Posts tagged neuroimaging
(Image caption: This is the happiness equation, where t is the trial number, w0 is a constant term, other weights w capture the influence of different event types, 0 ≤ γ ≤ 1 is a forgetting factor that makes events in more recent trials more influential than those in earlier trials, CRj is the CR if chosen instead of a gamble on trial j, EVj is the EV of a gamble (average reward for the gamble) if chosen on trial j, and RPEj is the RPE on trial j contingent on choice of the gamble. The RPE is equal to the reward received minus the expectation in that trial EVj. If the CR was chosen, then EVj = 0 and RPEj = 0; if the gamble was chosen, then CRj = 0. The variables in the equation are quantities that the neuromodulator dopamine has been associated with in previous neuroscience studies. Credit: Robb Rutledge, UCL)
Equation to predict happiness
The happiness of over 18,000 people worldwide has been predicted by a mathematical equation developed by researchers at UCL, with results showing that moment-to-moment happiness reflects not just how well things are going, but whether things are going better than expected.
The new equation accurately predicts exactly how happy people will say they are from moment to moment based on recent events, such as the rewards they receive and the expectations they have during a decision-making task. Scientists found that overall wealth accumulated during the experiment was not a good predictor of happiness. Instead, moment-to-moment happiness depended on the recent history of rewards and expectations. These expectations depended, for example, on whether the available options could lead to good or bad outcomes.
The study, published in the Proceedings of the National Academy of Sciences, investigated the relationship between happiness and reward, and the neural processes that lead to feelings that are central to our conscious experience, such as happiness. Before now, it was known that life events affect an individual’s happiness but not exactly how happy people will be from moment to moment as they make decisions and receive outcomes resulting from those decisions, something the new equation can predict.
Scientists believe that quantifying subjective states mathematically could help doctors better understand mood disorders, by seeing how self-reported feelings fluctuate in response to events like small wins and losses in a smartphone game. A better understanding of how mood is determined by life events and circumstances, and how that differs in people suffering from mood disorders, will hopefully lead to more effective treatments.
Research examining how and why happiness changes from moment to moment in individuals could also assist governments who deploy population measures of wellbeing to inform policy, by providing quantitative insight into what the collected information means. This is especially relevant to the UK following the launch of the National Wellbeing Programme in 2010 and subsequent annual reports by the Office for National Statistics on ‘Measuring National Wellbeing’.
For the study, 26 subjects completed a decision-making task in which their choices led to monetary gains and losses, and they were repeatedly asked to answer the question ‘how happy are you right now?’. The participant’s neural activity was also measured during the task using functional MRI and from these data, scientists built a computational model in which self-reported happiness was related to recent rewards and expectations. The model was then tested on 18,420 participants in the game ‘What makes me happy?’ in a smartphone app developed at UCL called 'The Great Brain Experiment'. Scientists were surprised to find that the same equation could be used to predict how happy subjects would be while they played the smartphone game, even though subjects could win only points and not money.
Lead author of the study, Dr Robb Rutledge (UCL Wellcome Trust Centre for Neuroimaging and the new Max Planck UCL Centre for Computational Psychiatry and Ageing), said: “We expected to see that recent rewards would affect moment-to-moment happiness but were surprised to find just how important expectations are in determining happiness. In real-world situations, the rewards associated with life decisions such as starting a new job or getting married are often not realised for a long time, and our results suggest expectations related to these decisions, good and bad, have a big effect on happiness.
"Life is full of expectations - it would be difficult to make good decisions without knowing, for example, which restaurant you like better. It is often said that you will be happier if your expectations are lower. We find that there is some truth to this: lower expectations make it more likely that an outcome will exceed those expectations and have a positive impact on happiness. However, expectations also affect happiness even before we learn the outcome of a decision. If you have plans to meet a friend at your favourite restaurant, those positive expectations may increase your happiness as soon as you make the plan. The new equation captures these different effects of expectations and allows happiness to be predicted based on the combined effects of many past events.
"It’s great that the data from the large and varied population using The Great Brain Experiment smartphone app shows that the same happiness equation applies to thousands people worldwide playing our game, as with our much smaller laboratory-based experiments which demonstrate the tremendous value of this approach for studying human well-being on a large scale."
The team used functional MRI to demonstrate that neural signals during decisions and outcomes in the task in an area of the brain called the striatum can be used to predict changes in moment-to-moment happiness. The striatum has a lot of connections with dopamine neurons, and signals in this brain area are thought to depend at least partially on dopamine. These results raise the possibility that dopamine may play a role in determining happiness.
Filed under happiness reward decision making neural activity neuroimaging striatum dopamine mathematical equation neuroscience science
The brains of children with autism are relatively inflexible at switching from rest to task performance, according to a new brain-imaging study from the Stanford University School of Medicine.
Instead of changing to accommodate a job, connectivity in key brain networks of autistic children looks similar to connectivity in the resting brain. And the greater this inflexibility, the more severe the child’s manifestations of repetitive and restrictive behaviors that characterize autism, the study found.
The study, published online July 29 in Cerebral Cortex, used functional magnetic resonance imaging, or fMRI, to examine children’s brain activity at rest and during two tasks: solving simple math problems and looking at pictures of different faces. The study included an equal number of children with and without autism. The developmental disorder, which now affects one of every 68 children in the United States, is characterized by social and communication deficits, repetitive behaviors and sensory problems.
“We wanted to test the idea that a flexible brain is necessary for flexible behaviors,” said Lucina Uddin, PhD, a lead author of the study. “What we found was that across a set of brain connections known to be important for switching between different tasks, children with autism showed reduced ‘brain flexibility’ compared with typically developing peers.” Uddin, who is now an assistant professor of psychology at the University of Miami, was a postdoctoral scholar at Stanford when the research was conducted.
“The fact that we can tie this neurophysiological brain-state inflexibility to behavioral inflexibility is an important finding because it gives us clues about what kinds of processes go awry in autism,” said Vinod Menon, PhD, the Rachel L. and Walter F. Nichols, MD, professor of psychiatry and behavioral sciences at Stanford and the senior author of the study.
Tracking shifts in connectivity
The researchers focused on a network of brain areas they have studied before. These areas are involved in making decisions, performing social tasks and identifying relevant events in the environment to guide behavior. The team’s prior work showed that, in children with autism, activity in these areas was more tightly connected when the brain was at rest than it was in children who didn’t have autism.
The new research shows that, in autism, connectivity in these networks that can be seen on fMRI scans is fairly similar regardless of whether the brain is at rest or performing a task. In contrast, typically developing children have a larger shift in brain connectivity when they perform tasks.
The study looked at 34 kids with autism and 34 typically developing children. All of the children with autism received standard clinical evaluations to characterize the severity of their disorder. Then, the two groups were split in half: 17 children with autism and 17 typically developing children had their brains scanned with fMRI while at rest and while performing simple arithmetic problems. The remaining children had their brains scanned at rest and during a task that asked them to distinguish between different people’s faces. The facial recognition task was chosen because autism is characterized by social deficits; the math task was chosen to reflect an area in which children with autism do not usually have deficits.
Children with autism performed as well as their typically developing peers on both tasks — that is, they were as good at distinguishing between the faces and solving the math problems. However, their brain scan results were different. In addition to the reduced brain flexibility, the researchers showed a correlation between the degree of inflexibility and the severity of restrictive and repetitive behaviors, such as performing the same routine over and over or being obsessed with a favorite topic.
“This is the first study that has examined how the patterns of intrinsic brain connectivity change with a cognitive load in children with autism,” Menon said. The research is the first to demonstrate that brain connectivity in children with autism changes less, relative to rest, in response to a task than the brains of other children, he added.
Guidance for new therapies
“The findings may help researchers evaluate the effects of different autism therapies,” said Kaustubh Supekar, PhD, a research associate and the other lead author of the study. “Therapies that increase the brain’s flexibility at switching from rest to goal-directed behaviors may be a good target, for instance.”
