The underlying mechanisms of MMN in 22q11.2DS

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Consequently, in this view reduced MMN amplitude in response to frequency deviant sounds might indirectly suggest abnormal monitoring of the environment and social cognition

deficits, including abnormal auditory emotion recognition which is crucial for social interactions and integration [52].

3.3 The underlying mechanisms of MMN in 22q11.2DS

The MMN from the perspective of predictive coding

The predictive coding framework propose that MMN as a prediction error signal arise within trials during auditory perception (the regularity violation or model adjustment hypothesis) and is suppressed between trials through dynamic synaptic changes during perceptual learning (the adaptation hypothesis). Accordingly, repeated presentation of standards will increase the efficacy of prediction error and elicit large mismatch response, when new stimuli are presented. In this framework, Larsen et al. (2019), using dynamic causal modeling for group comparison investigated the repetition dependent changes in ERPs and effective connectivity in a group of young non-psychotic 22q11.2 deletion carriers compared to typically developing individuals. The authors employed three models: adaptation model, prediction model and combined model that included the main cortical generators responsible for MMN generation, bilateral primary and secondary auditory cortices and right inferior frontal gyrus. Interestingly, model comparison revealed that adaptation to repeated sounds is reduced in individuals with 22q11.2 DS suggesting that the ability to adapt to the standard tones is impaired in this group compared to TD group [266]. Additionally, in the same group the authors report an altered backward, top-down functional connectivity from IFG to STG, as well as the intrinsic connection within right auditory cortex that did not, however, coincide with a MMN amplitude reduction [130]. Consequently, the 22q11.2deletion carriers express both abnormal top-down connectivity, an indicative of a disrupted precision of top-down predictions, and abnormal modulation within auditory cortex, an indicative of decreased adaptation. Importantly, a strong limitation of the model is the incomplete modelling of neural generators, namely the absence of subcortical thalamic auditory nuclei, strongly involved in both repetition suppression and prediction error, and abnormally developed in adolescents with 22q11.2 DS.

In line, our preliminary results regarding the standard and deviant ERPs suggest abnormal suppression as a possible mechanism underlying reduced amplitude of MMN.

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A hypothetical model for impaired MMN response to frequency deviants might be related to abnormal prediction error due to increased responses under repetition processing and thus reduced mismatch response when new stimuli are presented.

Figure 12. A hypothetical model of reduced MMN response from the perspective of predictive coding framework (adapted from Garrido et al., 2009). Altered right sided top-down functional connectivity from inferior frontal gyrus (IFG) to superior temporal gyrus (STG) and altered intrinsic connection within right primary auditory cortex (A1), as well as altered responses to standard stimuli are presumably the cause of reduced MMN in 22q11.2DS (right side) as compared to typically developing group (left side).

On the contrary, deficits in repetition suppression measured as sensory gating responses, a phenomenon in which the brain express reduced response to repeated stimuli in a paired click paradigm, are inconsistent in 22q11.2 deletion carriers. Rihs et al. (2013) and Vorstman et al.

(2009) report no deficit of P50 suppression, in children with 22q11.2 DS [9, 127],

while Zarchi et al. (2013) report reduced sensory gating in adults 22q11.2 deletion carriers relative to controls [38].

The MMN and gray matter volumes

The MMN amplitude reduction co-occurs with significant changes in scalp potential maps, pointing towards functional changes in underlying brain areas accountable for the response.

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Interestingly, the abnormal MMN response emerged during adolescence, a period of considerable brain changes and a vulnerable window for the emergence of psychotic disorders and thus the mismatch negativity response might reflect aberrant functional brain maturation in 22q11.2 DS.

Further, it is well established in 22q11.2 deletion carriers that from childhood to adolescence the brain is fine-tuning its architecture differently compared to the healthy population [251, 267]. While the age-related cortical thinning in the healthy subjects initiates in childhood in the primary sensorimotor areas, spreads rostrally over the frontal cortex, and caudally and laterally over the parietal, occipital, and lastly the temporal cortex [268], in the 22q1.2 DS a different developmental pattern is observed. In a longitudinal study Schaer et al. report subtle cortical thickening during childhood predominantly in the prefrontal cortex and increased cortical loss over widespread clusters starting with adolescence [269].

In addition, aberrant brain connectivity in adolescence has also been reported in humans [230, 231] and animal models of 22q11.2 DS [232]. Ottet et al. describe reduced left fronto-temporal connections and increased right fronto-frontal connections in patients with 22q11.2 DS compared with healthy participants [231].

In animal models, Chun et al. find disruptions in the activity of thalamocortical projections to the auditory cortex, that become evident only after 3 months of age in a mouse model of 22q11.2DS (corresponding to early adulthood in humans) [232].

Therefore, in 22q11.2 deletion carriers, decreased MMN observed during adolescence might indicate cortical gray matter loss over temporal cortical areas [84, 269] and\or aberrant thalamo-cortical projections, from medial geniculate nuclei to the auditory cortices [66, 117]

as previously reported in humans and animal models.

Nevertheless, contrary to this hypothesis, we do not observe significant correlations between reduced amplitude of MMN response and decreased gray matter volumes of cortical and subcortical auditory areas. These results, alongside with topographic differences might indicate an abnormal cortical and\or subcortical activation pattern yet fail to map a clear relationship between structural and functional changes in the auditory network.

Therefore, we presume that in 22q11.2 DS reduced MMN might be explained by underling abnormal functional activity, rather than being merely due to dispersed gray matter

diminution.

To our knowledge, this is the first study to investigate the link between the MMN measured at the scalp level with high density EEG and the volumetric estimates of underlying cortical

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and thalamic auditory areas derived from MRI T1 structural data within this clinical population, and thus replications of the results are crucial for clear conclusions.

The MMN and COMT gene

Individuals with COMT^MET/- genotype express four times lower rate of enzymatic activity compared to individuals with COMT^VAL/-,resulting in reduced ability to clear

dopamine from cortical synapses in the prefrontal cortex of COMT^MET/- carriers [270]. Higher dopamine levels due to abnormal enzymatic activity in 22q11.2 deletion carriers are linked with lower cognitive scores and sensory processing dysfunction, such as MMN reduction [31, 38]. Moreover, Zarchi et al. (2013) found an interaction effect of the COMT and PRODH genes showing PRODH to contribute to increased frequency-MMN amplitudes in

the COMT^VAL/-,but not in the COMT^MET/- polymorphism.

Our preliminary results replicate previous studies and reveal significant MMN deficit solely in 22q11.2DS^Met/- subjects relative to TD.

Interestingly, the increased dopamine levels have been related to altered function of NMDA-dependent glutamatergic neurons, especially in prefrontal cortical areas [36], and since MMN is dependent on NMDAr function [185], modification of MMN in COMT^MET/- carriers might highlight abnormal dopamine-glutamate interactions within the auditory networks involved in MMN.

3.4 Limitations

Importantly, we must highlight some limitations.

First, the 22q11.2 deletion carriers express heterogeneous levels of neuropsychiatric disorders and medication status that might influence our results. However, even though we did not control for the medication status or the neuropsychiatric profile we tried to address these issues.

Regarding the neuropsychiatric profile, no statistical differences in MMN amplitude (F(2, 67)

= .75, p = .47) or gray matter volumes [F (12,124) = .78, p= .66, Wilks' Λ = .86] were found between 22q11.2 DS individuals with ADHD, 22q11.2 DS individuals with other diagnoses (major depression, generalized anxiety, phobias) and 22q11.2 DS individuals without a diagnosis.

Regarding the medication status, we would expect enhanced MMN amplitude, meaning smaller differences between the groups, as the studies on this topic report either no change or enhanced MMN amplitude. For the first category of medication, the methylphenidate (ritaline\concerta), one study by Sawada et al. 2010 [271], demonstrate higher MMN amplitude at frontal (Fz) and

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parietal (Pz) channels after the intake of Concerta, while another study report no impact of Ritalin drug on MMN amplitude [272] in pediatric population. For the second category, the antidepressant of the selective serotonin reuptake inhibitor class, one randomized, double-blind, cross-over experiment with 20 healthy male volunteers who received either 15 mg of escitalopram (SSRI) or placebo, reported significantly increased MMN amplitude after the drug administration. This study suggests that increased serotonergic activity may enhance MMN [273]. For the third category of medication we used, the atypical antipsychotics (Risperdal\risperidone), no improvements in MMN response in patients with schizophrenia are reported after the administration of risperidone [274] or clozapine[275].

Secondly, we did not used specific hearing tests to measure the audition in our patients’ group, and since 22q11.2 DS is known to be associated with hearing problems, this might be a potential limitation. Nevertheless, when the time allowed after the MMN paradigm administration we did a brief behavioural test where the participants were asked to actively count the deviants (TD, N=47; 22q11DS, N=47). No differences in the ability to perceive and count the deviants were observed between the participants with 22q11.2 and typically developing individuals (t(df92) =1.13, p=.25).

Lastly, we used two different pre-processing pipelines related to baseline correction for the two articles, with the first one applying no baseline correction, and the second applying a baseline correction by subtraction of the averaged pre-stimulus 100 ms. This is an important topic in the traditional ERP community, strongly suggesting that the baseline correction must be done.

However, a considerable ERP literature from several groups, considers baseline subtraction a potential distortion, particularly when the pre-stimulus baseline activity may actually be meaningful and related to other post-stimulus activity of interest [276-279]. In such cases, the baseline correction can alter the post-stimulus topography and can have a critical effect on the results of the analyses. Consequently, we did not apply any baseline correction for the first article.

Despite all the aforementioned reasons, the standard method in MMN studies is to perform such correction and for our results to be comparable to prior literature for inclusion into meta-analyses, we decided to correct for the baseline in the second article. Interestingly, the baseline correction did not change the main effect that we observe, namely a reduced MMN in the 22q11DS participants compared to typical developing controls.

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