On How Memories Pass Between Generations

The BBC highlights a recent study titled “Parental olfactory experience influences behavior and neural structure in subsequent generations” in which the researchers at Emory University in Atlanta, GA trained mice to avoid a smell, and subsequently, these mice passed this aversion on to their “grandchildren.” The results are important for phobia and anxiety research.

Both the mice’s offspring, and their offspring, were “extremely sensitive” to cherry blossom and would avoid the scent, despite never having experiencing it in their lives. Remarkably, these changes extended to changes in brain structure.

From the abstract:

Using olfactory molecular specificity, we examined the inheritance of parental traumatic exposure, a phenomenon that has been frequently observed, but not understood. We subjected F0 mice to odor fear conditioning before conception and found that subsequently conceived F1 and F2 generations had an increased behavioral sensitivity to the F0-conditioned odor, but not to other odors. When an odor (acetophenone) that activates a known odorant receptor (Olfr151) was used to condition F0 mice, the behavioral sensitivity of the F1 and F2 generations to acetophenone was complemented by an enhanced neuroanatomical representation of the Olfr151 pathway. Bisulfite sequencing of sperm DNA from conditioned F0 males and F1 naive offspring revealed CpG hypomethylation in the Olfr151 gene. In addition, in vitro fertilization, F2 inheritance and cross-fostering revealed that these transgenerational effects are inherited via parental gametes. Our findings provide a framework for addressing how environmental information may be inherited transgenerationally at behavioral, neuroanatomical and epigenetic levels.

Fascinating.

How Dogs are Like Humans

A thought-provoking and interesting piece in The New York Times by Gregory Berns, a professor of neuroeconomics at Emory University, on how dogs are like humans in their thought processes. By teaching dogs to sit still in MRI machines, they were able to trace neurobiological evidence of emotions in dogs which are akin to the ones we experience:

By looking directly at their brains and bypassing the constraints of behaviorism, M.R.I.’s can tell us about dogs’ internal states. M.R.I.’s are conducted in loud, confined spaces. People don’t like them, and you have to hold absolutely still during the procedure. Conventional veterinary practice says you have to anesthetize animals so they don’t move during a scan. But you can’t study brain function in an anesthetized animal. At least not anything interesting like perception or emotion.

From the beginning, we treated the dogs as persons. We had a consent form, which was modeled after a child’s consent form but signed by the dog’s owner. We emphasized that participation was voluntary, and that the dog had the right to quit the study. We used only positive training methods. No sedation. No restraints. If the dogs didn’t want to be in the M.R.I. scanner, they could leave. Same as any human volunteer.

My dog Callie was the first. Rescued from a shelter, Callie was a skinny black terrier mix, what is called a feist in the southern Appalachians, from where she came. True to her roots, she preferred hunting squirrels and rabbits in the backyard to curling up in my lap. She had a natural inquisitiveness, which probably landed her in the shelter in the first place, but also made training a breeze.

With the help of my friend Mark Spivak, a dog trainer, we started teaching Callie to go into an M.R.I. simulator that I built in my living room. She learned to walk up steps into a tube, place her head in a custom-fitted chin rest, and hold rock-still for periods of up to 30 seconds. Oh, and she had to learn to wear earmuffs to protect her sensitive hearing from the 95 decibels of noise the scanner makes.

After months of training and some trial-and-error at the real M.R.I. scanner, we were rewarded with the first maps of brain activity. For our first tests, we measured Callie’s brain response to two hand signals in the scanner. In later experiments, not yet published, we determined which parts of her brain distinguished the scents of familiar and unfamiliar dogs and humans.

This is truly fascinating.

I have placed Gregory Berns’s upcoming book, How Dogs Love Us: A Neuroscientist and His Adopted Dog Decode the Canine Brain, into my Amazon queue.

Debunked: “Right-Brain” vs. “Left-Brain” Personalities

For years in popular culture, the terms “left-brained” and “right-brained” have come to signify disparate personality types, with an assumption that some people use the right side of their brain more, (those who are supposedly more creative/artistic) while some use the left side more (those who are more logical/analytical). But newly released research findings from University of Utah neuroscientists assert that there is no evidence within brain imaging that indicates some people are right-brained or left-brained:

Following a two-year study, University of Utah researchers have debunked that myth through identifying specific networks in the left and right brain that process lateralized functions. Lateralization of brain function means that there are certain mental processes that are mainly specialized to one of the brain’s left or right hemispheres. During the course of the study, researchers analyzed resting brain scans of 1,011 people between the ages of seven and 29. In each person, they studied functional lateralization of the brain measured for thousands of brain regions — finding no relationship that individuals preferentially use their left -brain network or right- brain network more often.