“We’re making progress in identifying a brain basis of autism, and we’re starting to get traction in pinpointing systems and signaling mechanisms that are not functioning properly,” Menon said. “This is giving us a better handle both in thinking about treatment and in looking at change or plasticity in the brain.”
(Source: med.stanford.edu)
Filed under autism brain activity neuroimaging default mode network neuroscience science
What sign language teaches us about the brain
The world’s leading humanoid robot, ASIMO, has recently learnt sign language. The news of this breakthrough came just as I completed Level 1 of British Sign Language (I dare say it took me longer to master signing than it did the robot!). As a neuroscientist, the experience of learning to sign made me think about how the brain perceives this means of communicating.
For instance, during my training, I found that mnemonics greatly simplified my learning process. To sign the colour blue you use the fingers of your right hand to rub the back of your left hand, my simple mnemonic for this sign being that the veins on the back of our hand appear blue. I was therefore forming an association between the word blue (English), the sign for blue (BSL), and the visual aid that links the two. However, the two languages differ markedly in that one relies on sounds and the other on visual signs.
Do our brains process these languages differently? It seems that for the most part, they don’t. And it turns out that brain studies of sign language users have helped bust a few myths.
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Filed under sign language neuroimaging communication lesion studies neuroscience science
Neymar’s brain on auto-pilot
Brazilian superstar Neymar’s brain activity while dancing past opponents is less than 10 per cent the level of amateur players, suggesting he plays as if on auto-pilot, according to Japanese neurologists.
Results of brain scans conducted on Neymar indicate minimal cerebral function when he rotates his ankle and point to the Barcelona striker’s wizardry being uncannily natural.
"From MRI images, we discovered Neymar’s brain activity to be less than 10 per cent of an amateur player," researcher Eiichi Naito said on Friday.
"It is possible genetics is a factor, aided by the type of training he does."
The findings were published in the Swiss journal Frontiers in Human Neuroscience following a series of motor skills tests carried out on the 22-year-old Neymar and several other athletes in Barcelona in February.
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(Image: Sergio Moraes / REUTERS)
Filed under Neymar motor control neuroimaging brain activity football neuroscience science
Antipsychotic drugs linked to slight decrease in brain volume
A study published today has confirmed a link between antipsychotic medication and a slight, but measureable, decrease in brain volume in patients with schizophrenia. For the first time, researchers have been able to examine whether this decrease is harmful for patients’ cognitive function and symptoms, and noted that over a nine year follow-up, this decrease did not appear to have any effect.
As we age, our brains naturally lose some of their volume – in other words, brain cells and connections. This process, known as atrophy, typically begins in our thirties and continues into old age. Researchers have known for some time that patients with schizophrenia lose brain volume at a faster rate than healthy individuals, though the reason why is unclear.
Now, in a study published in the open access journal PLOS ONE, a team of researchers from the University of Oulu, Finland, and the University of Cambridge has identified the rate of decrease in both healthy individuals and patients with schizophrenia. They also documented where in the brain schizophrenia patients have more atrophy, and have examined links between atrophy and antipsychotic medication.
By comparing brain scans of 33 patients with schizophrenia with 71 control subjects over a period of 9 years – from age 34 to 43 – the researchers were able to show that schizophrenia patients lost brain volume at a rate of 0.7% each year. The control participants lost brain volume at a rate of 0.5% per year.
Scientists have previously speculated that antipsychotic medication used to treat schizophrenia may be linked to this decrease in brain volume. Today’s research confirms this association, showing that the rate of decrease in volume was greater when the dose of medication was higher. However, the mechanisms behind this – and whether it was in fact the medication that was causing this greater loss of tissue – are not clear. Some researchers have previously argued that whilst older antipsychotic medications might cause brain volume decreases, newer antipsychotic medications may protect against these decreases. However, today’s research suggests that both classes of antipsychotic medication are associated with similar declines in brain volume.
