When giving a description of his working materials to The McGill Tribune in January 2017, Dr Randy McIntosh* said:
“[The brain] is a very complex system. Complex systems tend to operate as a network… in order to understand them, we actually have to really capture the network dynamics”.
Introducing a network.
I’d like to entertain for you the image of a collection of interconnected things, changing in space and in their relationship to one another upon response to a continuous instance of impressions. We’ll then watch how this collection unfolds, gathering the rules by which they play by. Things become described as nodes, and we’ll introduce an assumption: We’ll say that these instances that effect the relationship between these nodes are moments of information that sculpt the structure we’re imagining. In effect, we could say that the sum of all parts of this network you’ve just imagined is a dynamical model of the very world in which it is embedded. A delicate control of the instability of this imagined constellation, which we can now proceed to think of as a neural ensemble, helps us to generate the ever-unfolding world around us. Such imaginings take the lowest course through a contemporary view of the brain’s architecture.
As a dingy would against the barge of tanker, I’ve been thumped of late in the wake of bulky theories. Visuals are useful. Even before studying neuroscience, I would have insisted on so. If there was a problem at hand that required more than eight fingers and two thumbs, it could be off-loaded onto an imagined visual scene. But consider visualizing a brain at work! Although we should remain ever cautious of our claims to understand this organ of secrets, the amount of data now gathered of the brain at various stages of performance has fed an undertaking poised to recast the laboratory. In its reach is the enhancement of our treatment of the classical network disorder epilepsy, of furthering the capabilities of transcranial magnetic stimulation (TMS), and I’ll tentatively claim here too, that such a development could very well give grace to the future of psychotherapeutics. I will explore this shortly, but first, I must introduce you.
The Virtual Brain (TVB) is an open-source software package that simulates global brain behaviour, and as a crucial point, is adapted to the brain of any given individual applied to with a high degree of fidelity to the wet, organic thing. In integrating brain network dynamics it generates an impressive visual model, evoking the connectome, and it could very well be a game changer.
In the spring-time of its utility, TVB has already drawn considerable attention. This was evident at the 6th annual meeting on the TVB project at Berlin’s Charité in late February, and I found myself thinking not such a foolish thing that, as we close on the second decade of the twentieth century, we could be witnessing the birth of a dynamic systems medicine.
It’s an exciting prospect. In feed-forwarding data taken from the neural activity of patients, specialists could feasibly simulate an image of something close to that very brain in neurodegenerative decline, vis-à-vis Alzheimer’s disease or Multiple Sclerosis, or a picture of the post-ischemic neural ensemble in stroke. The advantage of this would lie in the ability to predict the effect of surgery, or perhaps even rescue function by guided interference of rogue brain activity. Discordant network dynamic may lie at the heart of chronic, debilitating psychological states or symptoms (psychosis, depression), which a virtual simulation tool may be particularly well suited to explore. With the rise of the use TMS in the treatment of resistant depression, TVB could support a treatment approach tailored to interact with the patient at the level of their very own brain activity, providing clinicians with robust models for individualised medicine. In speaking with one researcher on the crest of this movement, the idea of arresting or augmenting neural activity in such a way may not be beyond the boundary of possibilities.
II. Phenomenology: An inflection beyond the verge of ‘I’.
Say we were to unpack the recovering process of an individual who, emerging from a long stay of depression is met with the impression that something has been regained. Fresh, now and feeling once again capable, the individual steps into the morning of which they are more or less an agent of, impressed with their dictating of a day in which is once again rooted within the subtleties of their own motion. What that something is might avoid the classification of language – a sea change that may very well be resigned to the individual – but taking a leaf of insight from contemporary brain network research, we might just arrive at some clue as to the nature of that which unfolds upon the mind dis-eased. Here, brain network simulation is poised to aid a novel approach.
III. On Technological Advance.
TVB developed in answering a technical conundrum, which goes as follows: Neuroscientists have two powerful tools when measuring macroscopic brain activity; EEG/MEG and fMRI. That being said, neither tool is sufficient when describing global, structure-function relationships. Both are, roughly speaking, negative reflections of each other’s strengths: EEG, although superior of the two in terms of temporal resolution (the ‘when’ of activity) is burdened by low spatial correlation (the ‘where’ of activity), with the inverse being true for fMRI. Coupling the strengths of both has been of focus for scientists who, probing the broad repertoire of brain network dynamics, hope to meet this complex system upon the sheath of their lens. But, how? With the use of real anatomical evidence and integrating biologically realistic diffusion tensor imagining (DTI) with theories that describe patterns of neural activity, the architects of TVB, through sleepless diligence have furthered the development of an efficient, flexible, neuroinformatics platform capable of answering just the very issue.
TVB charts a contour of svelte ingenuity. As often is the case of innovative leaps, the idea is supposed to have appeared one evening over a cold, cerebral pint between two main-players in busy field of network neuroscience, Dr Viktor Jirsa (Director of the Institute de Neurosciences des Systèmes, and Director of Research at the CNRS, Marseille) and Dr Randy McIntosh* (Director of the Rotman Research Institute, Baycrest Centre, Toronto), and pair were soon joined by Dr Petra Ritter, BIH Johanna Quandt Professor for Brain Simulation at Berlin Institute of Health (BIH) and Charité – Universitätsmedizin Berlin.
Keep an eye to the horizon (and in particular to those manning the pipeline at Dr Ritter’s group; Michael Schirner deserving noteworthy attention). In light of contemporary assumptions of brain processes, and a recent move to incorporate a concept known as Bayesian belief propagation within the framework underlying TVB, it should give us reason to anticipate a convergence upon what some may consider to be the Holy Grail; a model of a unified theory of the brain. The upshot of which should be savoured for another day’s blog.
Nature’s tendency to coalesce has inspired the curious and the poets. In becoming scientists and still unfalteringly curious, they have determined our notions of the delicate and adapted ecosystems of earth, far from being a collection of parcellated phenomena, (the evolution of these ideas is captured in great detail by Andrea Wulf, in her ‘The Invention of Nature’) and find apt similarity in the nature of our very own brain. What makes TVB, and similar steps into the thick of modelling brain dynamics attractive, is how in the very human way it appeals to our visualising the rootedness and symphony beneath our scalp. It does not claim do give us a complete picture; that day, should it ever come might look wildly unfamiliar. However, TVB may be symptomatic of a turn from atomizing to a thesis of interconnectedness of incredible detail.
fMRI: Functional Magnetic Resonance Imaging.
DTI: Diffusion Tensor Imaging
TVB: The Virtual Brain