Following a two-year study, University of Utah researchers have debunked that myth through identifying specific networks in the left and right brain that process lateralized functions. Lateralization of brain function means that there are certain mental processes that are mainly specialized to one of the brain’s left or right hemispheres. During the course of the study, researchers analyzed resting brain scans of 1,011 people between the ages of seven and 29. In each person, they studied functional lateralization of the brain measured for thousands of brain regions — finding no relationship that individuals preferentially use their left -brain network or right- brain network more often.

“It’s absolutely true that some brain functions occur in one or the other side of the brain. Language tends to be on the left, attention more on the right. But people don’t tend to have a stronger left- or right-sided brain network. It seems to be determined more connection by connection, ” said Jeff Anderson, M.D., Ph.D., lead author of the study, which is formally titled “An Evaluation of the Left-Brain vs. Right-Brain Hypothesis with Resting State Functional Connectivity Magnetic Resonance Imaging.” It is published in the journal PLOS ONE this month.

From the paper’s abstract:

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater “left-brained” or greater “right-brained” network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed.

So while there are more creative/artistic people in the world, this study purports that the active parts of the brain do not account for said personality traits. You learn something new every day, right?

Can an Alligator Run the Hundred Meter Hurdles?

Gary Marcus, writing in The New Yorker, offers a summary of why artificial intelligence isn’t so intelligent (and has a long way to go to catch up with the human brain). He focuses on the research of Hector Levesque, who is a critic of the modern A.I.:

In a terrific paper just presented at the premier international conference on artificial intelligence, Levesque, a University of Toronto computer scientist who studies these questions, has taken just about everyone in the field of A.I. to task. He argues that his colleagues have forgotten about the “intelligence” part of artificial intelligence.

Levesque starts with a critique of Alan Turing’s famous “Turing test,” in which a human, through a question-and-answer session, tries to distinguish machines from people. You’d think that if a machine could pass the test, we could safely conclude that the machine was intelligent. But Levesque argues that the Turing test is almost meaningless, because it is far too easy to game. Every year, a number of machines compete in the challenge for real, seeking something called the Loebner Prize. But the winners aren’t genuinely intelligent; instead, they tend to be more like parlor tricks, and they’re almost inherently deceitful. If a person asks a machine “How tall are you?” and the machine wants to win the Turing test, it has no choice but to confabulate. It has turned out, in fact, that the winners tend to use bluster and misdirection far more than anything approximating true intelligence. One program worked by pretending to be paranoid; others have done well by tossing off one-liners that distract interlocutors. The fakery involved in most efforts at beating the Turing test is emblematic: the real mission of A.I. ought to be building intelligence, not building software that is specifically tuned toward fixing some sort of arbitrary test.

The crux, it seems to me, is how machines interpret the subtleties of human communication and how we talk. Marcus offers the following example in which a substitute of one word yields disparate answers:

The large ball crashed right through the table because it was made of Styrofoam. What was made of Styrofoam? (The alternative formulation replaces Stryrofoam with steel.)

a) The large ball
b) The table

Continuing, he explains:

These examples, which hinge on the linguistic phenomenon known as anaphora, are hard both because they require common sense—which still eludes machines—and because they get at things people don’t bother to mention on Web pages, and that don’t end up in giant data sets.

More broadly, they are instances of what I like to call the Long-Tail Problem: common questions can often be answered simply by trawling the Web, but rare questions can still stymie all the resources of a whole Web full of Big Data. Most A.I. programs are in trouble if what they’re looking for is not spelled out explicitly on a Web page. This is part of the reason for Watson’s most famous gaffe—mistaking Toronto for a city in the United States.

Levesque’s paper is short and easily accessible for the layman.

On Animal Intelligence

New research shows that we have grossly underestimated both the scope and the scale of animal intelligence. Primatologist Frans de Waal explains in the Saturday essay for The Wall Street Journal. This example on elephant intelligence is striking:

Experiments with animals have long been handicapped by our anthropocentric attitude: We often test them in ways that work fine with humans but not so well with other species. Scientists are now finally meeting animals on their own terms instead of treating them like furry (or feathery) humans, and this shift is fundamentally reshaping our understanding.

Elephants are a perfect example. For years, scientists believed them incapable of using tools. At most, an elephant might pick up a stick to scratch its itchy behind. In earlier studies, the pachyderms were offered a long stick while food was placed outside their reach to see if they would use the stick to retrieve it. This setup worked well with primates, but elephants left the stick alone. From this, researchers concluded that the elephants didn’t understand the problem. It occurred to no one that perhaps we, the investigators, didn’t understand the elephants.

Think about the test from the animal’s perspective. Unlike the primate hand, the elephant’s grasping organ is also its nose. Elephants use their trunks not only to reach food but also to sniff and touch it. With their unparalleled sense of smell, the animals know exactly what they are going for. Vision is secondary.

