Mind reading!

Neuroscientists at the UC Berkeley have used functional MRI technology to determine what someone is looking at just by analyzing their brain patterns.

Others have done this in the past using neural networks, but never with images. Haynes et al. (2007) had participants perform mental addition or subtraction and record what brain activity is occurring first. Then, participants were given numbers and they were able to choose whether to add or subtract, then they gave their answer. Post hoc analyses (long after participants were out of the scanner) lead to neural network models being able to predict using brain activity alone whether participants added or subtracted the numbers.

Gallant and colleagues (2008) have used similar methodology. Participants first had to view objects so researchers could determine brain patterns, then they were able to match up future brain patterns with past scans. While it’s not pure mind reading (since you need prior knowledge), it’s still pretty impressive.

This is good, because bad people don’t have a big database of scans involving brain patterns of previous knowledge. So evil doers will not be able to stick anyone in an fMRI and read their thoughts, thankfully. At least, not yet.

Price, Expectations, and Brain-Supported Lies

A recent article in the Proceedings of the National Academies of the Sciences by Hilke Plassmann and colleagues starts with this abstract:

Despite the importance and pervasiveness of marketing, almost nothing is known about the neural mechanisms through which it affects decisions made by individuals. We propose that marketing actions, such as changes in the price of a product, can affect neural representations of experienced pleasantness. We tested this hypothesis by scanning human subjects using functional MRI while they tasted wines that, contrary to reality, they believed to be different and sold at different prices. Our results show that increasing the price of a wine increases subjective reports of flavor pleasantness as well as blood-oxygen-level-dependent activity in medial orbitofrontal cortex, an area that is widely thought to encode for experienced pleasantness during experiential tasks. The paper provides evidence for the ability of marketing actions to modulate neural correlates of experienced pleasantness and for the mechanisms through which the effect operates.

Essentially, students were placed in an fMRI scanner and drank wines that were similar in price but were told that some wines were more expensive than others. The result? Participants rated the “more expensive” wines are better, and their brains responded appropriately! Orbitofrontal cortex was activated more in response to the more expensive wines, indicating a heightened emotional response (pleasure).

The impact of this is simple: if a product is more expensive, people will gain greater pleasure from purchasing it. This is not a previously unknown result, certainly. People will often justify their more expensive purchases, but this research shows that the brain responds differently to pricier (and therefore “better”) items. Even if you have to lie to yourself that the more expensive product is better, your brain will likely reflect the reality that you’ve constructed. Mind you, this experiment is not testing that, but it is a reasonable hypothesis to draw.

This research is relevant to a big debate going on right now in the home theater world. I just bought a flat-screen TV and have been outfitting my home theater with lots of high definition content. I’ve needed new cabling to accomplish all this, and I can either buy the $100 (!!!) Monster Cables from Best Buy or $5 cables from the Internet. The question that’s been brewing online is which cables are better. Apparently, some audiophiles can’t even tell the difference between a coat hanger and $100 Monster cables, yet people still buy the expensive cables, enjoy them, and claim to be able to hear better sound. Why? This research explains why.

Can you tell the difference?

Monkeys versus Undergraduates

I am home for the holidays and, like most other people, busy running around seeing friends, family, and shopping. However, I’ve run across a couple of interesting articles pitting the cognitive abilities of monkeys against undergraduates. Turns out that the monkeys can hold their own. Fascinating reading for those of you with downtime this holiday season/Winter Break!

Monkeys can do basic math involving sets of dots:

The article: http://biology.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pbio.0050328
The press release: http://dukemednews.org/news/article.php?id=10200

Monkeys have better numerical memory than humans:

The article: Inouea, S. & Matsuzawaa, T. (2007) Working memory of numerals in chimpanzees. Current Biology. 17(23), R1004-R1005.
The writeup: http://www.sciencedaily.com/releases/2007/12/071203094823.htm

Return of the two-tiered Civic dashboard

I have mentioned the two-tiered dashboard of my 2008 Civic in this blog before, and I wanted to touch on it one last time. I’ve gotten used to the dual-tiered dashboard, though I have complained about it in the past.

However, this research from Summala, Lamble & Laakso (1998) demonstrates that brake light detection is not so good when attention is focused at the speedometer and is better when focused on a display at the lower portion of the windshield. From the article’s abstract:

Perception of the lead car’s braking was measured on-road when subjects of various levels of driving experience were looking at a digital display located at the lower part of the windscreen, at the speedometer level, or in the mid-console. The brake lights of the lead car were either working normally or switched off. The results indicated that the detection of the lead car’s brake lights, in daylight, is substantially impaired when a following driver is looking at the speedometer area and brake lights do not contribute to detection at all when he/she is looking at a target in the mid-console… 

So peripheral vision is not that great for detecting brake lights when you’re looking down at your speedometer. It is pretty good, though, at the level of the lower windshield, which is where my speedometer is. So I must revise my assessment of the two-tiered Civic dashboard and say that it doesn’t seem to hurt driving performance by being digital instead of analog, and it may even assist with brake light detection. I suppose only an analysis of accident rates between the two types of speedometers will really tell which design is better, but for now, I endorse this new design.

HFES 2007 Annual Meeting: Interesting research!

There was some really interesting research at the HFES 2007 meeting in Baltimore that took place at the beginning of October. I actually commuted Monday-Thursday to Baltimore from Washington, D.C. - an hour trip each way. It was exhausting, so I don’t know how fully cognizant I was during a lot of the talks. But here is what I can remember that I found interesting:

• Meta-information: This was a panel discussion about displaying “information about information” - meta-information. This was especially interesting to me because the person I’ll be working with at the Naval Undersea Warfare Center, Dr. Susan Kirschenbaum, does a lot with how to display uncertainty information on submarines. All information about the environment comes in to submariners via computer. The information may not always be 100% accurate. If the computer is able to determine how it is uncertain about a reading or decision, how best to display that to the user?
• Visual displays: This was a great session because so much of the research relied on basic visual attention principles that I research. This was all applied - mostly towards aviation, though there was a talk on taxicab drivers. Factors like clutter, salience, and distraction were all mentioned as speakers discussed the next generation transportation displays.
• Neuroergonomics: This was another panel discussion led by George Mason’s own Dr. Raja Parasuraman. His goal is to use neuroscience research to inform the design and usability of complex systems. Human factors has been using behavioral data from cognition studies, and the next step is to use neuroimaging data to continue to inform design principles. The talks were heavily geared towards neuroscience, but it did have some great implications for movement perception, navigation, individual differences, and other important human factors topics.
• Augmented Cognition: Neuroergonomics is in contrast to a movement called Augmented Cognition, which is all about using real-time neuroimaging data (mostly EEG) to determine workload. It’s not a bad goal, but (A) I saw a lot of the Augmented Cognition talks, and they’re really far away from any reasonable implementation (B) Are drivers going to have to don their EEG helmet before driving? Just military? How convenient can you make it? (C) They’re still working on the real-time estimation of workload. The next question that they haven’t tackled is: then what? How do you change a system to adapt to that workload? That may be the hardest part.

Overall, it was a worthwhile conference for me to attend. I was glad to learn about the kinds of research that goes on in the human factors field, and what the “cutting-edge” is!