The researchers also looked at whether there was any link between the volume of brain lost and the severity of symptoms or loss of cognitive function, but found no effect.
Professor Juha Veijola from the Department of Psychiatry at the University of Oulu, Finland says: “We all lose some brain tissue as we get older, but people with schizophrenia lose it at a faster rate. We’ve shown that this loss seems to be linked to the antipsychotic medication people are taking. Research like this where patients are studied for many years can help to develop guidelines about when clinicians can reduce the dosage of antipsychotic medication in the long term treatment of people with schizophrenia.”
“It’s important to stress that the loss of brain volume doesn’t appear to have any effect on people over the nine year follow-up we conducted, and patients should not stop their medication on the basis of this research,” adds Dr Graham Murray from the Behavioural and Clinical Neuroscience Institute and the Department of Psychiatry at University of Cambridge. “A key question in future will be to examine whether there is any effect of this loss of brain volume later in life. We need more research in larger studies with longer follow-ups to evaluate the significance of these brain changes.”
Filed under antipsychotics schizophrenia neuroimaging cognitive function neuroscience science
(Image caption: Whole brain functional connectivity between the nucleus accumbens (NAc) and other brain areas in response to cannabis cues (vs. neutral cues) in all participants)
Dependence Alters the Brain’s Response to Pot Paraphernalia
New research from The University of Texas at Dallas demonstrates that drug paraphernalia triggers the reward areas of the brain differently in dependent and non-dependent marijuana users.
The study, published July 1 in Drug and Alcohol Dependence, demonstrated that different areas of the brain activated when dependent and non-dependent users were exposed to drug-related cues.
The 2012 National Survey on Drug Use and Health shows marijuana is the most widely used illicit drug in the United States. According to a 2013 survey from the Pew Research Center, 48 percent of Americans ages 18 and older have tried marijuana. The National Institute on Drug Abuse says that 9 percent of daily users will become dependent on marijuana.
“We know that people have a hard time staying abstinent because seeing cues for the drug use triggers this intense desire to seek out the drugs,” said Dr. Francesca Filbey, lead author of the study and professor at the Center for BrainHealth in the School of Behavioral and Brain Sciences. “That’s a clinically validated phenomenon and behavioral studies have also shown this to be the case. What we didn’t know was what was driving those effects in the brain.”
To find this effect, Filbey and colleagues conducted brain-imaging scans, called functional magnetic resonance imaging (fMRI), on 71 participants who regularly used marijuana. Just more than half of those were classified as dependent users. While being scanned, the participants were given either a used marijuana pipe or a pencil of approximately the same size that they could see and feel.
A comparison of the images revealed that the nucleus accumbens, the reward region in the brain, was activated in all users in response to the pipe. However, the strengths of the connections with other areas differed between dependent and non-dependent users.
“We found that the reward network is actually being driven by other areas unrelated to reward, like the areas in memory and attention or emotion,” Filbey said.
Non-dependent users showed greater activations in the orbital frontal cortex and hippocampus, suggesting that memory and attention were connected to the activation of the reward network. Dependent users had greater activations in the amygdala and anterior cingulate gyrus, suggesting a more emotional connection.
Additionally, the areas of the brain activated resemble areas activated for other addictions, such as nicotine or cocaine, lending greater support to the addictiveness of marijuana.
These findings suggest that marijuana abuse intervention needs to cater more specifically to a user’s level of addiction.
"Clinicians treating people with problems with marijuana dependence should consider the different processes that trigger the reward response when determining possible pharmacological or behavioral interventions,” Filbey said.
Filed under paraphernalia marijuana reward system neuroimaging nucleus accumbens brain activity neuroscience science
The area of the brain that plays a primary role in emotional learning and the acquisition of fear – the amygdala – may hold the key to who is most vulnerable to post-traumatic stress disorder.
Researchers at the University of Washington, Boston Children’s Hospital, Harvard Medical School and Boston University collaborated on a unique opportunity to study whether patterns of brain activity predict teenagers’ response to a terrorist attack.
