Tag: brain imaging

Bioethics Blogs

Advances in Neuroscience Strengthen Ethical Opposition to Harmful Experiments on Dogs

Guest Post: Jarrod Bailey, Cruelty Free International, London, UK.

Paper: Advances in Neuroscience Imply that Harmful Experiments in Dogs are Unethical

More than 200,000 dogs are used in harmful experiments every year worldwide, in research into human and animal diseases and in the testing of new drugs and agrochemicals. This continues despite significant public opposition to it, and of increasing scientific evidence of its poor human relevance and misleading nature. From a utilitarian perspective, these alter the harm-to-benefit balance of using dogs in experiments. If experiments on dogs cause more suffering than is commonly appreciated, and if they are not delivering the human benefits that are claimed of them, then these experiments must be reconsidered by those who fund, license, and conduct them.

But how do we know how much dogs can suffer, and how much joy they can experience and are thus deprived of in a laboratory? Many would argue that it is simply obvious that dogs have impressive cognitive capabilities, as well as experiencing positive and negative emotions. This is not enough for science, of course, which seems unable or unwilling to accept sentience in nonhumans as it does for humans, based on weight of evidence. For many years, efforts to understand the minds of dogs in more detail have centred on ethological research which, while extremely valuable, does have some associated, widely acknowledged caveats. It can only go so far, especially for those for whom the evidence it produces can perhaps never be sufficient to warrant a change of attitude and behaviour towards dogs.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

Autism Spectrum Disorder: Progress Toward Earlier Diagnosis

Stockbyte

Research shows that the roots of autism spectrum disorder (ASD) generally start early—most likely in the womb. That’s one more reason, on top of a large number of epidemiological studies, why current claims about the role of vaccines in causing autism can’t be right. But how early is ASD detectable? It’s a critical question, since early intervention has been shown to help limit the effects of autism. The problem is there’s currently no reliable way to detect ASD until around 18–24 months, when the social deficits and repetitive behaviors associated with the condition begin to appear.

Several months ago, an NIH-funded team offered promising evidence that it may be possible to detect ASD in high-risk 1-year-olds by shifting attention from how kids act to how their brains have grown [1]. Now, new evidence from that same team suggests that neurological signs of ASD might be detectable even earlier.

That evidence comes from a study of children at high risk of ASD, who as babies underwent specialized brain scans while asleep to measure connectivity between different regions of the brain [2]. Using a sophisticated computer algorithm to analyze the scans, researchers could predict accurately which infants would receive a diagnosis of ASD 18 months later—and which would not. While the results need to be confirmed in larger groups of babies, these findings suggest that neuroimaging may be a valuable tool for early detection of ASD.

In the new study, researchers enrolled 59 babies who were 6 months old and had an older sibling diagnosed with ASD.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

Antibody Makes Alzheimer’s Protein Detectable in Blood

Caption: The protein tau (green) aggregates abnormally in a brain cell (blue). Tau spills out of the cell and enters the bloodstream (red). Research shows that antibodies (blue) can capture tau in the blood that reflect its levels in the  brain.
Credit: Sara Moser

Age can bring moments of forgetfulness. It can also bring concern that the forgetfulness might be a sign of early Alzheimer’s disease. For those who decide to have it checked out, doctors are likely to administer brief memory exams to assess the situation, and medical tests to search for causes of memory loss. Brain imaging and spinal taps can also help to look for signs of the disease. But an absolutely definitive diagnosis of Alzheimer’s disease is only possible today by examining a person’s brain postmortem. A need exists for a simple, less-invasive test to diagnose Alzheimer’s disease and similar neurodegenerative conditions in living people, perhaps even before memory loss becomes obvious.

One answer may lie in a protein called tau, which accumulates in abnormal tangles in the brains of people with Alzheimer’s disease and other “tauopathy” disorders. In recent years, researchers have been busy designing an antibody to target tau in hopes that this immunotherapy approach might slow or even reverse Alzheimer’s devastating symptoms, with promising early results in mice [1, 2]. Now, an NIH-funded research team that developed one such antibody have found it might also open the door to a simple blood test [3].

Scientists know that tau loosened from abnormal tangles exits the brain and enters the bloodstream.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

What is Feminist Neuroethics About?

By Ben Wills

Ben Wills studied Cognitive Science at Vassar College, where his thesis examined cognitive neuroscience research on the self. He is currently a legal assistant at a Portland, Oregon law firm, where he continues to hone his interests at the intersections of brain, law, and society.
As the boundaries of what may be considered “neuroethics” extend with the development of new kinds of technologies and the evolving interests of scholars, its branches encounter substantial structures of adjacent scholarship. “Feminist neuroethics” is a multidimensional construct and a name that can be afforded both to approaches that fall within the bounds of mainstream neuroethics and metatheoretical challenges to the scope and lines of debate within neuroethics. While acknowledging that scholarship at the intersections of academic feminism/gender studies, feminist science studies, ethics, and neuroscience is much more substantial and diverse than I’m considering here, my modest aim in this post is to highlight how the label “feminist neuroethics” has been used to look at what scholars consider important for neuroethics. In so doing we can see what scholars in these fields see as worth highlighting when identifying their work as such.

The phrase “feminist neuroethics” is young, first used (to my knowledge) in peer-reviewed literature by philosopher Peggy DesAutels in her 2010 article on “Sex differences and neuroethics,” published in Philosophical Psychology (though see Chalfin, Murphy, & Karkazis, 2008 for a close antecedent). She writes that, having found herself considering the ethics of neuroscience, the neuroscience of ethics, and sex/gender differences, her “overlapping approach could neatly be summarized as feminist neuroethics” (p.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

Brain Scans Show Early Signs of Autism Spectrum Disorder

Source: Getty Images

For children with autism spectrum disorder (ASD), early diagnosis is critical to allow for possible interventions at a time when the brain is most amenable to change. But that’s been tough to implement for a simple reason: the symptoms of ASD, such as communication difficulties, social deficits, and repetitive behaviors, often do not show up until a child turns 2 or even 3 years old.

Now, an NIH-funded research team has news that may pave the way for earlier detection of ASD. The key is to shift the diagnostic focus from how kids act to how their brains grow. In their brain imaging study, the researchers found that, compared to other children, youngsters with ASD showed unusually rapid brain growth from infancy to age 2. In fact, the growth differences were already evident by their first birthdays, well before autistic behaviors typically emerge.

Autism spectrum disorder includes a range of developmental conditions, such as autism and Asperger syndrome, that are characterized by challenges in social skills and communication. Scientists have long known that teens and adults with ASD have unusually large brain volumes. Researchers, including Heather Hazlett and Joseph Piven of the University of North Carolina, Chapel Hill, found more than a decade ago that those differences in brain size emerge by about age 2 [1]. However, no one had ever visually tracked those developmental differences.

In the new study reported in Nature [2], Hazlett, Piven, and their colleagues set out to collect that visual evidence. They examined 106 infants at high risk of ASD, based on an older sibling with that diagnosis.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

Is Neuromarketing Influencing Pathological Shopping Behavior?

By Elena Lopez
Elena Lopez is currently pursuing her BBA at Goizueta Business School and is also pursuing a degree in Neuroscience at Emory College of Arts & Sciences. She is involved in volunteer-related organizations that help those with limited resources and offer free consulting services, such as Volunteer Medical Interpretation Services and Emory Venture Strategic Partners. Elena developed a curiosity for neuroethics after attending the NBB Paris study abroad program and the 3rd international Neuroethics Network conference. She hopes to combine her passion for science and business in her future career goals.

Just over a month has passed since the biggest holiday shopping season of the year, and many Americans are already planning how they will financially recover from their overspending and failed budgeting plans. Financial sites like Forbes and the CNBC personal finance page have already come out with articles titled “Oops, you overspent on the holidays” and “Holiday spending hangover? Get your finances back on track” in an attempt to help consumers recover from financial losses. Months before the frenzy began, NBC reported that the National Retail Federation forecasted sales for November and December 2016 would increase 3.6% from last year to reach a whopping $800 billion dollars- with 90% of those sales consisting of online purchases (Weisbaum, 2016). With the growing presence of the digital component in sales and advertising, interactions between consumers and retailers can be tailored to the individual and offer greater shopping experiences. In the same NBC report, Deloitte stated that digital interactions likely influence two-thirds of every dollar spent (Weisbaum, 2016).

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

On the ethics of machine learning applications in clinical neuroscience

By Philipp Kellmeyer

Dr. med. Philipp Kellmeyer, M.D., M.Phil. (Cantab) is a board-certified neurologist working as postdoctoral researcher in the Intracranial EEG and Brain Imaging group at the University of Freiburg Medical Center, German. His current projects include the preparation of a clinical trial for using a wireless brain-computer interface to restore communication in severely paralyzed patients. In neuroethics, he works on ethical issues of emerging neurotechnologies. He is a member of the Rapid Action Task Force of the International Neuroethics Society and the Advisory Committee of the Neuroethics Network.
What is machine learning, you ask? 
As a brief working definition up front: machine learning refers to software that can learn from experience and is thus particularly good at extracting knowledge from data and for generating predictions [1]. Recently, one particularly powerful variant called deep learning has become the staple of much of recent progress (and hype) in applied machine learning. Deep learning uses biologically inspired artificial neural networks with many processing stages (hence the word “deep”). These deep networks, together with the ever-growing computing power and larger datasets for learning, now deliver groundbreaking performances at many tasks. For example, Google’s AlphaGo program that comprehensively beat a Go champion in January 2016 uses deep learning algorithms for reinforcement learning (analyzing 30 million Go moves and playing against itself). Despite these spectacular (and media-friendly) successes, however, the interaction between humans and algorithms may also go badly awry.

The software engineers who designed ‘Tay,’ the chatbot based on machine learning, for instance, surely had high hopes that it may hold its own on Twitter’s unforgiving world of high-density human microblogging.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

Prescribing the Placebo Effect

By Sarika Sachdeva
This post was written as part of a class assignment from students who took a neuroethics course with Dr. Rommelfanger in Paris of Summer 2016. 

Sarika Sachdeva is an undergraduate junior at Emory studying Neuroscience and Behavioral Biology and Economics. She is involved with research on stimulant abuse and addiction under Dr. Leonard Howell at Yerkes National Primate Research Center. 
In 2006, Dr. Ted Kaptchuk designed a clinical drug trial to evaluate a new pain pill in patients with severe arm pain. Participants in the study were assigned to receive either the pill or an acupuncture treatment for several weeks. Dr. Kaptchuk found that the people who received acupuncture ended up with more pain relief than those who had taken the pain pill. This difference was surprising, not because the pain pill was expected to be more effective, but because neither treatment was real- the pain pills contained cornstarch and the acupuncture was done with false needles that never pierced the skin.

Placebos are often considered baseline measurements, used as the standard scientific method to determine if a drug is actually making a biological difference or if its effects are just ‘inside the head’ and no better than a sugar pill (Anderson 2013). Utilizing the placebo effect as a form of treatment carries a stigma: only 0.3% of physicians admit to regularly prescribing them, in contrast with data that indicates around 50% of physicians actually do (Rommelfanger 2013).
Image courtesy of Pixabay
Recently, however, there has been a growing body of evidence that placebos produce real physiological changes, making them an active treatment not unlike ibuprofen, aspirin, or other traditional pharmaceuticals.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

Guilty or Not Guilty: Policy Considerations for Using Neuroimaging as Evidence in Courts

By Sunidhi Ramesh
This post was written as part of a class assignment from students who took a neuroethics course with Dr. Rommelfanger in Paris of Summer 2016. 

Sunidhi Ramesh, an Atlanta native, is a third year student at Emory University where she is double majoring in Sociology and Neuroscience and Behavioral Biology. She plans to pursue a career in medicine and holds a deep interest in sparking conversation and change around her, particularly in regards to pressing social matters and how education in America is both viewed and handled. In her spare time, Sunidhi is a writer, bridge player, dancer, and violinist.
 In 1893, Dr. Henry Howard Holmes opened his World’s Fair Hotel to the world [1].
But what his guests did not know was that the basement was filled with jars of poison, boxes of bones, and large surgical tables. Chutes from the guest rooms existed only to slide bodies into a pile downstairs. In the few months that the hotel was open for the public, Holmes, dubbed America’s first serial killer, killed an estimated number of 200 guests. Two years later, he was put on trial, found guilty, and sentenced to death [1].

H. H. Holmes, image courtesy WikiCommons
“I was born with the devil in me. I could not help the fact that I was a murderer, no more than the poet can help the inspiration to sing,” Holmes is quoted to have said [1]. But our judicial system does not care much for whether or not a murderer “can help it.”

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.

Bioethics Blogs

The Predictive Power of Neuroimaging

By Ethan Morris
This post was written as part of a class assignment from students who took a neuroethics course with Dr. Rommelfanger in Paris of Summer 2016. 

Ethan Morris is an undergraduate senior at Emory University, majoring in Neuroscience and Behavioral Biology with a minor in History. Ethan is a member of the Dilks Lab at Emory and is a legislator on the Emory University Student Government Association. Ethan is from Denver, Colorado and loves to ski.   

Background and Current Research
Neuroscience is a rapidly burgeoning field that is increasingly facing complex issues as scientists learn more about the human brain and by extension, about personal identity. One technology that has gained attention in the last two decades is brain imaging, a technique that uses various tools to evaluate the brain’s functional response to the world. Some of the more commonly used brain imaging devices are functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), both of which measure blood flow (albeit by different mechanisms) through the brain. These blood flow results show which areas of the brain are metabolically active, and are thus activated by the task at hand. Using these devices, researchers can determine the activity of certain brain regions associated with certain types of sensory and perceptual processing, as well as cognitive function.

While used in clinical settings for neurological and psychiatric diagnoses, neuroimaging is also applied in a variety of research contexts to learn about the neural correlates of human behavior. One study examined fMRI activation levels in the amygdala, one of the brain’s centers for processing salient stimuli and emotion.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.