Can you hear what I see? How can the silence be so loud?

Our 5 senses of taste, smell, touch, sound, and sight help us to interact and better understand the world around us.  Integrating the feedback from these senses is vital to our survival.  Scientist have found that some individuals can integrate their senses in a way that if one is taken away our brain can make up the deficit in a way that has not been previously explored.
        In The New York Times, an article titled Why we "Hear" some silent GIFs,  reports on   individuals who have auditory responses to soundless visual aids.  A researcher from the Institute of Neuroscience and Psychology of the University of Glasgow made a social media post of a GIF, motion images without sound, and asked if any one could hear it.  Nearly 70 percent of the individuals who responded stated they could hear sound from the silent GIF.  Cognitive neuroscientists Elliot Freeman and Chris Fassnidge of the University of London call this visual-evoked-auditory-response or visual EAR.  Visual EAR is not just for images where you are expecting to hear a sound.  It is prevalent with flashes of light, range of motions, and abstract patterns as well.  One study shows 20 percent of individuals can hear sound during images of flashing light in silent videos.
The researchers at the California Institute of Technology categorize this phenomenon as a type of auditory synesthesia.  Individuals with synetheisia are known to perceive the world differently in which they have an automatic sensory cross activation.  For instance they might see letters or numbers as having colors.  For auditory synetheisia they perceive flashes of light or movements as having sound.  In one experiment they found 4 synesthetes that out performed nonsynesthetes in an experiment involving rhythmic flashes of light.  The subjects were shown 2 sets of  rhythmic flashes of lights.  This was done in 2 trials, one with sound the other without sound.  They were asked to determine if the second pattern of light had the same rhythm as the first.  Both groups performed equally as well with the trial that included sound.  However, with the trial that just had the flashes the synesthetes were accurate 75 percent of the time compared to 50 percent for the nonsynsthete control group.  It seems synesthetes have an advantage because they can "hear" visual patterns.
In recent studies using electrical brain stimulation they discovered signs that auditory and visual brain areas cooperate more in individuals with visual EAR and tend to compete more in non visual EAR individuals.  For them the sound of a flash of light can be powerful enough to drown out real world sounds.   In a talk presented by Dr. Dye at Loyola University Chicago, on Precedence and Recency Effects in Binaural Hearing were he discussed differentiation between sounds based on pitch or frequency.  In the study they wanted to examine the time interval between the source and the echo and which time interval  a lower frequency would be dominant.  As more research is done on the visual EAR individuals I would like to know if they differentiate sound differently than non visual EAR individuals.  Also If we added a visually loud stimulus to the echo or the source would the result be different compared to non visual EAR individuals?   Do visual EAR individuals have an advantage in auditory differentiation because they can better associate it with visual images?

Can you hear this?

           Dye , Raymond H, et al. “Lateralization of Simulated Sources and Echoes Differing in Frequency Based on Interaural Temporal Differences.” The Journal of the Acoustical Society of America, 22 Dec. 2016, 
Murphy, Heather. “Why We Hear Silent GIFs.” The New York Times, 8 Dec. 2017, https://www.nytimes.com/2017/12/08/science/why-we-hear-some-silent-gifs.html?rref=collection%2Fcolumn%2Ftrilobites, http://www.website.com
http://www.caltech.edu/news/caltech-neurobiologists-discover-individuals-who-hear-movement-1455

Impact of Sleep Quality and Sleep Duration on Cholesterol Levels

Josephine Owusu

NEURO 300

Dr. Morrison

Impact of Sleep Quality and Sleep Duration on Cholesterol Levels

Professional drivers, especially truck drivers, frequently experience harmful and unhealthy lifestyles and have elevated cardiovascular health risks. The global economy is to blame for their work conditions, because it requires industries to work round-the-clock under tight, controlled schedules. Their intermittent work schedule creates challenges to maintaining a healthy lifestyle, because it interferes with healthy nutritional habits as well as exercise, sleep, and social interactions. Their extensive and intermittent work hours are connected with sleep deprivation. Moreover, sleep quality and duration impact several features of health, such as, diabetes, hypertension, cardiovascular disease, and mortality.  

