Saturday, June 26, 2021

Tuning Into the Brain

Oscillations as a mechanism of binding, routing, and selection of thoughts.

The brain is plastic, always wiring and rewiring its neurons, even generating new neurons in some areas. But this plasticity does not come near the speed and scale needed to manage brain function at the speed of thought. At that perspective and scale, our brains are static lumps, which somehow manage to dynamically assemble thoughts, visions, impressions, actions, and so much more as we go about our frenetic lives. It has gradually become clear that neural oscillations, or electrical brain waves, which are such a prominent feature of active brains, serve centrally to facilitate this dynamic organization, joining up some areas via synchrony for focused communication, while leaving others in the dark- unattended and waiting for their turn in the spotlight. 

The physical anatomy of the brain is obviously critical to organizing all the possible patterns of neural activity, from the most unconscious primary areas of processing and instinct to whatever it is that constitutes consciousness. But that anatomy is relatively static, so a problem is- how do some brain areas take precedence for some thoughts and activities, while others take over during other times? We know that, very roughly, the whole brain tends to be active most of the time, with only slight upticks during intensive processing, as seen in the induced blood flow detected by methods such as fMRI. How are areas needed for some particular thought brought into a dynamic coalition, which is soon after dissolved with the next thought? And how do such coalitions contribute to information flow, and ultimately, thought?

Oscillations seem to provide much of this selectivity, and the last decade of research has brought an increasingly detailed appreciation of its role in particular areas, and of its broad applicability to dynamic selection and binding issues generally. A recent paper describes a bunch of simulations and related analytical work on one aspect of this issue- how oscillations work at a distance, when there is an inevitable lag in communication between two areas. 

Originally, theories of neural oscillation just assumed synchrony and did not bother too much with spatial or time delay separations. Synchrony clearly offers the opportunity of activating one area of the brain based on the activity of a separate driving area. For instance, primary visual areas might synchronize rhythmically with downstream areas and thus drive their processing of a sequence of signals, thus generating higher level activations in turn that ultimately constitute visual consciousness. Adding in spatial considerations increases complexity, since various areas of the brain exist at widely different separations, potentially making a jumble of the original idea. But on the other hand, feedback is a common, even universal, phenomenon in the brain, and requires some amount of delay to make any sense. Feedback needs to be (and anatomically must be) offset in time to avoid instant shut-down or freezing. 

Perhaps one aspect of anatomical development is to tune the brain so that certain coalitions can form with useful sequentially delays, while others can not, setting in the anatomical concrete a certain time-delay characteristic for each anatomically connected group. Indeed, it is known that myelination- the process of white matter development during childhood and early adulthood- speeds up axonal conduction, thus greatly altering the delay characteristics of the brain. Keeping these delays tuned to produce usable coalitions for thought could be a significant hurdle as this development proceeds, and explain some of the deep alterations of cognition that accompany it. The opportunity to assemble more wide-ranging coalitions of entrained neurons is obviously beneficial to complex thought, but just how flexible are such relations? Could the speeding up of one possible coalition destroy a range of others?

The current paper simply makes the case that delays are perfectly conducive to oscillatory entrainment, and also that regions with higher frequencies tend to more effectively drive downstream areas with slightly lower intrinsic frequencies, though other relationships can also exist. Both phenomena contribute to assymmetric information flow, from one area to the next, given oscillatory entrainment. The computer simulations the authors set up were relatively simple- populations of a hundred neurons with some inhibitory and most excitatory, all behaving as closely as possible to natural neurons, modestly inter-connected, with some connections to another second similar population, and each given certain stable or oscillatory inputs. Each population showed a natural oscillation, given normal behavior of neurons (with inhibitory feedback) and a near-white noise input baseline that they injected for each population. On top of that, they injected oscillatory inputs as needed to drive each population's oscillations to perform the experiment, at particular frequencies and phases.


The authors manipulated the phase delay between the two populations (small delta), and also manipulated the frequency mismatch between them (called de-tuning, big delta). This led to a graph like shown above, where each has its own axis and leads to a regimes (red) of high entrainment (B) and information transfer (C). The degree of entrainment is apparent in the graphs in D, taken from the respective black points in B, with the driver population in red, the receiver population in blue, as diagramed in A. In this case, practically all the points are in red zones, and thus show substantial entrainment.

While this simulation method appears quite powerful, the paper was not well-written enough, and the experiments not clear enough, to make larger points out of this work. It is one small piece of a larger movement to pin down the capabilities and exact nature and role of neural oscillations in the brain- a role that has been tantalizing for a century, and is at last starting to be appreciated as central to cognition.

Based on the following articles: