of researchers has developed an artificial intelligence program that can learn to take shortcuts through a labyrinth to reach its goal. In the process, the program developed structures akin to those in the human brain. The emergence of these computational "grid cells," described in the journal Nature, could help scientists design better navigational software for future robots and even offer a new window through which to probe the mysteries of the mammalian brain. In recent years, AI researchers have developed and fine-tuned deep-learning networks -- layered programs that can come up with novel solutions to achieve their assigned goal. For example, a deep-learning network can be told which face to identify in a series of different photos, and through several rounds of training, can tune its algorithms until it spots the right face virtually every time.

Rats use brain cells called grid cells to help them navigate, and this ability has been recreated by an AI program.Credit: Al Fenn/LIFE Coll./Getty Scientists have used artificial intelligence (AI) to recreate the complex neural codes that the brain uses to navigate through space. The feat demonstrates how powerful AI algorithms can assist conventional neuroscience research to test theories about the brain's workings -- but the approach is not going to put neuroscientists out of work just yet, say the researchers. The computer program, details of which were published in Nature on 9 May1, was developed by neuroscientists at University College London (UCL) and AI researchers at the London-based Google company DeepMind. It used a technique called deep learning -- a type of AI inspired by the structures in the brain -- to train a computer-simulated rat to track its position in a virtual environment.

When Jon was born prematurely at 26 weeks, he weighed around two pounds and had trouble breathing on his own. For two months he lived in an incubator and eventually grew into a healthy baby and toddler. At age four, he had two epileptic seizures. About a year later his parents began to notice that Jon couldn't remember things that happened in his daily life. He didn't recall watching TV or what happened at school or what book he read. Jon's IQ was normal, he could read and write, and did well at school.

The model can predict the response ofindividual cells and populations to parametric manipulations of both geometric (e.g.

The model can predict the response ofindividual cells and populations to parametric manipulations of both geometric (e.g.

The model can predict the response ofindividual cells and populations to parametric manipulations of both geometric (e.g.O'Keefe & Burgess, 1996) and orientational (Fenton et aI., 2000a) cues, extending a previous geometric model (Hartley et al., 2000). It provides a functional description of how these cells' spatial responses are derived from the rat's environment and makes easily testable quantitative predictions. Consideration ofthe phenomenon of remapping (Muller & Kubie, 1987; Bostock et aI., 1991) indicates that the model may also be consistent with nonparametric changesin firing, and provides constraints for its future development.

Several regions of the rat brain contain neurons known as head-direction celis, which encode the animal's directional heading during spatial navigation. This paper presents a biophysical model of head-direction cell acti vity, which suggests that a thalamocortical circuit might compute the rat's head direction by integrating the angular velocity of the head over time. The model was implemented using the neural simulator NEURON, and makes testable predictions about the structure and function of the rat head-direction circuit.

Several regions of the rat brain contain neurons known as head-direction celis, which encode the animal's directional heading during spatial navigation. This paper presents a biophysical model of head-direction cell acti vity, which suggests that a thalamocortical circuit might compute the rat's head direction by integrating the angular velocity of the head over time. The model was implemented using the neural simulator NEURON, and makes testable predictions about the structure and function of the rat head-direction circuit.