Human Brains, Because of Size, More Prone to Disconnection Syndromes Interview with:

Zoltan Toroczkai, PhD, Professor of Physics Concurrent Professor of Computer Science and Engineering Physics Department University of Notre Dame, Notre Dame, IN, 46556 --

Dr. Zoltan Toroczkai

Zoltan Toroczkai, PhD, Professor of Physics
Concurrent Professor of Computer Science and Engineering
Physics Department
University of Notre Dame, Notre Dame, IN, 46556 What is the background for this study?

Response: The mammalian brain is arguably the most complex information processing network and with billions of neurons and trillions of connections it presents formidable challenges to deciphering its fundamental mechanisms for information processing. In the brain, information is encoded into the spatio-temporal firing patterns of groups of neurons (population coding), making the connectivity structure of the network crucial for brain function. Damages to this network have been associated with diseases such as Alzheimer’s, autism and schizophrenia, and thus understanding the cortical network would also help better understand certain diseases of the brain.

An experimentally and computationally more feasible approach is to study the anatomical (physical connectivity) network between the functional areas of the cortex, a mosaic of brain patches, each associated with a specific function (e.g., visual, auditory, somatosensory). Based on phylogenic considerations one expects the existence of common fundamental network architectural (and implicitly, processing) principles to be present in all mammalian brains. However, the mammalian brain spans over five orders of variation in size and thus it is not clear at all what are this common architectural features and how would we find them. The challenge here is to compare networks of the same nature (information processing type) but of different orders, with different nodal identities, and of very different spatial embedding (geometrical size) properties. What are the main findings?

Response: Our manuscript, based on consistent physical connectivity experimental data (retrograde tracing) and subsequent network analysis demonstrates the existence of common cortical network features between two mammalian brains of very different sizes, namely, between mouse and macaque brains.

In our earlier work we were able to show that a model of the macaque neocortex with no free parameters captures many empirically observed features and makes predictions on network properties, which subsequently have been verified. The key feature of this model is the experimentally observed exponential decline of connection weight with distance (called EDR), where weight refers to the density of axons linking cortical areas. |

In the current paper we demonstrate that the EDR holds in the mouse as well, and that the same type of model can be used to describe the mouse interareal cortical network as the macaque, the model thus providing a common framework for network comparisons between different mammalian brains.

One outcome of this analysis is the observation that long-range interareal connections are much weaker in the larger primate brain when compared to the rodent, and thus, by extrapolation, they should be even weaker in the human, suggesting an increased vulnerability to disconnection syndromes in the human. Additional measurements of intra-area, local neuronal connections (running only within the gray matter) show that the EDR holds at this scale as well, indicating that the EDR could be part of a universal network structural organizational principle in the brain. What should readers take away from your report?

Response: The work presented in this paper is comparative connectomics, which studies the similarities and differences between brain neuronal networks and it can help capture the fundamental mechanisms for information processing common to all mammalian brains and separate from them species-specific features. The comparison is facilitated by the discovery of a common network organizational principle based on the spatial embedding features of network connections and their strengths (EDR), a feature that may be universally valid across the whole mammalian branch. What recommendations do you have for future research as a result of this study?

Response: There have only been a few studies performed in comparative connectomics such as this one, and thus a lot more can be learned from including data from other species. The classification of network features and their correlates with behavioral and evolutionary traits will help us better understand the emergence of brain function and ultimately the workings of the human brain and its diseases. The inclusion of additional data would also help test the universal character of the EDR principle. Is there anything else you would like to add?

Response: This work is the result of a collaboration between several research laboratories from France, US and Romania, both experimental and theoretical. Thank you for your contribution to the community.


Spatial Embedding and Wiring Cost Constrain the Functional Layout of the Cortical Network of Rodents and Primates
Szabolcs Horvát ,Răzvan Gămănuț ,Mária Ercsey-Ravasz ,Loïc Magrou,Bianca Gămănuț,David C. Van Essen,Andreas Burkhalter,Kenneth Knoblauch,Zoltán Toroczkai ,Henry Kennedy
Published: July 21, 2016

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Last Updated on July 21, 2016 by Marie Benz MD FAAD