What is pain in terms of neuroscience?

Please Visit: Neuroscience 2018

By: #Yohan John, #Neuroscientist at #BostonUniversity

Pain in the body is associated with pain receptors (nociceptors). But pain receptors might not cover all kinds of pain. Headaches, for example, are subjectively felt as originating in the head, but there are no pain receptors in the brain. (Some headaches may be a result of nociceptor activation in the tissue surrounding the brain. Headaches remain poorly understood.)

It makes sense therefore to think of pain as a particular (and still largely unknown) pattern of activity. Sometimes this pattern is a result of signals from the rest of the body, but sometimes the pattern seems to originate within the brain.

The question of the material basis of a feeling is a mystery, however. It sits at the boundary between science and philosophy. Philosophers call subjective experiential states qualia. They seem to be linked to brain states (which in turn are linked to bodily states), but beyond that we can say very little. We can simulate such states in machines, but that doesn’t really tell us if the machine is feeling anything. In fact the question of whether a machine feels anything may be unanswerable: each person only has access to their own consciousness.

We cannot directly perceive what another person or animal or robot is feeling. All we see are their reactions and their internal states as measured by our devices. We infer an experiential state by analogy with how our own experiences relate to outward behavior. When I get a headache, I might clutch my heads and groan. If I see the same in another person, I can infer that they are experiencing something similar. But how similar? It is impossible to say.

The Future of Brain Science

Neuroscience 2018

By: #

EricHaseltine, Ph.D., is a neuroscientist and the author of Long Fuse, Big Bang

If the past is any guide, the thrilling future of neuroscience has already arrived, but most of us just haven’t noticed it yet.

With previous scientific breakthroughs that elevated the human condition—such as the discovery that bacteria cause infectious disease (leading to antiseptics and antibiotics) and the discovery that silicon integrated circuits could be made inexpensively (fueling the digital revolution)—key discoveries emerged decades before anyone, let alone leading scientists, grasped their full importance.

Ignaz Semmelweis discovered that “cadaverous particles” (bacteria) caused disease in 1848, over 20 years before antiseptic techniques to combat infection were adopted. The integrated circuit and Complimentary Metal on Silicon (CMOS) developments in 1958 and 1963, respectively, occurred long before these discoveries made possible Moore’s Law (digital circuit performance doubles every 18 months), personal computers, mobile phones and the World Wide Web.

I believe that developments comparable to previous seminal scientific breakthroughs have already occurred in neuroscience, but most of the world hasn’t realized it yet for a number of reasons, chief among them that some of these earthshaking advances aren’t actually in neuroscience at all, but in fields such as Computational Mathematics and Artificial Intelligence(AI).

Big neuroscience advances

Before describing the “non-neuroscience” advances that are propelling neuroscience into an exciting future, let me focus on recent key breakthroughs that are in the field of neuroscience. Ian Stevensen and  Konrad Kording of Northwestern University showed in a 2011 paper in Nature Neuroscience, that neuroscientists have doubled the number of individual neurons that can be simultaneously recorded every seven years since 1950, producing a “Moore’s law” of neuroscience that has taken us from studying one neuron at a time, to nearly a thousand neurons at a time. Techniques such as opto-genetic recording, carbon nanotube electrode arrays, and injectable silver mesh arrays of nano-electrodes now enable neuroscientists to both listen to and stimulate vast arrays of neuron populations, all at the same time.

Apart from the therapeutic value of such massive recording and stimulation capabilities for treating diseases such as epilepsy and Parkinson’s, the ability to read and write to large populations of neurons has opened up the possibility of directly interfacing brains to computers.

Miguel Nicolelis of Duke University has already done this in monkeys, using an array of implanted electrodes in motor cortex to read and interpret neuronal discharges in large populations of neurons so that a monkey, with Nicholelis’s implants can precisely control an artificial robotic arm by “thinking” alone.

This staggering achievement illustrates the crucial importance of “non-neuroscience” advances to neuroscience itself: Nicolelis could not have made sense of the overwhelming flood of data pouring out of his monkey’s brains without the assistance high performance computers and Machine Learning (a kind of Artificial Intelligence) algorithms that learned to interpret complex firing patterns of the large populations of neurons that “learned” to control a robot arm.

Put another way, neuroscientists have gotten so good at studying the brain with micro recording techniques, that neuroscientists, by themselves, cannot hope to understand the overwhelming complexity of what they have discovered.

Enter Computational Math and AI

Fortunately for neuroscience, mathematicians, data scientists, and computer scientists have been wrestling with their own “information overload” challenges, coping with exponential increases in the volume, variety and velocity of digital data spawned by the Moore’s law revolution in digital technology.

Google, for instance, ingests unimaginable volumes of data every second, that they must somehow “monetize” (make money from, because their services are largely “free”) by precisely targeting digital advertisements to people who use Google search or Gmail. Google can only do this with the aid of massive cloud computing systems running complex math and AI algorithms that quickly recognize patterns (such as which people who search for item “A” are likely to purchase item “B”) and act upon these insights to serve up ads in real time. (When you enter a Google search you get back different ads in the sidebars than I do, because your likely purchasing behavior is different than mine.)