The team had already performed brain scans on Boston-area adolescents for a study on childhood trauma. Then in April 2013 two bombs went off at the finish line of the Boston Marathon, killing three people and injuring hundreds more. Even people who were nowhere near the bombing reported distress about the attack and the days-long manhunt for the suspects.
So, one month after the attack, Katie McLaughlin, then at Boston Children’s Hospital and Harvard Medical School and now an assistant professor of psychology at the UW; co-author Margaret Sheridan, of Boston Children’s Hospital and Harvard Medical School; and their fellow researchers sent online surveys to teenagers who had previously participated in studies to assess PTSD symptoms related to the attack.
By using functional Magnetic Resonance Imaging scans from before the attack and survey data from after, the researchers found that heightened amygdala reaction to negative emotional stimuli was a risk factor for later developing symptoms of PTSD.
The research study was published July 3 in the journal Depression and Anxiety.
“The amygdala responds to both negative and positive stimuli, but it’s particularly attuned to identifying potential threats in the environment,” said McLaughlin, the study’s first author. “In the current study of adolescents the more their amygdala responded to negative images, the more likely they were to have symptoms of PTSD following the terrorist attacks.”
The brain scans were conducted during the year prior to the bombing. At that time, the teens were evaluated for their responses to emotional stimuli by viewing neutral and negative images. Neutral images included items such as a chair or button. Negative images showed people who were sad, fighting or threatening someone else. Participants rated the degree of emotion they felt while looking at each image. The MRIs measured whether blood flow increased to the amygdala and the hippocampus when viewing negative images as compared to neutral images.
In the follow-up survey the teens were asked whether they were at the finish line during the bombing, how much media exposure they had after the attack, whether they were part of the lockdown at home or school while authorities searched for the suspects, and how their parents responded to the incident. They also were asked about specific PTSD symptoms, such as how often they had trouble concentrating and whether they kept thinking about the bombing when they tried not to.
Researchers found a significant association between amygdala activation while viewing negative images and whether the teens developed PTSD symptoms after the bombing.
McLaughlin said a number of previous studies have shown that people with PTSD had heightened amygdala responses to negative emotions, but researchers didn’t know whether that came before or after the trauma.
“It’s often really difficult to collect neurobiological markers before a traumatic event has occurred,” she said. By scanning the adolescents’ brains before the bombing, she and her fellow researchers were able to show that “amygdala reactivity before a traumatic event predicts your response to that traumatic event.”
While two-thirds of Americans will be exposed to some kind of traumatic event during their lifetime, most, fortunately, will not develop PTSD.
“The more we understand the underlying neurobiological systems that shape reactions to traumatic events, the closer we move to understanding a person’s increased vulnerability to them,” McLaughlin said. “That could help us develop early interventions to help people who might develop PTSD later.”
(Source: washington.edu)
Filed under PTSD amygdala brain activity neuroimaging negative emotions neuroscience science
The inability to ignore irrelevant stimuli underlies the impaired working memory and cognition often experienced by individuals diagnosed with schizophrenia, reports a new study in the current issue of Biological Psychiatry.
Our brains are usually good at focusing on the information that we are trying to learn and filtering out the “noise” or thoughts that aren’t relevant. However, memory impairment in schizophrenia may be related in part to a problem with this filtering process, which Dr. Teal Eich at Columbia University and her colleagues studied.
“Our assumption was that understanding the impairments in the component processes of working memory – the ability to hold and manipulate information in the mind – among patients with schizophrenia could be fundamental to understanding not only cognitive function in the disorder, which is widespread and has debilitating consequences, but also the disorder itself,” Eich explained.
The researchers recruited patients with schizophrenia and a control group of healthy volunteers to complete an item recognition task in the laboratory while undergoing a functional magnetic resonance imaging scan. In particular, they focused on analyzing potential activation differences in the ventro-lateral prefrontal cortex (VLPFC), a region of the brain implicated in working memory.
