The theoretical basis for our research stems from the concept of degeneracy. Degenerate systems have two characteristics: different networks can support the same function (many-to-one), and one region can be part of different functions depending on its interactivity in other brain regions (one-to-many). The notion of degeneracy in the brain seems counterintuitive, but because such a system is functionally redundant, it is fault-tolerant, and because different elements contribute to different portions of the output, it is highly adaptive.    


The following projects illustrate our research questions and approach:

Focal Changes in the Functional Capacity of Brain Tissue Affects Network Function:

The human brain shows functional changes (i.e., reorganizes) in relation to experience throughout life. An important implication of degeneracy is that focal functional changes affect not only specific brain regions, but also network function. Our research shows that focal changes in hippocampal function can alter the configuration of memory networks, and that these alterations can be linked to individual differences in memory performance (Protzner et al., Hum Brain Mapp, 2011; Protzner et al., J Neurosci, 2013). Interestingly, these focal changes can have even more widespread effects, in that they can alter networks that do not include the original region. For example, the hippocampus is not a region identified in the canonical language/word retrieval network. However, we have identified changes in networks that support good word retrieval performance in the context of focal changes to hippocampal function (Protzner & McAndrews, J Cog Neurosci, 2011). These findings indicate that the exploration of connectivity patterns may be crucial in understanding brain-behaviour coupling, and most of this work involves patients with medial temporal lobe epilepsy.

Characterizing Degeneracy with Scrabble® Expertise:


In this line of research, we want to show many-to-one function (i.e., that different networks can support the same function) in the word recognition system of young normal individuals. Visual word recognition is highly efficient and considered fully developed in literate adults. Competitive Scrabble players have extraordinary visual word recognition experience in that they spend extended amounts of time (e.g., years) practising this skill.  We want to see whether or not practise associated with this hobby changes the brain.  Specifically, outside the context of Scrabble, when Scrabble experts and controls perform a classic visual word recognition paradigm (the lexical decision task), we want to know if different neural networks support lexical decision task performance for these two participant groups.

Brain Signal Variability:

Network activity and connectivity reflect how the brain responds to a current environmental challenge. Computational research suggests that variability may reflect the brain’s capacity to respond to any challenge, as variability appears to be an important parameter reflecting information processing capacity. Although a great deal of theoretical work has been done on the link between brain signal variability and information processing capacity, few studies have examined these concepts empirically. Our recent work shows that critical regions involved in memory processing (i.e., hippocampus) produce signal with greater variability in the context of better memory (Protzner et al., Arch Ital Biol, 2010; Protzner et al., J Neurosci, 2013). We additionally identified a link between increased variability in a hippocampal network and better verbal memory performance when that same link could not be seen with regional co-activation measures (Protzner et al., J Neurosci, 2013). In essence, our work shows empirically, that signal variability provides unique information regarding the information processing capacity of critical regions and networks. 


Brain function is explored using the following techniques.