Brain

Researchers from the Universities of Birmingham and Oxford have discovered a specific area of the brain that plays a role in making an attempt to help others. The study, which was published in the journal Current Biology, demonstrates that the effortful, altruistic behavior—the decisions individuals make to benefit others—occurs in a different portion of the brain than the decisions one makes to benefit oneself physically.

It could be possible for clinicians to create methods for treating psychopathic behaviours if they have a better understanding of what exactly occurs in the brain when these decisions are made.

Additionally, it could help to better understand why individuals are willing to engage in common, labor-intensive acts of kindness like volunteering, recycling rubbish to reduce global warming, or stopping to assist strangers. The detected region lies in the front of the brain and is known as the anterior cingulate cortex gyrus (ACCg). Although it is well recognised to influence social behaviour, it has not yet been connected to making an attempt to assist others. Interestingly, the researchers discovered that when people choose self-serving actions, the ACCg is not active.

We frequently have to determine if we can be bothered to make an attempt to assist others out, from holding wide a door to volunteering for a charity, but the brain mechanisms underlying these acts have remained mysterious, according to Dr. Patricia Lockwood, the paper’s lead author. We have come a step closer to understanding what motivates some people, but not others, to conduct actions that are frequently physically taxing in order to help others — even when doing so doesn’t immediately benefit them.

38 people between the ages of 18 and 35 participated in the study. Each participant was required to participate in a difficult decision-making exercise and complete a questionnaire to rate their level of empathy.

While having a functional MRI scan, the subjects made decisions. This highlights several brain regions that are active when people choose to “work” or “rest” to assist themselves or another person.

They had to squeeze a gadget that assessed their grip strength if they selected the job option. They had to keep doing this for long enough to cross a threshold that was displayed on the screen in real time.

They were informed whether they would be working for themselves or for another person for each choice. They had to exert enough pressure to cross the finish line and receive the reward, which was a variety of points that could be exchanged for cash, either for themselves or for the other nameless person they were playing for.

The researchers were able to find patterns in the brain that indicated how much effort people were willing to put in by using a novel statistical approach to analyse the data.

They discovered that the ACCg was the only part of the brain to exhibit the effort pattern when people made these choices to assist others, but it did not respond in any way when people chose to exert effort in order to reward themselves. It’s interesting to note that individuals who reported having a high level of empathy also had the highest effort patterns in ACCg. The researchers discovered that those who shown greater effort in the ACCg also contributed greater grip strength.

The study team’s next step will be to look at what happens to persons who exhibit effortful helpful behaviour after experiencing lesions in that region of the brain as a result of a stroke or another type of brain injury.

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Additionally, they will study how antisocial behaviour affects a person’s ability to put forth effort in activities and their propensity to assist others.

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According to one study, consuming seven or more units of alcohol per week is connected with greater iron levels in the brain. Iron buildup in the brain has been linked to Alzheimer’s and Parkinson’s illnesses, and it may be a contributing factor to alcohol-related cognitive loss.

There is mounting evidence that even moderate alcohol intake might be harmful to brain health. Anya Topiwala and colleagues from the University of Oxford in the United Kingdom investigated the links between alcohol intake and brain iron levels.

Their 20,965 UK Biobank members revealed their personal alcohol usage, and their brains were examined using magnetic resonance imaging (MRI). Almost 7,000 people had their livers scanned utilising MRI to determine systemic iron levels. Everyone took a series of easy tests to measure their cognitive and motor performance. The average age of the participants was 55, and 48.6 percent were female. Although 2.7 percent identified as non-drinkers, the average weekly intake was roughly 18 units, which equates to around 7 1/2 cans of beer or 6 big glasses of wine.

The researchers discovered that alcohol use of more than seven units per week was connected with indicators of increased iron in the basal ganglia, a set of brain areas associated with motor control, procedural learning, eye movement, cognition, emotion, and other functions. Iron buildup in some brain areas was linked to poor cognitive performance.