The design of the task allowed for the assessment of the various components of working memory: 1) maintaining the memory itself, 2) inhibiting or ignoring irrelevant information, and 3) during memory retrieval, controlling the interference of irrelevant information.
While simply maintaining the memory, both groups showed a similar degree of activation in the VLPFC. During the inhibition phase, VLPFC activity is expected to decrease, which was indeed observed in the healthy group, but not in the patients. Finally, during interference control, patients performed worse and showed increased VLPFC activation compared to the healthy volunteers. Overall, the patients showed altered VLPFC functioning and significant impairments in their ability to control working memory.
“Our findings show that these patients have a specific deficit in inhibiting information in working memory, leading to impaired distinctions between relevant and irrelevant thoughts,” said Eich. “This result may provide valuable insights into the potential brain mechanisms underlying the reasons why these affected individuals are unable to control or put out of mind certain thoughts or ideas.”
This study adds to a growing literature suggesting that cognitive functions require both the activation of one set of regions and the inhibition of others. The failure to suppress activation may be just as disruptive to cortical functions as deficits in cortical activation.
Many years ago, the pioneering scientist Patricia Goldman-Rakic and her colleagues showed that the inhibition of regional prefrontal cortical activity was dependent upon the integrity of the GABA (gamma-aminobutyric acid) system in the brain, a chemical system with abnormalities associated with schizophrenia.
“We need to determine whether the cortical inhibitory deficits described in this study can be attributed to particular brain chemical signaling abnormalities,” said Dr. John Krystal, Editor of Biological Psychiatry. “If so, this type of study could be used to guide therapeutic strategies to enhance working memory function.”
(Source: elsevier.com)
Filed under schizophrenia working memory prefrontal cortex neuroimaging cognitive function neuroscience science
A neuroscientist at Rutgers University-Newark says the human brain operates much the same whether active or at rest – a finding that could provide a better understanding of schizophrenia, bipolar disorder and other serious mental health conditions that afflict an estimated 13.6 million Americans.
In newly published research in the journal Neuron, Michael Cole, an assistant professor at the Center for Molecular and Behavioral Neuroscience, determined that the underlying brain architecture of a person at rest is basically the same as that of a person performing a variety of tasks.
This is important to the study of mental illness because it is easier to analyze a brain at rest, says Cole, who made the discovery using functional magnetic resonance imaging (fMRI).
“We can now observe people relaxing in the scanner and be confident that what we see is there all the time,” says Cole, who initially feared his team might find that the brain reorganizes itself for every task. “If that had been the case, we would have had less hope that we could understand mental illness in our lifetime.”
Instead, Cole says, scientists can now make their search for causes of mental illness more focused – and he suggests at least one target of opportunity. The prefrontal cortex is a portion of the brain involved in high level thinking, as well as remembering what a person’s goal is and the task being performed.
Cole says it would be useful to explore whether connectivity between the prefrontal cortex and other areas of the brain is altered – while the brain is at rest – in people with severe mental illness. “And then we can finally say something fundamental,” he predicts, “about what’s different about the brain’s functional network in schizophrenia and other conditions.”
Those differences, in turn, could explain certain symptoms. For instance, what if a patient has visual hallucinations because poor connectivity between the prefrontal cortex and the portion of the brain that governs sight causes the hallucinations to override what the eyes actually see? Cole suggests that’s just one of the questions that analysis of the brain at rest might help to answer. Others include a person’s debilitating beliefs, such as overly negative self-assessment when depressed.
Opportunities to find better ways to improve patients’ lives might then follow. Cole notes that current medications for severe mental illness, when they help at all, typically do not relieve cognitive symptoms. It is possible the drugs will reduce hallucinations or depressing thoughts, but patients continue to have difficulty concentrating on the task at hand, and often find it hard to find or hold a job. Cole says that even solving that one issue would be a major step forward – and he hopes his new work has helped advance science toward achieving this goal.