Quality and duration of sleep both have a significant influence cholesterol levels through various mechanisms. Cholesterol is transported throughout the body, binded by proteins called lipoproteins. Lipoproteins can be divided into two central types, high density lipoprotein(HDL) and low density lipoprotein(LDL). Too much of LDL cholesterol is unhealthy, therefore it is often classified as "bad cholesterol.” Whereas, HDL has protective properties, so it is often denoted as “good cholesterol.” Endocrine activity is affected by sleep, which then influences several metabolic operations by modifying levels of hormones such as cortisol and thyrotropin. Such health afflictions and diseases not only lead to considerable reduced longevity, or lifespan among long haul drivers, but also have deleterious effects on roadway safety and thereby affect the over-all motoring public. Thus, this present study has two main purposes: 1) to create and analyze a cholesterol outline for long haul drivers, and 2) to determine the relationship between sleep periods/durations, sleep quality, and cholesterol concentrations levels in the sample of long haul drivers (Lemke et. al, 2017).

The investigators collected data for work organization and workplace factors that could possibly be linked to cholesterol amongst long-haul truck drivers. The investigators used a descriptive cross-sectional survey to gather data from 262 long-haul truck drivers from a large truck stop in North Carolina. With the assistance from additional key instruments and related sleep literature, the investigators used the Trucker Sleep Disorders Survey that has been used in other relevant sleep studies. The Trucker Sleep Disorders Survey included questions that measured compensation type and daily work hours. In particular, compensation type and daily work hours were categorical question. For instance, drivers were asked “On average, how many hours do you work in a day?” The response choices for this question were: 6 or less hours; 7–8 hours; 8–9 hours; 9–10 hours; 10–11 hours; 11–12 hours; 12–13 hours; 13–14 hours; and more than 14 hours (Lemke et. al, 2017). In addition, the survey included questions that measured sleep quality and sleep periods/durations. In order to measure sleep periods, drivers were asked, “On average, how many hours of sleep do you get on your workdays?”.  Their answers were categorized in compliance with the National Sleep Foundation standard rules: ‘Short’ (<7hrs.); ‘Optimal’ (7–9 hrs.) and ‘Long’ (>9hrs.). The drivers were also asked how often they got adequate sleep at night using the subsequent response choices: never, rarely, almost every night, and every night (Lemke et. al, 2017).

In order to examine the blood cholesterol levels in the sample of long-haul truck drivers, the drivers were administered a blood test to measure LDL (mg/dL), HDL (mg/dL), non-HDL (mg/dL), and total cholesterol (mg/dL). The cholesterol levels were expressed in milligrams (mg) of cholesterol per deciliter (dL) of blood. Then, the investigators carried out a descriptive analysis of the cholesterol levels of LDL, HDL, non-HDL, and total cholesterol. Next, they performed a succession of linear regression analyses to assess for probable, prognostic connections amongst workplace factors, sleep quality, sleep periods/durations and cholesterol (HDL, LDL, and total cholesterol) results.

Results showed that when asked about the number of hours that the long-haul drivers actually slept on their workdays, the drivers reported receiving an average of 6 hours and 55 minutes of sleep on their workdays. However, on their non-workdays, they reported receiving an average of 8 hours and 16 minutes.

Many long-haul truck drivers demonstrate high-risk indicators for serious physical health conditions. These include, but are not limited too, high cholesterol and increased risk for heart disease. Approximately 66% of drivers had low HDL scores (<40 mg/dL), and approx. 42% had a high cholesterol to HDL cholesterol ratio. This indicates a two-fold increased risk for heart disease. Sleep quality of drivers was linked to HDL, LDL, and total cholesterol, while sleep duration was linked to LDL cholesterol. These findings reveal how sleep quality and sleep durations can produce detrimental effects on cholesterol levels.

Furthermore, the findings of this investigation concerning the impact of sleep quality and sleep periods/durations on cholesterol levels, have shown that insufficient sleep periods and quality is coupled with reduced HDL cholesterol levels, insufficient sleep quality also heightens the risk of cardiovascular disease, and that sleep disruptions increase cholesterol levels.