This sort of digital mind-reading through esoteric pattern analysis is precisely the sort of thing that neuroscientists such as Nicolelis need both to interpret patterns of activity in large populations of neurons and to communicate with those same neurons.

One branch of AI, called “cognitive computing,” holds particular promise for extending Nicolelis work to humans (enabling humans to control robots with their minds or to help paralysis victims walk again with aid of robotic prosthetics). Cognitive computing, which goes well beyond simple pattern recognition, achieves deep understanding about the underlying causes of complex patterns, instead of simple recognition that patterns exist.

Whereas current machine learning AI systems can determine, from brute force statistics, which people who make Google searches will respond to different targeted ad promotions, these AI systems don’t know why there is a connection between Google search behavior and purchasing behavior, only that a useful correlation exists.

But using esoteric mathematics, such as the higher dimensional models described by Princeton University researchers Li, Bastian, Welsh and Rabitz in a 2015 article in the Journal of Physical Chemistry, cognitive computing experts are gaining deep insights into causal relationships among large numbers of variables (such as firing patterns of thousands of different neurons) in order to understand the deep meaning of complicated patterns.

The future is now

Armed with such AI-derived deep understanding, it will soon be possible for computers to communicate in real time with the brain in highly sophisticated ways, enabling such science fiction-sounding capabilities already demonstrated in the lab (see references) such as:

• Direct brain-to- brain communication through thought alone.
• Brain-to-brain transfer of learning and memory.
• Hybrid AI/Brain combinations (AI assisted brains) learning.
• Thought-controlled computers and machines.
• Mind controlled prosthetics for spinal cord patients and amputees.

While my last post, Where Will Evolution Take Humans Next, predicted that humans themselves—through gene editing of human embryos (e.g. through CRISPR/Cas9)—will directly determine the directions that Homo sapiens will soon evolve, here I predict yet another—far faster—form of human evolution: the blurring of the boundary between humans and the machines that humans invent.

That this marriage of humans and machines will occur, I have no doubt. The bigger question is, after it does happen, will human beings be more or less than they once were?

Only the future will tell.

What are top 10 brain damaging habits?

 

By: #Vansh Bhagat

#1 No Breakfast

We’ve seen it everywhere that Breakfast is one of the most important meals of the day.Those who do not eat breakfast will have lower blood sugar levels. After a long night without eating, this can lead to an insufficient supply of nutrients to your brain. If repeated often enough over a lifetime this can cause brain degeneration.

#2 Overeating

As if we’re not already feeling guilty enough about this one! Apparently, besides making us gain weight, feel bloated and damaging our self-esteem, overeating also causes hardening of brain arteries which can in turn decrease mental power. Sigh.

#3 Smoking

We all know smoking is bad for one’s health. The most freaky side effect of smoking is that is causes “multiple brain shrinkage”. It is also a suspected culprit in Alzheimer’s disease and other dementia-related diseases.

#4 High Sugar Consumption

Ditching the sugar habit will bring you more health benefits than most people realize. If you’re not convinced yet, turns out that high sugar consumption has been shown to disrupt the body’s ability to absorb proteins and nutrients,which causes malnutrition and issues with brain development. We may be starving ourselves and not even know it!

#5 Air Pollution

This one is a bit harder to solve on an individual basis unless you walk around with a face mask all the time. The brain needs incredible amounts of oxygen to function properly and constantly inhaling pollution decreases the oxygen supply to the body, leading to a decrease in brain efficiency.

#6 Sleep Deprivation

Long term sleep deprivation speeds up the death of brain cells. We want and need to keep our brain cells around for as long as possible! Sleep gives your brain a chance to rest and repair itself after long and sometimes stressful days. Make sleep a priority and do what it takes to get more of it!

#7 Head Covered While Sleeping

This one surprised me too. Sleeping with your head covered goes along with #5 in the fact that it reduces your oxygen intake at night. Since you are asleep, you might not even realize that you’re light-headed or air deprived. You also raise the chance of inhaling too much carbon dioxide. Play it safe and keep the covers off your face!

#8 Working Your Brain During Illness

Some of us are so driven or determined to succeed that we refuse to rest when we get sick. The truth is, when our body shows signs of illness, it’s often the body’s way of telling us we need to SLOW DOWN and reconsider our current lifestyle. It is also telling us that our BRAIN needs a break! Pushing through sickness, continuing to study or work or do whatever it is we do every day can actually decrease the effectiveness of and damage the brain.

#9 Lacking In Stimulating Thoughts

Basically, if we don’t use our brain and stretch it with new and stimulating thoughts, it will SHRINK.Thinking is a powerful tool and throughout all the years of your life, the thoughts you think create new pathways in the brain. You won’t stay the same forever – you’ll either create new pathways and improvements in your mind, or your brain will shrink to accommodate your lack of effort to think and discover new things. Weird!

