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Participation in the Virginia Neuroscience Initiative will open new opportunities for William & Marys neuroscientists.

Josh Burk says the VNI is a component of the Virginia Biosciences Health Research Corporation (VBHRC, also known as the catalyst) a state created non-profit corporation. Burk is chair of William & Marys Department of Psychology and an affiliated faculty member of the universitys expanding neuroscience program.

The VNI is an effort to bring together major research institutions within the commonwealth to collaborate more than they have in the past, Burk explained. Another aspect is that the commonwealth is putting funds into this, so theyre looking at return on investment.

Burk said VNI participation would be particularly beneficial for William & Marys neuroscience program, an initiative that straddles five departments and conducts one of the universitys most popular undergraduate major programs.

William & Mary is one of seven academic institutions participating as core members of VNI, along with five major medical centers: Carilion Clinic, Inova Health System, Sentara Healthcare, UVA Health System and VCU Health. VNI also includes industrial partners.

Burk says that VNI participation offers a number of benefits, all of which revolve around collaboration. For example, the alliance has increased access to scientific instruments throughout the commonwealth. VNI researchers can use facilities at other VNI institutions at the same rate as researchers in the home institution.

Say that I had a collaborator at the University of Virginia, I could put a core facility at UVA into my grant proposal, Burk explained. Its something that I would have access to and at the same rate as someone at UVA. Its going to really strengthen grant proposals.

He added that VINs mission of collaboration matchmaker begins with a registry of Virginia neuroscientists. William & Mary has a couple dozen names on the registry now, and Burk says the goal is to have 50, once the word gets out to students, graduate students and post-docs in the universitys neuroscience community.

Anyones whos interested should be in the registry students, faculty, graduate students, whomever, Burk said. Even if theyre not doing core neuroscience research, they might have expertise that could contribute to neuroscience.

The registry makes a good starting part to find a collaborator. Burk has been working in a successful long-term, inter-institutional collaboration, a partnership that has received two RO1 grants from the National Institutes of Health. The key to creating a successful research partnership is to find someone who is working on something similar, but who has different, complementary, skills.

But you need to be compatible to be able to work together, he said. This is where the registry helps, because you can call someone up or invite them to come visit.

Burk pointed out that William & Mary has a lot to offer a statewide neuroscience collaboration, offering a wide range of experts from cellular-molecular research to behavioral and cognitive neuroscience to computational neuroscience.

He added that there are a number of core facilities available on campus as well, led by the nuclear magnetic resonance facility operated by Myriam Cotten, associate professor of applied science.

Thats a piece of equipment thats unique within Virginia, and there are very few instruments like that around the world, Burk said.

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W&M joins statewide neuroscience alliance | Williamsburg Yorktown ... - Williamsburg Yorktown Daily

When Cormac McCarthy writes an essay on the origin of language and the history of the unconscious mind, you can expect to find yourself wiser after reading it. The author, who has a cult fanbase for his novels The Road, All the Pretty Horses, and No Country For Old Men, doesnt disappoint in his new piece for the science magazine Nautilus.

It turns out McCarthy has been thinking about the unconscious and how it relates to human language for a couple of decades. He has indulged this exploration as a member of the Santa Fe Institute, a nonprofit organization whose researchers study the underlying, shared patterns in complex physical, biological, social, cultural, technological, and even possible astrobiological worlds, according to its website.

And now McCarthy has somehow distilled the lofty ideas, unanswered questions, and epiphanies collected during this long inquiry into a beautifully written narrative.

But of course he did. Thats his calling, as he writes in the essay: The facts of the world do not for the most part come in narrative form. We have to do that.

The Kekul Problem begins with McCarthys take on one of historys most famous dreams: the German chemist August Kekuls vision of the ouroboros, a snake eating itself, which provided a visual answer to his question about the shape of the benzene molecule. He shared that solution with the world in an 1865 paper.

This story raises a logical problem, points out McCarthy (who favors minimal punctuation and doesnt use apostrophes in negative contractions):

The problem of coursenot Kekuls but oursis that since the unconscious understands language perfectly well or it would not understand the problem in the first place, why doesnt it simply answer Kekuls question with something like: Kekul, its a bloody ring, To which our scientist might respond: Okay. Got it. Thanks.

Why the snake? That is, why is the unconscious so loathe to speak to us? Why the images, metaphors, pictures? Why the dreams, for that matter.

A logical place to begin would be to define what the unconscious is in the first place. To do this we have to set aside the jargon of modern psychology and get back to biology. The unconscious is a biological system before it is anything else. To put it as pithily as possiblyand as accuratelythe unconscious is a machine for operating an animal.

The rest of the essay gently sinks into that question, examining what the unconscious doesnt do (like tell us to keep breathing), and where it excels (in solving mathematical equations, for instance).

Its actually so common for mathematicians to solve problems in their dreams that George Zweig, the Russian-American physicist and friend to McCarthy, calls sleeping the Night Shift. The unconscious teaches usour conscious, decision-making brainlessons through recurring dreams, McCarthy explains, writing this hilarious dialogue for that mysterious part of our primeval minds:

Here the unconscious may well be imagined to have more than one voice: Hes not getting it, is he? No. Hes pretty thick. What do you want to do? I dont know. Do you want to try using his mother? His mother is dead. What difference does that make?

While language is useful for describing problems, thinking is an unconscious act, McCarthy demonstrates, pointing out that because of language, we can remember novels and booksbut we do that using concepts and visual representations in our mind, not by remembering the words we read.

