Entries in neuroscience (11)


Brains Understanding Computers Understanding Brains

“Computers aren’t smart.”  That’s the first thing my professor said on the first day of in Intro to Computer Science. “They’re dumb, but they’re fast,” he added.  At first I couldn’t believe what my professor was saying.  Computers seem to be quite intelligent.  IBM’s Watson could compete with Jeopardy! champions.  Need to know the answer to a question?  Just type it into Google.  Over the last few years, as I’ve learned more about computer science, I’ve come to learn that what my professor said on that first day of class is absolutely true.
In order to work, computers require extremely specific and detailed instructions laid out in a code they can understand.  Leave out a semicolon at the end of a line?  Forget it.  The computer will stop working.  A computer is nothing without a human brain to help it along.
The real value to a computer, of course, is its speed.  Today, an average laptop can carry out over a billion instructions in just one second.  Need to add up a million numbers in a spreadsheet?  Today’s computers can do so instantly.  Today’s computers can analyze massive amounts of data in very short amounts of time.
This is welcome feature for researchers studying the brain.  A single brain scan today can generate several gigabytes of data.  Even 25 years ago, this was unthinkable [1].  With new projects like the US Government’s BRAIN Initiative, research centers across the country are generating more data on the human brain than ever before [2].  To analyze this data, researchers are working hard to develop new algorithms and computational techniques.  Many scientists have expressed how important it is to train new researchers in the science of “big data” if we are ever going to truly understand how the brain works [3], [4].
The “big data” methods being used to better understand the human brain are the same that determine which advertisements show up in your web browser; the same that help Google decide what you’re searching for; the same that stock brokers use on Wall Street; and the same that the NSA controversially uses to “protect” sensitive American communications.
With big data, computers are starting to look like they might actually be smarter than humans.  But this isn’t true.  Without a human brain to ask the right questions and interpret the results, big data algorithms are worthless.  Rather, humans and computers are beginning to form a symbiotic relationship.  We use computers to speed up our own mental processing.  And now in neuroscience, we use computers and the artificial intelligence we have given them, to better understand our own intelligence, and our own minds.
[1] https://en.wikipedia.org/wiki/History_of_hard_disk_drives
[2] http://www.braininitiative.nih.gov/index.htm
[3] Sukel, K. “Big Data and the Brain: Peaking at the Future of Neuroscience.” BrainFacts.org, 8 Dec 2015. Web.
[4] Van Horn, JD. “Opinion: Big data biomedicine offers big higher education opportunities. Proc Natl Acad Sci USA, 7 June 2016:113(23):6322-4 doi: 10.1073/pnas/1607582113.



Brain Connectivity and Video Game Addiction

Pokemon Go, a game that allows users to catch Pokemon while walking around, has taken the world by storm. The app has surpassed Netflix, Twitter, and Tinder in popularity.  The game’s immense success got me curious about video game addiction and the neuroscience behind it.

In a study published in Addiction Biology in December 2015, researchers found that there were differences in brain connectivity in adolescent boys who were compulsive video game players compared to boys without the disorder. fMRI was performed on 106 boys aged 10-19 who were being treated for Internet gaming disorder and 80 boys without the disorder. In those with Internet gaming disorder, brain regions associated with vision and hearing (auditory cortex and frontal eye field) had enhanced connection to the motor cortex and  “salience network”, which focuses attention on important events and response action. Researchers also found increased coordination between the dorsolateral prefrontal cortex and the temporoparietal junction, which has also been seen in patients with neuropsychiatric conditions such as schizophrenia, Down’s syndrome, and autism. The study was a collaboration between Chung-Ang University School of Medicine in South Korea and the University of Utah School of Medicine.

The researchers stated that it’s unknown whether persistent video gaming causes rewiring of the brain or whether individuals with differently wired brains are drawn to video games. While Pokemon Go has benefitted its users by increasing fitness and becoming a social experience, it has also caused accidents due to distracted users. Pokemon Go certainly seems to have gained quite a following. Who knows what an fMRI study could reveal… 







Street Drug W-18 Has Grabbed the Attention of Canadian and United States Law Enforcement

A new street drug called W-18 claims to be 10,000 times more powerful than morphine, produces a heroin-like high, and may be the most deadly drug seen in several decades. Subsequently, U.S. law enforcement, scientists and government are scrambling to characterize this drug and determine the potential harm, if any. On June 1st 2016, Canada passed laws making W-18 illegal to possess, produce, or traffic.

On June 2nd 2016, scientists gathered at Northeastern University for a conference co-hosted by the Center for Drug Discovery (CDD) at Northeastern University and the National Institute on Drug Abuse (NIDA) to discuss the chemistry and pharmacology of addiction research. The symposium was led by a discussion on W-18, and recent unpublished scientific results characterizing its mechanism of action. Several scientists from this conference indicated that W-18 is not an opiate at all, as it failed to demonstrate any reasonable affinity for opioid receptors in cellular experiments. In addition, a common test for determining opioid specificity is a blocking experiment performed with naloxone (Narcan), as this drug blocks the effects of all known opiates. Results from this experiment indicated that naloxone does not block the effects of W-18, further disproving the claims that this drug is a synthetic opiate. The misrepresentation of this street drug as a synthetic opiate has deceived opiate dependent users in thinking that they can tolerate such a drug and that Narcan will be able to reverse accidental overdose. These claims are simply untrue and unfortunately may result in death from this street drug. While the exact target of this drug is still unknown, scientists mentioned that W-18 was toxic in cellular assays, supporting the effects law enforcement and hospitals have witnessed from victims who have used W-18 and/or combined its use with other illicit substances. In addition, deaths related from this drug are likely underrepresented due to the difficulty in detecting the drug in toxicology tests. Law enforcement officials in Philadelphia say they haven't been able to prove that W-18 has killed anyone. "It scares the living crap out of us, but we haven't seen it yet," said Patrick Trainor, spokesman for the DEA's Philadelphia office.” [excerpt from philly.com]

No information on W-18 is currently available on NIDA’s website.

Dr. Bryan Roth, M.D., Ph.D., Director of the National Institute of Mental Health Pyschoactive Drug Screening Program at UNC School of Medicine was recently quoted on his preliminary results in a recent news article on VICE NEWS, an international news organization. That article can be found here:


A recent article on W-18 posted on philly.com:




Individual differences shape empathetic drive

Dr. Spock had an exceptional, in fact other-worldly ability to read the thoughts of people he encountered.

A new report in the journal Motivation and Emotion suggests this may not be just for Vulcans.

Mind-Reading Motivation (MRM) is a new construct detailed by lead author Jordan Carpenter (University of Pennsylvania) and corresponding author Dr. Melanie Green (Associate Professor, University of Buffalo).

MRM involves using cues from other people’s behavior – facial expressions, hand movements, body posture and ‘language’ and hundreds of other non-verbal cues to try to figure out what they are thinking.  People high in MRM have a tendency to speculate on others’ thoughts and enjoy doing so whereas people low in MRM dislike or have no interest in doing so.

Two features of MRM stood out to me: One, that the motivation to understand the thoughts of others was not related to direct benefit. Although the outcome of striving for mental synergy can definitely lead to improved teamwork and greater social harmony, these outcomes, at best, would be delayed;  Two, that MRM seems to go beyond coarse perception and develops what Dr. Green described as “…richer psychological portraits of those around them. It’s the difference between saying ‘this person strives for success, but is afraid of achieving it’ as opposed to ‘this person is a great cook’.”

Dr. Green’s work in the Department of Communication and her co-author colleagues at the Hass School of Business at UC Berkeley interpret their findings of individuals who have high or low MRM with respect to they types of information and social cues that could influence MRM groups differently.  This has significant implications for relationships as well as in generic vs. targeted advertising.

Beyond improving ads for a commercial product, it is fascinating to me to consider how MRM could be described in the context of prodromal psychiatric disease. Is the motivation to understand the thoughts of others an early signal of later more extreme changes in social engagement or withdrawal?

From a neuroimaging perspective, which areas of the brain are engaged when interpreting the thoughts of others? What does MRM as a mental practice derive in neurotransmitter release in the short and long term? Do high MRM individuals necessarily change their behavior based on their interpretations?

Integrating static and social information quickly (possibly in part by MRM) may be a hallmark of success – where one example in science might be successful grant writing.  Besides technical precision in a proposal, successful applications seem to contain a fickle element that makes them inherently attractive – a mixture of confidence and mutual understanding with the reviewer, despite the single-blinded mechanism (at least via NIH). Perhaps a subconstruct could be described as Remote Mind-Reading Motivation, RMRM, or even POMRM to at least tap into the mind of your grants Program Officer.


Article: Jordan M. Carpenter, Melanie C. Green, Tanya Vacharkulksemsuk. Beyond perspective-taking: Mind-reading motivation. Motivation and Emotion, 2016; 40 (3): 358 DOI: 10.1007/s11031-016-9544-z


Epigenetics and our sense of smell

The olfactory sensory neurons (OSNs) are a unique population of neurons that allow us to detect and identify specific odorants. The odorants are detected when they bind to specific olfactory receptors (ORs) expressed by the OSNs. Once an odorant is bound, a signaling cascade is initiated to notify neurons in the adjacent olfactory bulb and the rest of the olfactory pathway that the odorant is present.  

Usually, OSNs express a single olfactory receptor, and the axons of all OSNs that express the same OR meet at the same location within the olfactory bulb. It’s a great system – all inputs for a particular odor meet up in the same region of the olfactory bulb, presumably to consolidate and simplify the odor signals received by the brain.

But this system is also complex. It relies on each and every OSN expressing a single OR. In mice, this requires a selection of one OR out of a possible 1,400. Once chosen, the OR selection needs to be maintained throughout the life of the neuron, or bananas might start to smell like garbage.

On the surface, it makes sense that epigenetic regulation would be involved in the OR selection process – as one gene must be expressed in the face of a multitude of options. But how does this actually happen?

A recent study by Lyons, DB et al (1), used an army of mouse models to parse out important protein expression patterns necessary for the installment of a single OR in a single OSN. To begin, they found that the epigenetic protein lysine-specific demethylase 1 (LSD1) is involved in de-silencing individual ORs through histone H3 lysine K9 (H3K9) demethylase activity.  This initial process allows the next step to occur, transcriptional activation through histone H3 lysine K4 (H3K4) trimethylation, which initiates production of the OR.

So how is the selective expression of a single OR maintained? This is achieved through induction of adenylate cyclase 3 expression by the OR. Adenylate cyclase 3 expression downregulates LSD1 expression, and prevents the transcriptional activation of other ORs. Thus, once Adenylate cyclase 3 is expressed, the neuron becomes “trapped” through a feedback loop into making a single OR. And there you have it – bananas continue to smell like bananas.


1)     Lyons DB, Allen WE, Goh T, Tsai L, Barnea G, Lomvardas S. An epigenetic trap stabilizes singular olfactory receptor expression. Cell, 2013, 154, 325-336.