Tag Archives: connectivity

Connectivity is not one idea

Sebastian Seung sold the idea that “we are our connectome”. What does that mean? Connectivity is a problem to me. Of course, the brain works only because there are connections between cells and between larger parts of the brain. But how can we measure and map it. Apparently there are measurement problems.

When some research says that A is connected to B it can mean a number of things. A could be a sizable area of the brain that has a largish nerve tract to B. This means that some neurons in A have axons that extend all the way to B, and some neurons in B have synapses with each of those axons. We could be talking about smaller and smaller groups of neurons until we have a pair of connected neurons. This is anatomy – it does not tell us when and how the connections are active or what they accomplish, just that a possible path is visible.

On the other hand A and B may share information. A and B are active at the same time in some circumstance. They are receiving the same information, either one from the other, or both from some other source. Quite often this means they are synchronized in their activity; it is locked together in a rhythm. Or they may react differently but always to the same type of information. Or one may feed the other information (directly or indirectly). A and B need only be connected when they are involved in the function that gives them shared information. Here we see the informational connection but necessarily the path.

A and B may be connected by a known causal link. A makes B active. Whenever A is active it causes B to be active too. This causal link gives no automatic information about path or even, at times, what information may be shared.

On a very small scale cells that are close together can be connected by contacts with glial cells, local voltage potentials and chemical gradients. Here the connections are even more difficult to map.

And finally overall there are control mechanisms that switch on and off various connection routes.

The whole brain is somewhat plastic and so can change its connectivity structure over time to better serve the needs of the individual. When it comes down to it, the connectivity that makes us each unique, the results of learning and memory, is the most plastic. It is changing all the time and can be very hard to map.

Saying “connectome” without any detailed specification is next to meaningless and “we are our connectome” is certainly true but somewhat vacuous.

A recent paper (citation below) took 4 common ways of measuring connectivity and compared them pair-wise. None of the pairs had a high level of agreement and some pairs had hardly any. There may be a lot of reasons for this but a big one has to be that the various methods were not measuring the same thing. In general, authors say that they are measuring, by what method and why. These nuances occasional do not make it to the abstract or conclusion, often never make it to the press release, and nearly never to news articles.

Here is the abstract and a diagram from the Jones paper.

connectionpairsMeasures of brain connectivity are currently subject to intense scientific and clinical interest. Multiple measures are available, each with advantages and disadvantages. Here, we study epilepsy patients with intracranial electrodes, and compare four different measures of connectivity. Perhaps the most direct measure derives from intracranial electrodes; however, this is invasive and spatial coverage is incomplete. These electrodes can be actively stimulated to trigger electrophysical responses to provide the first measure of connectivity. A second measure is the recent development of simultaneous BOLD fMRI and intracranial electrode stimulation. The resulting BOLD maps form a measure of effective connectivity. A third measure uses low frequency BOLD fluctuations measured by MRI, with functional connectivity defined as the temporal correlation coefficient between their BOLD waveforms. A fourth measure is structural, derived from diffusion MRI, with connectivity defined as an integrated diffusivity measure along a connecting pathway. This method addresses the difficult requirement to measure connectivity between any two points in the brain, reflecting the relatively arbitrary location of the surgical placement of intracranial electrodes. Using a group of eight epilepsy patients with intracranial electrodes, the connectivity from one method is compared to another method using all paired data points that are in common, yielding an overall correlation coefficient. This method is performed for all six paired-comparisons between the four methods. While these show statistically significant correlations, the magnitudes of the correlation are relatively modest (r2 between 0.20 and 0.001). In summary, there are many pairs of points in the brain that correlate well using one measure yet correlate poorly using another measure. These experimental findings present a complicated picture regarding the measure or meaning of brain connectivity.”
ResearchBlogging.org

Jones, S., Beall, E., Najm, I., Sakaie, K., Phillips, M., Zhang, M., & Gonzalez-Martinez, J. (2014). Low Consistency of Four Brain Connectivity Measures Derived from Intracranial Electrode Measurements Frontiers in Neurology, 5 DOI: 10.3389/fneur.2014.00272

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