#10 Talking Rarely

Similar to #9, talking to people helps your brain to grow and develop. Participating in intellectual conversations will stretch and strengthen your brain and help the efficiency of the brain over time.

So as you can see, your brain is a marvelous gift. It’s fun learning new facts about how to take care of and develop the best brain possible. Don’t ignore these important little diddies of info! Do what it takes to keep your brain healthy and strong for your entire life and you won’t regret it.

How is psychology related to neuroscience?

By: Trish Hinojosa, B.A. in psychology; have worked in social cognition + sys neuroscience labs.

Psychology is the scientific study of behavior and mental processes. A behavior is any directly observable action or reaction, and metal processes include internal processes such as: thinking, feeling, and desiring. Historically, these mental processes could only be observed indirectly. Advancements in neuroscience and neuroimaging have made it possible to look at these internal processes more directly (assuming the scientist has designed a valid experiment). 

Importantly, our neurobiology constrains our behaviors and mental processes. Since psychologists aim to explain, predict, and control (e.g., preventing unwanted behaviors and promoting desirable behaviors) psychological phenomenon, an understanding of the neurobiological and neuropharmacological underpinnings of behavior and mental processes can help scientists make better predictions and design better interventions/treatment plans (e.g., targeting the neurological mechanisms or brain networks that underly speech problems in an individual with parkinson disease) . 

When psychology and neuroscience get together, they can tackle the following topics:

• Psychophysics and Perception
• Behavior/Systems/Cognition (I personally analyze data from this domain)
• Plasticity and Neural Development
• Clinical and Experimental Neuropsychology
• Neuropsychopharmacology.

Ultimately, psychology and neuroscience challenge, clarify, and inform one another's theories, hypotheses, and methods. The idea that psychology and neuroscience are completely at odds with one another is a false dilemma.

How can I start learning neuroscience?

 

By: #Connor Gallimore, B.S. Psychology & Neuroscience, University of #NorthCarolina at Chapel Hill

When it comes to complex topics like this, I’m a fan of the Bottom-up approach to learning. This involves starting with the most basic, fundamental concepts of a subject and slowly integrating your new knowledge about them into the grand, wholistic view of the field.

For #neuroscience, it seems natural to me to begin with the neuron. Learn about its physical structure, and the #electrochemical properties that allow it to transmit information from cell to another. Learn about the types of cells that various types of neurons project onto, and the areas of the brain acting as the ultimate destination of a pathway’s signal. Learn about the different neurotransmitters released at each synapse, and how they contribute to the cell’s observed properties.

Most importantly, ask hard-hitting questions. Is this particular type of neuron excitatory, or inhibitory? How does this relate to the #electrophysiology? What does its morphology tell you about its function? Was it designed advantageously to serve its observed purpose? Why are there 5 different types of dopamine receptors? What is the purpose of a closed-loop system, or inhibitory gating? What kinds of pathways have been well-characterized in research, and what are the functional consequences of these pathways for the organism’s perception or behavior? For instance, why does the basal ganglia have both a direct, and indirect pathway?

There is a wide array of subfields that approach neuroscience at various levels of abstraction, from the molecular and #genetic, to the cellular, to the systems level, to the #cognitive and decision-making level, even to the level of social interaction, or the utilization of #computational and #mathematical modeling. The beauty of neuroscience is that there are so many different angles one can approach the topic and still find a plethora of unanswered questions.

The field is your playground. But beware: a truly in-depth understanding of neuroscience across these levels of analysis requires years to build. Take it from me, it’s so much fun to learn about.

   
    What Is Neuroscience?

By: #Joyce Schenkein, PhD in Neuropsychology, Former Neurology Faculty (PhD/MD) at University of #Pittsburgh

Neuroscience is the scientific study of the nervous system. Traditionally, #neuroscience has been seen as a branch of biology. neuroscience - Google Search
In response to the questioner's note I originally added details that weren't saved or something. I've just  been confused because how much of neuroscience overlaps with psychology  and philosophy? 

The natural sciences began as Philos0phy because the research methodology was not developed.  Also, people relied upon the opinions of their predecessors, as opposed to obtaining new knowledge.

Eventually, real data was collected to replace speculations.  So for instance, the question as to whether man is a blank slate (tabula rasa) at birth, has been replaced by longitudinal data showing that children are born with temperaments (in other words, the dials are set at birth) 
So then next  the question becomes,  what can be changed with early intervention.? More research.....No need for Philosophers
Neuroscience had a later debut because nerves are 1.tiny 2, hidden 3.work extremely quickly . 
A high resolution microscope was required to advance "The Neural doctrine", which suggested that nerves are discrete units and not a single strand of spaghetti woven into a huge ball called the brain. 

As technology advances, neuroscience can answer progressively more difficult questions.  Insofar as consciousness has not been explained, #Neuroscientists do experimenters, but Philosophers also go over the data trying to understand what it means.