But as soon as an elephant picks up a stick, its nasal passages are blocked. Even when the stick is close to the food, it impedes feeling and smelling. It is like sending a blindfolded child on an Easter egg hunt.

On a recent visit to the National Zoo in Washington, I met with Preston Foerder and Diana Reiss of Hunter College, who showed me what Kandula, a young elephant bull, can do if the problem is presented differently. The scientists hung fruit high up above the enclosure, just out of Kandula’s reach. The elephant was given several sticks and a sturdy square box.

Kandula ignored the sticks but, after a while, began kicking the box with his foot. He kicked it many times in a straight line until it was right underneath the branch. He then stood on the box with his front legs, which enabled him to reach the food with his trunk. An elephant, it turns out, can use tools—if they are the right ones.

Worth reading in entirety.

On Plasticity and Social Connections

Barbara Fredrickson’s op-ed titled “Your Phone vs. Your Heart” in The New York Times this weekend hits a nerve (so to speak):

In short, the more attuned to others you become, the healthier you become, and vice versa. This mutual influence also explains how a lack of positive social contact diminishes people. Your heart’s capacity for friendship also obeys the biological law of “use it or lose it.” If you don’t regularly exercise your ability to connect face to face, you’ll eventually find yourself lacking some of the basic biological capacity to do so.

The human body — and thereby our human potential — is far more plastic or amenable to change than most of us realize. The new field of social genomics, made possible by the sequencing of the human genome, tells us that the ways our and our children’s genes are expressed at the cellular level is plastic, too, responsive to habitual experiences and actions.

The gist is that by alienating away from human connection, your brain chemistry/structure changes (the concept is called plasticity). But it can be changed (for the better, in terms of how you feel) if you spend meaningful time with others. So step away from Twitter, slow down on the text messaging, and make plans to go out for dinner with a friend.

On Albert Einstein’s Unusual, but Average-Sized, Brain

After Albert Einstein died in 1955, a pathologist named Thomas Harvey removed Einstein’s brain, photographed it with great care, cut it up into 240 blocks, sliced some of those blocks into slides, and prepared a roadmap to help future scientists navigate the pieces. Slides and photographs were distributed to researchers, but many have since been lost.

Dean Falk, a senior scholar at Santa Fe’s School for Advanced Research, has spent years studying the photographs of Einstein’s brain and is the lead author of a new study, published in the journal Brain, that relies on a collection of rarely seen photographs to analyze it.

Falk’s team compared Einstein’s brain with those of 85 other humans already described in the scientific literature and found that the great physicist did indeed have something special between his ears. Although the brain, weighing 1230 grams, is only average in size, several regions feature additional convolutions and folds rarely seen in other subjects. For example, the regions on the left side of the brain that facilitate sensory inputs into, and motor control of, the face and tongue are much larger than normal; and his prefrontal cortex—linked to planning, focused attention, and perseverance in the face of challenges—is also greatly expanded.

The key takeaway: Einstein’s brain was normal sized, but had a lot more convolutions than that of the average human brain (on record).

Photographs of Einstein’s brain.

The link to the full paper is here.

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(via Washington Post)

The Dueling Analytical and Empathetic Networks in the Brain

A new paper in NeuroImage by Anthony Jack, Abigal Dawson, et al. suggests that there are two dueling (reciprocal) pathways in the brain: social vs. physical. From the abstract:

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or default mode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. We hypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which is directed towards understanding the external world. Thus, engaging one mode activates one set of regions and suppresses activity in the other. We test this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently associated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presentation modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation, mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results indicate the reciprocal inhibition is not attributable to constraints inherent in the tasks, but is neural in origin. Hence, there is a physiological constraint on our ability to simultaneously engage two distinct cognitive modes.

Basically: being (overly) empathetic represses analytic thought, and vise versa. Science Daily summarizes:

When the analytic network is engaged, our ability to appreciate the human cost of our action is repressed.

At rest, our brains cycle between the social and analytical networks. But when presented with a task, healthy adults engage the appropriate neural pathway, the researchers found.

The study shows for the first time that we have a built-in neural constraint on our ability to be both empathetic and analytic at the same time.

The work suggests that established theories about two competing networks within the brain must be revised. More, it provides insights into the operation of a healthy mind versus those of the mentally ill or developmentally disabled.

This is quite fascinating. Clearly, more research on this topic is warranted and will continue, but for now, this is preliminary food for thought.

