Frontal Midline Theta Activity Explains Differences in Reaction Time Variability Between ASD and ADHD

Background: Reaction time (RT) measures have long been recognised as a valuable indicator of cognitive performance in ASD (e.g. Jensen, 1992). RT data as it currently stands lacks specificity to a single psychiatric population and so has not been seen as a particularly useful marker for ASD. Our previous findings have shown that RT data, in particular, variation in reaction times (RT variability/RTV), may show some specificity between autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD) (Tye et al. 2016) but this is not always clear (Tye et al. 2013). Brain function studies point towards a relationship between RT measures and medial frontal (MF) brain activity (Bellgrove et al. 2004; McLoughlin et al. 2014). Our recent work showed a strong relationship between RT measures and an EEG source signal from the MF region of the brain in the 5-7 Hz frequency range (theta) (McLoughlin et al. 2014). However, there is little research into the neurophysiological underpinnings of this relationship, nor of the relationship between theta activity and ASD.

Objectives: To understand the underlying neurophysiology of RT data in ASD, and further to examine if theta-indexed neurophysiological measures can clarify differences and similarities between ASD and ADHD in RTs.

Methods: Children with ASD (n=19), ADHD (n=18) and typically developing controls (TDC; n=26) completed the CPT-OX task, with concurrent EEG recording, which was identical to that used in our previous studies (McLoughlin et al. 2010, 2011; Tye et al. 2014.). Instructions indicated to respond only to the target in cue-target sequences (XOX-OXO). The remainder were attentional stimuli (e.g. XOX-OXO) or distractors. Power and phase were calculated in the theta frequency band to compare inhibitory stimuli (e.g. XOX-ODO) to other stimuli (e.g. XOX-OXO) using independent components (IC) of the EEG data.

Results: We showed alterations in only ADHD children for RTV and mean RTs, However, we found abnormalities in both ASD and ADHD for theta power compared to TDC across all stimuli. We also found abnormalities in the phase onset of theta time-locked to inhibitory stimuli in ADHD compared to the ASD and TDC group. Greater theta phase variability was associated with increased RT variability across all groups.

Conclusions:  Our results suggest that children with both ASHD and ASD have altered cognitive control, indexed by decreased theta power localised to a source in the MF cortex. However, we show that the integrity of MF systems may be more compromised in ADHD compared to both ASD and TDC indicated by increased RTV and theta phase variability. Our findings may suggest disparate cortical sources for RT abnormalities in ASD and ADHD. Cognitive theories differ in whether they propose shared underlying causes between the disorders or disparate etiological pathways. Our findings confirm the importance of cognitive control in both ASD and ADHD pathophysiology but also suggest that some abnormalities in ASD may be independent of demands on the cognitive control system in ADHD, consistent with a model of limited shared causal pathways to the disorders.