We propose a computational framework for understanding and modeling human consciousness. This framework integrates many existing theoretical perspectives, yet is sufficiently concrete to allow simulation experiments. We do not attempt to explain qualia (subjective experience),but instead ask what differences exist within the cognitive information processing system when a person is conscious ofmentally-represented information versus when that information isunconscious. The central idea we explore is that the contents of consciousness correspond to temporally persistent states in a network of computational modules. Three simulations are described illustratingthat the behavior of persistent states in the models corresponds roughly to the behavior of conscious states people experience when performing similar tasks. Our simulations show that periodic settling to persistent (i.e., conscious) states improves performanceby cleaning up inaccuracies and noise, forcing decisions, and helping keep the system on track toward a solution.
Consciousness is a thriving industry. Consciousness is a buzzing business in neuroscience labs and brain institutes. Just a few decades ago, consciousness barely registered as a credible subject for science. Perhaps no one did more to legitimize its study than Francis Crick, who launched a second career in neurobiology after cracking the genetic code. In the 1980s Crick found a brilliant collaborator in the young scientist Christof Koch. In some ways, they made an unlikely team. Crick, a legend in science, was an outspoken atheist, while Koch, 40 years younger, was a Catholic yearning for ultimate meaning. Together, they published a series of pioneering articles on the neural correlates of consciousness until Crick died in 2004. Koch went on to a distinguished career at Caltech before joining the Allen Institute for Brain Science in Seattle. Today, as the president and chief scientific officer, he supervises several hundred scientists, engineers, and informatics experts trying to map the brain and figure out how our neural circuits process information. The Institute recently made news with the discovery of three giant neurons connecting many regions of the mouse brain, including one that wraps around the entire brain. The neurons extend from a set of cells known as the claustrum, which Crick and Koch maintained could act as a seat of consciousness. Koch is one of the great thinkers about consciousness. He has a philosophical frame of mind and jumps readily from one big idea to the next.
Science is a crowning glory of the human spirit and its applications remain our best hope for social progress. But there are limitations to current science and perhaps to any science. The general mind-body problem is known to be intractable and currently mysterious. This is one of many deep problems that are universally agreed to be beyond the current purview of Science, including quantum phenomena, etc. But all of these famous unsolved problems are either remote from everyday experience (entanglement, dark matter) or are hard to even define sharply (phenomenology, consciousness, etc.). In this note, we will consider some obvious computational problems in vision that arise every time that we open our eyes and yet are demonstrably incompatible with current theories of neural computation. The focus will be on two related phenomena, known as the neural binding problem and the illusion of a detailed stable visual world.
Elon Musk's secretive "brain-machine interface" startup, Neuralink, stepped out of the shadows on Tuesday evening, revealing its progress in creating a wireless implantable device that can – theoretically – read your mind. At an event at the California Academy of Sciences in San Francisco, Musk touted the startup's achievements since he founded it in 2017 with the goal of staving off what he considers to be an "existential threat": artificial intelligence (AI) surpassing human intelligence. Two years later, Neuralink claims to have achieved major advances toward Musk's goal of having human and machine intelligence work in "symbiosis". Neurolink says it has designed very small "threads" – smaller than a human hair – that can be injected into the brain to detect the activity of neurons. It also says it has developed a robot to insert those threads in the brain, under the direction of a neurosurgeon.
Without a doubt, cognitive computing systems are a hot topic around boardrooms, executive suites, and conference tables at major technology firms, which are investing both financial and human resources to bring these systems to fruition. At the same time, government offices throughout the world are holding similar discussions, and these efforts are starting to come to fruition as well. Cognitive computing systems mine both structured and unstructured data to offer hypotheses and solutions for consideration by humans. They thrive on massive amounts of data: greater availability yields better analysis. In addition, cognitive computing systems rely on humans to train them through supervised learning.