It’s a fine line between love and hate in the brain.
Researchers have found results that suggest that the areas in the brain involved in hatred are also activated by love. The researchers scanned human subjects while they viewed the face of a person they hated, and also faces of acquaintances for whom they had neutral feelings.
They then calculated a “hate score” - this was to quantify how much the participant hated each individual. Their results showed that viewing a hated face revealed a basic pattern of activity in the brain, that seems unique to “hate”. This “hate network” has components that have been considered to be important in generating aggressive behaviour and translating this behaviour into action. Most intriguingly though, the network involved regions that are almost identical to the ones activated by passionate, romantic love.
The researchers conclude that the link of these two brain areas may account for why love and hate are so closely linked to each other in life.
I think it is important to remember that there could be so many possible explanations for why these areas light up in both hate and love - a reaction to faces, threats (i.e. maybe you are super sensitive to threat when thinking about the person you love being taken away, etc.) but it’s an interesting study none the less.
These findings won’t appear on any Hallmark card, but romantic love tends to activate the same reward areas of the brain as cocaine, research has shown.
Now Yale School of Medicine researchers studying meditators have found that a more selfless variety of love — a deep and genuine wish for the happiness of others without expectation of reward — actually turns off the same reward areas that light up when lovers see each other.
“When we truly, selflessly wish for the well-being of others, we’re not getting that same rush of excitement that comes with, say, a tweet from our romantic love interest, because it’s not about us at all,” said Judson Brewer, adjunct professor of psychiatry at Yale now at the University of Massachusetts.
Brewer and Kathleen Garrison, postdoctoral researcher in Yale’s Department of Psychiatry, report their findings in a paper scheduled to be published online Feb. 12 in the journal Brain and Behavior.
The neurological boundaries between these two types of love become clear in fMRI scans of experienced meditators. The reward centers of the brain that are strongly activated by a lover’s face (or a picture of cocaine) are almost completely turned off when a meditator is instructed to silently repeat sayings such as “May all beings be happy.”
Such mindfulness meditations are a staple of Buddhism and are now commonly practiced in Western stress reduction programs, Brewer notes. The tranquility of this selfless love for others — exemplified in such religious figures such as Mother Theresa or the Dalai Llama — is diametrically opposed to the anxiety caused by a lovers’ quarrel or extended separation. And it carries its own rewards.
“The intent of this practice is to specifically foster selfless love — just putting it out there and not looking for or wanting anything in return,” Brewer said. “If you’re wondering where the reward is in being selfless, just reflect on how it feels when you see people out there helping others, or even when you hold the door for somebody the next time you are at Starbucks.”
A new study of the brain of a maths supremo supports Darwin’s belief that intellectual excellence is largely due to “zeal and hard work” rather than inherent ability.
University of Sussex neuroscientists took fMRI scans of champion 'mental calculator’ Yusnier Viera during arithmetical tasks that were either familiar or unfamiliar to him and found that his brain did not behave in an extraordinary or unusual way.
The paper, published this week (23 September 2013) in PloS One, provides scientific evidence that some calculation abilities are a matter of practice. Co-author Dr Natasha Sigala says: “This is a message of hope for all of us. Experts are made, not born.”
Cuban-born Yusnier holds world records for being able to name the days of the week for any dates of the past 400 years, giving his answer in less than a second. This is the kind of ability sometimes found in those with autism, although Yusnier is not on the autistic spectrum. Unlike those with autism or the related condition Asperger’s, he is able to explain exactly how he calculates his answers – and even teaches his system and has written books on the subject.
The study, carried out at the Clinical Imaging Sciences Centre on the University of Sussex campus, suggests that Yusnier has honed his ability to create short cuts to his answers by storing information in the middle part of the brain specialised for long-term working memory (the hippocampus and surrounding cortex). This type of memory helps us carry out tasks in our area of expertise with speed and efficiency.
Although the left side of his brain was activated during mathematical problems – which is normal for all brains – the scientists observed that something slightly different happened when Yusnier was presented with unfamiliar problems.
The scans showed marked connectivity of the anterior parts of the brain (prefrontal cortex), which are involved in decision making, during the unfamiliar calculations. This supports Yusnier’s report that he was building in an extra step to his mental processes to turn an unfamiliar problem into a familiar one. His answers to the unfamiliar questions had an 80 per cent degree of accuracy (compared with more than 90 per cent for familiar questions) and his responses were slightly slower.
