Neurofeedback has been applied effectively in various areas, especially in the treatment of children with attention-deficit/hyperactivity disorder (ADHD). This study protocol is designed to investigate the effect of slow cortical potential (SCP) feedback and a new form of neurofeedback using near-infrared spectroscopy (NIRS) on symptomatology and neurophysiological parameters in an adult ADHD population. A comparison of SCP and NIRS feedback therapy methods has not been previously conducted and may yield valuable findings about alternative treatments for adult ADHD. The outcome of both neurofeedback techniques will be assessed over 30 treatment sessions and after a 6-month follow-up period, and then will be compared to a nonspecific biofeedback treatment. Furthermore, to investigate if treatment effects in this proof-of-principle study can be predicted by specific neurophysiological baseline parameters, regression models will be applied. Finally, a comparison with healthy controls will be conducted to evaluate deviant pretraining neurophysiological parameters, stability of assessment measures, and treatment outcome. To date, an investigation and comparison of SCP and NIRS feedback training to an active control has not been conducted; therefore, we hope to gain valuable insights in effects and differences of these types of treatment for ADHD in adults. This study is registered with the German Registry of Clinical Trials: DRKS00006767 , date of registration: 8 October 2014.

Resting-state functional magnetic resonance imaging (rs-fMRI) has the potential to investigate abnormalities in brain network structure and connectivity on an individual level in neurodevelopmental disorders, such as autism spectrum disorder (ASD), paving the way toward using this technology for a personalized, precision medicine approach to diagnosis and treatment. Using a case-control design, we compared five patients with severe regressive-type ASD to five patients with temporal lobe epilepsy (TLE) to examine the association between brain network characteristics and diagnosis. All children with ASD and TLE demonstrated intact motor, language, and frontoparietal (FP) networks. However, aberrant networks not usually seen in the typical brain were also found. These aberrant networks were located in the motor (40%), language (80%), and FP (100%) regions in children with ASD, while children with TLE only presented with aberrant networks in the motor (40%) and language (20%) regions, in addition to identified seizure onset zones. Fisher’s exact test indicated a significant relationship between aberrant FP networks and diagnosis (p = 0.008), with ASD and atypical FP networks co-occurring more frequently than expected by chance. Despite severe cognitive delays, children with regressive-type ASD may demonstrate intact typical cortical network activation despite an inability to use these cognitive facilities. The functions of these intact cognitive networks may not be fully expressed, potentially because aberrant networks interfere with their long-range signaling, thus creating a unique “locked-in network” syndrome.

Resting-state functional magnetic resonance imaging provides dynamic insight into the functional organization of the brains’ intrinsic activity at rest. The emergence of resting-state functional magnetic resonance imaging in both the clinical and research settings may be attributed to recent advancements in statistical techniques, non-invasiveness and enhanced spatiotemporal resolution compared to other neuroimaging modalities, and the capability to identify and characterize deep brain structures and networks. In this report we describe a 16-year-old female patient with autism spectrum disorder who underwent resting-state functional magnetic resonance imaging due to late regression. Imaging revealed deactivated networks in deep brain structures involved in monoamine synthesis. Monoamine neurotransmitter deficits were confirmed by cerebrospinal fluid analysis. This case suggests that resting-state functional magnetic resonance imaging may have clinical utility as a non-invasive biomarker of central nervous system neurochemical alterations by measuring the function of neurotransmitter-driven networks. Use of this technology can accelerate and increase the accuracy of selecting appropriate therapeutic agents for patients with neurological and neurodevelopmental disorders.

Background: Normative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state network informed treatments in pediatric movement disorders. Method: Cross-spectral dynamic causal modelling of resting-state fMRI was investigated in 19 neurotypically developing 5-7-year-old children. Fully connected six-node motor network models were created for each hemisphere including primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging were used to create a group model for each hemisphere; Purdue Pegboard Test (PPBT) scores for relevant hand motor behavior were also entered as a covariate at the group level to determine the brain-behavior relationship. Results: Overall, the resting-state functional MRI effective connectivity of motor cortico-basal ganglia-cerebellar networks was similar across hemispheres, with greater connectivity in the left hemisphere. The motor network effective connectivity relationships between the nodes were consistent and robust across subjects. Additionally, the PPBT score for each hand was positively correlated with the thalamus to contralateral cerebellum connection. Discussion: The normative effective connectivity from resting-state functional MRI in children largely reflect the direction of inter-nodal signal predicted by other prior modalities and was consistent and robust across subjects, with differences from these prior task-dependent modalities that likely reflect the motor rest-action state during acquisition. Effective connectivity of the motor network was correlated with motor behavior, indicating effective connectivity brain-behavior relationship has physiological meaning in the normally developing. Thus, it may be helpful for future studies in children with movement disorders, wherein comparison to normative effective connectivity will be critical for network-targeted intervention. Impact Statement: This is the first study to use pediatric resting-state functional MRI to create a normative effective connectivity model of the motor network and to also show correlation with behavior, which may have therapeutic implications for children with movement disorders.