Brain complexity: solving visual confusion (Introduction)

by David Turell , Wednesday, June 29, 2016, 20:39 (3069 days ago) @ David Turell

Another article on the complexities involved in giving us useful vision. It is an interview and I'm reproducing answers which compare our brain to computers that are said to be very different. Note the first comment:-http://www.scientificamerican.com/article/unlocking-the-mystery-of-how-the-brain-creates-vision/?WT.mc_id=SA_DD_20160629-"It's that computers are giving us the closest thing that we have right now to an analogous mechanism. The brain is really, really complex. It deals with massive amounts of data. We need help in organizing these data and computers can do that. Right now, there are algorithms that can identify an object as a phone or as a mug, just like the brain. But are they doing the same thing? Probably not.-***-"There are two ways that information flows. In the first way, which we call “bottom up,” information begins with points of light entering our eyes that fall onto your retinae. These points are processed by our visual systems and transformed into increasingly complex forms, from points to lines to edges to shapes and, ultimately, to objects and scenes. But the problem is that this array of light coming into our eyes is noisy and difficult to interpret, so just progressively making more and more complex interpretations of the light image would be rather slow.-"To help solve this problem, our brains appear to use a wide array of “top-down influences.” That is, our experience and memories help us to anticipate and interpret what is in front of us. We've all seen a keyboard in front of a computer before, so if I show you a very blurry image of one, your experiences fill in the gaps before you have a clear picture.-***-" visual illusions exploit our unconscious expectations. Disconcertingly, these same predictions can also influence our memories. One study I performed looked at false memories. If I showed you an image with an oven in it, for example, you might later recall seeing an oven and a refrigerator, because you typically see ovens and refrigerators in the same space. In fact, one image I used was of my own kitchen, which had a strange set-up. My washer and dryer were stacked one on top of the other inside the kitchen, but when asked to recall the image, many people remembered seeing a refrigerator because that's what should have been there.-"We have a very good idea of how low-level information is processed. That is, the early bit where points of light are transformed into lines, etc. At the same time, we are also beginning to have a better understanding of how we process very high levels [of information], that is, how a kitchen or a keyboard is represented in our brains. But we don't know how to connect low-level visual input with such high-level information. And this is where computer vision models are proving to be extremely interesting. As working systems, they actually have to come up with a solution to this problem - how you take points of light and figure out what scene you are looking at.-***-"On the human side, it's amazing how much we don't know about how the brain understands the visual scene. That's really incredible when you consider that the visual scene affects every aspect of our understanding. My expectations at the office and at the swimming pool are going to be radically different. Based on the visual input I receive, my language, my actions, even my goals will be different. The more effective we can be in understanding the environment around us, the more we can build models of how people generally reason about the world using this rich source of information.-***-"We're still working with crude human neuro-imaging techniques. The tools we have to visualize what is happening inside the human brain are exciting, but each point in our data is actually the average response over millions of neurons, making it very difficult to understand the micro-structure of neural information processing. There are 86 billion or so neurons, each an individual cell that transmits information in the human brain, and we are very far away from neuroscientific methods that will allow us to see how each of these units interact with one another. We're limited by that."-Comment: This all plays to my overarching point. Our brain is a biological camera. It cannot be like the camera eyes of a robot running on a computer, so as described our brain adds necessary parts to give us an integrated picture, that is obviously very useful and accurate. We cannot expect anything else. Can we be fooled? Obviously. is that critical? No.