Neurons can operate in reverse
eurekalert.org
Neurons can operate in reverse
1–10 of 33 posts
Re: Neurons can operate in reverse
#2I wonder if this will have applications to synthetic modeling of the neuron.
Re: Neurons can operate in reverse
#3I wonder if this will have applications to synthetic modeling of the neuron.
Indeed, it seems that some kind of 'backpropagation' does happen in the brain, in contrary to what was always believed. This might have impact on machine learning research.
Re: Neurons can operate in reverse
#4I wonder if this will have applications to synthetic modeling of the neuron.
Indeed, it seems that some kind of 'backpropagation' does happen in the brain, in contrary to what was always believed. This might have impact on machine learning research.
> contrary to what was always believed
This is the statement that always comes back to bite biologists. If it's "theoretically possible", biology is probably already doing it somewhere.
Re: Neurons can operate in reverse
#5I wonder if this will have applications to synthetic modeling of the neuron.
Indeed, it seems that some kind of 'backpropagation' does happen in the brain, in contrary to what was always believed. This might have impact on machine learning research.
It's always seemed intuitively surprising that there's no feedback mechanism within neurons to aid learning. What's the currently favoured mechanism for learning, neurons feeding back to previous neurons?
Re: Neurons can operate in reverse
#6I didn't think this was new... I remember hearing about this effect last year and having it attributed to Oligodendrocytes, I believe.
That said, it's a very important development, because until the last few years the glial cells have mostly been considered to be support cells (e.g. supplying nutrients to the neurons, removing waste products and dead cells, myelinating axons, etc.). But, now we know that they can affect the surrounding neurons and may play a role in things like learning and memory.
Re: Neurons can operate in reverse
#7I wonder if this will have applications to synthetic modeling of the neuron.
There have been recent discoveries about synapses as well. It turns out that synapses are pretty complex. Lots of single celled organisms seem to have pretty "smart" behavior for their size. It turns out a lot of that data processing happens around the cell membrane. These mechanisms are the evolutionary roots of synapses.
http://www.brainsciencepodcast.com/bsp/2008/12/6/surprising-...
Re: Neurons can operate in reverse
#8Anyone else immediately jump to PTSD when they read this?
Re: Neurons can operate in reverse
#9Earlier quoted context omitted.
Indeed, it seems that some kind of 'backpropagation' does happen in the brain, in contrary to what was always believed. This might have impact on machine learning research.
It's always seemed intuitively surprising that there's no feedback mechanism within neurons to aid learning. What's the currently favoured mechanism for learning, neurons feeding back to previous neurons?
There's no single mechanism in neuroscience to explain learning in general, because the current understanding is that "learning" is a very vague term that covers many types of adaptation, and each has its own mechanism.
I'm not familiar with any network-level mechanisms, but there are many local (synapse- or dendrite-level) ones. The one I'm most familiar with is spike-timing dependent plasticity (STDP) [1], which modifies the strength of a synapse based on the millisecond-level timing of action potentials. When cell A tends to fire just before cell B, and the two have synapses connecting them, then cell B will increase the strength of its synapses to A. The reverse is true too: if cell A tends to fire just after cell B, then the synapses will decrease in strength. This is a form of Hebbian learning [2].
[1]: http://en.wikipedia.org/wiki/Spike-timing-dependent_plastici...
Re: Neurons can operate in reverse
#10Earlier quoted context omitted.
Indeed, it seems that some kind of 'backpropagation' does happen in the brain, in contrary to what was always believed. This might have impact on machine learning research.
It's always seemed intuitively surprising that there's no feedback mechanism within neurons to aid learning. What's the currently favoured mechanism for learning, neurons feeding back to previous neurons?
Yes, recurrent connections are one of the mechanisms that could be responsible for learning. These are used to 'steer' front-end neurons, for example to focus on a certain feature.
There is also 'Hebbian learning', which means that the connections between neurons that fire at the same time become stronger.