He describes language as a force that at some point took possession of our brains, like a parasitic invasion:

The sort of isolation that gave us tall and short and light and dark and other variations in our species was no protection against the advance of language. It crossed mountains and oceans as if they werent there. Did it meet some need? No. The other five thousand plus mammals among us do fine without it. But useful? Oh yes. We might further point out that when it arrived it had no place to go. The brain was not expecting it and had made no plans for its arrival. It simply invaded those areas of the brain that were the least dedicated.

Eventually McCarthy does offer an answer to that question of why Kekuls unconscious conjured up the snake. I wont share it, but Ill tell you its related to the unconscious minds long history, dating back to the earliest humans of two million years ago, predating language by about 900,000 years.

Read the whole essay at Nautilus to find out, but keep in mind its just a hypothesis. After all, as McCarthy writes, How the unconscious goes about its work is not so much poorly understood as not understood at all.

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Cormac McCarthy explains the brutal, beautiful neuroscience of the unconscious - Quartz

VAIL Your brain is complex, but meditation makes it work better, says neuroscientist, Marjorie Hines Woollacott, Ph.D.

Woollacott is a research scientist and university professor who was certain that the brain was a purely physical entity controlled by chemicals and electrical pulses. Consciousness, she used to assert, was what she and her highly trained brain could perceive.

Meditation taught her to think outside the box, and the box is our bodies and physical perceptions. Her scientific research about meditation found that consciousness extends beyond the brain.

brain activity

She has been conducting scientific research for 10 years.

Her sister meditated and introduced her to it. Woollacott loves her, but dismissed her was one of those "Woo-woo" people.

"My boyfriend called her a bubblehead," Woollacott said.

Her sister invited her to a meditation confab in upstate New York. Woollacott was skeptical but wanted to visit my sister, so she went. The yogi touched Woollacott's head and she felt an energy flow through her head and down to heart. She was amazed, but still a scientist.

"There were no scientific findings about this," Woollacott said, so she started her own study. "The scientific mind in me thought this was too way out there."

'neurons in your brain'

In a controlled laboratory setting, people strapped on gear that attached 256 electrodes on their heads. Woollacott measured the amount of attention they were giving complex tasks, and found that meditators had twice the mental acuity of sedentary adults. Meditation quiets the mind and trains the brain to focus on the task at hand, she said.

"When your mind is quiet and it's not distracted by a million thoughts," Woollacott said.

"As a scientist, consciousness is solely the product of neurons in my brain," Woollacott said. "But because I've had experiences in meditation that tell me otherwise, I've now done research to say it's much more, and that consciousness can exist without the activity of neurons in my brain and that we have a connection with a vast consciousness that we are part of. That more vast consciousness contracts down into our own awareness. In certain moments, it can expand back outward that connects us with other parts of reality."

Woollacott herself meditates, which is how she started down this road. She will speak about her findings in a Vail Symposium Consciousness Series program today at Colorado Mountain College in Edwards. She's also conducting a workshop Friday morning.

The Friday morning workshop will be less of a lecture and more experiential, as Woollacott leads participants in an in-depth exploration of the nature of consciousness from both the scientific perspective and that of direct experience, discussing how each contributes to a complete understanding of the topic.

Woollacott has been a neuroscience professor at the University of Oregon for more than three decades and a meditator for almost four. Her research has been funded by the National Institutes of Health and the National Science Foundation. She has written more than 180 peer-reviewed research articles, several about meditation

Staff Writer Randy Wyrick can be reached at 970-748-2935 and rwyrick@vaildaily.com.

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Neuroscience proves meditation makes your brain work better - Vail Daily News

Whether we condemn the villain in a movie or feel that somebody has wronged us personally, many of us make moral judgments on a daily basis. From a neuropsychological viewpoint, the act of judging a moral situation is incredibly complex and has a lot to do with intentionality - did the perpetrator really mean to do those awful things? What happens in our brain when we know that whoever caused the harm did so unintentionally? New research investigates the neuroanatomical basis of forgiveness.

The new study examines the role of a brain area called the anterior superior temporal sulcus (aSTS) in forgiving those who make unintentional mistakes.

The researchers were led by Giorgia Silani from the University of Vienna in Austria, and the study was carried out in collaboration with scientists from Trieste University in Italy and Boston College in Massachusetts. The findings were recently published in the journal Scientific Reports.

As the authors explain, making a mature moral judgment about a wrongful act involves not only considering the damage done, but also the perpetrator's intention and mental state. When there is a clear contradiction between the two, however, intention seems to take precedence over the result of the action.

Indrajeet Patil, the study's primary author, details this further and puts the new research into context:

"Behavioural studies have already shown that when the intention and outcome of an action are conflicting, as in the case of sometimes serious accidental harm, people tend to focus mainly on the intentions when formulating a judgment. And this is more or less a universal feature of mature moral judgments across cultures," Patil explains.

"To date, however, very few studies have taken on this issue from an anatomical point of view, to gain an understanding of whether differences in the volume and structure of certain areas of the brain might explain variations in moral judgment. This research attempted to explore precisely this aspect."

To do this, the researchers asked 50 participants to complete a moral judgement task. The volunteers were presented with 36 unique stories and four potential outcomes for each of them.

Each scenario comprised four parts: some background information; a so-called foreshadowing segment, in which it was suggested that the outcome would be either neutral or harmful; information on the neutral or intentionally harmful mental state of the agent; and, finally, the consequence, which revealed the agent's action and the resulting outcome.

Participants read each story and were asked to give their moral judgment by answering questions regarding "acceptability" and "blame." Namely, the participants were asked: "How morally acceptable was [the agent]'s behavior?" and "How much blame does [the agent] deserve?" The volunteers gave answers based on a scale from 1 to 7.

While answering the questions, the participants' brain activity was analyzed using voxel-based morphometry - a neuroimaging technique that allows for a holistic examination of brain changes while simultaneously preserving a high degree of brain region specificity.

The researchers also used neuroimaging to localize the neural areas responsible for the so-called theory of mind (ToM). ToM, or "mentalizing," is a person's ability to correctly attribute mental states - such as beliefs, intentions, and desires - to others based on their behavior. Mentalizing also refers to the person's ability to explain and predict other people's behavior based on these inferences.

The results revealed a connection between the differences in moral judgement severity about unintentional harm and the volume of the left aSTS brain region.

More specifically, the more developed the aSTS was, the less blame was attributed to the wrongdoers. "The greater the gray matter volume [in this area], the less accidental harm-doers are condemned," the authors write.

Patil further explains the findings:

"The aSTS was already known to be involved in the ability to represent the mental states (thoughts, beliefs, desires, etc.) of others. According to our conclusions, individuals with more gray matter at aSTS are better able to represent the mental state of those responsible for actions and thus comprehend the unintentional nature of the harm. In expressing judgment they are thus able to focus on this latter aspect and give it priority over the especially unpleasant consequences of the action. For this reason, ultimately, they are less inclined to condemn it severely."

This study opens up new avenues for neuroscientific research. Patil and colleagues recommend that further studies use more realistic contexts to study moral judgments, as well as using a more demographically diverse study sample.

Learn about a newly discovered mechanism for memory formation.

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Why do some of us find it easier to forgive? Neuroscience sheds light - Medical News Today

More brain stimulation news came this week when researchers at the University of Zurich pinpointee the brain mechanism that regulates decisions between honesty and self-interest. Using transcranial direct current stimulation, they could even increase honest behavior.

The work highlights a deliberation process between honesty and self-interest in the right dorsolateral prefrontal cortex (rDLPFC).

Christian Ruff, UZH Professor of Neuroeconomics, said:

This finding suggests that the stimulation mainly reduced cheating in participants who actually experienced a moral conflict, but did not influence the decision making process in those not in those who were committed to maximizing their earnings. These brain processes could lie at the heart of individual differences and possibly pathologies of honest behavior

When researchers applied transcranial direct current stimulation over a region in the right dorsolateral prefrontal cortex, during a dice rolling task, participants were less likely to cheat. However, the number of consistent cheaters remained the same. (Michel Andr Marchal, et al. Increasing honesty in humans with noninvasive brain stimulation)

Another story featuring the prefrontal cortex showed that its neurons helped teach the hippocampus to process memories. The research looked at memory flexibility and interference, the mechanisms by which the brain interprets events and anticipates their likely outcomes.

The study was by Matthew Shapiro, PhD, from Icahn School of Medicine at Mount Sinai. The results suggest that neurons in the medial prefrontal cortex instruct hippocampal neurons to learn rules which differentiate memory-based predictions in otherwise identical situations. The mechanisms revealed could improve understanding of psychiatric conditions, such as schizophrenia, that involve hippocampal and prefrontal cortex interactions.

NIH-funded research involving 446 children reported that insight into differences in treatment response in patients with childhood absence epilepsy could come from precision medicine. Childhood absence epilepsy (CAE) is the most common form of pediatric epilepsy.

The results suggest knowledge of specific gene variants in children with CAE may help predict what drugs would work best for them. For example, two specific forms of the calcium channel genes appeared more often in children for whom ethosuximide did not work. Two other variants of the calcium channel genes were found in children for whom lamotrigine did work, but one form of the drug transporter gene was associated with a continuation of seizures. (Glauser TA et al. Pharmacogenetics of Antiepileptic Drug Efficacy in Childhood Absence Epilepsy. Annals of Neurology. March 25, 2017)

A new study published this week in the Proceedings of the National Academy of Sciences hones our understanding of a uniquely human skill; the ability to instantaneously assess a new environment and get oriented thanks to visual cues.

Whereas humans can look at a complex landscape like a mountain vista and almost immediately orient themselves to navigate its multiple regions over long distances, other mammals such as rodents orient relative to physical cues like approaching and sniffing a wall that build up over time.

The way humans navigate their surroundings and understand their relative position includes an environment-dependent scaling mechanism, an adaptive coordinate system with differences from other mammals, according to the study led by researchers at The University of Texas at Austin.

Our research, based on human data, redefines the fundamental properties of the internal coordinate system,

said Zoltan Nadasdy, lead author of the study and an adjunct assistant professor in the universitys Department of Psychology.

Dysfunction in this system causes memory problems and disorientation, such as we see in Alzheimers disease and age-related decline. So, its vital that we continue to further our understanding of this part of the brain, he said.

By measuring brain activity in the entorhinal cortex, researchers identified three previously unknown traits of the system:

(Zoltan Nadasdy et al. Context-dependent spatially periodic activity in the human entorhinal cortex)

A pair of preclinical studies suggest that silencing the SCA2 gene, using antisense oligonucleotide therapy, may help prevent neurological symptoms associated with spinocerebellar ataxia type 2 and amyotrophic lateral sclerosis.

Finally, in Sweden, Karolinska Institute researchers report a method to force astrocytes to transmute into dopamine neurons, that work like normal midbrain dopamininergic neurons. The finding, could be the first step in an alternate therapeutic approach for Parkinsons disease.

Image: DARPA

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This Week in Neuroscience News 4/16/17 - ReliaWire

Yale College undergraduates for the first time can choose neuroscience as a major. The new major was developed through a joint effort by the Department of Molecular, Cellular and Developmental Biology (MCDB) and the Department of Psychology.

Neuroscience aims to understand how the brain produces behavior, with the goals of advancing human understanding, improving physical and mental health, and optimizing performance. This entails a highly interdisciplinary effort that spans molecules to minds.

MCDB and Psychology worked closely together to create this major because we want our students to have broadly integrative and rigorous training in neuroscience, only possible through our joint curriculum, said Marvin Chun, the Richard M. Colgate Professor of Psychology, and professor of neuroscience in the Yale School of Medicine, who helped spearhead the effort.

There has been a strong interest among students and faculty for a major in neuroscience, which is also the subject of several federal research initiatives, said Damon Clark, assistant professor of MCDB and of physics, who helped lead the collaboration in MCDB.

Yale has an excellent neuroscience graduate program, and this new course of study builds on Yales strengths to offer an undergraduate degree in neuroscience, Clark said.

Neuroscience majors will be admitted via application, and an unofficial course description and requirements are available here.

Qualifying students may receive a B.S. or B.A. in neuroscience as early as 2017-2018.

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Yale College creates new neuroscience major - Yale News

Daeyeol Lee, newly named as the Dorys McConnell Duberg Professor of Neuroscience, focuses his research on the brain mechanisms of decision-making, in particular the role of the prefrontal cortex and basal ganglia in reinforcement learning and economic choices.

The long-term goal of research in Lees laboratory is to understand how appropriate behaviors are chosen and their outcomes are evaluated by the neural networks in the cerebral cortex and basal ganglia of the brain.The laboratory also investigates how the brain combines various abstract quantities, such as time, probability, and magnitude, to optimize our decision strategies.Research in his laboratory is highly interdisciplinary and capitalizes on the insights from formal theories of economics and reinforcement learning as well as computational neuroscience of neural coding and behavioral studies of decision-making. Lee also develops novel behavioral paradigms that can probe the core processes of decision-making. Combined with the use of multi-electrode recording systems, this research seeks to unravel the biological basis of willful actions.

Lee graduated from Seoul National University (Korea) with a degree in economics and earned his Ph.D. in neuroscience from the University of Illinois at Urbana-Champaign. He then received postdoctoral training in neurophysiology at the University of Minnesota. Lee held faculty positions at Wake Forest University School of Medicine and the University of Rochester before coming to Yale in 2006 as associate professor of neurobiology. In addition to his new appointment, he also serves as professor of psychology and of psychiatry.

Lee is the author of the book Birth of Intelligence and has published over 80 original research articles, including several papers in Science, Nature Neuroscience, and Neuron. He has received the Fellowship for Prominent Collegians from Korea Foundation for Advanced Studies, a university fellowship from the University of Illinois, and the James S. McDonnell Foundation Cognitive Neuroscience Grant. His research has been funded by the National Institute of Health continuously since 1999.

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Daeyeol Lee named the Duberg Professor of Neuroscience - Yale News

Intricate, symmetric patterns, in tiles and stucco, cover the walls and ceilings of Alhambra, the red fort, the dreamlike castle of the medieval Moorish kings of Andalusia. Seemingly endless in variety, the two dimensionally periodic patterns are nevertheless governed by the mathematical principles of group theory and can be classified into a finite number of types: precisely seventeen, as shown by Russian crystallographer Evgraf Federov. The artists of medieval Andalusia are unlikely to have been aware of the mathematics of space groups, and Federov was unaware of the art of Alhambra. The two worlds met in the 1943 PhD thesis of Swiss astronomer Edith Alice Muller, who counted eleven of the seventeen planar groups in the adornments of the palace (more have been counted since). All seventeen space groups can also be found in the periodic patterns of Japanese wallpaper.

Without conscious intent or explicit knowledge, the creations of artists across cultures at different times nevertheless had to conform to the constraints of periodicity in two dimensional Euclidean space, and were thus subject to mathematically precise theory. Does the same apply to the endless forms most beautiful, created by the biological evolutionary process? Are there theoretical principles, ideally ones which may be formulated in mathematical terms, underlying the bewildering complexity of biological phenomema? Without the guidance of such principles, we are only generating ever larger digital butterfly collections with ever better tools. In a recent article, Krakauer and colleagues argue that by marginalizing ethology, the study of adaptive behaviors of animals in their natural settings, modern neuroscience has lost a key theoretical framework. The conceptual framework of ethology contains in it the seeds of a future mathematical theory that might unify neurobiological complexity as Fedorovs theory of wallpaper groups unified the patterns of the Alhambra.

The contemporary lack of ethological analysis is part of a larger deficit. Darwins theory of natural selection, arguably the most important theoretical framework in biology, is prominent by its absence in modern neuroscience. Darwins theory has two main tenets: the unguided generation of heritable variation, and the selection of such variation by an environmental niche to produce adaptive traits in organisms. The general role of the animal brain is to enable adaptive behaviors. It is reasonable to argue that a study of these adaptive behaviors (natural behaviors) should guide the experimental study of brain circuits. Indeed, this was the premise of the field of ethology developed by Tinbergen, Lorenz and von Frisch in the mid-twentieth century. The observational field studies of core natural behaviors such as mating, aggression and critical-period learning by ethologists enabled the subsequent elucidation of the underlying neural circuitry by neuroethologists.

In contrast to this empirical method of observing a freely behaving animal in its adaptive niche (natural settings) is the controlled experimental approach developed by Pavlov and Skinner to study conditioned behaviors, and psychophysical tests developed by experimental psychologists to characterize perception. This approach draws inspiration from physics, with its emphasis on isolating a system from external influences. The animal is placed in a controlled environment, subjected to simple stimuli and highly constrained in its behavior (e.g., forced to choose between two alternatives). The majority of contemporary neuroscientific studies use the controlled experimental approach to behavior with ethological analysis taking a back seat. Krakauer et al argue that all of the emphasis on tool building and gathering large neural data sets, while neglecting ethological grounding, has led the field astray.

The rationale of the current approach is that detailed recordings of neural activity (neural correlates) associated with behavior, and interventions in the behavior by suitable circuit manipulations, go beyond mere description of behavior and therefore provide greater explanatory power. Krakauer et al challenge this school of thought and argue that neither method is fruitful without first understanding natural behaviors in their own right, to set a theoretical context and guide experimental design. The tools to record and manipulate neural activity cannot substitute for ethological analysis, and may even impede progress by providing a false narrative of causal-interventionist explanation.

Misplaced concreteness in recording/manipulating neural activity can lead to the mereological fallacy, which incorrectly attributes to a part of a system a property of the whole system. The authors point to the popular mirror neurons as an example. Mirror neurons show the same activity when a primate performs a task, as compared to when the primate observes a different actor performing the task. However, this partial match between neural activities, does not by itself imply any similarity of psychological state between the observer and the actor. It would therefore be a conceptual error to use the activity of the mirror neurons as an interchangeable proxy for the psychological state. Krakauer et al hold that such an error is prevalent in the literature.

Generally, it is impossible to obtain a complete system-wide measurement of neural activity. Even the best current efforts to measure the activity of thousands of neurons falls far short of recording the electrical activity of entire nervous systems, including all of the axons, dendrites and chemical messages. There is no escape from the need to generalize from partial neural observations. These generalizations are fragile and may not provide any insight into the adaptive behaviors unless the experiments are carefully designed, taking those behaviors explicitly into account. Ignoring Darwin is not a good recipe for success in gaining biological understanding. Conversely, the authors draw upon studies of Bradykinesia in Parkinsonian disease, sound localization in barn owls, navigation in electric fish and motor learning, to show that ethologically informed experimental design coupled with neural activity measurements and perturbations can lead to better insight.

The call to re-focus on natural behaviors is timely but not really controversial. However, Karakauer et. al. proceed to make stronger claims regarding behaviors as emergent phenomena that cannot even in principle be explained in neural terms. Here they are on shakier ground. Quasi-mystical claims regarding emergence in biology are endemic in the literature and uncomfortably echo discarded notions of Cartesian dualism and Bergsonian vitalism. In support of their argument Krakauer et al refer to the collective behavior of flocks of birds, which exhibit large-scale spatiotemporal patterns (murmurations) not obvious from the behavior of one or a few birds. The fallacy of the argument is starkly evident in an amplifying commentary in The Atlantic on Krakauers article, where it is noted that the patterns can be reproduced in simple models of flocking with elementary rules dictating the flight behavior of individual birds in the context of their neighbors. This is in keeping with innumerable studies throughout the twentieth century: It has been repeatedly observed that seemingly complex patterns can be explained by simple, local rules.

These exercises demonstrate that complex collective behavior of systems can indeed be explained by simple rules of interactions between the elements of the system. Snatching defeat from the jaws of victory, the Atlantic commentary concludes that you would never have been able to predict the latter (i.e. the flocking patterns) from the former (the simple rules). But this was precisely what was done by the computer models cited, namely the flocking patterns were predicted by the simple rules! Perhaps what is implied is that the outcome of the model is not obvious in a subjective sense: i.e. we may not be able to do the math in our heads to connect the dots between the interaction rules and the collective behaviors (though this can be disputed one can indeed build the relevant intuition using appropriate theoretical, paper-pencil calculations of a pre-computer age, nineteenth century variety). However, that is a statement about our subjective feelings about the topic and has no bearing on the in principle question as to whether simple interaction rules lead to complex macroscopic behaviors. We now understand that they can. Working out the connections between the microscopic details and macroscopic behaviors may be practically challenging, but much theoretical progress has been made on this topic, and no in principle explanatory gap exists between the microscopic and macroscopic. Leaving aside the canard of emergence, Krakauer et al have hit upon a central issue that bears amplification. The problem with the mechanistic-reductionist explanation of nervous systems is not that there is an in principle gap between microscopic neuronal details and macroscopic behaviors (emergence), but that this style of explanation is largely divorced from Darwins theory of natural selection. This is particularly evident in the lack of niche-adaptive behaviors in driving experimental design, as pointed out by Krakauer et al. As is customary in the neuroscience literature, in contrasting the how (mechanistic) style of explanation from the why (adaptive) style of explanation of behavior, Krakauer et al invoke David Marrs computational level of analysis and Tinbergens ultimate causes. Marr defines three levels of analysis, computation (problem to be solved), algorithm (rules) and implementation (physical). Tinbergens analysis of behavior is separated into proximate or mechanistic explanations and ultimate or adaptive explanations. However, one might as well directly go to Darwin, since the context is broader than that of computational explanations or ethology, and originates in a fundamental tension between the biological and physical sciences.

Questions regarding function (in the English dictionary sense of purpose) belong exclusively to the biological domain. Exorcism of teleological considerations was central to modern physics; an explanation such as the purpose of the sun is to give light has no place in a physics textbook. Yet a statement with the same epistemological status, that the function of hemoglobin is to transport oxygen would be completely uncontroversial in a biology textbook. This cognitive dissonance between the status of teleological explanations in the two sciences has historical roots. Aristotles biological teleology stood in contrast with Democritus physics-style atomism. The teleology-atomism contrast in understanding nature is not special to classical Greek philosophy and occurs for example in classical Hindu philosophy. The role of function in the dictionary sense of purpose continues to be debated in the contemporary philosophy of biology. The working neuroscientist may regard these philosophical discussions as a waste of time (or worse, as crypto-vitalism). However as the recent controversy over defining DNA function in the ENCODE project shows, lack of agreement about function has practical consequences for the scientific community.

A more satisfactory treatment of function could dispel much of the theoretical confusion in understanding brain complexity. Coherent conceptual accounts already exist. Card-carrying biologists like Ernst Mayr have distinguished between cosmic teleology, corresponding to an inherent purposefulness of Nature that has no place in modern science, and teleonomy, or apparent purposefulness instantiated in genetic programs evolved through natural selection. Animal behavior within the lifetime of an individual is highly purposeful, executing programmed behaviors adapted to ecological niches. The program of instructions or the genetic code itself of course changes over evolutionary time scales. Developmental and adult plasticity of the nervous system does not fundamentally negate the existence of species-specific adaptive behaviors; indeed, plasticity itself is an evolved species-specific mechanism (as is illustrated by the convergent evolution of vocal learning in multiple taxa including humans and songbirds).

Fragments of a theory of design that deals squarely with teleonomic issues exist, including the ethological considerations and computationalist accounts referred to in Krakauers article. However, without a more robust, mathematically sound and conceptually coherent theoretical enterprise that has better explanatory power and provides guidance to experimental design, we are likely to be staring for a long time at the intricate patterns of neurobiological wallpaper without uncovering the underlying simplicities.

What is the way forward? Fedorov discovered the mathematics of space groups governing the patterns of Alhambra by studying crystals rather than by visiting the palace. It is possible that the underlying mathematical principles, that govern apparently purposeful biological systems, have their own intrinsic logic and may be discovered independently in a different domain. This is indeed the hope of researchers in the field of modern Machine Learning, who aim to discover the abstract principles of intelligence in a technological context largely removed from neuroscience. Human engineers, in trying to solve problems that often resemble those that animal nervous systems may have encountered in their adaptive niches, have come up with mathematically principled theoretical frameworks. These engineering theories classically include the three Cs (Communications, Computation and Control) and one should add Statistics or Machine Learning. These theories are taught in different departments in universities, but the modern context of interconnected systems and distributed networks has also brought the disciplines together into a mix that is ripe for connecting to neuroscience.

In terms of engineering metaphors in neuroscience, the computer has dominated, as can be seen from the discussions in Krakauers article. This may be a mistake: while no doubt the most popular textbook metaphor for brains, Theories of Computation as substantiated by Turings model or Von Neumanns computer architecture separating processors from memory, have been singularly unsuccessful in providing biological insight into brain function or experimental guidance to the practicing neuroscientist. It may also provide a simple explanation for the negative results obtained in the recent study by Jonas and Kording where standard analysis methods used by neuroscientists were unsuccessful in shedding insight into the architecture of a computer programmed to play a video game.

This study has led to much self-flagellation, but the neuroscience data analysis methods actually have been quite successful in exploring a different engineering metaphor for nervous systems, namely signal and image processing, usually studied in the context of communications or control. Paradigmatic of this success is our understanding of the primate visual system, understanding that has now borne fruit in a multi-billion-dollar Machine Vision industry. If the neuroscience data analysis methods fail in understanding a Von Neumann computer architecture separating processor from memory and using precise elements, its not such a big deal since no one expects the brain to conform to that architecture anyway. It is telling that the modern advances in Machine Learning have come from an abandonment of the digital, rule-based AI methods of traditional computer science, and an adoption of the analog, linear algebra and probability theory based methods more in the domain of statisticians, physicists and control theorists. Calling for interdisciplinary research is a clich, but the theoretical framework we need for neuroscience is unlikely to be based in an existing academic department.

Modern neuroscience needs pluralism not only in the epistemological levels of analysis, as Krakauer et al calls for, but also in the diversity of species studied. The biological counterpart to engineering theorizing is the comparative method that looks at a broad range of species across taxa to find cross-cutting principles. The comparative method has been in decline for decades, under pressure from the expansion of studies of a few model organisms, particularly those suited for translational medical research. The tool-building drive has forced this decline further: we now study the visual system of the mouse not because vision is a primary niche-adaptation for this species (an ethological dictum known as Kroghs principle), but simply because elaborate genetic tools are available.

We cannot brute force our way through the complexities of nervous systems. There is no doubt that we need better tools, but the best tool that we have for the problem perhaps resides in our own craniums. If there are no deep theoretical principles to be found in the study of animal nervous systems, then we are doomed to cataloguing the great variety of detail that is characteristic of biology, and tools will dominate. The hope is that underlying the endless and beautiful forms produced by the struggle for existence are mathematically quantifiable simplicities, fearful symmetries as it were. Then ideas will win the day.

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Is Neuroscience Limited by Tools or Ideas? - Scientific American

How has neuroscience changed over the past decade? In a new paper, Hong Kong researchers Andy Wai Kan Yeung and colleagues take a look at brain science using the tools of citation analysis.

Yeung et al. extracted data from 2006-2015 from Web of Science and Journal Citation Reports (JCR), which track publications and citations. All journals that the JCR classifies in the Neurosciences category were included.

The first change Yeung et al. noticed was that the number of published neuroscience papers has been growing steadily, although keep in mind that the increasing volume of papers is a phenomenon not limited to neuroscience.

Looking at which kinds of papers received the most citations, Yeung et al. noticed a shift towards the more psychological and behavioural side of brain science. The Web of Science Psychology category went from #6 in terms of citations in 2006 up to #1 in 2015, while Behavioral sciences went from #3 to #2. The more biological areas of neuroscience, such as Physiology and Biochemistry, molecular biology, declined in terms of citations. A sign of the times?

A breakdown of papers by the national affiliations of the authors reveals the growth of Chinese neuroscience over the 2006 to 2015 period. While just 3% of papers had at least one author based in China in 2006, by 2015 this had risen to over 11%. China has overtaken Germany, the UK, Japan, and other countries such that China is now #2 on the world neuroscience authorship list.

Finally, Yeung et al. tracked the impact factor (average citations per paper) of ten core neuroscience journals over time. This reveals little change from 2006 to 2015 although the venerable Journal of Neuroscience (established 1981) has lost some ground to Neuroimage (founded 1992).

Overall, this is an interesting little paper. The results dont contain any big surprises, but its nice to be able to see where neuroscience is going.

Yeung AW, Goto TK, & Leung WK (2017). The Changing Landscape of Neuroscience Research, 2006-2015: A Bibliometric Study. Frontiers in Neuroscience, 11 PMID: 28377687

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The Landscape of Neuroscience 2006 - 2015 - Discover Magazine (blog)

Elon Musk has a reputation as the worlds greatest doer. He can propose crazy ambitious technological projectslike reusable rockets for Mars exploration and hyperloop tunnels for transcontinental rapid transitand people just assume hell pull it off.

So his latest venture, a new company called Neuralink that will reportedly build brain implants both for medical use and to give healthy people superpowers, has gotten the public excited about a coming era of consumer-friendly neurotech.

Even neuroscientists who work in the field, who know full well how difficult it is to build working brain gear that passes muster with medical regulators, feel a sense of potential. Elon Musk is a person whos going to take risks and inject a lot of money, so it will be exciting to see what he gets up to, says Thomas Oxley, a neural engineer who has been developing a medical brain implant since 2010 (he hopes to start its first clinical trial in 2018).

Neuralink is still mysterious. An article in The Wall Street Journal announced the companys formation and first hires, while also spouting vague verbiage about cranial computers that would serve as a layer of artificial intelligence inside the brain.

So IEEE Spectrum asked the experts about whats feasible in this field, and what Musk might be planning. First, though, a little background.

Musk did give a few seemingly concrete details at a conference last year (video excerpt below). His neural lace would serve as a digital layer above the cortex, he said. Its components wouldnt necessarily require brain surgery for implantation; instead, the hardware could be injected into the jugular and travel to the brain through the bloodstream.

Neural implants are already a medical reality: Some 150,000 people with Parkinsons disease have had brain surgery to receive deep-brain stimulators, implants that send regular pulses of electricity through patches of brain tissue to control patients tremors. Researchers are now experimenting with these pacemaker-like devices to treat depression and other neuropsychiatric diseases. Some epilepsy patients also have a new type of implant that monitors their brains for signs of impending seizures and sends out stimulating pulses to head them off.

Musks neural lace would presumably be designed to treat some disease first; otherwise, its hard to imagine the technology gaining regulatory approval. But his descriptions dont make it sound like existing brain stimulators, but rather like experimental brain-computer interfaces (BCI) that record brain signals and use the information to control external devices like computer cursors and robotic arms. These BCI implants have shown great promise in giving more autonomy to people with paralysis, but none have yet been approved for clinical use.

Now, to the experts!

Mary Lou Jepsen is a Silicon Valley bigwig who recently founded the startup Openwater to develop a noninvasive BCI for imaging and telepathy (the latter could conceivably be done by reading out thought patterns in the brain). Like Musk, shes interested in both medical applications and augmenting peoples natural abilities. But she says any invasive neural technology brings medical hurdles, even if it doesnt require splitting open patients skulls.

The approach as I understand it (not much is published) involves implanting silicon particles (so called neural lace) into the bloodstream. One concern is that implanting anything in the body can cause unintended consequences, says Jepsen. For example, even red blood cells can clog capillaries in the brain when the red blood cells are made more stiff by diseases like malaria. This clogging can reduce or even cut off the flow of oxygen to the parts of the brain. Indeed, clogging of cerebral capillaries has been shown to be a major cause of Alzheimers progression. Back to neural lace: One concern I would have is whether the silicon particles could lead to any clogging.

Jepsen notes that the Wall Street Journal article lists a few neuroscientists who have reportedly been hired on for Neuralink, but says thats just the first step in a long process. Its exciting, but embryonic, she says.

Thomas Oxley is a practicing neurologist and the inventor of the stentrode, a neural probe that can be delivered to the brain through blood vesselsso he has plenty of thoughts about the technology Musk might be developing. Hes CEO of Synchron, the company thats developing the technology and planning its first clinical trial for 2018 in Australia.

