What are /r/neuroscience's favorite Products & Services?

From 3.5 billion Reddit comments

Algoriths to Live By by Brian Christian and Tom Griffiths. Written for the lay person so very accessible, by a brilliant cognitive scientist at Princeton (though at Berkeley when the book was written).

Vision by David Marr. One of the first and most important books that anyone interested in cognition and computation will ever read. Absolute must if you want to understand why the field began looking at the mind more or less like a computer.

I have to second the principles of neural science as it truly is the bible of neuroscience, but if you’re a real beginner I could not recommend neuroscience: exploring the brain more. Used it in neuro 100 first year of college. I’m a senior now and I still use it because of its clear descriptions that don’t involve vocabulary or concepts you may not understand yet.

Edit: typo

Scholarpedia has some good articles on more advanced concepts and most articles on there are written by experts in their field. I find scholarpedia does a better job at explaining topics. A great plus to scholarpedia is their citations are usually well known literature on the topic, which you can then refer to for very in-depth understandings and as sources for research projects.

But seriously we just use Wikipedia for terminology things. Its a great resource and you will waste a lot of time and energy avoiding it.

This page is a great place to start: http://www.scholarpedia.org/article/Basal_ganglia

It's obviously not a paper by itself but it's full of helpful references that could be a jumping off point. Are you looking for specific numbers of neurons, or just relative strengths and targets of projections?

I recommend this three courses specialization in coursera https://www.coursera.org/specialization/neuro/14 Specially the first one which covers a ver complete introduction in neuroscience and it is relatively easy. To start first there is a very good website called brainfacts which have very interesting articles and a small introductory book free to download. If you want a more specific book and you can purchase it I recommend Neuroscience: exploring the brain, and maybe a little more difficult is the Purves neuroscience. There are also very interesting videos in Ted.com made by top neuroscientist.

I hope this helped

There are literally thousands of potential drugs with each one having dozens of possible effects as well as effects where it might interact with other drugs or substances.

This lists some that are addictive https://recovergateway.org/substance-abuse-resources/drug-addiction-effects/

This lists street drug impacts. https://www.webmd.com/mental-health/addiction/street-drugs-risks

My advice based on what I have observed in friends who have abused drugs - don't.

If your question relates to a specific one then if you talk about that then there are websites that list the impacts etc.

Most researchers agree that the brain must somehow employ a neuronal mechanism for the process of binding different features of a stimulus together. How this happens is still under debate. An hypothesis called binding-by-synchrony does have some empirical evidence supporting it (http://www.scholarpedia.org/article/Binding_by_synchrony), however not everybody in the field shares this view. One of the major questions is how binding can occur over different sensory domains. How does the brain 'know' which information originates from the visual domain and which from, for example, the auditory domain. In the end all features of a stimulus, irrespective of their sensory modality, must be 'bound' together in a single conscious percept. How this happens is still very much a mystery.

In terms of basic background there's a lot of textbooks that are often recommended here. Purves is one, Kandell another, and there are almost certainly other good ones out there. Given your programming slant, you might be into computational neuroscience. For a start that requires only light background in the basics, you might want to check out the Coursera class on computational neuro (https://www.coursera.org/course/compneuro). I believe they code in Matlab but you could probably do the exercises in Python. If you can't get your hands on a copy of Matlab, then you can use Octave instead; they're largely compatible in terms of syntax and data types.

From the article:

>Last week, the duo uploaded their paper, titled “Could a neuroscientist understand a microprocessor?” after a classic from 2002.

This is the link to the "classic" from 2002. Really a great read!

EDIT: changed the link to direct to a [slightly differently formatted, but] more accessible site for the 2002 article. Would love feedback if this is still not accessible for some folks -- I think there was a best link from CMU that I couldn't find at this very moment, but it probably is accessible to anyone, at least in the US!

This is the correct answer. Scholarpedia articles are written by well known researchers in the field and do a good job of citing their sources. For example, here is the Scholarpedia page about memory. It was written by Howard Eichenbaum (RIP), who is a pioneer in memory research.

While the Na^+ /K^+ /ATPase does play a role in maintaining the resting potential, the bulk of the effect is actually due to the difference in the membrane permeability of Na^+ versus K^+, per the Goldman-Hodgkin-Katz equation (see here).

I think boundary extension is a very interesting example which demonstrates how a seemingly faulty memory can in fact be a good thing.

I discovered this specific concept when watching this talk (it's 40 minutes, rest is Q&A) which I also highly recommend to study in case you want to write about this topic in your writing course.

Also, regarding your depression I wish you all the best.

Interesting idea, what types of analysis are you aiming for?

Probably the most interesting thing I know about in this vein is the analysis of the stock market as a self-organized critical system, similar to some prevailing theories on brain dynamics. The first article also references a few more similar studies, if you're interested.

