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I ran across this url to Paul Krugman being insightful and thoughtful regarding the general question of What is usually a Model and What do we use them commercially in Science? It s about economics and specifically types of development economics, however the general questions of methodology connect with social sciences more broadly. It is in the
The following ad should come in the Cognitive Neuroscience Newsletter soon: Postdoctoral Positions at Northwestern University Memory Systems, Intuition and Modeling Department of Psychology Laboratories of Paul Reber Ken Paller Multiple postdoctoral openings available on two new projects targeted at accelerating expertise development from training using memory systems theory. One project will build up
I got another request to discuss yet another media declare that technology is unappealing for our brains. It s actually another good instance of really poor science reporting on tv, so I won t link it, nevertheless the topic seems generally of curiosity and it is apparently based with a curious underlying folk
I was inspired to answer some questions from your middle school student conducting a research project on game titles. Since I am serious about the topic generally, I should probably discover how to answer most of these questions with an age-appropriate level. My attempt: Jose asks: 1. Do games affect the neural?
This is definitely a interesting piece within the philosophy of science and popular understandings of science: How our botched idea of science ruins everything /article/index/268360/how-our-botched-understanding-of-science-ruins-everything As an exercise on the reader, explain what's incorrect with his complaint that what many people think of science is in fact the opposite of science. Some helpful ideas
How and where memory is situated the brain, particularly memory acquired through practice
How experience shapes action, perception and weighed pervasive mechanisms of plasticity throughout the brain
Investigating memory system interactions and intuitive making decisions using visual category learning.
Check the Presentations link within the right side bar to view the most recent ideas and reports as presented as posters and talks at recent conferences.
I ran across this hyperlink to Paul Krugman being insightful and thoughtful concerning the general question of What is usually a Model and What do we use them commercially in Science?
It s about economics and specifically styles of development economics, nevertheless the general questions of methodology connect with social sciences more broadly.
It is inside a way unfortunate that for most of us the style of a successful field of scientific endeavor is basic physics. The objective on the most basic physics can be a complete description products happens. In principle and apparently used, quantum mechanics provides for a complete account of the goes on inside, say, a hydrogen atom. But most things we would like to analyze, during physical science, can not be dealt with at this level of completeness. The only exact type of the global weather strategy is that system itself. Any style of that method is therefore to some extent a falsification: it leaves out some many areas of reality.
How, then, does the meteorological researcher decide things to put into his model? And how does he decide whether his model is really a good one? The answer to your first question could be that the choice of model represents a variety of judgement and compromise. The model has to be something you probably know how to make that may be, you're constrained because of your modeling techniques. And the model need to be something you are able to construct given your resources time, money, and patience are certainly not unlimited. There may be lots of models possible given those constraints; which or ones you end up picking actually to make depends on educated guessing.
And can you be sure that the model is a great one? It will not be right in the method that quantum electrodynamics is appropriate. At a certain point you may well be good enough at predicting your results may be used to repeated practical use, just like the giant weather-forecasting models that run on today s supercomputers; in this case predictive success might be measured with regards to dollars and cents, plus the improvement of models is a quantifiable matter. In the early stages of an complex science, however, the criterion to get a good model is much more subjective: it is really a good model whether it succeeds in explaining or rationalizing some of the you see from the world in a very way that you do not have expected.
There is fashionable nice description of an Dishpan model by David Fultz as an illustration showing a hyper-simplified model that illustrated some emergent properties great for meteorology.
What resonates with me at night about Krugman s description is often a common involvement in building the most convenient, descriptive models that people hope illuminate underlying principles in complex processes. In Economics, particularly Macro, the scientific goal is always to understand systems of unmanageable complexity interactions among each of the people and institutions that produce economic activity. In Neuroscience and Psychology, we seek to understand the mental faculties, fashionable system of unmanageable complexity.
I also prefer simple models having a small number of parameters as an instance concepts, while wearing a lots of admiration and respect for modelers who take about the complexity to build up from individual neurons each themselves having nearly unmanageable complexity, fwiw. The simple models also is not right inside same sense Krugman describes above, nevertheless they can are the cause of some useful fraction with the variance we try and explain and hopefully expose some deeper principles which may even eventually direct neural-level modeling.
There s a fantastic question within the other end in the complexity spectrum too, about why it can be worth even building simple models having a few parameters past simply making theoretical statements like changing x results in a change in y. Such theoretical statements will be the bread and butter of normal approaches to Psychological Science, especially experimental work, but I ll leave the solution as a fitness, perhaps to get tackled during my graduate seminar the very next time I teach modeling hints: quantification and prediction are essential.
Memory Systems, Intuition and Modeling
Multiple postdoctoral openings now available on two new projects aimed towards accelerating expertise development from training using memory systems theory. One project will build up methods to help the use of intuition in making decisions. The second project makes use of targeted memory reactivation to improve consolidation processes and speed learning. Both projects reflect collaborative research between laboratories of Professor Paul Reber and Professor Ken Paller /. Also see for more information about the local cognitive neuroscience environment.
We are trying to find postdoctoral candidates using a strong curiosity about human memory research along with expertise in several of the following areas: memory systems research, experimental behavioral methods, computational simulation modeling, multivariate pattern analysis, EEG recording and analysis.
Interested candidates can send inquiries and application materials to Susan Florczak. Applications are going to be evaluated when received and hiring decisions made on the rolling basis. Multiple two-year appointments are available today. Applications ought to include a cover letter, CV, and names with a minimum of three references.
We are looking to engage a new Research Assistant for your lab. Applications for that RA position moves through NU Human Resources.
I got another request to discuss yet another media state that technology is detrimental for our brains. It s actually additionally a good instance of really poor science reporting on tv, so I won t link it, however the topic seems generally interesting and it is apparently based over a curious underlying folk style of cognition worth contemplating.
How would this work? How could technology make us less smart? The core idea is the fact be looking things up, we memorize less and for that reason we are less smart than we will be otherwise. But this misses the situation of substitution. If you aren t memorizing something you'll be able to look up, would you learn another thing instead?
To me, the interesting underlying idea is: Memory doesn t come with an off switch
We are constantly recording experiences from your environment. Of course, not everything gets remembered, so maybe we focus too much for the memory failures. But we aren t consciously turning our memories don / doff through the day. So if we're also trying to memorize arbitrary facts that individuals could lookup on google instead, during that time we aren t doing another thing that could have gone a useful memory trace. Note that I m describing this just as one attention/perception bottleneck, nevertheless it could certainly be a memory consolidation level bottleneck at the same time which is really the actual constraint that keeps us from remembering everything we all experience.
The only technique for this argument to actually make sense should be to have a strong theory that everything we may have memorized as an alternative to relying on google is a bit more valuable in our internal knowledge state than everything we learn instead. I think which is going to get a hard case to create. And it won t be about technology.
There s another way to generate a possible technology hurts the mind case according to skill learning/strengthening. If memory is often a skill that may be improved by intensive practice, then concentrated tries to memorize arbitrary information could theoretically allow you to better at remembering and also over time, you d just get smarter. But there is no evidence anywhere that long-term memory could be strengthened in this way and many everyone has tried to accomplish this.
Working memory looks to get trainable, however if anything, technology that produces you hold a matter in mind while setting up the keyphrases to look up is going to expand your WM in lieu of causing it to atrophy.
So no, technology will not be going to produce us less smart. It s almost certain for being overwhelmingly inside the other direction the access furnished by the internet to incredibly rich and diverse varieties of information means the standard knowledge content in the average brain in the 21st century is really a lot more versus the 20th and other prior time.
I was motivated to answer some questions coming from a middle school student conducting a research project on online games. Since I am thinking about the topic generally, I should probably learn how to answer these types of questions in an age-appropriate level. My attempt:
1. Do video gaming affect the brain? Do games affect the thought processes? Do video gaming damage the thinking part of the mind?
Yes, game titles can affect mental performance, like other things that you do plenty of. However, these changes can sometimes be to the better. There is recent evidence improvements in visuospatial attention how we see the world following computer game play. There may also be changes for your worse, like increasing aggression, but these usually are not yet well understood.
2. Can video gaming improve people s knowledge? Can they help people s grades advance in school? Or can they get bad grades?
Video games probably won t help you in class very much. They can lead to further problems in schoolwork when kids play way too many games and don t sustain homework and assignments. If you happen to be getting your homework done, doing offers won t hurt and might actually help somewhat.
3. Can video gaming make people lose time? With family and friends? Time outside?
If you spend a lot of time on games , nor make time for friends, family, proper exercise and sleep, then that may very likely lead to further problems.
4. Can game titles make people sick? Gain weight? Headaches or maybe a tumor?
Some people report dizziness and nausea upset stomach from games that provide you first person perspective. This is most likely related on the kind of motion sickness you may get when riding within a car. In rare cases, some individuals may react badly to flashing lights/sounds in games. In general, games won t cause you to sick. If you eat in a unhealthy way when playing videogames, that may lead to fat gain and other illnesses.
5. Can game titles make people hooked on what their mainly about? How do they do that? Why do people get addicted?
Gaming addiction just isn't well understood. Games aren t addictive the best way other things are just like cigarettes. However, you will discover certainly a number of people who have problems during 2 and 3 above. They seem to learn so much it messes up a great deal of other things in life. That looks as being similar to being addicted. It also will look like lots of other problems that teenagers often come across mood swings, depression, difficulty in pertaining to others. I do not think it truly is well known whether games could cause those problems or whether kids having those varieties of problems for another reason why sometimes like to play plenty of videogames.
Thank you quite definitely for your help.
As an exercise on the reader, explain wrong with his complaint that what the majority of people think of science is definitely the opposite of science.
Seems as being a topic we should be discussing in 205. I think it s the right degree of meta to get a class on experimental design.
Rapid learning of higher-order statistics in implicit sequence learning K. R. Thompson P. J. Reber Implicit learning involves extracting experienced regularities and statistical variation from your environment as a way to improve behavior. Because information about environmental structure is acquired outside awareness, it's challenging to determine the nature on the information that
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