Concurrent measurements of neural activity at multiple scales, sometimes performed with multimodal techniques, become increasingly important for studying brain function. However, statistical methods for their concurrent analysis are currently lacking. Here we introduce such techniques in a framework based on vine copulas with mixed margins to construct multivariate stochastic models. These models can describe detailed mixed interactions between discrete variables such as neural spike counts, and continuous variables such as local field potentials. We propose efficient methods for likelihood calculation, inference, sampling and mutual information estimation within this framework. We test our methods on simulated data and demonstrate applicability on mixed data generated by a biologically realistic neural network. Our methods hold the promise to considerably improve statistical analysis of neural data recorded simultaneously at different scales.

CRISPR gene editing technology became nearly a household name with its potential to affect humanity. And a baby was born with three parents. While some decry the developed world is falling apart due to changing political environments, science and technology innovation is likely to continue thriving. In fact, innovation is occurring so fast, I believe 2017 will be the year governments begin to consider forming new science, technology, and futurist agencies and organizations to better contend with the rapid change. The old ones are mired in bureaucracy, conservative religious ideology, and the past--unable to contend with issues like nanotechnology, artificial intelligence, and virtual reality.

Because all of the low-hanging scientific and technological fruit has supposedly been plucked. You can invent broad technologies like electrification, the light bulb, plumbing and sanitation, the telephone, refrigeration, the internal combustion engine, and the digital computer only once. Therefore most new technologies will consist of slight improvements on the old ones and that will not propel future economic growth. But have all broad technologies really been invented already? Below are three core technologies whose elaborations during the next decade will conjure into existence a world with far less transactional friction, amazing cures, and much smarter machines.

This year has seen the birth of the first three-person baby, a dangerous Zika epidemic and a huge injustice overturned by medical science. There were also breakthroughs in a range of deadly diseases. A year ago hardly anyone had heard of Zika virus. Now the birth of babies with underdeveloped brains - known as microcephaly - is all too familiar. The World Health Organization declared the disease, which is spread by mosquitoes, a public health emergency.

Chatbots are programs that mimic conversation with people using artificial intelligence. With recent advances in AI these have become much more accurate, especially when focused on a specific domain. Combine these advances with the consumer trend towards messaging -- people are now spending more time in messaging apps than in social media -- and it seems we might be about to enter the age of the chatbot. We decided to take a closer look at the top emerging chatbot start-ups in text chat, across a range of industries, and pick out the most promising. You can find out more about the 25 companies below, or discover more chatbot startups on our search engine.

The gold rush for artificial intelligence (AI) is officially in full swing. Big players like Google and Facebook and small teams alike are in an all-out sprint toward the goal of creating the next generation of AI assistants that will fundamentally change how we live and work. I am in awe at the pace of progress, because every week it feels like a new barrier is breached, a tool grows more robust, or a new startup is launched with the ability to transform an industry. However, the most surprising observation continues to be people's underestimation of AI. Specifically how the general population seems so unable, or unwilling, to imagine that a machine could ever match a human's ability in any job -- particularly their own.

HARI SREENIVASAN: But first: 2016 has been a wild ride, one that we're not likely to forget anytime soon, much of it focused on politics, but many things happened in the world of science and technology as well. William Brangham starts our review for our weekly segment, the Leading Edge. WILLIAM BRANGHAM: Indeed, we wanted to look at some of the more remarkable discoveries and innovations, and setbacks that we saw in the scientific world this year. WILLIAM BRANGHAM: So, everyone is doing their year-end best-of list for 2016. The biggest one by far was a historic find announced in February, the detection of gravity waves.

Meet YoloData, one of the latest DMV-area data analytics startups promising to make sense of millennials for businesses. The Ashburn, Va.-based startup provides data scientists and business developers with an aggregated data platform focused on how millennials might respond to a business. Co-founder and CEO Bryan Short said the platform collects financial and health data, mostly, from public government sources and a few private partnerships, but it also lets customers import their own private data for individual analysis. In January, the nine-month-old company will close its first round of $500,000 backed mostly by local angel investors who have previously invested in Short's previous ventures, including a few mobile apps. This raise will be used to prep YoloData's technology for beta testing in the spring.

And upon that sand a new God will walk." It may not quite be that bad. But a wall won't keep them out, a new work permit scheme won't stop their freedom of movement. The rise of the robots could be next year's big story. Ever since the Luddites smashed their first loom, mechanisation has been putting people out of work. But the process is speeding up, accelerating all the time and the next wave could be crashing down, near you, soon.

I wrote this article at Alexandria (VA) during the first meeting on artificial intelligence in medical imaging, C-MIMI (Conference on Machine Intelligence in Medical Imaging), organized by SIIM (Society for Imaging Informatics in Medicine). Almost 200 participants attended 16 presentations of scientific papers, classes and lectures. The abstract presenters didn't just attend to showcase the results of their research, but also for the variety of topics covered. From algorithms for reading bone age to the prediction of deletion of the chromosomal arm 1p / 19q in low-grade gliomas, it is difficult to find an area in radiology in which the techniques of machine learning cannot be applied. The idea of using computers for evaluating medical images is not new.