There are approximately 20 billion neurons in the cortex (there are another 66 billion in other parts of the brain, but let's just go with the cortex to simplify things a little. Other parts of the brain are structured differently). 75% of those are pyramidal cells, while the rest are mainly interneurons, which aren't believed to store information. Each pyramidal cell can have 1-10 thousand synapses. Synapses are pretty unreliable, so it isn't clear if "synapse weights" are really relevant, but there does appear to be some type of "permanence" value in each synapse. Let's say this equates to 4 bits of information, or about 16 different levels of permanence.

16 billion * 1-10 thousand * 4 bits = 8 - 80 TB of data.

Of course, this is just the cortex, and is a rough approximation. Hierarchical Temporal Memory, a theoretical computational model of the cortex, uses what essentially amounts to large bloom filters with thresholds as neurons, which are a form of probabilistic memory storage. This means that you can store a tremendous amount of information in a small area, but it isn't easy to get the information back (it really can only check if incoming information is likely to have been seen before), and it only can do so to a certain degree of accuracy. Essentially, the brain has a certain amount of memory, but it's probably not like normal computer memory.

This was mine http://www.barnesandnoble.com/mobile/p/human-brain-in-photographs-and-diagrams-with-cd-rom-john-nolte/1100607223/2689706137173?st=PLA&sid=BNB_DRS_Marketplace+Shopping+Textbooks_00000000&2sid=Google_&sourceId=PLGoP20436&k_clickid=3x...

Though maybe too study tool ish

I second this, especially since OP has very specific research interests. Maybe this is naïve of me, but that seems to me like it'd make the PI search easier!

OP, if you don't have access to search for papers on a database like JSTOR, then start with Google Scholar.

No prob! Honestly, I feel your pain.

> so you're saying I should take programming classes

I mean... if it's something that *you find interesting and that you think you have a reasonable chance of making money at (if that's your goal). Here's a great place to start: http://www.codecademy.com/ Plenty of support here on reddit too. Seems to be an in demand skill set...

I just really enjoy design and programming. And it seems to be a pretty in demand area... with decent salary prospects. I know now that I should have studied IT or CS or web development... maybe all three kind of thing... in school; just gotten a BS degree in CS.

Anyway yeah, if money is your primary concern right now, I suggest sales. I kind of hate sales, but I've done it. I've sold power equipment, hair products, roofing supplies... I even sold cell phones with a master's degree. People we're really funny. "Dude! You should be like a principal or dean or something! And stop psychoanalyzing me!" :) But yeah, sales fields are kind of cut throat, easy enough to get in to with any kind of bachelor's degree though. And I liked learning about the various products. I really liked the cell phones! I like tech.

But yeah, overall, I really dig the design/programming stuff and I haven't paid a dime to learn any of it! And like I said, after about a year now, I've started applying to some entry level stuff... nothing yet, but I learn something new almost every day and meet cool people online here who have a passion for it and know how to go about landing a job in the field. Other than that... it's kind of sales if you want to make some money...

And the stats still say that having a bachelor's is better than not having one in terms of total life-time earnings. So there's a little bit of silver lining there.

http://www.sciencedirect.com/science/article/pii/S0960982211009377

http://gallantlab.org/

But yes, I'm also skeptical: not a real structural understanding of the brain (or not even just these zones).

Are you trying to get a degree for a profession? Or just learn about it while still doing art? Otherwise, why not just learn it on your own for fun?

I'm not sure how valuable this is, but might be worth checking out

• https://www.coursera.org/course/medicalneuro

Thanks!

I found this article, which talks about other theories in addition to the ones that you mentioned, interesting. It's a little long.

It's called shunting and it functionally behaves as opening channels that allow current to oppose a depolarization. The input resistance of the cell drops and current leaks out rather than propagate down the dendrite.

Scholarpedia has a decent explanation: http://www.scholarpedia.org/article/Neural_inhibition

As someone really into neuroscience (not a scientist though), I feel that much is unsure at this stage of development in neuroscience. Philosopher David Chalmers refers to the question of how and why we have subjective experiences as the "hard problem" -- problem that cannot be answered even if we know all the relevant mechanisms of information processing of the brain... You could check out this link: http://www.scholarpedia.org/article/Hard_problem_of_consciousness

Personally, I believe that there is something higher than mere biological machine; even if there isn't, we are perhaps still missing a big part of the puzzle.

I would recommend finding something in the field which looks interesting to you. Either a paper or presentation or some work being done in a lab somewhere. If you are unsure where to start here is a good curated list of topics. You won't understand most of it, but you should look for something that feels like you could spend years working on it.

From there read up on the topic as much as you can and figure out what you are missing? Try to find out: * Does working on the topic require a lot of programming? What languages (R, Python, Java) are the primary tools written in? * Is there a lot of math involved and what kind? Probability/statistic, differential equations, graph theory, etc? * What kind of science background is involved. Are you working on the molecular level, systems level or behavioral level?

Oh that sounds really neat, this isn't the same idea as your research but have you heard of this http://www.spritzinc.com ... its an app for iWatches or any small device that reads emails that uses data that figured out which letters the eye reads first and uses that information to help the reader read their emails faster with limited space. I doubt its the same process, but might be interesting to you. Thank you so much for your input, I am scared mainly about money and not having enough time to do research, but there really is--like you've said--no other way to really figure out what you want to do. So thanks!

Goddamnit Jeff Hawkins' Thousand Brains theory is probably correct, isn't it?

I just looked him up. Funny coincidence: he has a new book on it coming out in about two weeks.

Here you go https://www.amazon.com/Signal-Processing-Neuroscientists-Introduction-Physiological/dp/0123708672

You probably don't need the wavelet stuff. I see there is a second edition out now....and wow.....it goes into some very advanced topics. The second edition could probably be renamed Signal Processing for Electrical Engineering Grad Students with an Interest in Neuroscience.

Are you comfortable with Fourier transforms (not necessarily directly calculating, but more the basic concepts?) If not watch some youtube videos. And flip through the first edition.

Thirding this - it's actually called Principles of Neural Science. It's been called the bible of neuroscience more than once, and its in literally every neuroscience lab I've ever stepped foot in (seriously they seem to self-procreate). It's on amazon and is by far the most comprehensive, solidly biology-based neuro book out there. It's also pretty readable, which is a nice plus!

I saw that book on Amazon as well (The Biology of Desire). Looks promising. I might buy that one.

The publication of Neurobiology of alcohol dependence looks interesting as well, will read that.

I noticed that J. Grisel will release her book Never Enough: The Neuroscience and Experience of Addiction in February 2019. This one will probably contain the most recent knowledge as well, because it's yet to be released.

Thanks!

Yes, but a distinction probably needs to be made; latent or innate memories do seem to exist, I think they are more commonly researched as innate behaviors or more commonly simply instincts, so the one that comes to mind is that your visual system has evolved to perceive big dark looming things and we later learn to attach behavior/meaning to it, this last part is what we sometimes consider learning and seems to be possible during our sleep.

​

Interestingly it can also go by other names, for instance (another example) if you were to stare at a simple puzzle before going to bed, had a dream where you pieced it together, upon waking up you could use that knowledge to solve it in real life, well we use this technique all the time, but we simply group it under imagination or creativity ( the answer came in my dreams !).

​

Source: I study memory ,cognition and AI and have chapters on memory and sleep in my book if you need an overview:

Conscious Artificial Intelligence: Part 1. Foundations

​

​

To my knowledge, there is no "Neuroscience stats" book, but give it a try to Aaron and Aaron's book. It is great as an introduction and more to stats for behavioral scientists and students https://www.amazon.com/Statistics-Psychology-Arthur-Aron-Ph-D/dp/0136010571

Because you are primarily working with behavioral data, perhaps some experiment design book would be the most useful? I might recommend recommend Bayesian Inference in Statistical Analysis by Box & Tiao, or Statistical Principles in Experiment Design by Winer et al. Most Unis offer stats courses on experiment design, so if you have access to those, that would be good too.

Highly recommend The Annotated Hodgkin and Huxley: A Reader's Guide by Indira Raman and David Ferster.

https://www.amazon.com/Annotated-Hodgkin-Huxley-Readers-Guide/dp/0691220638

They do an exceptional job breaking down challenging biophysical concepts presented by the H&H papers. H&H laid the foundational work for electrophysiologists, but most electrophysiologists will admit that the H&H papers are challenging to work through alone. The H&H papers make many new discoveries that weren't yet associated with conventional nomenclature. This annotated book highlights these new discoveries and what modern concepts and nomenclature are associated with them. It also includes appendices that go into detail on the math and physics behind these significant neurophysiological findings.

I'm commenting here just to say I'm in pretty much the exact same boat. I'm trying to learn the concepts behind the math as I go, as it comes up in the research I'm assisting with. Yet, a lot of those things are covered in math far beyond what I ever took or had to take back when I was in my general education credit classes. I just heard the term "Fourier transform" for the first time a couple of weeks ago because it came up in something I'm working on in my neuroscience lab! I have never been required to take physics, so I never have.

Back when I was struggling in my math classes, though, Khan Academy helped a bit.

Thanks for this perspective. I saw this posted in /r/science and came here to see what the neuroscientists were saying about it. As an outsider, I was shocked by how dismissive of the field Kording seems in the first article I read about this a few days ago. But I guess if he has a good reputation and respect in the field, he can get away with that and people (at least some/most people) don't take it the wrong way.

Thank you for your taking time to comment on my post! No need to apologise. Opinions are and will be just opinions. I started writing relatively recently, so I need as much constructive criticism as I can get. As for the title and some of the paragraphs, you are right; it might be a bit misleading. As far as your other doubts on the validity of my arguments are concerned, I'd direct you to this answer on Quora (https://www.quora.com/Why-is-instinct-generally-considered-to-be-overridden-in-humans/answer/Gus-Griffin) which I found really interesting. It might shed more light on the way I see instinct, which, from what I could read, is a bit different from yours.

Have a great day!