Similar to this experiment, Dr. Baura also presented research on sleep deprivation amongst long-haul drivers at Loyola’s Neuroscience seminar. In Dr. Baura’s presentation, she showed that truck drivers are at a high-risk for several health diseases (especially sleep apnea). She also revealed that long-haul truck drivers received approximately 5 hours of sleep per day, which is relatively close to the results in Lemke et. al study. Dr. Baura presented electroencephalograms from Mitler’s study which showed that drivers experiences episodes of stage 1 sleep while they were driving between the hours of 11 p.m. – 5 a.m (Mitler et. al, 1997). Both Baura’s presentation and Lemke’s investigation show that long-haul truck drivers are still a disregarded profession from a public health perceptive. In addition, Baura and Lemke’s investigations emphasize the need for stakeholders in healthcare to take action by implementing all-inclusive worksite health organizations. The public health sector and the haulage industry should recognize and address these issues, and joint action from both sides should be taken to treat drivers’ work conditions.   

Work Cited

Lemke, Michael & Apostolopoulos, Yorghos & Hege, Adam & Wideman, Laurie & Sönmez, Sevil. (2017). Work, Sleep, and Cholesterol Levels of U.S. Long-Haul Truck Drivers. Industrial Health. 55. 10.2486/indhealth.2016-127.

Mitler, M. M., Miller, J. C., Lipsitz, J. J., Walsh, J. K., & Wylie, C. D. (1997). The Sleep Of Long-Haul Truck Drivers. The New England Journal of Medicine,U.S. National Library of Medicine. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC243092/

A Vaccine to Tackle the Opioid Epidemic?

The topic on opioid-induced hyperalgesia made me interested in looking into the opioid epidemic we currently have in the United States.

Currently, heroin is one of the most preferred illicit drugs of choice, and like mentioned in the article, is taken by a variety of people. With heroin being  Rich and poor, the psychologically distressed because of abuse or because they are looking for the high. Heroin is processed from morphine, which comes from the opium poppy plant, giving the family of drugs the appropriate name of “opioids”. Drugs like Vicodin, Percocet, and OxyCotin are all made from synthetic morphine and are given with the intention to relieve pain but are illicitly used to induce a high. In recent years, heroin has been laced with fentanyl and the number of heroin users alone has tripled in the United States between the years of 2003 and 2014.

While the Chicago area is ranked number one nationally for emergency room visits related to heroin use, the issue is a global one. All over the United States the deaths from heroin overdoses have also tripled in the past 15 years, and even the current President of the United States has declared the opioid crisis a public health emergency. Programs exist, but getting people to commit to the program is hard, and not to relapse shortly after is even harder. There are medications as well, like methadone, buprenorphine, and naltrexone. Each of these treatments do work in their own way, but patients experience undesirable side effects and also might be able to take enough heroin to get over the unpleasant effects or not follow through with their plan. Addiction is an ongoing struggle, because addictive substances transform the brain’s pleasure circuits, causing changes that linger long after users stop taking the drug.

The idea behind the vaccine is simple, what if someone were to take heroin and instead of feeling the pleasurable effects they normally would, they just would not feel anything at all? Heroin is preferred over morphine because heroin has an easier time slipping through the blood-brain barrier. While giving a vaccine might sound a little strange, if we talked about addiction as an illness or disease, then it does not seem as strange. The pleasure is all processed in the brain, so Dr. Kim Janda’s lab at the University of Washington in collaboration with the Scripps Research Institute looked into how a vaccine could be a viable option for battling addiction. It is not like a typical vaccine in the nature of what it would do, like help the immune system generate antibodies to train the body in preparation for the real thing. The vaccine instead would inhibit the effects of heroin. Janda says the difference, however, with this vaccine, is it’s focus on targeting heroin, morphine (since the body degrades heroin into morphine), and an opioid called 6-acetyl morphine, an intermediate between heroin and morphine.

The idea to use a vaccine to battle addiction has been around for a (surprisingly) long time. The efforts to create a vaccine, however, were not as favorable as first trying out different methods like using less potent drugs so that patients can better deal with the terrible withdrawal symptoms. With an increasing number of users, other methods were put to the test. Vaccines for addiction still face criticism today, even in the face of overwhelming positivity towards the advancement of the vaccine. While it’s only been tested on rhesus monkeys and mice, most people seem to think it’s a step in the right direction while critics see it as not helping, since the person does not tackle it on their own or get to the underlying cause of substance abuse.

The vaccine, if passes human trials and was made available, would be another weapon in the battle against addiction. Coupled with psychotherapy, heroin dependencies could become an easier habit to beat. But like stated in the article, if the person does not want the help, they will not change.

Opioid Prevalence in the United States

In 2013, physicians across the country collectively wrote about 25 million prescriptions for different opioid medications. Opioids are medically used to lessen moderate to severe pain in patients, but can very easily be mishandled or incorrectly mixed with additional prescription medications, resulting in a variety of negative side effects. Many patients being treated with opioids struggle with tolerance and dependency issues, and approximately twelve percent of these patients develop a disorder due to and related to their opioid usage. This increase in accessibility and neglect of proper medical supervision led to a widespread misuse issue of several different forms of prescription opioids, such as Oxycodone and Hydrocodone. 

Although there are other more well-known opioids being misused such as heroin and fentanyl, research has shown that prescription drugs remain significant contributors to the opioid crisis. In order to combat this nationally-recognized issue, both the U.S. Department of Health and Human Service and the National Institution of Health developed a set of main initiatives, including the increased research aimed toward designing pharmaceutical alternatives for opioid medications, as well as studying the specific nature of opioids themselves in order to improve upon the current medications being distributed.

In the study “Mu Opioid Splice Variant MOR-1K Contributes to the Development of Opioid-Induced Hyperalgesia,” researchers isolated and studied a certain negative characteristic of opioids. At times, patients receiving opioid medication for chronic pain management actually experienced heightened sensitivity to pain, rather than a decrease. In order to determine where this operational error occurred, researchers identified a genetic variant of a opioid receptor (Mu receptor MOR-1) that contained a variation in the splice site where coding and non-coding regions are supposed to separate. An abnormal variation in a splice site like what occurs in the MOR-1K variant disturbs the separation of these two segments, producing a receptor that functions slightly differently from the rest. In this here considered study, the MOR-1K receptor variant leads to decreased response to opioids, as well as an increase in surrounding cellular activity. 

Although this study considers a seemingly very small portion of the many aspects that contributes to opioid reception and function within the human body, it represents a pattern of opioid-concentrated research that directly impacts a massive community in the U.S. Studies like this one add another piece of information to the scientific and medical community’s collective understanding of the nuances of opioid structure and function. 

“Opioid Overdose.” Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 29 Aug. 2017, www.cdc.gov/drugoverdose/opioids/prescribed.html.

Abuse, National Institute on Drug. “Opioid Overdose Crisis.” NIDA, 1 June 2017, www.drugabuse.gov/drugs-abuse/opioids/opioid-overdose-crisis.

Oladosu FA, Conrad MS, O’Buckley SC, Rashid NU, Slade GD, Nackley AG (2015) Mu Opioid Splice Variant MOR-1K Contributes to the Development of Opioid-Induced Hyperalgesia. PLoS ONE 10(8): e0135711. doi:10.1371/journal.pone.0135711

Sleeping at Work

Sleeping at Work

            In today’s society, sleep has been seen as such an important aspect when it comes to one’s daily routine. Not only does sleeping or napping allow one to feel well rested and attentive, but it also allows one to be more prepared and ready to accomplish a certain task or work for the continuing day. The more hours of sleep we are able to attain, the more productive and efficient our workdays become. Though to some sleep may not appear as a dire necessity to get effective work accomplished, it has been found through different research studies that more hours of sleep or small effective naps in between work can allow for a more productive and alert day.

             Many companies today have allowed for individuals to take naps throughout the day to help combat unproductive hours later on. This has been able to show more productivity. Furthermore, occupations in Spain have all been known to operate on a similar system of siestas before lunchtime. By doing this, working individuals as well as students go home for roughly two to three hours, partaking in their lunch as well as sleeping for a set amount of time. Once awake, it is said that people who have taken a siesta or have slept for a set amount of hours during a day have been able to do more later on and feel more energized.

            In the New York Times article, “Take Naps at Work. Apologize to No one,” by Tim Herrera, the idea behind taking naps at a specific point throughout the day is emphasized heavily. Throughout the article, Herrera gives his own viewpoint of the problem that comes with not taking a sleep break as well interviews CEOs of companies that advocate for sleep breaks alongside psychologists, neuroscientists, and doctors who give their opinion on why sleep throughout the day can be seen as essential. In an interview with Josh Bersin, founder of Deloitte, Bersin explains in his interview with Herrera why he believes naps during the day need to be implemented. As stated by him, “Companies are suffering from tremendous productivity problems because people are stressed out and not recovering from the workday.” Bersin goes on to further explain that with the everlasting hours of continuous work throughout a given day, there’s comes a point where this stress needs to be combated with a break throughout the day.

From a neuroscience standpoint, Herrera interviewed and gathered information based on a study published in “Nature Neuroscience.” In this study, researchers decided to see how people’s perceptual performance changed throughout the day. They conducted this study four times throughout the day with two different sets of people. The first group of people didn’t take a nap throughout the day. The results obtained were able to show that with each test conducted, perceptual performance deteriorated. However, with the second group, the results were the opposite. The second group was given a 30 minute or 60 minute nap and with this time to sleep, their perceptual performance was seen to stay the same as it already was or with some, the perceptual performance was seen to have improved. According to Sara Mendick who was a co-author of this study as well as a professor of psychology at University of California, Riverdale and who was interviewed by Herrera, Mendick concluded that naps were able to have very similar benefits that overnight sleeping has. Along with this, she claimed that different types of sleep at different times can benefit an individual in different ways. She explained how 20-60 minute naps can help with memorization learning specific bits of information while a 90 minute nap in the day can give you a full cycle of sleep. These bits of information explained by Mendick showed the accurate representation of how much sleep is able to help in our day.

During a neuroscience seminar at Loyola University Chicago on December 5, 2017, Dr. Gail Baura presented her research work on truck drivers falling asleep on late night trips. In her research study, she examined four groups of people; two of the groups were truck drivers who were accomplishing trips in the United States and the other two groups were truck drivers who were accomplishing trips in Canada. Within this study, Baura examined the amount of sleep that these truck drivers were getting each night and was able to correlate it to late night accidents or the amount of times that truck drivers had to pull over during the night to rest. As a result, the truck drivers who got more amount of sleep (even if it was by an hour or two) were able to show less accidents on the road late at night and were also able to work a longer duration for driving late at night. These results from the study are able to correlate to Tim Herrera’s article in terms of how more sleep equates to better work ethic as well as more productive hours.

With the effort of Herrera’s article alongside Dr. Baura’s research, it is evident that more sleep and sleep during the day can give one better attentive effort as well as more productive hours during the day. Tim Herrera was able to show this with the interviews conducted as well as the studies that were conducted by Sara Mendick. Alongside this, Dr. Gail Baura’s research was able to demonstrate what longer sleep and sleep during the day can do for one. As shown, sleep is very important and it is able to determine the outcome of productivity as well as safeness for truck drivers.

Works Cited

·      Herrera, Tim. “Take Naps at Work. Apologize to No One.” The New York Times, The New York Times, 23 June 2017, www.nytimes.com/2017/06/23/smarter-living/take-naps-at-work-apologize-to-no-one.html.

·      Baura, Gail, and Merrill M Mitler. “The Sleep of Long Haul Truck Drivers.” NEJM_TruckDrivers.Pdf | Powered By Box, 19 Nov. 2017, luc.app.box.com/v/neuroseminar/file/251218239087.

