This week I'm trying out a new hack, using the flashcard program Mnemosyne, which I found at the end of a blog trail. Mnemosyne's flashcards come with a twist, which emphasizes how people create long-term memories. People learn best when they are repeatedly exposed to a subject over the course of days and weeks, rather than crammed into a few hours or one day. This phenomena is called spaced learning.
Rather than showing you random flashcards, Mnemosyne utilizes spaced learning by scheduling flashcards for you over a period of days and weeks. Whenever you see a flashcard, you rate how well you know it from 0-5. If you remember the card well (e.g. rating 4-5), Mnemosyne will not show you the card again for weeks. However, if you remember it poorly (e.g. 1-2), Mnemosyne will schedule for a few days later; just before you forget it. In that way, you're constantly reinforcing tenuous knowledge.
To give the program a spin, I downloaded some vocabulary flashcards for French, and hiragana/katakana flashcards for Japanese. It's only been a few days, but it seems to work well.
Then I started thinking about how this could be applied to science. You could create flashcards for signaling cascades, which certainly have a lot of connections to remember. As a systems neuroscientist, I could create cards for anatomical connections, but few of those are relevant at any given time.
One thing that's frustrated me as I learn a new literature is the patchwork nature of my memory for papers. For example, I know T1R# receptors are responsible for sweet, and umami taste, but I can't recall whether they share the T1R1, T1R2, or T1R3 receptors. I just google it. Yet I can name
I've tried to reinforce my paper memory by always taking notes on them in Mendeley. And I write the Walk Along the Paper Trail series in part to make me remember the papers I write about. But these efforts don't cover nearly enough papers, nor do they contain the repeated, spaced learning that works well.
I've started to build a Mnemosyne database of papers. On one "side," I write the first and last authors of the paper and the year. The other side contains the methods, and key findings. Hopefully by doing this I can refer to papers by name, instead of calling them things like, "That Carlson lab paper where they invented the empty neuron system." After a few days use, I can remember ~15 papers by name, lab, date, and key findings.
The downside of this memory is that is rote, ignoring connections between papers, and serious analyses of them. But I think that is an issue best resolved via other methods.
*Ok, I'll try: Sandy Alomar, Jim Thome, (2nd base is killing me, Tony Fernandez? [yes]), Omar Vizquel, Matt Williams, David Justice, Marquis Grissom, Manny Ramirez, Chad Ogea, Paul Nagy,