The brain’s ability to preserve memories lies at the heart of our basic human experience. But how does the brain’s mechanism for memory make sure we remember the most significant events and not clog our minds with superfluous details?
According to a new study by Columbia University researchers, the brain plays back and prioritizes high-reward events for later retrieval and filters out the neutral, inconsequential events, retaining memories that will be useful to future decisions.
Published today in the journal Nature Communications, the findings offer new insights into the mechanisms of both memory and decision making.

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The brain’s ability to preserve memories lies at the heart of our basic human experience. But what is its mechanism to make sure we remember the most significant events and keep our minds free of superfluous details?
According to a new study by Columbia University researchers, the brain plays back and prioritizes high-reward events for later retrieval and filters out the neutral, inconsequential events, retaining only memories that are useful to future decisions.
Published on Nov. 20 in the journal Nature Communications, the findings offer new insights into the mechanisms of both memory and decision making.

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Choosing to forget something might take more mental effort than trying to remember it, researchers at The University of Texas at Austin discovered through neuroimaging.
These findings, published in the Journal of Neuroscience, suggest that in order to forget an unwanted experience, more attention should be focused on it. This surprising result extends prior research on intentional forgetting, which focused on reducing attention to the unwanted information through redirecting attention away from unwanted experiences or suppressing the memory's retrieval.

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The human brain has a region of cells responsible for linking sensory cues to actions and behaviors and cataloging the link as a memory. Cells that form these links have been deemed highly stable and fixed.
Now, the findings of a Harvard Medical School study challenge that model, revealing that the neurons responsible for such tasks may be less stable, yet more flexible than previously believed.
The results, published Aug. 17 in the journal Cell, cast doubt on the traditional notion that memory formation involves hardwiring information into the brain in a fixed and highly stable pattern.

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If you’ve had the pleasure of reading bedtime books to young children, you’ve observed one of the reasons why narratives are so compelling. During their childhood, my daughters wanted to hear the same book, Goodnight Moon, over and over: Even after dozens of readings, they continued to excitedly predict what would be on the next page and to take great pleasure in being right.
That childhood desire of children—wanting to hear books read aloud and repeatedly requesting those few they know well enough to predict—encompasses powerful brain drives that become memory enhancers.

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Why is it that you can remember the name of your childhood best friend that you haven’t seen in years yet easily forget the name of a person you just met a moment ago? In other words, why are some memories stable over decades, while others fade within minutes?
Using mouse models, Caltech researchers have now determined that strong, stable memories are encoded by “teams” of neurons all firing in synchrony, providing redundancy that enables these memories to persist over time. The research has implications for understanding how memory might be affected after brain damage, such as by strokes or Alzheimer’s disease.

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A new piece of a difficult puzzle -- the nature of memory -- fell into place this week with a hint at how brain cells change structure when they learn something.

Interactions between three moving parts -- a binding protein, a structural protein and calcium -- are part of the process by which electrical signals enter neural cells and remodel the molecular structures thought to enable cognition and the storage of memories.

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It began about a decade ago at Syracuse University, with a set of equations scrawled on a blackboard.  Marc Howard, a cognitive neuroscientist now at Boston University, and   Karthik Shankar, who was then one of his postdoctoral students, wanted to figure out a mathematical model of time processing: a neurologically computable function for representing the past, like a mental canvas onto which the brain could paint memories and perceptions. “Think about how the retina acts as a display that provides all kinds of visual information,” Howard said. “That’s what time is, for memory. And we want our theory to explain how that display works.”

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