Dr Sigala explains: “Although this kind of ability is seen among some people with autism, it is much rarer in those not on that spectrum. Brain scans of those with autism tend to show a variety of activity patterns, and autistic people are not able to explain how they reach their answer.
"With Yusnier, however, it is clear that his expertise is a result of long-term practice – and motivation.”
She adds: “It was beyond the scope of our paper to discuss the debate on deliberate practice vs. innate ability. But our study does not provide evidence for specific innate ability for mental calculations. As put by Charles Darwin to Francis Galton: ’ […] I have always maintained that, excepting fools, men did not differ much in intellect, only in zeal and hard work; I still think this an eminently important difference.’”
What if what you saw with your eyes could be interpreted in a brain-scanner? Well, that just happened. Check it out:
Gallant’s coauthors acted as study subjects, watching YouTube videos inside a magnetic resonance imaging machine for several hours at a time. The team then used the brain imaging data to develop a computer model that matched features of the videos – like colors, shapes and movements – with patterns of brain activity.
“Once we had this model built, we could read brain activity for that subject and run it backwards through the model to try to uncover what the viewer saw,” said Gallant.
Subtle changes in blood flow to visual areas of the brain, measured by functional MRI, predicted what was on the screen at the time – whether it was Steve Martin as Inspector Clouseau or an airplane. The reconstructed videos are blurry because they layer all the YouTube clips that matched the subject’s brain activity pattern. The result is a haunting, almost dream-like version of the video as seen by the mind’s eye.
Neuroscience might be taking over the world with data on brain connections and replica projects, as well as applying data onto digital software applications for use in clinical studies. Recent reports praise, dispute, and test how the study of neuroscience is claiming to ease addiction, build a computerized replica of the human brain, and even improve focus by 400 percent.
Scientists from the University of Massachusetts Medical School are applying neuroscience research to areas of the brain which concentrate on addiction. In an interview with Boston’s NPR news station, W.B.U.R., scientists explain how addiction effects areas of the brain that would “hard-wire” it into recognizing and supporting an addiction. Searching for the “neural roots of addiction,” these scientists apply techniques like meditation and technology to ward off symptoms of addiction.
A new study provides neurobiological evidence for dysfunction in the neural circuitry underlying emotion regulation in people with insomnia, which may have implications for the risk relationship between insomnia and depression.
“Insomnia has been consistently identified as a risk factor for depression,” said lead author Peter Franzen, PhD, an assistant professor of psychiatry at the University of Pittsburgh School of Medicine. “Alterations in the brain circuitry underlying emotion regulation may be involved in the pathway for depression, and these results suggest a mechanistic role for sleep disturbance in the development of psychiatric disorders.”
The study involved 14 individuals with chronic primary insomnia without other primary psychiatric disorders, as well as 30 good sleepers who served as a control group. Participants underwent an fMRI scan during an emotion regulation task in which they were shown negative or neutral pictures. They were asked to passively view the images or to decrease their emotional responses using cognitive reappraisal, a voluntary emotion regulation strategy in which you interpret the meaning depicted in the picture in order to feel less negative.
Results show that in the primary insomnia group, amygdala activity was significantly higher during reappraisal than during passive viewing. Located in the temporal lobe of the brain, the amygdala plays an important role in emotional processing and regulation.
In analysis between groups, amygdala activity during reappraisal trials was significantly greater in the primary insomnia group compared with good sleepers. The two groups did not significantly differ when passively viewing negative pictures.
“Previous studies have demonstrated that successful emotion regulation using reappraisal decreases amygdala response in healthy individuals, yet we were surprised that activity was even higher during reappraisal of, versus passive viewing of, pictures with negative emotional content in this sample of individuals with primary insomnia,” said Franzen.
The research abstract was published recently in an online supplement of the journal SLEEP, and Franzen will present the findings Wednesday, June 5, in Baltimore, Md., at SLEEP 2013, the 27th annual meeting of the Associated Professional Sleep Societies LLC.
The American Academy of Sleep Medicine reports that about 10 to 15 percent of adults have an insomnia disorder with distress or daytime impairment. According to the National Institute of Mental Health, 6.7 percent of the U.S. adult population suffers from major depressive disorder. Both insomnia and depression are more common in women than in men.