Dr. Baura on Drowsy Drivers and Self-Driving Cars

Loyola’s Dr. Gail Baura spoke on sleep deprivation research in long-haul truck drivers, and its relevance to the current debate on self-driving cars.  Dr. Baura’s assigned article, “The Sleep of Long-haul Truck Drivers”, from the New England Journal of Medicine, reported on a study done in 1988 using multiple methods of data recording.  This included a questionnaire on sleep habits, electroencephalogram and eye-movement recordings, infrared videos of the driver and of the speed and position of the truck, along with polysomnography during sleep periods each night.  Together these data were designed to analyze the drowsiness of truck drivers and the effects it has on their performance.  The study used 80 drivers on normal, revenue-producing routes of two 10-hour schedules and two 13-hour schedules, each set at different times of the day. 

On average, the drivers reported a need for 6-8 hours of sleep each night to be fully alert, but over the course of this study only got 4.78 hours of measured sleep per night.  The results suggested circadian influence when incidents of measured stage-1 sleep at the wheel only occurred during 11pm and 5am.  These findings show that shift workers need to be informed of the importance of sleep and a reliable schedule that follows the body’s natural circadian rhythm, and the risks that come with sleep deprivation. 

Dr. Baura explained the problems with this study in particular and the topic as a whole.  She says there are many proposed measurements of driver drowsiness and performance, and this one is not the best, but is also not the most recent, and there is no true “winner” when it comes to this field of study.  Each method has its flaws, and it’s up to the opinion of the researcher to determine which has the best trade-offs.  This is because drowsiness is variable with each subject - some people have droopy eyes and a low heart-rate, while others will have a glassy-eyed stare or rapid blinking just before drifting into the first sleep-state.  This makes it hard to design a device that can record and recognize these symptoms, and could lead to a high rate of false alarms if they were ever implemented as safety systems in commercial and noncommercial vehicles.

We know this is true because the safety systems already implemented in noncommercial vehicles have overwhelming reports of false alarms, according to Dr. Baura, making the warnings more of an annoyance than a life-saver.  Dr. Baura said this is largely due to the problems with the sensors.  Most sensors used in manual and self-driving cars are less than ideal, because each has its own “blind-spots” - satellite, for example, is useless on a cloudy day.  Some manufacturers try to get around this by combining multiple types of sensors, as do researchers in the field of this study, but Dr. Baura emphasized that this does not mean they add up to a more accurate analysis, it just combines a lot of iffy data and gives false hope for a safer solution.  In Scientific American’s article, “Redefining ‘Safety’ for Self-Driving Cars”, this is an example of how self-driving cars are far from perfect. 

This problem is rooted in the main obstacle for self-driving cars today - human error.  We have yet to find a perfect solution to analyzing a car’s surroundings without risking false assumptions, and poor sensors are only the beginning of the problem.  Even when the right assumption is made, the car has to be programmed to find the safest solution to the environment.  Human-error has been the sole source of self-driving car accidents, aside from one incident in which a truck backed up and hit a self-driving shuttle that had sensed the truck but was only programmed to stop and wait.  The truck hit the shuttle’s bumper and then stopped, so no serious injuries occurred.  However, this exposes the greater issue of unpredictable human error and the infinite ways it can out passengers in danger.  Self-driving cars must obey traffic laws, but car accidents usually take place when drivers disobey these laws, and the safest response is often to disobey laws as well.  The article explains that when a situation does not have a predetermined response, self-driving cars will pull over and stop until the environment returns to normal.  This sounds logical, but Scientific American argues that this is not always the right choice.  What if the best response is to speed up and avoid a collision, or to swerve before there’s time to signal? 

In both drowsiness research and self-driving programming, the biggest obstacle is creating a system that accounts for all human variability, but human behavior is largely unpredictable.  Until we can find a way to program for this, self-driving cars will never be 100% accident-free while sharing the road with human drivers - drowsy or not.

Sources

Mitler, M. M., et. al. (1997) The Sleep of Long-Haul Truck Drivers. Massachusetts     Medical Society, The New England Journal of Medicine, 24 Feb. 2016, https://luc.app.box.com/v/neuroseminar/file/251218239087

Saripalli, Srikanth. “Redefining ‘Safety’ for Self-Driving Cars.” Scientific American, The Conversation US, Inc., 29 Nov. 2017, www.scientificamerican.com/article/redefining-ldquo-safety-rdquo-for-self-driving-cars/.