On Memory Distortion and Invention

A new study by Brent Strickland and Frank Keil at Yale has shown that people’s memory may become distorted in just a few seconds:

Fifty-eight uni students watched three types of 30-second video clip, each featuring a person kicking, throwing, putting or hitting a ball or shuttlecock. All videos were silent. One type of video ended with the consequences of the athletic action implied in the clip – for example, a football flying off into the distance. Another type lacked that final scene and ended instead with an irrelevant shot, for example of a linesman jogging down the line. The final video type was scrambled, with events unfolding in a jumbled order. Crucially, regardless of the video type, sometimes the moment of contact – for example, the kicker actually striking the ball – was shown and sometimes it wasn’t. 

After watching each video clip, the participants were shown a series of stills and asked to say if each one had or hadn’t featured in the video they’d just watched. Here’s the main finding. Participants who watched the video type that climaxed with the ball (or shuttlecock etc) flying off into the distance were prone to saying they’d seen the causal moment of contact in the video, even when that particular image had in fact been missing.

In other words, because seeing the ball fly off implied that the kicker (or other protagonist) had struck the ball, the participants tended to invent a memory for having seen that causal action happen, even when they hadn’t. This memory distortion happened within seconds, sometimes as soon as a second after the relevant part of the video had been seen.

This memory invention didn’t happen for the videos that had an irrelevant ending, or that were scrambled. So memory invention was specifically triggered by observing a consequence (e.g. a ball flying off into the distance) that implied an earlier causal action had happened and had been seen. In this case, the participants appeared to have “filled in” the missing moment of contact from the video, thus creating a causally coherent episode package for their memories. A similar level of memory invention didn’t occur for other missing screen shots that had nothing to do with the implied causal action in the clip.

This isn’t the first of such studies, but it is further evidence that the way we process memories may be easily manipulated…

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(via Research Digest)

 

The Placebo Effect and the Self Management System

Nicholas Humphrey, a theoretical psychologist and author of A History of the Mind, has a fascinating post on the placebo effect and the relation between the health management system and what he dubs the self-management system. The basic premise is this: we know the placebo effect has a way of making people feel better in the medicinal sense. But what if we could prime people to change their behavior, attitudes, and personality?

It’s been a tremendous surprise for experimental psychology and social psychology, because until now it’s been widely assumed that people’s characters are in fact pretty much fixed. People don’t blow with the wind, they don’t become a different kind of person depending on local and apparently irrelevant cues . . . But after all, it seems they do.

So if we don’t discount the placebo effect in medicine, how does it fit in with the rest of the argument?

Placebos work because they suggest to people that the picture is rosier than it really is. Just like the artificial summer light cycle for the hamster, placebos give people fake information that it’s safe to cure them. Whereupon they do just that.

This suggests we should see the placebo effect as part of a much larger picture of homeostasis and bodily self-control. But now I’m ready to expand on this much further still. If this is the way humans and animals manage their physical health, there must surely be a similar story to be told about mental health. And if mental health, then—at least with humans—it should apply to personality and character as well. So I’ve come round to the idea that humans have in fact evolved a full-blown self management system, with the job of managing all their psychological resources put together, so as to optimise the persona they present to the world.

You may ask: why should the self need any such “economic managing”? Are there really aspects of the self that should be kept in reserve? Do psychological traits have costs as well as benefits? But I’d say it’s easy to see how it is so. Emotions such as anxiety, anger, joy will be counterproductive if they are not appropriately graded. Personality traits—assertiveness, neuroticism, and friendliness—have both down- and up-sides. Sexual attractiveness carries obvious risks. Pride comes before a fall. Even high intelligence can be a disadvantage (we can be “too clever by half”, as they say). What’s more—and this may be the area where economic management is most relevant of all— as people go through life they build up social psychological capital of various kinds that they need to husband carefully. Reputation is precious, love should not be wasted indiscriminately, secrets have to be guarded, favors must be returned.

So, I think humans must have come under strong selection pressure in the course of evolution to get these calculations right. Our ancestors needed to develop a system for managing the face they present to the world: how they came across to other people, when to flirt, when to hold back, when to be generous, when to be mean, when to fall in love, when to reject, when to reciprocate, when to punish, when to take the lead, when to retire, and so on. . . All these aspects had to be very carefully balanced if they were going to maximize their chances of success in the social world. 

Fortunately our ancestors already had a template for doing these calculations, namely the pre-existing health system. In fact I believe the self management system evolved on the back of the health system. But this new system goes much further than the older one: it’s job is to read the local signs and signs and forecast the psychological weather we are heading into, enabling us to prejudge what we can get away with, what’s politic, what’s expected of us. Not surprisingly, it’s turned out to be a very complex system. That’s why psychologists working on priming are discovering so many cues, which are relevant to it. For there are of course so many things that are relevant to managing our personal lives and coming across in the most effective and self-promoting ways we can.

You should read the entire piece here.