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Memory Guide > Newsletters > Issue 82 > Companion Podcast > Transcript

This is the 3rd podcast for Memory & Mind News, a companion program to the Memory News Digest, a monthly newsletter put out by Memory Key dot com, a website devoted to providing information about memory and learning to help you achieve permanent memory improvement.

In this podcast, I will be discussing some of the news items that didn’t make it into the digest. References and links can be found on the website.

There’s a new report from Irene Pepperberg on what her Grey parrot can do. I love these. The parrot was asked, "How many total X?" when presented sequentially with 2 small sets of objects, and required to answer with a vocal English number label. He did this without explicit training, demonstrating addition abilities comparable to those of nonhuman primates and young children.

You might recall an earlier report where Alex, the 28-year-old African grey parrot that has lived in Pepperberg’s lab for I don’t know how many years, demonstrated an understanding of zero – an abstract notion that humans typically don't understand until age three or four, and that can indeed significantly challenge learning-disabled children

Of course, some birds are known for their smarts – they’re not all bird-brains! Ravens are another bird species known to be fairly intelligent. But I always like to see researchers moving away from the traditional primate species. You don’t have to be closely related to humans to have cognitive abilities!

But back to humans. While we’re on the subject of number processing, a recent imaging study has found confirmed the involvement of the intraparietal sulcus in processing symbolic numerical stimuli such as Arabic numerals, and found that this is true of 4 year olds as well as adults, demonstrating that the neural locus of numerical cognition takes form early in development, prior to sophisticated symbolic numerical experience.

It’s an interesting issue – this one of specialization. As the researchers of a recent paper remark, the cerebral cortex is a remarkably homogeneous structure suggesting a rather generic computational machinery. This enables considerable, and very useful, flexibility in the human brain, of course. But given the increasingly detailed map we’re developing of specialized brain regions, we have to ask how such specialization arose. Are different areas intrinsically specialized, or do they differ simply in their position in the processing hierarchy and in their inputs? Computer modeling now suggests that the same computational principles apply everywhere, and highlight the importance of different input signals in forming functional specialization.

At this point, of course, one is inescapably reminded of Hubel and Wiesel’s classic experiment with kittens. By initially depriving the kittens of sight in one eye, they demonstrated that the cells necessary for binocular vision simply don’t develop. Later studies showed that there is a critical period during which the appropriate experience is needed for particular cells to be ‘tuned’, as it were, to the right stimulus. Once that time has passed, it is too late.

But of course cognitive processes involve a number of interacting brain regions. We may talk of the ‘pleasure center’ or the ‘language area’, but there is no one specific structure that is solely responsible for these functions. As one of the items in the digest reports -- the brain in action can be compared to a symphony, with specialized sections required to pitch in at the right time to produce the desired melody, with some regions, too, acting as conductors.

Nor does the complexity of the brain’s functioning limit itself to the where of activity. There is also the how of activity. Motor skill acquisition, for example, is a complex process. Sleep research has indicated that many of the processes involved in motor learning require sleep or long periods of time. But a new study shows that there are also two distinct processes that only require minutes. One process apparently responds weakly to error but retains information well, whereas the other responds strongly to error but has poor retention.

Decision making, too, is a complex process. We make decisions based on incomplete information all the time – indeed, you could argue our information is always incomplete! Because of that, we often change our minds as we get new information. Decision-making thus often progresses in fits and starts, as we explore our options. Exactly how this complex process proceeds in the brain is something we don’t know a lot about. Now a new imaging study has enabled researchers to tease apart how different regions of the cerebral cortex process uncertain information and integrate it into decision making.

The researchers used a navigation task, as subjects made their way through a computer-generated 3D maze. While their brains were being scanned, the subjects were "placed" in different parts of the maze. The researchers were looking at two "cognitive states" – one was a belief about where the subject was in the maze, and the other was a set of "operant" states: either a "proceed or update mode" or a "reevaluate or back-track mode."

It was found that "belief maintenance" processes are performed principally by the anterior prefrontal cortex, while "belief back-track" processes occur in the medial prefrontal cortex.

And then there’s the whole question what we should process. The world contains an infinity of information; we can’t process everything; our neurons can’t respond to every single stimulus in the environment.

So, we don’t perceive everything. And even more so, we don’t remember all that we perceive. If we did, our memories would be as real as the events themselves! How do we select what to encode as part of the memory? A long-standing concept in psychology is the distinction between ‘top-down’ and ‘bottom-up’ processes. Does the general send orders to the soldiers (top-down) or do the people on the ground make the decisions, leaving their leaders to deal with the situation as best they may? How much do central processes in the brain control what we perceive? How much is done at sensory level? A recent imaging study brings us a little closer to understanding this process by finding evidence that control signals originating in the prefrontal cortex help determine which perceptual information will bound into the memory.