Parieto Frontal Integration Theory by Richard Haier & rex Jung https://pubmed.ncbi.nlm.nih.gov/17655784/

Neuroscience of intelligence by Richard Haier provides a great primer https://www.amazon.com/Neuroscience-Intelligence-Cambridge-Fundamentals-Psychology/dp/110746143X

Also read predictors of life/academic success. Two major predictors are IQ and conscientiousness ( lets call it C) this is one of the big five traits used in psychology to map out ones personality unlike other things in psychology this has substantial evidence to support it. C is genetically influenced researchers came to know about this from twin studies in which two twins whit almost same genetics when raised apart in different environments showed same personality traits. Prefontal cortex is known to have influence on C as this area suppresses impulsivity and giving priority to certain tasks among other things.

Like the commenter before said, Cohen is a fantastic source. I’d like to add this one for most artifacts you’ll see in EEG data.

In slide 25 of this slideshare, the box in upper right labeled "Pam Schiller's Brain Booster" is a tabular format presentation by Dr Pam Schiller, early childhood educator, documenting windows of opportunity for learning.

https://www.slideshare.net/FrogStreet/frog-street-prek-curriculum-tour-guide-33238040?qid=f1a94c24-a8c9-44a4-b452-6c67208b918e&v=&b=&from_search=22

Incognito, David Eagleman is a really great book but is a little more surface level. If you want a more challenging book check out Four Dimensions in Consciousness by Richard Pico, I read it but didn't understand much.

Well, the data is available. There's no reason to blindly accept what anyone tells you about the job prospects of a given degree. Looking at the most biotech-oriented job market in the country (Boston, MA) on indeed.com:

• 41 results: http://www.indeed.com/jobs?q=Neuroscience+phd&l=Boston%2C+MA

• 175 results: http://www.indeed.com/jobs?q=Molecular+Biology+phd&l=Boston%2C+MA

41/175 = Neuroscience PhD has 23% of the job postings of Molecular Biology. Doing it for a few other markets:

• New York, NY: 49%

• Washington, DC: 80%

• San Fransisco, CA: 19%

• Philadelphia, PA: 41%

If you do Molecular Biology as a Neuroscience student, you can certainly try and pass yourself off as a molecular biologist, apply for those jobs, and maybe you'll be successful. However, your degree that they're not looking for will not help you. The only time a Neuroscience degree will potentially help you is if you intend to stay in academia (and even that is probably debatable).

It's a little old, but still one of my personal favorites given that the data is longitudinal, they did an excellent job conceptualizing and assessing generalized cognitive impairment, and looked at first-episode psychosis.

https://www.researchgate.net/profile/John_Sweeney6/publication/8664085_Hill_SK_Shuepbach_D_Herbener_ES_Keshavan_MS_Sweeney_JA._Pretreatment_and_longitudinal_studies_of_neuropsychological_deficits_in_antipsychotic-nave_patients_with_schizophrenia._...

Pretty sure that Dr. Robert Becker documented with extensive scientific studies exponential metastasis rates of cancer tumors and damage to DNA from ambient electromagnetic fields waaaaay less than a 2,000 watt microwave oven in his book The Body Electric.

And then got bankrupted for it.

Have you browsed Etsy for any cartoonists (or watercolor painter or whatever style/medium you want)? Plenty of folks on Etsy are willing to do custom jobs.

Here's a dopamine related option, if you want something on the lighter side

I used an open source programme called Inkscape (https://inkscape.org) to make figures for my PhD thesis (in Neuroscience) and also for a paper I published in Scientific Reports. It’s a wee bit tricky getting started with but there’s tonnes of guides and tips online and once you’ve got it it’s very flexible.

Thanks again :)

Alternatively perhaps pre-synpatic neuron can release both excitatory and inhibitory neurotransmitters simultaneously? As before the post synaptic neuron can develop either excitatory or inhibitory receptors.

In fact both mechanisms mentioned here: https://tinyurl.com/mfw5v5h

...and perhaps the growth of these receptors is governed by post-synaptic spike in conjunction with neuromodulatory reward signal (eg presence of dopamine).

Intuitively I would have thought such a mechanism must exist for rule 2) otherwise there is no means to weaken a connection (other than by overriding an excitatory connection with additional inhibitory ones... which would be wasteful).

3rd year college student taking Neurophysiology for my Kinesiology degree (though not required). Here's a link on the exact book we are using. https://libgen.is/book/index.php?md5=2C0F256A9E3CDCBBFEE6675FC9A6CC28 Neuroscience is cool and interesting,but be aware on the many obstacles you will encounter on trying to grasp the content. The book covers the principles and foundations of neuroscience, it's tough, yet rewarding. Definitely changed my perspective on the brain (in a good way). Enjoy!

I have tested many times and I always get maximum 13 score before masturbating (yes 13, not 14 I remember wrong), moreover I feel that I remember the numbers easier after masturbating, not placebo effect, I have tested many times. Why don't you test by yourself?http://www.cambridgebrainsciences.com/play/digit-span

If you know the science behind this, please pm me

Hello, I'm from VietNam and this is SERIOUS, no JOKING: I found out that after masturbating, my working (short term) memory is better, I use http://www.cambridgebrainsciences.com/play/digit-span to test, be4 masturbating: I score 13, after masturbating I score 14 3 times, can you explain why?

Check this paper by Jordan and Rumelhart.

The relational inductive bias is interesting. My naive guess would be that it's arranged in a cognitive "hierarchy" like

Recognize Blocks -> Movable objects of a certain shape and weight that can collide -> Inverse model for movement planning

The tricky part is the inverse model. Not just learning it, but how you work "backwards" from a "hallucinated" target arrangement. Smooth trajectories may be invertible e.g. on the block surface, but might be really complex when it comes to high-dimensional muscle movements. Furthermore, I'm not convinced that working 'backwards' from a desired state is the solution we use. Perhaps there's another hierarchy of memory-based heuristics that guides the planning bit. For example when we think of walking to an ice cream truck (our desired state) we don't do it in terms of "move left foot then right repeatedly", but just "walking". Then again, sensorimotor predictions seem efortless to us despite the difficulty of the task, so who knows, maybe there is a ton of machinery dedicated to something like inversion.

If you go to a university you can get around the paywall for this article on the neurobiology of emotion perception:

https://www.semanticscholar.org/paper/Neurobiology-of-emotion-perception-I%3A-the-neural-of-Phillips-Drevets/f054cd8e9728201ac55c535bcb57b04816a0c172

> Understanding visual scenes requires the visual system to infer the three-dimensional structure of the world from the two-dimensional projections on our retinae. This task is complicated by the fact that objects closer to the viewer will often block or occlude the view of objects farther away, as depicted in Figure 1. This produces visual borders that are owned by the closer, occluding objects.

http://www.scholarpedia.org/article/Border-ownership_coding

I hope this concept helps you understand the illusions. Basically your brain comes up with a hypothesis that includes an object that is otherwise invisible. In the kanizsa triangle case the hypothesis changes the border ownership of the slices taken out of the circle.

Sort of, but not really. Basically it’s a theory that visual inputs are processed in a hierarchy going from lower order to higher order visual areas.

Lower order areas process simple features and then relay the signal upward to the next visual structure in the hierarchy. Each visual structure performs more complex processing than the previous structure, this way the visual representation becomes increasingly complex as it goes from lower to higher order visual regions.

A good visualization is in figure 2 - http://www.scholarpedia.org/article/Models_of_visual_cortex

Thank you for answering my question Dr. Koch, but I'm not sure I understand your answer. David Chalmers (http://www.scholarpedia.org/article/Hard_problem_of_consciousness) argues that there's a difference between using empirical methods to answer the "easy" problem of consciousness--answering questions about an agent's awareness of features of their environment--and the "hard" problem of consciousness--answering questions about what it's like to experience, or what we typically care about when we talk about consciousness. In this sense, consciousness and awareness are not the same. I'm also not certain if abduction is sufficient enough to infer the consciousness of other agents (e.g, it doesn't allow us to tell if Artificial Intelligence has consciousness). Are these kind of philosophical understandings of consciousness addressed in your book? Thanks again for taking the time to answer questions

For computational neuroscience, add in dynamical systems.

For ex, the Fitzhugh-Nagumo model of cell firing.

What about standard measures, such as Victor-Purpura, Van Rossum, etc? There is a quite good overview here, the guy who wrote it is one of the current leaders in this field: http://www.scholarpedia.org/article/Measures_of_spike_train_synchrony

In addition to what's recommended here, Scholarpedia has good in-depth neuroscience pages to read once you understand the basics. Before that, stick to textbooks/books for laymen.

First, it's probably worth noting that being in a position to actually to actually ask that question would be an incredible luxury.

That aside, if you are talking about knowing all the details of the the anatomy and physical structure of the brain, then it certainly helps, but probably won't be enough (as /u/bloodthirstymouse and /u/Stereoisomer pointed out).

In the scientific community, usually people will talk about how the brain's physical structure serves as a relatively static scaffold or backbone on top of which all the very dynamic brain activity occurs -- the scaffold constrains these dynamics, but there is still tons of variability in terms of the neuronal activity and behaviors that arise. Likewise, I doubt we'll be able to understand or treat diseases solely from an understanding of this scaffold, but it's hard to say for sure. New methods/techniques can drastically change what's possible. As a related note, some even like to link concepts from chaos theory to predicting brain activity, which assert that it's literally impossible to predict future activity beyond a short time span or "event horizon."

Here's a short/sweet article that's a good framework for thinking about the different types of brain connectivity: http://www.scholarpedia.org/article/Brain_connectivity

Are you asking in terms of biological plausibility of your plasticity rules, or in term of learning scheme applied to reinforcement learning in artificial models, regardless of biological plausibility? In case of the former, 1 and 3 and 4 are plausible and in accordance with the general rules of STDP (http://www.scholarpedia.org/article/Spike-timing_dependent_plasticity).

From what I understand your model doesn't respect Dale's law (a neuron can release only one type of neurotransmitter, therefore can only be excitatory or inhibitory). Your second rule stipulates that an excitatory neuron could become inhibitory, which isn't biologically plausible. Normally with STDP you can have depression or potentiation of synaptic strength, depending on the timing of the pre and post synaptic potentials.

It's hard to put the concepts into context without knowing what your context is, but you might look into the idea of attractor networks. I think there could be some links to the criticality theories you're talking about, although I've never heard anything about criticality applied to neuroscience, so I may be misinterpreting the question at hand.

Hi Tortenkopf! I was just freaked out when I've read most of the studies, but now it seems everything is back to normal, and yes if damage was done I'm pretty optimistic nothing would stay even in my PFC functions.

I reckon you have read these studies but the maps litreview: http://www.maps.org/research-archive/mdma/litupdate3/ivas.html and the baboon study with the serotonerg regrowth, and even greater number that preexperimant state: https://www.researchgate.net/publication/13691262_In_vivo_detection_of_short-_and_long-term_MDMA_neurotoxicity_-_A_positron_emission_tomography_study_in_the_living_baboon_brain

With the regrowth in the lower parts, does anyone know what does it mean? Eg you say terrific most of the time, and I'm wondering if this rewiring, the increase in terminals might be also cause of it. (I don't want doses for that, indeed I'm not fan of mdma, also effect is in what is connected/wired, just curious)

here's one https://www.researchgate.net/profile/Fergus_Craik/publication/232468480_Levels_of_processing_A_retrospective_commentary_on_a_framework_for_memory_research/links/0a85e535693ad02b60000000.pdf

I like the great courses

https://www.thegreatcourses.com/courses/your-deceptive-mind-a-scientific-guide-to-critical-thinking-skills.html

https://www.thegreatcourses.com/courses/the-creative-thinker-s-toolkit.html

> Also does the effect double up each time you learn a new language

No it's nowhere near that level of specificity. I've just heard it as a possibility in discussions about intelligence. It's controversial, don't have any sources at the moment.

Here's a really great article from interviewing a neuroscienctist about sleep and it's affect on your brain and body. Sleep is much more serious and important than people give it credit for. https://getpocket.com/explore/item/sleep-should-be-prescribed-what-those-late-nights-out-could-be-costing-you

I've been working to improve my sleep schedule, I hope it helps!

If we're talking quantum fuckery, I prefer Johnjoe McFadden. Life on the Edge, written with Jim Al-Khalili, touches on this stuff and more.

How can i tell if the subject of the book Becoming Supernatural is vetted and worth a serious read, or if it’s more dismissible pseudoscience?

Start with neurons their antatomy, ion channels and different receptors, as well as how action potentials work. Then learn about inhibitory/excitory neurons and neurotransmitters. Then start learning about neural pathways for different systems that interest you. Then start on neuroanatomy, the roles of different brain regions, as well as cortical cell layers.

Neuroscience is a massive field but neurons is the base for all of it.

Here is a pretty good intro text:

https://www.amazon.com/Neuron-Brain-5th-Ed/dp/0878936092

A plastic brain model which is useful for neuroanatomy and displaying on one's desk.

https://www.amazon.com/Principles-Neural-Science-Fifth-Kandel/dp/0071390111/ref=sr_1_5?dchild=1&keywords=neuroscience+textbook&qid=1592935806&sr=8-5

If you want to learn about the brain check out most neuroscience text book. While the information will be presented in a less fun way it will not be pop science. Most university libraries will allow you to search for what books their neuroscience courses use and then you can order the older/or current editions, depending on how much you want to spend, on amazon or ebay.

I've recently been reading this book, Nutrition Essentials for Mental Health: A Complete Guide to the Food-Mood Connection. I'm not a medical doctor, but there is some compelling evidence showing that low levels of certain neurotransmitters (like GABA) can be a result of dietary and microbiome issues. Worth looking at if you're curious.

https://www.amazon.com/dp/0393709949/?coliid=I1PG5500QQBYA4&colid=TJXTYALKVLVH&psc=1&ref_=lv_ov_lig_dp_it

I second Oliver Sacks - Hallucinations or this oliver sacks book. Also "Tale of Dueling Neurosurgeons" is good and provides a more general overview

I love this one:

https://www.amazon.com/Secret-World-Sleep-Surprising-Science/dp/0230107591/ref=sr_1_fkmrnull_1?keywords=The+Secret+World+of+Sleep%3A+The+Surprising+Science+of+the+Mind+at+Rest&qid=1556476017&s=gateway&sr=8-1-fkmrnull

​

For a more technical view my oldish copy of Neuroscience edition 5. I think (Purves) had a great chapter, not sure newer editions still have it.

Spikes: Exploring the Neural Code is a great book for people from a physics background who want to learn neuroscience.

