Supplementary Materials

Hyper- and Hypo-activations in mTBI revealed by MEG using only the Correct Trials during

WM Tasks

In addition to the analysis of MEG responses in all target trials during the N-back tasks, we

also investigated the group differences of MEG responses just in the target trails with correct

response. The analysis procedure was identical to the one used for all target trials (See Method

and Materials). Again, MEG signals in 1-, 2-, and 3-back conditions were treated as repeat

measures during the ANOVA analysis. Figure S1 shows the significant hyper- and hypo-

activations in combat-related mTBI versus control subjects, using only the target trials with

correct responses during the MEG working memory N-back tasks. The group differences using

just the correct trials were highly similar to the ones using all target trials (see Fig. S1 versus Fig.

2). We believe that the subtle differences were due to less number of trials leading to lower

signal-to-noise ratio when using just the correct trials compared to using all target trials.

MEG Findings across Frequency Bands during WM Task

In the present study, we analyzed the WM MEG responses separately for different frequency

bands. Although brain rhythms are associated with all forms of cognitive activity, and appear in

a wide range of cortical and sub-cortical regions, their role in facilitating cognitive functions is

far from understood (Cannon et al. 2014). Usually, oscillatory signals in alpha band are the brain

rhythms with the highest amplitude among all frequency bands. Although the precise origin of

cortical alpha oscillations is still under investigation, thalamo-cortical interactions are thought to

be pivotal (Hughes and Crunelli 2005). Recent studies challenge the longstanding dogma that

alpha band oscillations are the signature of a passive idling brain state (Sadaghiani and

Kleinschmidt 2016). Instead, it has been proposed that alpha band oscillations serve as

mechanisms by which cognitive control networks exert top-down modulation on local and

distributed information processing, as alertness, selective attention, and adaptive control (see

cited references and review in (Sadaghiani and Kleinschmidt 2016)). In particular, it was

suggested that frontal-parietal (FP) activities modulate long-range communication in alpha band

for phasic adaptive control including WM (Dosenbach et al. 2007; Seeley et al. 2007; Sadaghiani

and Kleinschmidt 2016). As the foremost node, dlPFC plays a key role in the FP network for

WM (Sadaghiani and Kleinschmidt 2016). Our MEG findings of dlPFC hyper-activation in alpha

band (see Fig. 2 and Table 2) suggest over-recruitment for the cognitive control function of top-

down modulation in combat-related mTBI during the WM test.

Beta band oscillations are thought to be most associated with the cortico-basal ganglia-

thalamic (CBT) loop (Cannon et al. 2014). Recent studies have challenged the traditional idea of

beta oscillations in the CBT loop as being purely movement-related and suggested beta

oscillations play an important role in top-down cognitive functions such as perception, attention,

decision-making, and/or WM (see cited references and review in (Cannon et al. 2014)). In the

present study, the co-existence of MEG hypo-activation in beta band (also in other bands to some

extent) from ACC and hyper-activation from FP, dlPFC and vmPFC suggest abnormal top-down

cognitive function in the mTBI group. Future studies are needed to further understand causality

between the hypo-activation in ACC and hyper-activation from the other PFC regions in the beta

band.

The high frequency gamma band oscillations require the involvement of excitatory pyramidal

neurons and inhibitory fast-spiking (FS) interneurons, with frequencies of the oscillation related

to the decay of the inhibition in the range of 30-90 Hz (Whittington et al. 2000; Cannon et al.

2014). The process is referred to as pyramidal-interneuronal network gamma, and the gamma

oscillations are thought to create cell assemblies and facilitate selective neuronal communication

through coherence and frequency selectivity (Cannon et al. 2014). The gamma oscillations

contribute to basic cognitive computations (e.g., filtering signals by coherence and/or frequency)

and to major cognitive functions (e.g., attention, and multi-modal coordination). In addition,

gamma rhythms often interact with beta and/or alpha rhythms in which beta and/or alpha

rhythms provide top-down gain control (Cannon et al. 2014; Fries 2015). In the present WM

study, the MEG hyper-activation in gamma band from FP, dlPFC, vmPFC, and OFC may

suggest disinhibition in these areas in individuals with combat-related mTBI.

At the low frequency end, the theta rhythms are associated with a modulation of gamma-

synchronization strength, particularly with theta phase modulating gamma-strength (see cited

references and review in (Fries 2015)). It was suggested that top-down attentional influences are

mediated by beta-band synchronization, that the selective communication of the attended stimuli

is implemented by gamma-band synchronization, whereas gamma is rhythmically reset by a

theta rhythm (Fries 2015). Furthermore, it was proposed that theta-rhythmic gamma resetting

corresponds to the termination of the attentional selection and potential shift of attention to

another stimuli (Fries 2015). During the N-back WM test, the shift of attention from one letter to

another happens often. The MEG hyper-activation from FP may suggest over recruitment of this

region for compensating the deficiency of attention shifts in individuals with combat-related

mTBI.

Finally, increased slow-waves in delta-band brain rhythms have often been seen in

individuals with traumatic brain injury (Lewine et al. 1999, 2007, Huang et al. 2009, 2012, 2014)

which may explain the MEG low-frequency hyper-activation in the present study. When

examining the mechanism of abnormal delta rhythms, electrophysiological studies in animals

show that abnormal delta activity is from gray matter neurons that have experienced de-

afferentation due to neurological injuries in underlying white matter, resulting from axonal injury

or blockage / limitation in the cholinergic pathways (Ball et al. 1977; Gloor et al. 1977; Schaul et

al. 1978; Schaul 1998).

Traditionally, neuronal activity from different frequency bands is considered to reflect

different neuronal mechanisms. However, it is now understood that any given frequency band

can be produced by multiple mechanisms in different brain areas (Ainsworth et al. 2011; Cannon

et al. 2014), and one brain area may simultaneously produce oscillations in multiple frequency

bands, via multiple mechanisms (Roopun et al. 2008a, 2008b; Cannon et al. 2014). Our MEG

analysis of WM responses revealed common, as well as different abnormalities across frequency

bands in individuals with combat-related mTBI.

Figure Captions

Figure S1: Using only the trials with correct responses, MEG working memory N-back task

revealed hyper- and hypo-activations in combat-related mTBI versus control subjects. MEG

signals in 1-, 2-, and 3-back conditions were treated as repeat measures.

β bandγ band

δ-θ bandα band

R L

p=0.01 mTBI < ctrl p=0.001 p=0.01 mTBI > ctrl p=0.001

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