Oxley came up with his stentrode as an alternative to typical electrodes that are placed directly in the brain tissue. Those standard electrodes enable high-fidelity recording from individual neurons, but the stiff silicon and metal structures cause inflammation in the brain tissue, and scar tissue often forms around them over time. The idea of moving up the blood vessel is that you avoid any direct penetration of the brain tissue, Oxley says, and thus avoid damaging it. In Oxleys system, a catheter is snaked up a vein to deliver the stentrode to one of the tiny blood vessels that nourishes the neurons. From there, they cant record neurons activity directly, but Oxley says the different type of signal can be deciphered with the right kind of signal processing.

If Musk is working on a similar delivery system for his neural lace, Oxley says, we shouldnt expect results anytime soon. The medical device pathway takes a long time, and we had to conduct a lot of science to get to the point where we are now, he says. For the past two years, his research group has been working in sheep to develop a catheter delivery system that reliably positions an operational recording system in the motor cortex region of the brain.

Synchrons upcoming clinical trial will test the stentrode as a BCI for people with paralyzed or missing limbs, who will use the recorded neural signals to control exoskeletons and robotic prosthetics. Oxley says theres a big potential market for such devices, including people who have suffered strokes, spinal cord injuries, ALS, muscular dystrophy, and amputations. He notes that a McKinsey Global Institute report from 2013 estimated that 50 million people in advanced economies could benefit from such robotic human augmentation. So if Musks Neuralink is following a similar technological path to Synchron, hell be able to make a sound business case.

As for clotting concerns, Oxley says neurologists routinely use permanent stents in patients brains to keep blood vessels open. They act like scaffolds that push against the walls of the blood vessel. We understand how to manage patients with medication to ensure those stents dont close over, he says.

Charles Lieber and Guosong Hong offer another possibility for delicately inserting a BCI into the brain. Lieber, a Harvard professor of chemistry and engineering, and Hong, one of his postdocs, are developing an electronic mesh that is injected by syringe into the brain tissue, where it unfurls to make contact with many neurons.

The mesh electronics can be precisely targeted to any brain region by syringe injection and forms a seamless and stable interface with neural tissuebecause it behaves very much like the brain tissue we seek to study, Lieber says. Mesh electronics cause negligible damage or chronic immune response. His group has shown that the mesh is stable in the brain and can record from individual neurons over many months.

Hong adds that the mesh electronics can both record from and stimulate neurons, opening up a variety of medical applications. It will provide transformative capabilities for treatment of neurological and neurodegenerative diseases such as Parkinsons and Alzheimers diseases via deep-brain stimulation, he says, as well as providing next-generation brain computer interfaces.

Although Musk made reference to the neural lace acting as a digital layer above the cortex, these researchers dont think its likely that Musks technology will resemble their unfurling electronic mesh. Hong notes that the three neuroscientists mentioned as Neuralinks first hires work on very different kinds of brain implants.

Vanessa Tolosa of Lawrence Livermore National Lab has been working on flexible polymer probes that look like little dipsticks; Philip Sabes of University of California, San Francisco has experimented with a micro-ECoG array that drapes over the outer surface of the brain; and Timothy Gardner of Boston University works on carbon fiber electrodes that look like bundles of threads.

While Musks description of a neural lace layer makes Sabess superficial array sound like the winning contender, such a device couldnt be injected through the jugular and travel through blood vessels to reach the upper surface of the brain. Its possible that we shouldnt take his works literallyMusk may have been speaking metaphorically about technology that would add a new layer of intelligence to the human brain.

Michel Maharbiz, an electrical engineering professor at UC Berkeley, is working on tiny electrodes called neural dust. These sound like something that Musk would take an interest in; the idea is that tiny wireless electrodes could be scattered through the nervous system, acting together to record signals.

The teams current version of this tech is a device that measures 2.4 cubic millimeters, and theyre working to scale it down much furtherfirst to 1mm3, and eventually down to 50mm3. Recently, Maharbiz and his colleagues demonstrated that their current mote of neural dust could record from a nerve while wirelessly receiving power and sending out data.

While Maharbiz couldnt say whether neural lace and neural dust might have some similarities, he knows that scaling down his own tech to make it small enough to work in the brain is a big challenge. The obstacles are a combination of circuit design, materials, communication schemes, and power, he says, noting that his teams work on miniaturization is a difficult, multi-year endeavor which will happen in phases.

To make a BCI work inside the brains tiny blood vessels, Maharbiz says, it would have to either place electrodes measuring about 100 microns inside the vessels, or use long microwires that connect to a larger piece of electronics sited elsewhere in the vascular system.

Musks Neuralink team clearly has plenty of technical challenges ahead in miniaturizing a device, enabling its safe delivery and positioning in the brain, and figuring out how to use it to treat a serious medical disorder. Once Musk figures all that outand he will, of course, because hes a doerhe can move on to neurotech for the general public. Then we can all get BCIs that channel our thoughts and commands directly to our smartphones and computers, increasing our efficiency and opening up brave new worlds.

Oxley, the stentrode inventor, doesnt expect to see miracles from the Neuralink team anytime soon. But hes excited anyway, saying that Musks willingness to tackle the big technical challenges of neural engineering shows the maturity of the field. Its a huge validating moment, he says. The field of brain-computer interfaces is now taking center stage in Silicon Valley, and being recognized as one of the next great endeavors.

IEEE Spectrums biomedical blog, featuring the wearable sensors, big data analytics, and implanted devices that enable new ventures in personalized medicine.

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5 Neuroscience Experts Weigh in on Elon Musk's Mysterious "Neural Lace" Company - IEEE Spectrum