What kind of stuff are you most interested in? I wonder what the kind of material you're engaged in with a maths background. Is anything strictly 'off-limits' because of less exposure to biology or lab based knowledge?

Probably maths in general is most interesting to me. I like using maths and thinking about maths. How I would like to apply those techniques so far is pointing towards neuroscience and the brain. Like for most 16-19 year olds, there is a sexy draw to consciousness, behaviour, cognition, etc. I've read Godel Escher and Bach, The Man who Mistook his Wife for a Hat, Predictably Irrational, Thinking Fast and Slow, a flurry of Game Theory and Behavioural Economics using calculus, Superintelligence, a couple of intros to Philosophy of Mind), etc. However, if I'm going to read about formal techniques and go beyond the scope of the syllabus then really I only do that with maths. It's the only subject I've read university texts for (albeit, very basic analysis, newtonian mechanics using vector calculus and a 'methods' approach to stochastic calculus)

Forgive what probably seems like me talking my way into a decision. I suppose hashing it out properly is one good way to reach a decision. Just worried I'm going to get 3-4 years into my education and realise I've locked myself out of what I find interesting.

I'm reading 'Thinking, Fast and Slow' by Daniel Kahneman, and in the first few chapters he talks extensively about how pupil diameter is a faithful indicator of cognitive 'load' during tasks which require focused attention. He found that pupil diameter was also approximately proportional to the difficulty of the task (more difficult -> more dilated). I'm not sure if it's related to impulsivity but I haven't looked into it.

Here are some papers

Fascinating! Thank you for your thorough reply and literature suggestions. I am going to look at one of these around Yuletide. I AM very interested in the biological side even though my application will be in CS.

(I know it's a long shot but any thoughts on the following books: Artificial Intelligence: A Modern Approach, by Peter Norvig Reinforcement Learning, Sutton & Barto The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer Series in Statistics))

I'm thinking of going a bit into the biological aspects before diving into the typical Machine Learning stuff. I'd love to know after what current models have been styled.

The 50 ideas you really need to know series has a great book on the most important concepts in neuroscience.

50 human brain ideas you really need to know

I'm an first year MSc Physio student. I have found Neuroscience by Krebs (https://www.amazon.co.uk/Neuroscience-Lippincotts-Illustrated-Reviews-Lippincott/dp/1451110456/ref=sr_1_2?ie=UTF8&qid=1499336141&sr=8-2&keywords=krebs+neuroscience) to be brilliant. It's got a good amount of detail with useful pictures.

Kandel's Principles of Neural Science is good. Pdf available online. Concussion falls under traumatic brain injury. I have a friend who did her honours in this field. Worked under a prof named Ramesh Rajan at Monash university, you might want to check him out. Awesome guy. Just as a heads up, you will most likely be working with rodent models in TBI.

• The Emotional Brain - Joseph Ledoux
• Descartes' Error - Anthony Damasio

If you're doing EEG or MEG, there's a book you might be interested in. I checked out a copy from my campus library, and I'm working through it to familiarize myself with time-frequency analyses.

In my lab (psycholinguistics, EEG) we use fieldtrip, EEGLAB, and EP toolkit. There's a lot of coding you can do directly in MatLab too, which is what Mike Cohen's book is geared for.

I'm in the same boat as you, so I've started on this book which uses Matlab. It's a neuro comp-sci book, and then I use Khan Academy for math as needed. Turned out I was way behind on my math, so I'm working through the whole Khan Academy gamut. It takes time but the videos and exercises are really good.

And as a cognitive neuroscientist, the pure simplicity and logic of math is a wiff of fresh air compared to the noisy data we usually work with :) One day, I can return to the book I mentioned above with a clear understanding. But pure math has already proven valuable in my work, just for the sake of understanding patterns.

When i was an undergrad, i really enjoyed learning the fundamentals from this book: http://www.amazon.com/Cognitive-Neuroscience-Biology-Mind-4th/dp/0393913481 It reads really well, has beautiful images and gives a Sound basis for further reading for people with no or not much knowledge in the field. Good luck!

On the Organization of Behavior by D.O. Hebb. One of the best, most cited, and least read books. Hebb's ideas go way beyond merley strengthening and weakening synapses, but does a great job of linking in historical evidence and predicting the roles of sequences and rhythms.

http://www.amazon.com/Organization-Behavior-Neuropsychological-Theory/dp/0805843000/ref=sr_1_1?ie=UTF8&qid=1452583214&sr=8-1&keywords=hebb+organization+of+behavior

What kind of paper? Don't you have access to most of the journals through your university? I can browse many journals at home with VPN-Access, provided by my university. For books, try these: http://www.amazon.com/Principles-Neural-Science-Fifth-Kandel/dp/0071390111/ref=sr_1_1?ie=UTF8&qid=1452278840&sr=8-1&keywords=principles+of+neural+science OR (less detailed) http://www.amazon.com/Neuroscience-Exploring-Mark-F-Bear/dp/0781778174/ref=sr_1_1?ie=UTF8&qid=1452278819&sr=8-1&keywords=neuroscience

I heard some rumours that at least the Kandel is available as a free PDF in the internet, just use google with the proper terms ;)

The book I started with was "Mathematics for Neuroscientists" (http://www.amazon.com/Mathematics-Neuroscientists-Fabrizio-Gabbiani/dp/0123748828/ref=sr_1_1?ie=UTF8&qid=1447603957&sr=8-1&keywords=neuroscience+mathematics) which discusses broad mathematical subjects applied to neuroscience, but assuming little knowledge of math.

