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I ran across this url to Paul Krugman being insightful and thoughtful concerning the general question of What is often a Model and What do we use them commercially in Science? It s about economics and specifically kinds of development economics, even so the general questions of methodology affect social sciences more broadly. It is inside a
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 today on two new projects aimed towards accelerating expertise development from training using memory systems theory. One project will establish
I got another request to touch upon yet another media report that technology is detrimental for our brains. It s actually another good illustration showing really poor science reporting in media, so I won t link it, however the topic seems generally appealing and it seems to be based using a curious underlying folk
I was inspired to answer some questions coming from a middle school student carrying out a research project on video gaming. Since I am enthusiastic about the topic generally, I should probably understand how to answer most of these questions in an age-appropriate level. My attempt: Jose asks: 1. Do games affect the neural?
This is definitely an interesting piece around the philosophy of science and popular understandings of science: How our botched comprehension of science ruins everything /article/index/268360/how-our-botched-understanding-of-science-ruins-everything As an exercise to your reader, explain wrong with his complaint that what the majority of people think of science is really 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 mind
Investigating memory system interactions and intuitive selection using visual category learning.
Check the Presentations link within the right side bar to determine the most recent ideas and reports as presented as posters and talks at recent conferences.
I ran across this connection to Paul Krugman being insightful and thoughtful in regards to the general question of What is really a Model and What do we utilize them for in Science?
It s about economics and specifically kinds of development economics, nevertheless the general questions of methodology sign up for social sciences more broadly.
It is in a very way unfortunate that for many people of us the look of a successful field of scientific endeavor is basic physics. The objective on the most basic physics is usually a complete description of the items happens. In principle and apparently used, quantum mechanics provides a complete account of the items goes on inside, say, a hydrogen atom. But most things you want to analyze, even physical science, are not dealt with during this level of completeness. The only exact type of the global weather product is that system itself. Any style of that technique is therefore rather a falsification: it leaves out some many issues with reality.
How, then, does the meteorological researcher decide things to put into his model? And how does he decide whether his model is usually a good one? The answer on the first question would be that the choice of model represents a blend of judgement and compromise. The model has to be something you probably know how to make that is certainly, you might be constrained by the modeling techniques. And the model have to be something you may construct given your resources time, money, and patience are certainly not unlimited. There may be many models possible given those constraints; which or ones you select actually to develop depends on educated guessing.
And you ought to that the model is great? It will do not be right in the method that quantum electrodynamics is correct. At a certain point you might be good enough at predicting that your particular results can be used to repeated practical use, such as the giant weather-forecasting models that run on today s supercomputers; therefore predictive success could be measured with regard to dollars and cents, along with the improvement of models turns into a quantifiable matter. In the early stages of the complex science, however, the criterion for the good model is a bit more subjective: it can be a good model whether or not this succeeds in explaining or rationalizing some of the items you see from the world in the way that you may not have expected.
There is and a nice description of your Dishpan model by David Fultz as an illustration showing a hyper-simplified model that illustrated some emergent properties helpful for meteorology.
What resonates when camping about Krugman s description can be a common fascination with building the easiest, descriptive models that individuals hope illuminate underlying principles in complex processes. In Economics, particularly Macro, the scientific goal should be to understand systems of unmanageable complexity interactions among every one of the people and institutions that produce economic activity. In Neuroscience and Psychology, we try to understand the brain, and a system of unmanageable complexity.
I also prefer simple models using a small few parameters for example concepts, while using a lots of admiration and respect for modelers who take within the complexity to construct up from individual neurons each themselves having nearly unmanageable complexity, fwiw. The simple models also can't be right inside same sense Krugman describes above, but they also can be the cause of some useful fraction with the variance we make an effort to explain and hopefully expose some deeper principles that will even eventually direct neural-level modeling.
There s a fantastic question for the other end from the complexity spectrum likewise, about why it can be worth even building simple models that has a few parameters past simply making theoretical statements like changing x leads to a change in y. Such theoretical statements include the bread and butter of normal approaches to Psychological Science, especially experimental work, but I ll leave the solution as a workout, perhaps for being tackled inside 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 geared towards accelerating expertise development from training using memory systems theory. One project will establish methods to improve use of intuition in making decisions. The second project make use of targeted memory reactivation to reinforce consolidation processes and speed learning. Both projects reflect collaborative research between your laboratories of Professor Paul Reber and Professor Ken Paller /. Also see for more information about the local cognitive neuroscience environment.
We are searhing for postdoctoral candidates using a strong desire for human memory research with expertise in a few 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 is going to be evaluated when received and hiring decisions made using a rolling basis. Multiple two-year appointments are available today. Applications includes a cover letter, CV, and names for a minimum of three references.
We can also be looking to work with a new Research Assistant with the lab. Applications to the RA position moves through NU Human Resources.
I got another request to discuss yet another media declare that technology is not good for our brains. It s actually fashionable good demonstration of really poor science reporting in the news, so I won t link it, however the topic seems generally appealing and it definitely seems to be based with a curious underlying folk type of cognition worth planning on.
How would this work? How could technology make us less smart? The core idea is always that be looking things up, we memorize less and thus we are less smart than we can easily be otherwise. But this misses the situation of substitution. If you aren t memorizing something you are able to look up, does one 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 environment. Of course, not everything gets remembered, so maybe we focus too much about the memory failures. But we aren t consciously turning our memories on / off through the day. So if were trying to memorize arbitrary facts that people could lookup on google instead, during that time we aren t doing something different that could have remaining a useful memory trace. Note that I m describing this for an attention/perception bottleneck, nonetheless it could certainly be a memory consolidation level bottleneck likewise which is possibly the actual constraint that keeps us from remembering everything we go through.
The best way for this argument to completely make sense would be to have a strong theory that everything we'd 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 that is certainly going to become a hard case to generate. And it won t sometimes be about technology.
There s another way to create a possible technology hurts your brain case determined by skill learning/strengthening. If memory is often a skill that could be improved by intensive practice, then concentrated efforts to memorize arbitrary information could theoretically allow you to be better at remembering well as over time, you d just get smarter. But there is no evidence anywhere that long-term memory may be strengthened in this way and many folk have tried to make this happen.
Working memory looks to become trainable, however if anything, technology that produces you hold a matter in mind while adding the search words to look up is going to expand your WM instead of causing it to atrophy.
So no, technology just isn't going for making us less smart. It s almost certain for being overwhelmingly inside other direction the access given by the internet to incredibly rich and diverse forms of information means the standard knowledge content from the average brain in the 21st century can be a lot more compared to 20th or another prior time.
I was motivated to answer some questions from the middle school student doing research project on online games. Since I am serious about the topic generally, I should probably discover how to answer such questions with an age-appropriate level. My attempt:
1. Do games affect the mind? Do games affect the thought process? Do video gaming damage the thinking part of as their pharmicudical counterpart?
Yes, game titles can affect the human brain, like whatever else that you do lots of. However, these changes can sometimes be with the better. There is recent evidence improvements in visuospatial attention the way you see the world following computer game play. There may also be changes for that worse, like increasing aggression, but these usually are not yet well understood.
2. Can games improve people s knowledge? Can they help people s grades improve in school? Or can they get bad grades?
Video games probably won t help you in class very much. They can make trouble in schoolwork when kids play a great number of games and don t sustain homework and assignments. If you're getting your homework done, doing offers won t hurt and could actually help slightly.
3. Can online games make people lose time? With family? Time outside?
If you spend an excessive amount time on games and never make time for friends, family, proper exercise and sleep, then that can very likely lead to further problems.
4. Can game titles make people sick? Gain weight? Headaches or perhaps a tumor?
Some people report dizziness and nausea upset stomach from games giving you first person perspective. This is more than likely related towards the kind of motion sickness you may get when riding in the car. In rare cases, a lot of people may react badly to flashing lights/sounds in video gaming. In general, games won t cause you to be sick. If you eat in the unhealthy way when playing videogames, that could lead to extra weight and other health conditions.
5. Can game titles make people dependent on what their mainly about? How do they do that? Why do people get addicted?
Gaming addiction is just not well understood. Games aren t addictive just how other things can be like cigarettes. However, you can find certainly a number of people who have problems as with 2 and 3 above. They seem to learn so much so it messes up a great deal of other things later on in life. That looks much like being addicted. It also look like lots of other problems that teenagers often come across mood swings, depression, difficulty in pertaining to others. I do not think it really is well known whether games could cause those problems or whether kids having those sorts of problems for one more reason sometimes like to play lots of videogames.
Thank you a lot for your help.
As an exercise towards the reader, explain what's incorrect with his complaint that what the majority of people think of science is definitely the opposite of science.
Seems being a topic we should be discussing in 205. I think it s the right amount of meta for any 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 can be challenging to determine the nature with the information that
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