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Endogenous Electric Fields May Guide Neocortical Network Activity

(Note: this is a repost of my original post from 2010 Jul. I'm reposting some old posts to work within the ResearchBlogging.org framework.)

I’ve been geeking out about this paper for a week or so now, so I just finally decided to put together a post about it to explain why I think it’s so awesome.

I’ve been thinking about the foundations of electrophysiological research in neuroscience. The earliest experiments on the electrical properties of neurons were performed on giant squid axons because the axons in these animals are quite large and thus easy to record from. That is, the axons are visible to the naked eye, which means they’re very easy to insert recording electrodes into. From the earliest (Nobel Prize winning experiments) by Hodgkin and Huxley in the 1930s and 40s it was shown that neurons communicate via the transmission of electrical “all or none” action potentials. Decades of biochemistry and electrophysiology in the intervening years have shed a lot of light on the biological and biophysical mechanisms that give rise to these action potentials.

Of course, one of the major outstanding questions in neuroscience is how do you go from millions of individual neurons firing these rapid, near-impulse electrical potentials to a unified behavioral and cognitive experience?

Over the last decade there has been an explosion in the role that endogenous, electrophysiological oscillations play in cognition. To unpack that a little bit, back in the 1920s Hans Berger (about whom I need to write a whole post) found that if you use sensitive recording electrodes attached to the scalp, you can pick up the electrical activity of the brain. As an aside, interestingly these first experiments were performed on patients with small holes in their skulls because the electrical signals were better. I conducted an entire experiment just looking at this phenomenon. Again, decades of research have shown that these electrical fields probably represent the summed activity of millions of synaptic electrical potentials. That is, in order for an action potential to fire, ion channels open in each neuron changing the flow of electrical charge into and out of the cell. Millions of these charges sum together (it’s complicated) and these summed charges can be picked up using EEG.

With EEG (either on the head, outside the skull, or implanted inside the skull onto the brain), really clear oscillations can be observed. In fact, these oscillations are so obvious, that Hans Berger noticed them early on.

Hans Berger EEG

It turns out that the amplitude of these oscillations is modulated by cognitive tasks. Sometimes they oscillate faster or stronger, sometimes slower or weaker. Using math (and science!) we can easily show that different parts of the brain seem to have “preferred” oscillations. No one is sure why. Using even more math, my friend and colleague Ryan Canolty (among others) showed that when slow oscillations are at their lowest points, you’re more likely to see an increase in neuronal activity. I’ve got a paper coming out soon (that I’ll surely write about here) showing that this effect depends on the frequency and location in the brain of the slow oscillation, as well as what the person is doing.

Anyway, it’s often interpreted that the slow oscillation represents the extracellular membrane potential. That is, the space in between neurons has a charge, and if this charge is a little lower (the trough of the slow oscillation) then neurons are more likely to fire (more activity). If the charge is larger (the peak) then neurons are less likely to fire (less activity).

So what’s really been twisting my noodle is that maybe this interpretation is wrong. Maybe across millions of years of divergent evolution, the axon of a giant squid has evolved to perform computations necessary for the survival of giant squids, and maybe mammalian neurons have evolved somewhat differently. Maybe individual action potentials are important in humans, but maybe they’re not the only things doing “computing” in the brain. Maybe these oscillations are also playing an important computational role. Maybe they’re not just epiphenomena of action potentials. But maybe there’s a complex feedback system between action potentials and oscillations.

And that’s just what Flavio Fröhlich and David McCormick have shown. And that’s why this paper is awesome. I’m pretty sure that the more research that’s done on this topic, the more it will be shown that oscillations are pretty key players in this whole consciousness and cognition thing.

Fröhlich F, & McCormick DA (2010). Endogenous electric fields may guide neocortical network activity. Neuron, 67 (1), 129-43 PMID: 20624597


  1. So we already know that external EFs effect neuronal firing, from all the TMS and DC studies right? I suppose its obvious that endogenous EFs would affect neuronal firing as well, but its good to have some evidence that this is in fact the case, and as the authors suggest, it means that positive and negative feedback loops are possible between the EFs and the neuronal columns.

    Could this also be a way to explain how the neurons fire in sync to produce the specific freq brain waves you EEG guys measure? How about as a solution to the Binding Problem?

    I've always wondered how neurons synchronize across large cortical areas (like several cm of brain tissue) as, fast though the spiking is, action potentials have a limited speed, and then there's a synapse between each one (although synaptic transmission is fast too).

    What do you think the implications of this study are Brad? You can speculate a little more as its your blog rather than a paper!

  2. Well, TMS just blasts a cortical region, inducing action potentials. These EFs are subthreshold, but still affecting the probability of action potentials.

    As for that I think it means, I speculate a bit at the end of this paper:

    "We propose that fluctuations in the local and global extracellular membrane potential bias the statistics of local neuronal firing rates, analogous to Up and Down states, which can influence cortical processing (Holcman and Tsodyks, 2006; Frölich and McCormick, 2010). These low-frequency fluctuations would coordinate multiple brain regions and allow for parallel processing by overlapping neuronal networks with the distributed pattern of low-frequency phase regulating information flow within and between networks (Engel et al., 2001; Sejnowski and Paulsen, 2006) acting as a type of switch or router."

    My friend Ryan showed that this low-frequency extracellular phase coordination biases neuronal spiking even at long distances: