Brain signal variability relates to stability of behavior after recovery from diffuse brain injury

Abstract

Variability or noise is an unmistakable feature of neural signals; however such fluctuations have been regarded as not carrying meaningful information or as detrimental for neural processes. Recent empirical and computational work has shown that neural systems with a greater capacity for information processing are able to explore a more varied dynamic repertoire, and the hallmark of this is increased irregularity or variability in the neural signal. How this variability in neural dynamics affects behavior remains unclear. Here, we investigated the role of variability of magnetoencephalography signals in supporting healthy cognitive functioning, measured by performance on an attention task, in healthy adults and in patients with traumatic brain injury. As an index of variability, we calculated multiscale entropy, which quantifies the temporal predictability of a time series across progressively more coarse time scales. We found lower variability in traumatic brain injury patients compared to controls, arguing against the idea that greater variability reflects dysfunctional neural processing. Furthermore, higher brain signal variability indicated improved behavioral performance for all participants. This relationship was statistically stronger for people with brain injury, demonstrating that those with higher brain signal variability were also those who had recovered the most cognitive ability. Rather than impede neural processing, cortical signal variability within an optimal range enables the exploration of diverse functional configurations, and may therefore play a vital role in healthy brain function.

Understanding variability in the BOLD signal and why it matters for aging

“…McIntosh et al 2008). Similarly, variability is lower in patients with traumatic brain injury (Raja Beharelle et al 2012), and variability measures reliably predict task performance in these patients and in those with epilepsy (Protzner et al 2013), just as they do in healthy children, young adults and older adults. Thus, brain variability has been shown to be a useful way to understand both normal and abnormal brain function, particularly in its senstivity to individual differences in cognition.…”

Post-Traumatic Stress Constrains the Dynamic Repertoire of Neural Activity

“…This type of mechanism would be predicted by dynamical systems theory (Deco et al, 2009(Deco et al, , 2013, and to our knowledge this is among the first empirical observations of such a mechanism in the context of brain function. The fact that hypersynchrony and the concomitant decrease in variability were particularly severe in a subnetwork of temporal lobe structures, including the hippocampus and amygdala, suggests that this increasingly constrained neural functioning may be related to such symptoms as re-experiencing of memories, emotional reactivity, impaired extinction, and increased sensitivity to stimulation (Pitman et al, 2012).…”

“…For the past two decades, a body of empirical evidence has accumulated demonstrating the ability of MEG to detect weak signals emanating from deep brain structures, such as the hippocampus (Kirsh et al, 2003;Hamada et al, 2004;Cornwell et al, 2008a), amygdalae (Cornwell et al, 2007(Cornwell et al, , 2008b(Cornwell et al, , 2010Luo et al, 2007;Hung et al, 2012), and thalamus (Bish et al, 2004;Bardouille and Ross, 2008). Moreover, several studies based on physiologically realistic simulations (Attal and Schwartz, 2013;Balderston et al, 2013)-some using CTF Systems machines (Quraan et al, 2011;Mills et al, 2012)-have demonstrated the ability of beamformer or minimum variance current estimate solutions to localize deep generators.…”

“…Moreover, several studies based on physiologically realistic simulations (Attal and Schwartz, 2013;Balderston et al, 2013)-some using CTF Systems machines (Quraan et al, 2011;Mills et al, 2012)-have demonstrated the ability of beamformer or minimum variance current estimate solutions to localize deep generators.…”

“…Although PTSD is primarily defined in psychological terms, the neurophysiological effects of traumatic stress are increasingly recognized as an important facet of the PTSD phenotype (Pitman et al, 2012). For instance, exposure to traumatic stress can affect gray matter volume in such structures as the hippocampi (Kitayama et al, 2005), the ventromedial prefrontal cortex (Kasai et al, 2008, and the dorsal anterior cingulate cortex (Kitayama et al, 2006).…”