Nathan Alder and Michael J. Larson, PhD, Psychology and Neuroscience
Introduction
A key issue in mild traumatic brain injury (TBI; also known as concussion) research is the identification and validation of a cost-effective, physiological measure that accurately identifies individuals who have experienced a mild TBI, is robust against motivation difficulties, and aids in the prediction of which individuals will experience persisting cognitive or emotional side effects. Nearly two million cases of TBI occur each year (Langlois, Rutland-Brown, & Thomas, 2004). Mild TBI is considered a major health concern (Ragnarsson, 2002) and can be associated with some long-term functional deficits including memory decline and decreased job satisfaction (Carroll et al., 2004; Iverson, 2005). Attempts to accurately quantify and validate measures of mild TBI have proven difficult given the large variability in injury presentation, location, and severity. Damage to the corpus callosum, the largest white-matter bundle in the brain that connects the two cerebral hemispheres, is highly related to slowed processing speed and poor clinical outcomes following mild TBI (e.g., Bazarian et al., 2007). For example, Viano et al. (2005), in an innovative study of head impacts based on National Football League (NFL) player concussions, showed that, across all participants, the largest strain during impact occurred due to tensile forces on the corpus callosum. Despite these findings, no single physiological index assessing corpus callosum function has been directly tested to determine its utility in accurate classification and longer-term prognosis of individuals with mild TBI.
Scalp-recorded event-related potentials (ERPs) provide a technique to non-invasively measure the electrophysiological response to visual stimuli as signals cross the corpus callosum. ERPs are changes in the brain’s electrical waveforms due to responses toward stimuli (Broglio, Pontifex, O’Connor, & Hillman, 2009; Pontifex, O’Connor, Broglio, & Hillman, 2009). We aimed to test an ERP index of interhemispheric transfer as such a measure. Specifically, we intended to test the utility of electrophysiological interhemispheric transfer time as a physiologic measure that accurately identifies individuals who have experienced a mild TBI. We hypothesized that electrophysiological interhemispheric transfer times are sensitive and specific to mild TBI relative to neurologically healthy control participants following acute mild TBI.
Methodology
Study participants with mild TBI were referred by local physicians and athletic trainers and posted flyers. Individuals in the mild TBI group sustained a TBI as defined by the American Congress of Rehabilitation Medicine (Kay et al., 1993) and further clarified by the World Health Organization (WHO; Carroll, Cassidy, Holm, Kraus, & Coronado, 2004). Participants received an informed consent form, with the study session scheduled to occur within one month of their injury. Study sessions involved two main parts: 1) completion of self- and other-report measures of current symptoms and functioning; 2) completion of the ERP interhemispheric-transfer experimental task.
Computerized Testing and EEG Task: We followed the verified electrophysiological interhemispheric transfer protocol used by Brown et al., (Brown, Larson, & Jeeves, 1994; Moes, Brown, & Minnema, 2007) wherein participants wearing a 128-electrode sensor EEG net were asked to determine if two simultaneously presented letters are “match” or “non-match”. To summarize, two letters were simultaneously presented for 60ms in two of four locations that form the corners of an imaginary rectangle surrounding a central fixation point. Participants indicated whether the letters matched or did not match by pressing a key. Stimuli were presented in random order, with five blocks of 100 trials for a total of 500 trials to ensure adequate signal-to-noise ratio.
Results
Our final sample consisted of 32 individuals who had received a concussion and 19 matched control participants. The mean age of the control group was 22.7 years (SD=2.4), and the mean age of the concussion group was 23.4 years (SD=4.7). We ran a Group by Visual field by Hemisphere repeated measures analysis of variance (ANOVA). The findings indicated a main effect of visual field (F(1,49) = 9.10, p = .004), with faster latencies to the right visual field than the left visual field when collapsed across control and mild TBI groups. Importantly, there was also a Visual field by Hemisphere interaction (F(1,49) = 30.98, p < .001), indicating that the direct pathway across the corpus callosum was faster than the indirect pathway for both visual fields. Unfortunately, the Group by Visual field by Hemisphere interaction was not significant (F(1,49) = .81, p = .37), indicating the speed of interhemispheric transfer was similar between the mild TBI and the control participants.
Discussion
We found evidence of interhemispheric transfer for both groups, however, the magnitude of the interhemispheric transfer was not significantly different between the two groups. Current findings do not support our hypothesis that individuals with concussion would have slower interhemispheric transfer times than the control participants. We plan to continue data collection in order to increase our sample size and power to further investigate if these differences are significant.
Conclusion
We aimed to examine if electrophysiological interhemispheric transfer times are sensitive and specific to mild TBI relative to neurologically healthy control participants following acute mild TBI. Our results did not adequately answer our research question and more data needs to be collected. Further studies should examine individuals with concussion within 48 hours, rather than within the first 3 weeks. This method may determine if acute concussions have an effect on interhemispheric transfer time. Other future directions of study include looking for a correlation between interhemispheric transfer time and injury severity or time-sense injury.
References
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