Functional connectivity changes associated with fMRI neurofeedback of right inferior frontal cortex in adolescents with ADHD

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is associated with poor self-control, underpinned by inferior fronto-striatal deficits. We showed previously that 18 ADHD adolescents over 11 runs of 8.5 min of real-time functional magnetic resonance neurofeedback of the right inferior frontal cortex (rIFC) progressively increased activation in 2 regions of the rIFC which was associated with clinical symptom improvement. In this study, we used functional connectivity analyses to investigate whether fMRI-Neurofeedback of rIFC resulted in dynamic functional connectivity changes in underlying neural networks.Whole-brain seed-based functional connectivity analyses were conducted using the two clusters showing progressively increased activation in rIFC as seed regions to test for changes in functional connectivity before and after 11 fMRI-Neurofeedback runs. Furthermore, we tested whether the resulting functional connectivity changes were associated with clinical symptom improvements and whether they were specific to fMRI-Neurofeedback of rIFC when compared to a control group who had to self-regulate another region.rIFC showed increased positive functional connectivity after relative to before fMRI-Neurofeedback with dorsal caudate and anterior cingulate and increased negative functional connectivity with regions of the default mode network (DMN) such as posterior cingulate and precuneus. Furthermore, the functional connectivity changes were correlated with clinical improvements and the functional connectivity and correlation findings were specific to the rIFC-Neurofeedback group.The findings show for the first time that fMRI-Neurofeedback of a typically dysfunctional frontal region in ADHD adolescents leads to strengthening within fronto-cingulo-striatal networks and to weakening of functional connectivity with posterior DMN regions and that this may be underlying clinical improvement.

Global Cortical Network Distinguishes Motor Imagination of the Left and Right Foot

“…Functional networks, on the other hand, are estimated from statistical models applied to brain signals recorded using functional imaging modalities such as fMRI or EEG. Functional brain connectivity has revealed differences in the default mode network (DMN) in the brain for various neuropsychiatric disorders, such as Alzheimer's disease [36], Parkinson's disease [37], epilepsy [38], attention deficit hyperactivity disorder (ADHD) [39], mood disorders [40], and schizophrenia [41]. Recent findings on EEG functional networks derived from MI tasks were discussed in Hamedi et al [42].…”

Multimodal Neuroimaging-based Prediction of Adult Outcomes in Childhood-onset ADHD using Ensemble Learning Techniques

“…The abnormalities of these regions were supported by a variety of existing neuroimaging and machine learning studies. Specifically, a substantial number of task-based and resting-state fMRI studies have consistently reported the decreased functional activation in right IFG (Cao et al, 2006; Konrad et al, 2006; Rubia et al, 2019; Rubia et al, 1999; Silk et al, 2005; Smith et al, 2006) and reduced functional connectivity between right MFG and right IPL (Lin et al, 2015; Vance et al, 2007) in children with ADHD as compared with normal controls. In addition, a substantial existing multivariate machine learning and ELTs-based studies have commonly reported that the functional activation and connectivity in frontal and parietal areas are associated with the classification performance between children with ADHD and normal controls (Brown et al, 2012; Colby et al, 2012; Deshpande et al, 2015; dos Santos Siqueira et al, 2014; Fair et al, 2012; Iannaccone et al, 2015; Qureshi et al, 2017).…”

Amygdala Circuitry During Neurofeedback Training and Symptoms’ Change in Adolescents With Varying Depression

“…Participants were recruited from the community and inpatient units at the University of Minnesota (U of M) using flyers and permission to contact parents. The sample size of 53 participants is significantly larger than the only two pediatric neurofeedback samples published at the time of this work's submission (Cohen Kadosh et al, 2016;Alegria et al, 2017;Rubia et al, 2019). However, given the study's novelty with regards to the sample composition and the neurofeedback task, we had no a-priory justification for our sample size.…”

“…Limited neurofeedback adolescent trials have found improved symptoms via increased inferior PFC activity in healthy adolescents and upregulated emotion regulation networks' engagement in adolescents with attention deficit hyperactivity disorders (ADHD;Cohen Kadosh et al, 2016;Alegria et al, 2017). FC analyses conducted by the same sample employed by Alegria et al (2017), revealed that the underlying mechanism for symptom improvement may be the FC differences between the PFC and frontostriatal systems and the default mode network (Rubia et al, 2019). Though unrelated to adolescent depression, these are -to date-the only published pediatric neurofeedback studies aside from our study (Quevedo et al, 2019).…”