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This is the most comprehensive investigation of moderate alcohol use and iron buildup to date. Although drinking was self-reported and may be understated, it was thought to be the only realistic way to determine the consumption of such a large population. One weakness of the study is that MRI-derived assessments of brain iron are indirect representations of iron levels, which may confound other brain alterations associated with alcohol intake with changes in iron levels.

Given the frequency of moderate drinking, even little connections can have a significant influence across whole communities, and actions to limit consumption in the general population may be beneficial.

Alcohol causes iron build up in Brain

Topiwala continues, “In the largest study to date, we discovered that drinking more than 7 units of alcohol per week was connected with iron buildup in the brain. Higher brain iron levels have been associated to worse cognitive function. Iron buildup might be the cause of alcohol-related cognitive impairment.”

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A new research presented at the European Academy of Neurology (EAN) Congress 2022 found that the majority of persons who experience ischemic strokes with no recognised risk factors had underlying illnesses.
The study indicated that 67.7 percent of stroke patients with previously undetected major risk factors (UMRF) had one major risk factor. From 2003 to 2018, researchers from the Centre Vaudois in Lausanne, Switzerland, examined the health records of 4,354 stroke patients from the ASTRAL registry, 1,125 of whom had UMRF.

Dylipidaemia, an imbalance of blood fats such as excessive cholesterol or elevated triglyceride levels, was the most commonly found vascular risk factor (61.4 per cent of patients).

High blood pressure was the second most prevalent risk factor (23.7 percent of patients), and one in ten (10.2 percent of patients) had atrial fibrillation, a disorder that produces a rapid and often irregular pulse.

Using multivariate analyses, the researchers discovered a link between UMRF patients and younger age, non-Caucasian ethnicity, contraceptive usage in women under the age of 55, and smoking in patients 55 and older. The study also discovered a link between antiplatelet (blood thinner) usage before to the stroke and a higher BMI (BMI).

The most frequent form of stroke happens when a blood clot or other obstruction shuts off blood flow to the brain.

According to the study’s lead author, Dr. Andre Rego, the findings shed light on main risk factors for ischemic stroke.

“Our findings highlight the need of evaluating and treating blood fat imbalances including excessive cholesterol and triglyceride levels, as well as blood pressure and detecting and treating patients with atrial fibrillation and type 2 diabetes,” Dr. Rego said.

“There was little clinical information regarding the incidence, patient profile, and stroke causes in patients with acute ischemic stroke who had previously undetected significant vascular risk factors prior to our study. We expect that this study will aid in the identification of possible stroke patients who will require more extensive prevention and surveillance in the future.”

A new study connects a daily cycle in brain temperature to survival following traumatic brain damage.

According to new study, normal human brain temperature changes significantly more than previously assumed, and this might be an indication of good brain function. In healthy men and women, while the average mouth temperature is less than 37°C, the average brain temperature is 38.5°C, with deeper brain areas frequently reaching 40°C, particularly in women throughout the day. Human brain temperature research have hitherto depended on data collected from brain-injured patients in critical care, when direct brain monitoring is frequently required.

Recently, a brain scanning technology known as magnetic resonance spectroscopy (MRS) has allowed researchers to assess brain temperature in healthy persons non-invasively.

However, until today, MRS has not been used to investigate how brain temperature fluctuates during the day, or how an individual’s ‘body clock’ impacts this.

Researchers at the Medical Research Council (MRC) Laboratory for Molecular Biology in Cambridge, UK, have created the first 4D map of healthy human brain temperature. This map challenges numerous previously held beliefs by demonstrating the astonishing extent to which brain temperature changes by brain area, age, gender, and time of day. Importantly, these findings call into question a commonly held idea that the temperature of the human brain and body are the same.

Daily brain temp cycle related to survival

The study, which was published in the journal Brain, also included an examination of data from traumatic brain injury patients, which revealed that the occurrence of daily brain temperature cycles highly correlated with survival. These results have the potential to improve our knowledge, prognosis, and treatment of brain damage.

In health, there is an unusual variance in brain temperature.

The researchers selected 40 volunteers, aged 20-40 years, to be scanned at the Edinburgh Imaging Facility, Royal Infirmary of Edinburgh, in the morning, afternoon, and late evening during one day to examine the healthy brain.

They also provided the participants a wrist-worn activity monitor, which allowed them to account for genetic and lifestyle variances in the timing of each person’s body clock, or circadian rhythm.

Also Read: Brain regulates illness symptoms: Study

Knowing the biological time of day that each brain temperature test was performed at allowed variances in each volunteer’s body clock to be included into the study for both ‘night owls’ and’morning larks.’

The average brain temperature in healthy subjects was 38.5°C, which was more than two degrees higher than the temperature recorded under the tongue. The researchers also discovered that brain temperature differed based on the time of day, brain area, sex and menstrual cycle, and age.

While the brain surface was normally colder, deeper brain areas were regularly higher than 40°C, with 40.9°C being the highest measured brain temperature. Brain temperature varied by roughly 1°C among all participants, with the greatest brain temperatures reported in the afternoon and the lowest at night.

On average, female brains were around 0.4°C warmer than male brains. This sex difference was most likely caused by the menstrual cycle, as most females were scanned during the post-ovulation phase of their cycle, and their brain temperature was around 0.4°C higher than females examined during the pre-ovulation period.

The findings also revealed that brain temperature increased with age across the subjects’ 20-year span, most notably in deep brain areas, where the average rise was 0.6°C. According to the researchers, the brain’s ability to cool down may decline with age, and further study is needed to determine whether this is linked to the development of age-related brain problems.

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Researchers from Massachusetts General Hospital and Beth Israel Deaconess Medical Center found that the quantity of brain wave data acquired during nighttime sleep studies might predict future health outcomes, bolstering the idea of sleep as a “window” into health.
The findings reveal that a model based on quantitative sleep data may accurately predict the 10-year risk of all 11 health outcomes studied. Dementia (RR = 6.2), death (RR = 5.7), and moderate cognitive impairment or dementia (RR = 4.0) were the three outcomes with the greatest risk ratios linked with poor-to-average sleep. “It’s surprising that sleep can predict the future incidence of 11 outcomes spanning neurological, psychiatric, cardiovascular, and mortality conditions even before the actual diagnosis,” said lead author Haoqi Sun, a doctorate in machine learning and computational neuroscience and an instructor in neurology at Massachusetts General Hospital. “We already know that sleep provides health information, but it’s still surprising that brain activity during sleep may reflect so much information, let alone other critical signals like breathing and heart rates.”

Quantitative studies of sleep microstructure in 8,673 persons who had a diagnostic sleep investigation in a sleep centre were performed as part of the study.

Quantitative assessments of sleep microstructure were performed on 8,673 persons who received a diagnostic sleep study using polysomnography at a sleep centre. The participants were 51 years old on average, with 51 percent of them being female.
The data acquired by nocturnal EEG, a recording that detects brain waves, yielded 86 characteristics, according to the researchers. They divided the individuals into three groups based on their sleep quality: bad, average, and good, and used a statistical model to estimate health risks. Medical codes, brain imaging reports, drugs, and/or cognition scores were used to assess health outcomes. Age, sex, BMI, and the usage of specific prescription medications were all taken into account as potential confounders.

While sleep medicine doctors commonly utilise sleep studies to diagnose sleep problems like obstructive sleep apnea, Sun believes the findings indicate that deciphering sleep data might play a bigger role in health care.
“The capacity to predict future incident health outcomes using noninvasive physiologic measures of sleep would be crucial,” he added, “since it would allow early treatments to avert adverse consequences.”

A specially constructed odour delivery device, together with machine learning-based analysis of scalp-recorded electroencephalogram, according to the findings of a new study from the University of Tokyo. Researchers have been able to see when and where scents are processed in the brain thanks to this technology.

The study discovered that while odour information in the brain is unrelated to perception during the early stages of processing, unpleasant odours are processed more quickly than pleasant odours once perception occurs. Because smell perception issues might be an early indication of neurodegenerative illnesses, learning more about the neurological roots of odour perception could lead to a better understanding of those diseases in the future.