What kind of "concepts" do you mean? I assume the program is towards cognitive neuroscience / biological psychology / neuropsychology rather than really hardcore (cellular) biological stuff. My first uni course about that used Kalat's Biological Psychology which I remember being a very nice general introduction, http://www.amazon.com/Biological-Psychology-James-W-Kalat/dp/1305105400 (there may be something weird about the soft cover version being incomplete, I just saw in a comment).

Amazon.fr have an "international edition" at half the price, the content seems identical : http://www.amazon.fr/Neuroscience-Exploring-Mark-F-Bear/dp/1451109547/ref=sr_1_1?ie=UTF8&qid=1439912568&sr=8-1&keywords=Neuroscience%3A+Exploring+the+Brain

Anyway, thanks!

Kandel's "in Search of Memory" is a great read and explains how memory seems to work in the context of his life and research (he won the Nobel Prize for his work): http://www.amazon.com/In-Search-Memory-Emergence-Science/dp/0393329372

If you want to get more into understanding the circuitry, I always recommend the Bear/Connors/Paradiso textbook for anyone who wants to learn more about neuroscience topics but doesn't have much background on the subject. They're very good writers and present information very clearly. If you're looking to find it cheap I would get a used 2nd or 3rd edition, but this is the newest (fourth): http://www.amazon.com/Neuroscience-Exploring-Mark-Bear-PhD/dp/0781778174/

You'd probably be more interested in cognitive science or cog psych. than neuroscience. Neuro is more about the biology and chemistry of the brain whereas cog sci/psych. are more about the mind, decision making and behavior.

The cog psych. text I used in class was "Cognitive Psychology: Connecting Mind, Research, and Everyday Experience," 3rd ed. by Bruce Goldstein.

Unfortunately I really don't know how it compares to others. Also, I never took cog sci. so I don't have any recommendations for that.

Hi friend,

I just graduated with a degree in neuroscience two weeks ago. I loved every second, and this: http://www.amazon.com/The-Britannica-Guide-Brain-eBook/dp/0762433698 was my best friend throughout my undergraduate education. I actually got it MY junior year in high school, so I figured I should pass it on to you :). It covers many questions in neuroscience ranging from the basics to tougher issues in cognition and vision, and does an excellent job of explaining everything. Not to mention it's pretty cheap ;) Let me know if you have any questions about neuroscience in college, I'm happy to help!

Sure, I'd say you have a chance. I don't think AI will help you very much in computational neuroscience (you'll learn about perceptrons, but those are pretty much a historical curiosity), but it's not a bad class to have had, as it's in some ways a history of how we've thought about intelligence. Statistics and machine learning are pretty much necessary tools these days, so definitely a good idea. If you're comfortable with differential equations, that will help. If you'll want to be modeling spiking data, you should learn about point processes.

There are very few good books, but the following give what I consider to be a pretty good grounding in computational neuroscience, though you might at times use them as jumping off points for doing research outside the book.

• Foundations of Cellular Neurophysiology
• Theoretical Neuroscience

Self Comes to Mind by Antonio Dimasio is a fantastic delve into consciousness, it's written in simple language so it should be a good book to start on. Also check out free online classes/lectures from Coursera, MIT and Harvard.

Hello past me! I got my BS in biomedical engineering and now I'm in my first year of a neuro phd program, woo!

Definitely brush up on the basics, maybe borrow an intro neuro textbook from a library (I skimmed through From Neuron to Brain before I started). Yes, you will be taking some "intro" courses the first year, but most of my professors teach the class with the assumption that the students took neuro classes in undergrad, which I did not (plus I graduated from undergrad in 2009...).

If you know what you're interested in and could post it in here, we might be able to come up with some interesting papers or good books to read that are more specific to you. For example, I am interesting in cortical networks and my PI suggested I check out Connectome. I will be honest, I have not read it yet as I have plenty of papers I have to read every week, but I plan on getting to it over the summer.

Nope, only comments I disagree with. And we are both operating under the assumption that nothing has been proven -- this is purely philosophical.

I'm sure that I am a narcissistic jerk, but there are actually some pretty good not-yet-scientific ideas about what consciousness is. I would highly suggest Daniel Dennett's Consciousness Explained or anything by Douglas Hofstadter (I Am A Strange Loop is my personal favorite).

I apologize for being a jerk, and for being unable to succinctly sum up a complex theory of consciousness in a reddit comment, but I hope you will check out these amazing authors despite my arrogance...