Perception, of course, includes perceiving other people, and here we really get cognitive! We bring so much with us when we interact with other people. One of the things we bring is of course out-group prejudice.

There was an interesting study into prejudice reported last month. By scanning subjects' brains while they were thinking about people either politically like or different from them, researchers found that different areas of the brain are active in the two cases.

The researchers looked specifically at the medial prefrontal cortex – an area of the brain that’s critical to making inferences about other's mental states. Part of the area – the ventral part -- also seems to be more engaged when people are performing tasks that involves thinking about their friends.

Accordingly, the researchers theorized that the ventral part might contribute to inferences about people similar to oneself, while the dorsal region might be more involved in thinking about dissimilar people.

In the study, college students were shown pictures of two people and told that one of them had liberal views and took part in activities typical of students at liberal arts colleges, while the other person was described as a fundamentalist Christian with conservative political views and activities. Then, while their brains were scanned, they were asked questions such as whether the person would look forward to going home for Thanksgiving, enjoy having a roommate from a different country, or think that European movies were better than Hollywood movies.

As hypothesized, the ventral region was more active when they thought about the person like them, and the dorsal region was more engaged when considering the person unlike them. The researchers also found that the appropriate regions were more active the more similar the students considered themselves to the person.

The researchers concluded that their findings support the theory that people tend to use knowledge about themselves to infer the mental states of others, and suggest that prejudice may arise in part because we assume that the mental states of those that don’t belong to our ‘group’ don’t correspond to our own – which is why we think about them with a different part of our brain. This suggests, of course, that the best way of dealing with prejudice is to focus on the similarity between people.

The whole how-we-perceive-other-people thing is of course a defining feature of autism. In a recent study, researchers created autistic mice by deleting a gene in certain parts of the brain. By autistic, I mean mice that show deficits in social interaction that are reminiscent of autistic humans. They also had physical abnormalities in their brains that mimic some cases of autism. So, the finding is at least suggestive, and does support other recent studies indicating a mutation in this particular gene could cause at least some forms of autism.

And that’s it for this month’s podnews; I hope you enjoyed it.

References

Pepperberg, I.M. 2006. Grey Parrot (Psittacus erithacus) Numerical Abilities: Addition and Further Experiments on a Zero-Like Concept. Journal of Comparative Psychology, 120(1), 1-11.
http://www.eurekalert.org/pub_releases/2005-07/bu-agp070805.htm

Cantlon, J.F., Brannon, E.M., Carter, E.J. & Pelphrey, K.A. 2006. Functional Imaging of Numerical Processing in Adults and 4-y-Old Children.
Full Text at PLoS
http://biology.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pbio.0040125

Wyss, R., König, P. & Verschure, P.F.M.J. 2006. A Model of the Ventral Visual System Based on Temporal Stability and Local Memory.
Full Text at PLoS (Free)
http://biology.plosjournals.org/perlserv/?request=get-document&doi=10%2E1371%2Fjournal%2Epbio%2E0040120

Wiesel, T.N. & Hubel, D.H. 1963. Single-cell responses in striate cortex of kittens deprived of vision in one eye. Journal of Neurophysiology, 26,1003--1017.

Smith, M.A., Ghazizadeh, A. & Shadmehr, R. 2006. Interacting Adaptive Processes with Different Timescales Underlie Short-Term Motor Learning.
Full text at PLoS
http://biology.plosjournals.org/perlserv/?request=get-document&doi=10%2E1371%2Fjournal%2Epbio%2E0040179

Summerfield, C., Greene, M., Wager, T., Egner, T. & Mangels, J.H.J. 2006. Neocortical Connectivity during Episodic Memory Formation.
Full text at PLoS (Free)
http://biology.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pbio.0040128

Yoshida, W. & Ishii, S. 2006. Resolution of Uncertainty in Prefrontal Cortex.Neuron, 50, 781-789.
http://www.eurekalert.org/pub_releases/2006-05/cp-wwc052506.htm

Mitchell et al. 2006. Dissociable Medial Prefrontal Contributions to Judgments of Similar and Dissimilar Others. Neuron, 50, 655–663.
http://www.eurekalert.org/pub_releases/2006-05/cp-bsy051106.htm

New findings help pinpoint autism's genetic roots
http://www.eurekalert.org/pub_releases/2006-05/usmc-nfh042806.htm