Does the aroma of a hot cup of coffee help you get your day off to a good start? Or do you find the strong, heady stuff too much to bear? According to new research, whether you think the smell of your morning beverage is nice or not may influence how quickly your brain absorbs it.

A group of researchers at the University of Tokyo developed a system that can distribute 10 different odours in a precise and timely manner. Participants were given the smells and asked to judge how pleasant they were while wearing noninvasive scalp-recorded electroencephalogram (EEG) caps, which capture brain activity.

For the first time, the team was able to interpret EEG data using machine learning-based computer analysis to see when and where a wide range of odours were processed in the brain with great temporal resolution.

“We were surprised that we could detect signals from presented odours from very early EEG responses, as early as 100 milliseconds after odour onset, suggesting that odour information is represented in the brain quickly,” said Mugihiko Kato, a doctoral student at the University of Tokyo’s Graduate School of Agricultural and Life Sciences.

The brain detected the scent before the individual could consciously perceive it, which took several hundred milliseconds.

“Our research revealed that diverse characteristics of perception, such as scent pleasantness, unpleasantness, and quality, come from separate spatial and temporal brain processing,” Kato stated.

“Unpleasantness was represented in the brain before pleasantness and perceived quality,” said Project Associate Professor Masako Okamoto of the Graduate School of Agricultural and Life Sciences. Participants’ brains were able to distinguish unpleasant aromas (such as rotting and rancid smells) from neutral or pleasant odours as early as 300 milliseconds after onset. However, pleasant odours (such as flowery and fruity aromas) were not represented in the brain until 500 milliseconds or later, at the same time as the odour’s quality was conveyed.

Significant regions of the brain involved in affective, semantic (language), and memory processing become most active between 600 and 850 milliseconds following smell onset.

The perception of unpleasant odours earlier in life may serve as an early warning system for future risks. Across sensory modalities, the way each sensory system engages the central nervous system differs (smell, light, sound, taste, pressure, and temperature). “Okamoto stated that when and where olfactory (smell) perception arises in the brain aids our understanding of how the olfactory system operates.” Furthermore, we believe that our research has larger methodological implications. For example, it was not previously recognised that scalp-recorded EEG may be used to assess odour representation from as early as 100 milliseconds. “

This high temporal resolution imaging of how our brains process odours could one day lead to a better understanding of the mechanics of neurodegenerative disorders like Parkinson’s and Alzheimer’s, in which odour dysfunction is an early warning sign. The team is interested in pursuing a number of further research topics. “Odours are perceived along with other sensory information, such as vision, in our daily lives, and each sense influences the perception of the other,” Kato explained. “Although we only used olfactory stimuli in this study, we believe that examining brain activity in more natural settings, such as combining odours with a movie, is crucial.” Maybe Smell-O-Vision will make a comeback?

Understanding how the brain works, particularly how information is processed during various activities, is difficult without understanding how many axons exist in the brain and how many connect distinct functional areas. An approach developed by Burke Rosen and Eric Halgren at the University of California, San Diego, published March 24 in the open-access journal PLOS Biology, demonstrates that, despite the functional importance of connections between distant regions of the brain, the actual number of these connections is low.

Researchers merged diffusion MRI data from the Human Connectome Project with histological cross-sections of the corpus callosum, the primary tract that links the left and right sides of the brain, in the new study.

The Human Connectome maps the strength of all brain connections but does not reveal the exact number of axons, whereas histological cross-sections provide estimates for how many axons are packed into a particular volume. The number of axons in the cerebral cortex was estimated by combining connection strengths and axon densities.

According to the findings, the cerebral cortex has over 2.5 billion long-distance axons. Despite this enormous number, they discovered that the number of connections between distinct functional brain areas was rather modest.

“Our discovery that cortical regions are sparsely linked means that integration occurs either by linkage of dense local connections or through rare, extremely privileged long-range axons.”