Research on the Cognitive Neuroscience of Memory
- How and where memory occurs in the brain, particularly memory acquired through practice
- How experience shapes action, perception and thought through pervasive mechanisms of plasticity throughout the human brain
- Implicit and explicit memory contributions to perceptual-motor skill learning
- Implicit and explicit memory in visual category learning
- How general cognitive ability can be improved through cognitive practice
- Repetitive training of working memory span to improve cognition
- For both younger adults and to remediate age-related cognitive decline
- Perceptual-motor skill learning using the SISL task
- Working memory training using the SeVi-WM task
- Using computational modeling and functional neuroimaging to study interactions among the brain’s memory systems
Check the Presentations link on the right side bar to see the most recent ideas and reports as presented as posters and talks at recent conferences.
309 Cresap Laboratory
Department of Psychology
Phone: (847) 467-5779
2029 Sheridan Road
Evanston, IL 60201
Good article on Cognitive Science versus Artificial Intelligence in the Atlantic from a few weeks ago.
Douglas Hofstadter, the Pulitzer Prize–winning author of Gödel, Escher, Bach, thinks we’ve lost sight of what artificial intelligence really means. His stubborn quest to replicate the human mind.
This is the key point, in my opinion:
“I don’t want to be involved in passing off some fancy program’s behavior for intelligence when I know that it has nothing to do with intelligence. And I don’t know why more people aren’t that way.”
I’ve had the chance recently to tell the story of how I came to Cognitive Neuroscience from originally studying Computer Science and this captures the main idea quite well.
Especially the last part of the quote — I really don’t understand why more people don’t think this way. I’ve thought that ever since Deep Blue beat the best chess players in the world, why isn’t anybody organizing competitions for actually smart chess playing programs that aren’t allowed to brute force search billions of positions? I guess there just aren’t enough of us who think that is an interesting problem. Or maybe among those of us who do, there aren’t any who have the time to work on that problem since there are so many other interesting problems in trying to study human intelligence.
I wrote a short piece for a gaming-oriented online magazine, GLHF (Good Luck, Have Fun!) talking about the neuroscience of skill learning and how it applies to getting better at even things like video games. The magazine is generally focused on Starcraft2 and the professional e-sports scene around Starcraft (although I think they want to get into Dota2 as well).
I clipped images of the piece below, but you can access it directly either via the main magazine url: http://glhfmag.com/
Or you can go directly to the relevant issue via: http://issuu.com/glhfmag/docs/glhf_magazine_6_issuu_single_page?e=5965119/4641972
Can’t believe I didn’t Randomness this one already…
Real-Time Strategy Game Training: Emergence of a Cognitive Flexibility Trait
- Brian D. Glass, W. Todd Maddox, & Bradley C. Love
The main finding: increased cognitive flexibility after 40 hours of playing Starcraft. Of note, the assessment of cognitive flexibility was done by meta-analytic Bayes factor across a wide array of assessments. That’s very creative and maybe the right way to be approaching measurement of subtle transfer effects. If the transfer effect is in a process that is partly represented across a variety of measures, you’d need someway of combining the measures and also partially out the target process. Also of note, the participants were all female because they wanted non-gamers (defined as <2 hours/week) and there weren’t any male non-gamers at UT Austin.
The review paper for Neuropsychologia is officially available.
Memory systems research has typically described the different types of long-term memory in the brain as either declarative versus non-declarative or implicit versus explicit. These descriptions reflect the difference between declarative, conscious, and explicit memory that is dependent on the medial temporal lobe (MTL) memory system, and all other expressions of learning and memory. The other type of memory is generally defined by an absence: either the lack of dependence on the MTL memory system (nondeclarative) or the lack of conscious awareness of the information acquired (implicit). However, definition by absence is inherently underspecified and leaves open questions of how this type of memory operates, its neural basis, and how it differs from explicit, declarative memory. Drawing on a variety of studies of implicit learning that have attempted to identify the neural correlates of implicit learning using functional neuroimaging and neuropsychology, a theory of implicit memory is presented that describes it as a form of general plasticity within processing networks that adaptively improve function via experience. Under this model, implicit memory will not appear as a single, coherent, alternative memory system but will instead be manifested as a principle of improvement from experience based on widespread mechanisms of cortical plasticity. The implications of this characterization for understanding the role of implicit learning in complex cognitive processes and the effects of interactions between types of memory will be discussed for examples within and outside the psychology laboratory.
Brain Training in PLoS One: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0055518
Brain Training Game Boosts Executive Functions, Working Memory and Processing Speed in the Young Adults: A Randomized Controlled Trial
Rui Nouchi, Yasuyuki Taki, Hikaru Takeuchi, Hiroshi Hashizume,Takayuki Nozawa, Toshimune Kambara, Atsushi Sekiguchi, Carlos Makoto Miyauchi, Yuka Kotozaki, Haruka Nouchi, Ryuta Kawashima
The title seems to accurately tell the results of the experiment. Training was Nintendo BrainAge versus Tetris in a randomized controlled trial design. WM & PS went up in participants who did BrainAge >> Tetris (Simple Reaction Time went up in Tetris). Participants were young, mean age 20, n=16 per group. Training was 15m/day 5 days/week for 4 weeks. Somewhat surprisingly strong results for relatively low total hours of training in younger adults. Recruiting, compliance, retention look very strong though. I guess you could worry about expectancy effects but everything else looks very solid. A big, elaborate assessment battery was used. I haven’t looked at every piece of it, but Ravens (RAPM) curiously went up a lot in both groups.