brain model

My mouth hasn’t shut up about you since you kissed it. The idea that you may kiss it again is stuck in my brain, which hasn’t stopped thinking about you since well before any kiss.
—  Alex Turner (Love Letter to Alexa Chung)
A team of neuroscientists at John Hopkins University has found that within the first 5 or 6 hours of practicing a new motor skill, the brain shifts the new instructions from short term memory to the areas responsible for permanent motor skills. As subjects initially learned a task, the prefrontal cortex - involved in short- term memory and many kids of learning - was relatively active. When the subjects returned 51/2 hours later, they had no trouble retracing the movements. But at that point, the premotor cortex, the posterior parietal cortex, and the cerebellum - regions that control movements - had taken over. During the intermission, it seems, the neural links that form the brain’s internal model of the task had shifted from the prefrontal region to the motor control region. Even without practice, after 5 or 6 hours the formula for the task was virtually hard-wired into the brain. This suggest that a newly learned skill could be impaired, confused, or even lost if a person tried to learn a different motor task during the critical 5-to-6 hour period, when the brain is trying to stabilize the neural representation and retention of the original task.
—  John J. Ratey, M.D., A User’s Guide to the Brain: Perception, Attention, and the Four Theaters of the Brain. 
Balancing Time and Space in the Brain: A New Model Holds Promise for Predicting Brain Dynamics

For as long as scientists have been listening in on the activity of the brain, they have been trying to understand the source of its noisy, apparently random, activity. In the past 20 years, “balanced network theory” has emerged to explain this apparent randomness through a balance of excitation and inhibition in recurrently coupled networks of neurons. A team of scientists has extended the balanced model to provide deep and testable predictions linking brain circuits to brain activity.

Lead investigators at the University of Pittsburgh say the new model accurately explains experimental findings about the highly variable responses of neurons in the brains of living animals. On Oct. 31, their paper, “The spatial structure of correlated neuronal variability,” was published online by the journal Nature Neuroscience.

The new model provides a much richer understanding of how activity is coordinated between neurons in neural circuits. The model could be used in the future to discover neural “signatures” that predict brain activity associated with learning or disease, say the investigators.

“Normally, brain activity appears highly random and variable most of the time, which looks like a weird way to compute,” said Brent Doiron, associate professor of mathematics at Pitt, senior author on the paper, and a member of the University of Pittsburgh Brain Institute (UPBI). “To understand the mechanics of neural computation, you need to know how the dynamics of a neuronal network depends on the network’s architecture, and this latest research brings us significantly closer to achieving this goal.”

Earlier versions of the balanced network theory captured how the timing and frequency of inputs—excitatory and inhibitory—shaped the emergence of variability in neural behavior, but these models used shortcuts that were biologically unrealistic, according to Doiron.

“The original balanced model ignored the spatial dependence of wiring in the brain, but it has long been known that neuron pairs that are near one another have a higher likelihood of connecting than pairs that are separated by larger distances. Earlier models produced unrealistic behavior—either completely random activity that was unlike the brain or completely synchronized neural behavior, such as you would see in a deep seizure. You could produce nothing in between.”

In the context of this balance, neurons are in a constant state of tension. According to co-author Matthew Smith, assistant professor of ophthalmology at Pitt and a member of UPBI, “It’s like balancing on one foot on your toes. If there are small overcorrections, the result is big fluctuations in neural firing, or communication.”

The new model accounts for temporal and spatial characteristics of neural networks and the correlations in the activity between neurons—whether firing in one neuron is correlated with firing in another. The model is such a substantial improvement that the scientists could use it to predict the behavior of living neurons examined in the area of the brain that processes the visual world.

After developing the model, the scientists examined data from the living visual cortex and found that their model accurately predicted the behavior of neurons based on how far apart they were. The activity of nearby neuron pairs was strongly correlated. At an intermediate distance, pairs of neurons were anticorrelated (When one responded more, the other responded less.), and at greater distances still they were independent.

“This model will help us to better understand how the brain computes information because it’s a big step forward in describing how network structure determines network variability,” said Doiron. “Any serious theory of brain computation must take into account the noise in the code. A shift in neuronal variability accompanies important cognitive functions, such as attention and learning, as well as being a signature of devastating pathologies like Parkinson’s disease and epilepsy.”

While the scientists examined the visual cortex, they believe their model could be used to predict activity in other parts of the brain, such as areas that process auditory or olfactory cues, for example. And they believe that the model generalizes to the brains of all mammals. In fact, the team found that a neural signature predicted by their model appeared in the visual cortex of living mice studied by another team of investigators.

“A hallmark of the computational approach that Doiron and Smith are taking is that its goal is to infer general principles of brain function that can be broadly applied to many scenarios. Remarkably, we still don’t have things like the laws of gravity for understanding the brain, but this is an important step for providing good theories in neuroscience that will allow us to make sense of the explosion of new experimental data that can now be collected,” said Nathan Urban, associate director of UPBI.


50s/grease AU!!!

kayo leads the pink ladies, and is renowned for being the literal toughest girl around. she started her gang as more of a protection against harassment squad than anything else. then theres marion, who used to have a bit of a thing with scott but now she’s sweet on moffie, the nicer one of the group. rich-bitch penny is the last member of the pink ladies. her parents disapprove of her choice of friends, but she’s loyal to her girl gang.

brains is the new kid, come over from england with his adoptive father. despite being absolutely terrified of the thought, he enrolls in the school and is taken in by the pink ladies. he might not be a girl, but if kayo’s not looking out for him, then he’ll be squashed like a bug on the windshield of the tracy boys’ cars.

the tracy brothers make up the t-birds. they’re the sons of the late jeff tracy, and work in his auto shop, building and repairing cars. they all have big dreams that they can’t really make happen in their small town, making them all a bit rebellious.

scott, the eldest, is a few years out of high school and goes to community college to try and get himself educated for a better job and finally get them all out of their hick town. john balances the checkbooks and makes sure the business stays afloat. virgil, is a high school senior and is thoroughly in his rebellious phase, gets caught up in a lot of drag races in and out of school hours. both gordon and alan think he’s really cool and are always begging to let them go with him, but he insists they stay behind.

the pink ladies and the t-birds are close knit gangs, especially given that kayo had been adopted by jeff before he passed away. aaaand, that’s all i got!

this was really just an excuse to draw clothes, lets be real.


Looks n Books 😍

anonymous asked:

*gives yugi and yami sea salt ice cream (there is a sea salt ice cream model,forgot who made it tho)* its called sea salt ice cream,it has a balanced taste of salty and sweet

Yugi: Woah! This is really tasty!

Yami: Aibou, don’t bite your ice cream. You’ll get brain freeze…

Yugi: WAWAWA! *brain freeze*

Yami: -v-);

(Model credits: x)