(Source: news.rutgers.edu)
Filed under mental illness neuroimaging prefrontal cortex schizophrenia neuroscience science
Neuroscientists leading the largest longitudinal adolescent brain imaging study to date have learned that predicting teenage binge-drinking is possible. In fact, say the researchers in the group’s latest publication, a number of factors – genetics, brain function and about 40 different variables – can help scientists predict with about 70 percent accuracy which teens will become binge drinkers. The study appears online July 3, 2014 as an Advance Online Publication in the journal Nature.
First author Robert Whelan, Ph.D., a former University of Vermont (UVM) postdoctoral fellow in psychiatry and current lecturer at University College Dublin, and senior author Hugh Garavan, Ph.D., UVM associate professor of psychiatry, and colleagues conducted 10 hours of comprehensive assessments – these included neuroimaging to assess brain activity and brain structure, along with other measures such as IQ, cognitive task performance, personality and blood tests – on each of 2,400 14-year-old adolescents at eight different sites across Europe.
“Our goal was to develop a model to better understand the relative roles of brain structure and function, personality, environmental influences and genetics in the development of adolescent abuse of alcohol,” says Whelan. “This multidimensional risk profile of genes, brain function and environmental influences can help in the prediction of binge drinking at age 16 years.”
A 2012 Nature Neuroscience paper by the same researchers identified brain networks that predisposed some teens to higher-risk behaviors like experimentation with drugs and alcohol. This new study develops on that earlier work by following those kids for years (the participants in the study are now 19 years old) and identifying those who developed a pattern of binge-drinking. The 2014 Nature study aimed to predict those who went on to drink heavily at age 16 using only data collected at age 14. They applied a broad range of measures, developing a unique analytic method to predict which individuals would become binge-drinkers. The reliability of the results were confirmed by showing the same accuracy when tested on a new, separate group of teenagers. The result was a list of predictors that ranged from brain and genetics to personality and personal history factors.
“Notably, it’s not the case that there’s a single one or two or three variables that are critical,” says Garavan. “The final model was very broad – it suggests that a wide mixture of reasons underlie teenage drinking.”
Some of the best predictors, shares Garavan, include variables like personality, sensation-seeking traits, lack of conscientiousness, and a family history of drug use. Having even a single drink at age 14, was also a powerful predictor. That type of risk-taking behavior – and the impulsivity that often accompanies it – was a critical predictor. In addition, those teens who had experienced several stressful life events were among those at greater risk for binge-drinking.
One interesting finding, says Garavan, was that bigger brains were also predictive. Adolescents undergo significant brain changes, so in addition to the formation of personalities and social networks, it’s actually normal for their brains to reduce to a more efficient size.
“There’s refining and sculpting of the brain, and most of the gray matter – the neurons and the connections between them, are getting smaller and the white matter is getting larger,” he explains. “Kids with more immature brains – those that are still larger – are more likely to drink.”
Garavan, Whelan and colleagues believe that by better understanding the probable causal factors for binge-drinking, targeted interventions for those most at risk could be applied.
Gunter Schumann, M.D.,professor of biological psychiatry and head of the section at the Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, is the principle investigator of the IMAGEN study, which is the source of this latest paper. “We aimed to develop a ‘gold standard’ model for predicting teenage behavior, which can be used as a benchmark for the development of simpler, widely applicable prediction models,” says Schumann. “This work will inform the development of specific early interventions in carriers of the risk profile to reduce the incidence of adolescent substance abuse. We now propose to extend analysis of the IMAGEN data in order to investigate the development of substance use patterns in the context of moderating environmental factors, such as exposure to nicotine or drugs as well as psychosocial stress.”
In the future, the researchers hope to perform more in-depth analyses of the brain factors involved and determine whether or not there are different predictors for abuse of other drugs. A similar analysis, which is using the same dataset to look at the predictors of cannabis use, is planned for the near future.
(Source: uvm.edu)
Filed under binge-drinking alcohol neuroimaging brain activity brain structure neuroscience science