When you daydream the pattern of activity in your brain, at least to a neuroscientist, is known as the default mode network. The recent discovery of this brain state came as something of a surprise since it occurs when you’re not actively thinking about or doing anything. Scientists can measure brain activity by looking at changes in the amount of oxygen carried by the blood to different parts of the brain. A technique called functional magnetic resonance imaging (fMRI) here highlights the ‘resting’ patterns of brain activity in 34 patients with schizophrenia. These data suggest that the default mode network may be altered in patients with schizophrenia, who still have symptoms despite taking medication. Now the challenge is to find out why.
“The neural changes that we found associated with physical sensation and movement systems suggest that reading a novel can transport you into the body of the protagonist,“ says Gregory Berns. "We already knew that good stories can put you in someone else’s shoes in a figurative sense. Now we’re seeing that something may also be happening biologically.”
- Does reading actually change the brain? | Futurity
Everyone who has ever looked at a pretty fMRI scan or read a popular science article linking some sexy human behavior to a blob on a pretty brain scan (so, “nearly everyone”) needs to read this blog entry at The New Yorker:
…a lot of those reports are based on a false premise: that neural tissue that lights up most in the brain is the only tissue involved in some cognitive function. The brain, though, rarely works that way. Most of the interesting things that the brain does involve many different pieces of tissue working together. Saying that emotion is in the amygdala, or that decision-making is the prefrontal cortex, is at best a shorthand, and a misleading one at that. Different emotions, for example, rely on different combinations of neural substrates. The act of comprehending a sentence likely involves Broca’s area (the language-related spot on the left side of the brain that they may have told you about in college), but it also draws on the parts of the brain in the temporal lobe that analyze acoustic signals, and part of sensorimotor cortex and the basal ganglia become active as well. (In congenitally blind people, some of the visual cortex also plays a role.) It’s not one spot, it’s many, some of which may be less active but still vital, and what really matters is how vast networks of neural tissue work together.
Don’t lose faith. Techniques like fMRI have unlocked some amazing science about the workings of the brain, but they are still pretty low-resolution, and can only take snapshots. What about the actions of individual neurons that fMRI can’t see? What if some processes are explained better using dynamic observations instead of snapshots, like video instead of photos?
…simple explanations of complex brain functions that often make for good headlines rarely turn out to be true. But that doesn’t mean that there aren’t explanations to be had, it just means that evolution didn’t evolve our brains to be easily understood.
Considering it’s the most advanced biological computer ever created, that shouldn’t surprise anyone, right?
I’ve never cared much for dream interpretation. Most of our remembered dreams have always seemed like our minds filling gaps in dreams with our previous experiences and perceptions. Sorry to the psychoanalytic/psychodynamic people out there, but I never bought into it.
This is actually pretty amazing. Scientists have begun to reconstruct images from dreams and hallucinations.
It sounds like science fiction: While volunteers watched movie clips, a scanner watched their brains. And from their brain activity, a computer made rough reconstructions of what they viewed.
The reconstructions are blends of the YouTube snippets, which makes them blurry. Some are better than others. If a human appeared in the original clip, a human form generally showed up in the reconstruction. But one clip that showed elephants walking left to right led to a reconstruction that looked like “a shambling mound,” Gallant said. The YouTube clips hadn’t shown elephants and so “we just had to make do with what we had.”
The quality could be improved by better techniques to blend human forms, as well as a bigger storehouse of moving images, he said.
Still, the overall results are “one of the most impressive demonstrations of the scientific knowledge of how the visual system works,” said Marcel Just, director of the Center for Cognitive Brain Imaging at Carnegie Mellon University.
Think about the possibilities. How much would you pay to have your dreams reconstructed? What about visual representations of schizophrenic hallucinations? Could we apply this technology to coma patients and see what they are experiencing? This is a peek inside the human mind AND the human visual system.
Some people say that reading “Harry Potter and the Sorcerer’s Stone” taught them the importance of friends, or that easy decisions are seldom right. Carnegie Mellon University scientists used a chapter of that book to learn a different lesson: identifying what different regions of the brain are doing when people read.
Researchers from CMU’s Machine Learning Department performed functional magnetic resonance imaging (fMRI) scans of eight people as they read a chapter of that Potter book. They then analyzed the scans, cubic millimeter by cubic millimeter, for every four-word segment of that chapter. The result was the first integrated computational model of reading, identifying which parts of the brain are responsible for such subprocesses as parsing sentences, determining the meaning of words and understanding relationships between characters.
As Leila Wehbe, a Ph.D. student in the Machine Learning Department, and Tom Mitchell, the department head, report today in the online journal PLOS ONE, the model was able to predict fMRI activity for novel text passages with sufficient accuracy to tell which of two different passages a person was reading with 74 percent accuracy.
“At first, we were skeptical of whether this would work at all,” Mitchell said, noting that analyzing multiple subprocesses of the brain at the same time is unprecedented in cognitive neuroscience. “But it turned out amazingly well and now we have these wonderful brain maps that describe where in the brain you’re thinking about a wide variety of things.”
Wehbe and Mitchell said the model is still inexact, but might someday be useful in studying and diagnosing reading disorders, such as dyslexia, or to track the recovery of patients whose speech was impacted by a stroke. It also might be used by educators to identify what might be giving a student trouble when learning a foreign language.
“If I’m having trouble learning a new language, I may have a hard time figuring out exactly what I don’t get,” Mitchell said. “When I can’t understand a sentence, I can’t articulate what it is I don’t understand. But a brain scan might show that the region of my brain responsible for grammar isn’t activating properly, or perhaps instead I’m not understanding the individual words.”
Researchers at Carnegie Mellon and elsewhere have used fMRI scans to identify activation patterns associated with particular words or phrases or even emotions. But these have always been tightly controlled experiments, with only one variable analyzed at a time. The experiments were unnatural, usually involving only single words or phrases, but the slow pace of fMRI — one scan every two seconds — made other approaches seem unfeasible.
Wehbe nevertheless was convinced that multiple cognitive subprocesses could be studied simultaneously while people read a compelling story in a near-normal manner. She believed that using a real text passage as an experimental stimulus would provide a rich sample of the different word properties, which could help to reveal which brain regions are associated with these different properties.
“No one falls asleep in the scanner during Leila’s experiments,” Mitchell said.
They devised a technique in which people see one word of a passage every half second — or four words for every two-second fMRI scan. For each word, they identified 195 detailed features — everything from the number of letters in the word to its part of speech. They then used a machine learning algorithm to analyze the activation of each cubic centimeter of the brain for each four-word segment.
Bit by bit, the algorithm was able to associate certain features with certain regions of the brain, Wehbe said.
“The test subjects read Chapter 9 of Sorcerer’s Stone, which is about Harry’s first flying lesson,” she noted. “It turns out that movement of the characters — such as when they are flying their brooms — is associated with activation in the same brain region that we use to perceive other people’s motion. Similarly, the characters in the story are associated with activation in the same brain region we use to process other people’s intentions.”
Exactly how the brain creates these neural encodings is still a mystery, they said, but it is the beginning of understanding what the brain is doing when a person reads.
“It’s sort of like a DNA fingerprint — you may not understand all aspects of DNA’s function, but it guides you in understanding cell function or development,” Mitchell said. “This model of reading initially is that kind of a fingerprint.”
A complementary study by Wehbe and Mitchell, presented earlier this fall at the Conference on Empirical Methods in Natural Language Processing, used magnetoencephalography (MEG) to record brain activity in subjects reading Harry Potter. MEG can record activity every millisecond, rather than every two seconds as in fMRI scanning, but can’t localize activity with the precision of fMRI. Those findings suggest how words are integrated into memory - how the brain first visually perceives a word and then begins accessing the properties of the word, and fitting it into the story context.
Concern for equality linked to logic, not emotion.
By Lisa Wade, PhD
A new study finds that people with high “justice sensitivity” are using logic, not emotions. Subjects were put in a fMRI machine, one that measures ongoing brain activity and shown videos of people acting kindly or cruelly toward a homeless person.
Some respondents reacted more strongly than others — hence the high versus low justice sensitivity — and an analysis of the high sensitivity individuals’ brain activity showed that they were processing the images in the parts of the brain where logic and rationality live. “Individuals who are sensitive to justice and fairness do not seem to be emotionally driven,”explained one of the scientists, “Rather, they are cognitively driven.”
Activists aren’t angry, they reasonably object to unjust circumstances that they understand all too well.
Image borrowed from Jamie Keiles at Teenagerie, who is a high sensitivity individual.
Check it out: The first neurobiological model for third-party punishment
Here’s a a very recent update to my last post on the Neurobiology of Punishment by Joshua W Buckholtz and René Marois, breaking down the events that take place in the brain when asked to make decisions regarding punishment. Of the five processes you have the frontal cortex (higher mental functions) the amygdala (emotional responses) and the intraparietal sulcus and temporal-parietal junction (interpreting the intent of others, thoery of mind).
In the modern criminal justice system, judges and jury members – impartial third-party decision-makers – are tasked to evaluate the severity of a criminal act, the mental state of the accused and the amount of harm done, and then integrate these evaluations with the applicable legal codes and select the most appropriate punishment from available options. (…)
..it’s assumed legal decision-making is purely based on rational thinking, research suggests that much of the motivation for punishing is driven by negative emotional responses to the harm. This signal appears to be generated in the amygdala, causing people to factor in their emotional state when making decisions instead of making solely factual judgments.
Getting ahead of ourselves: glossy brain porn v. emotion
What happens if the jury is presented with neuroscientific evidence suggesting what may have caused the accused to offend, e.g., a brain scan showing a tumor? This may challenge the negative emotional response since it’s been reported that this type of evidence is so seductive to juries. >law & order, donk donk<
Findings point to potential biomarkers for early detection of at-risk youth
Researchers at the University of California, San Diego School of Medicine have discovered impaired neuronal activity in the parts of the brain associated with anticipatory functioning among occasional 18- to 24-year-old users of stimulant drugs, such as cocaine, amphetamines and prescription drugs such as Adderall.
The brain differences, detected using functional magnetic resonance imaging (fMRI), are believed to represent an internal hard wiring that may make some people more prone to drug addiction later in life.
Among the study’s main implications is the possibility of being able to use brain activity patterns as a means of identifying at-risk youth long before they have any obvious outward signs of addictive behaviors.
The study is published in the March 26 issue of the Journal of Neuroscience.
“If you show me 100 college students and tell me which ones have taken stimulants a dozen times, I can tell you those students’ brains are different,” said Martin Paulus, MD, professor of psychiatry and a co-senior author with Angela Yu, PhD, professor of cognitive science at UC San Diego. “Our study is telling us, it’s not ‘this is your brain on drugs,’ it’s ‘this is the brain that does drugs.’”
In the study, 18- to 24-year-old college students were shown either an X or an O on a screen and instructed to press, as quickly as possible, a left button if an X appeared or a right button if an O appeared. If a tone was heard, they were instructed not to press a button. Each participant’s reaction times and errors were measured for 288 trials, while their brain activity was recorded via fMRI.
Occasional users were characterized as having taken stimulants an average of 12 to 15 times. The “stimulant naïve” control group included students who had never taken stimulants. Both groups were screened for factors, such as alcohol dependency and mental health disorders, that might have confounded the study’s results.
The outcomes from the trials showed that occasional users have slightly faster reaction times, suggesting a tendency toward impulsivity. The most striking difference, however, occurred during the “stop” trials. Here, the occasional users made more mistakes, and their performance worsened, relative to the control group, as the task became harder (i.e., when the tone occurred later in the trial).
The brain images of the occasional users showed consistent patterns of diminished neuronal activity in the parts of the brain associated with anticipatory functioning and updating anticipation based on past trials.
“We used to think that drug addicts just did not hold themselves back but this work suggests that the root of this is an impaired ability to anticipate a situation and to detect trends in when they need to stop,” said Katia Harlé, PhD, a postdoctoral researcher in the Paulus laboratory and the study’s lead author.
The next step will be to examine the degree to which these brain activity patterns are permanent or can be re-calibrated. The researchers said it may be possible to “exercise” weak areas of the brain, where attenuated neuronal activity is associated with higher tendency to addiction.
“Right now there are no treatments for stimulant addiction and the relapse rate is upward of 50 percent,” Paulus said. “Early intervention is our best option.”
Being in a group makes some people lose touch with their personal moral beliefs, researchers find.
When people get together in groups, unusual things can happen — both good and bad. Groups create important social institutions that an individual could not achieve alone, but there can be a darker side to such alliances: Belonging to a group makes people more likely to harm others outside the group.
The research is in NeuroImage. (full access paywall)
Research: “Reduced self-referential neural response during intergroup competition predicts competitor harm” by M Cikara, AC Jenkins, N Dufour, and R Saxe in Neuroimage. Published online June 2014 doi:10.1016/j.neuroimage.2014.03.080
Image: When people are in a group, they feel more anonymous, and less likely to be caught doing something wrong. They may also feel a diminished sense of personal responsibility for collective actions. The image shows one of Banksy’s murals called ‘Riot’. The image is for illustrative purposes only. Credit Sal Taylor Kydd.