Extensive sampling of neural activity during rich cognitive phenomena is critical for robust understanding of brain function. Here we present the Natural Scenes Dataset (NSD), in which high-resolution functional magnetic resonance imaging responses to tens of thousands of richly annotated natural scenes were measured while participants performed a continuous recognition task. To optimize data quality, we developed and applied novel estimation and denoising techniques. Simple visual inspections of the NSD data reveal clear representational transformations along the ventral visual pathway. Further exemplifying the inferential power of the dataset, we used NSD to build and train deep neural network models that predict brain activity more accurately than state-of-the-art models from computer vision. NSD also includes substantial resting-state and diffusion data, enabling network neuroscience perspectives to constrain and enhance models of perception and memory. Given its unprecedented scale, quality and breadth, NSD opens new avenues of inquiry in cognitive neuroscience and artificial intelligence. The authors measured high-resolution fMRI activity from eight individuals who saw and memorized thousands of annotated natural images over 1 year. This massive dataset enables new paths of inquiry in cognitive neuroscience and artificial intelligence.

It's often said that men and women's brains work so differently that one sex is from Venus and the other is from Mars. Well now a new study supports this hypothesis after finding 1,000 genes that are much more active in one gender than the other. It looked into how male and female mouse brains differ by probing areas that are known to program'rating, dating, mating and hating' behaviours. The behaviours -- for example, male mice's quick determination of a stranger's sex, females' receptivity to mating, and maternal protectiveness -- help the animals reproduce and their offspring survive. These differences are also likely reflected in the brains of men and women, the researchers from Stanford Medicine said.

Computing the Neural Network Forecasts: We use an advanced neural network model and a genetic programming learning algorithm to create the neural networks used to forecast the direction of the SP500. The output of a neural network is a numerical value that ranges from minus one (-1.0) to plus one ( 1.0), with -1.0 being a very strong indication of a negative slope over the forecast days and 1.0 being a very strong indication of a positive slope over the forecast days. For the 1-day model, the trading position we show in the Summary above is determined by computing an average network output value (ANO) from the individual networks and applying this average value to the setpoints which are also shown above. When this ANO rises above the long setpoint, a long position is given. When the ANO falls below the short setpoint, a short position is given.

A brain-computer interface (BCI) is a technology to provide direct communication between the brain and an external device. In this project, we have utilized noninvasive electroencephalography (EEG) to record and decode neural activity during the observation and mental imagery of visual stimuli. Our platform has demonstrated successful discrimination between face and scene image categories during visual observation and imagery periods. Additionally, we have shown above chance decoding accuracy during real-time prediction of face and scene imagery and resting state. This platform provides further insight into the use of visual imagery, a protocol that has not yet been much tested for BCI applications.

Elon Musk appears close to beginning the first ever human trials of his brain-computer interface technology. A new job posting for a'Clinical Trial Director' at Neuralink reveals that the neurotech startup is preparing to take its brain chip research to the next stage. Neuralink has already conducted trials on pigs and monkeys, including a successful experiment involving a nine-year-old macaque capable of playing video games using only its mind. The firm eventually hopes to use the technology to allow "human-AI symbiosis". Early human trials, which Mr Musk said last month will take place in 2022, will likely involve people with paralysis using Neuralink's interface to gain direct neural control of a computer cursor.

Elon Musk has demonstrated the Neuralink brain chip in a pig, a monkey and we could soon see preform in a human brain. The firm posted a new job listing for a clinical trial director, which says the right candidate will'work closely with some of the most innovative doctors and top engineers, as well as working with Neuralink's first Clinical Trial participants.' The position is based in Fremont, California and provides the candidate with commuter benefits, meals and'an opportunity to change the world.' It also indicates that the job will mean leading and building'the team responsible for enabling Neuralink's clinical research activities,' as well as adhering to regulations. Neuralink posted a new job listing, first spotted by Bloomberg, for a clinical trial director, which says the right candidate will'work closely with some of the most innovative doctors and top engineers, as well as working with Neuralink's first Clinical Trial participants Although the posting does not say when the trials will begin, Musk revealed last month that they are less than a year away - meaning human trials could start this year.

The billionaire entrepreneur Elon Musk's brain chip startup is preparing to launch clinical trials in humans. Musk, who co-founded Neuralink in 2016, has promised that the technology "will enable someone with paralysis to use a smartphone with their mind faster than someone using thumbs". The Silicon Valley company, which has already successfully implanted artificial intelligence microchips in the brains of a macaque monkey named Pager and a pig named Gertrude, is now recruiting for a "clinical trial director" to run tests of the technology in humans. "As the clinical trial director, you'll work closely with some of the most innovative doctors and top engineers, as well as working with Neuralink's first clinical trial participants," the advert for the role in Fremont, California, says. "You will lead and help build the team responsible for enabling Neuralink's clinical research activities and developing the regulatory interactions that come with a fast-paced and ever-evolving environment."

Elephant trunks may be one of the most sensitive body parts in the animal kingdom. Michael Brecht at the Bernstein Center for Computational Neuroscience in Berlin and his colleagues dissected the heads of three Asian elephants (Elephas maximus) and five African bush elephants (Loxodonta africana). All the animals had lived in zoos and died of natural causes or had been euthanised because of severe health problems. These dissections are rare because the procedure is difficult. "The head of an elephant with the trunk and everything is about 600 kilograms," Brecht says.

Researchers have built a sensor capable of recording signals from the human brain in record-breaking detail, opening up new possibilities for brain-computer interfaces. A team of engineers and surgeons, led by University of California San Diego professor Shadi Dayeh, used a densely packed grid embedded with thousands of electrocorticography (EC0G) sensors to allow them to read activity from the brain's cortex in 100 times higher resolution than existing technologies. Early applications could include surgeons receiving ultra clear brain signal information, providing better guidance for removing tumours without damaging healthy tissue, as well as surgically treating drug-resistant epilepsy. Longer-term, the brain device could be used as a permanent wireless implant to assist people living with paralysis or other neurodegenerative diseases like Parkinson's, which can be treated with electrical stimulation. Beyond that, the ECoG technology could be developed for use in the emerging field of brain-computer interfaces, which have a huge range of potential applications – from controlling a computer just by thinking, to streaming music directly to your brain.

A pair of researchers from the University of Montreal today published a pre-print research paper on creating "more intelligent artificial agents" by imitating the human brain. We've heard that one before, but this time's a little different. The big idea here is all about giving artificial intelligence agents more agency. Despite the progress made in social neuroscience and in developmental psychology, only in the last decade, serious efforts have started focusing on the neural mechanisms of social interaction, which were seen as the "dark matter" of social neuroscience. Basically, there's something other than just algorithms and architecture that makes our brains tick.