Functional Magnetic Resonance Imaging Investigation of the Effects of Neurofeedback Training on the Neural Bases of Selective Attention and Response Inhibition in Children with Attention-Deficit/Hyperactivity Disorder

Centre de Recherche en Neuropsychologie et Cognition, Département de Psychologie, Université de Montréal, Montréal, Canada.
Applied Psychophysiology and Biofeedback (Impact Factor: 1.13). 04/2006; 31(1):3-20. DOI: 10.1007/s10484-006-9001-y
Source: PubMed


Two functional magnetic resonance imaging (fMRI) experiments were undertaken to measure the effect of neurofeedback training (NFT), in AD/HD children, on the neural substrates of selective attention and response inhibition. Twenty unmedicated AD/HD children participated to these experiments. Fifteen children were randomly assigned to the Experimental (EXP) group whereas the other five children were randomly assigned to the Control (CON) group. Only subjects in the EXP group underwent NFT. EXP subjects were trained to enhance the amplitude of the SMR (12-15 Hz) and beta 1 activity (15-18 Hz), and decrease the amplitude of theta activity (4-7 Hz). Subjects from both groups were scanned one week before the beginning of NFT (Time 1) and 1 week after the end of NFT (Time 2), while they performed a "Counting Stroop" task (Experiment 1) and a Go/No-Go task (Experiment 2). At Time 1, in both groups, the Counting Stroop task was associated with significant activation in the left superior parietal lobule. For the Go/No-Go task, no significant activity was detected in the EXP and CON groups. At Time 2, in both groups, the Counting Stroop task was associated with significant activation of the left superior parietal lobule. This time, however, there were significant loci of activation, in the EXP group, in the right ACC, left caudate nucleus, and left substantia nigra. No such activation loci were seen in CON subjects. For the Go/No-Go task, significant loci of activation were noted, in the EXP group, in the right ventrolateral prefrontal cortex, right ACcd, left thalamus, left caudate nucleus, and left substantia nigra. No significant activation of these brain regions was measured in CON subjects. These results suggest that NFT has the capacity to functionally normalize the brain systems mediating selective attention and response inhibition in AD/HD children.

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Available from: Johanne Lévesque, Oct 17, 2014
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    • "However, these authors used a combined SMR and Beta based neurofeedback training. Hence, based on their study design it is not clear whether increases in SMR or Beta activity caused the performance improvements in the Digit Span test (forward) (Lévesque et al., 2006; Beauregard and Lévesque, 2006). "
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    ABSTRACT: In the present study, we investigated how the electrical activity in the sensorimotor cortex contributes to improved cognitive processing capabilities and how SMR (sensorimotor rhythm, 12-15Hz) neurofeedback training modulates it. Previous evidence indicates that higher levels of SMR activity reduce sensorimotor interference and thereby promote cognitive processing. Participants were randomly assigned to two groups, one experimental (N=10) group receiving SMR neurofeedback training, in which they learned to voluntarily increase SMR, and one control group (N=10) receiving sham feedback. Multiple cognitive functions and electrophysiological correlates of cognitive processing were assessed before and after 10 neurofeedback training sessions. The experimental group but not the control group showed linear increases in SMR power over training runs, which was associated with behavioural improvements in memory and attentional performance. Additionally, increasing SMR led to a more salient stimulus processing as indicated by increased N1 and P3 event-related potential amplitudes after the training as compared to the pre-test. Finally, functional brain connectivity between motor areas and visual processing areas was reduced after SMR training indicating reduced sensorimotor interference. These results indicate that SMR neurofeedback improves stimulus processing capabilities and consequently leads to improvements in cognitive performance. The present findings contribute to a better understanding of the mechanisms underlying SMR neurofeedback training and cognitive processing and implicate that SMR neurofeedback might be an effective cognitive training tool.
    Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 04/2014; 126(1). DOI:10.1016/j.clinph.2014.03.031 · 3.10 Impact Factor
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    • "Response inhibition as measured by go/no-go tasks has emerged as one of the principal paradigms for studying ADHD (Aron and Poldrack, 2005). Using this task, it has been clearly demonstrated that children (Beauregard and Levesque, 2006; Derefinko et al., 2008; Durston et al., 2003; Inoue et al., 2012; Ma et al., 2012; Monden et al., 2012; Siniatchkin et al., 2012; Smith et al., 2006; Solanto et al., 2009; Vaidya et al., 1998), adolescents (Schulz et al., 2004; Tamm et al., 2004) and adults (Dibbets et al., 2009; Karch et al., 2010; Mulligan et al., 2011; Sebastian et al., 2012; Vasic et al., in press) with ADHD have response inhibition deficits. An extensive review of functional neuroimaging in healthy adults indicates that widespread regions of the frontal cortex, especially the right inferior frontal gyrus (IFG), are associated with response inhibition (Aron and Poldrack, 2005). "
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    ABSTRACT: An objective biomarker is a compelling need for the early diagnosis of attention deficit hyperactivity disorder (ADHD), as well as for the monitoring of pharmacological treatment effectiveness. The advent of fNIRS, which is relatively robust to the body movements of ADHD children, raised the possibility of introducing functional neuroimaging diagnosis in younger ADHD children. Using fNIRS, we monitored the oxy-hemoglobin signal changes of 16 ADHD children (6 to 13 years old) performing a go/no-go task before and 1.5 h after MPH or placebo administration, in a randomized, double-blind, placebo-controlled, crossover design. 16 age-and gender-matched normal controls without MPH administration were also monitored. Relative to control sub-jects, unmedicated ADHD children exhibited reduced activation in the right inferior frontal gyrus (IFG) and middle frontal gyrus (MFG) during go/no-go tasks. The reduced right IFG/MFG activation was acutely nor-malized after MPH administration, but not after placebo administration. The MPH-induced right IFG/MFG activation was significantly larger than the placebo-induced activation. Post-scan exclusion rate was 0% among 16 right-handed ADHD children with IQ > 70. We revealed that the right IFG/MFG activation could serve as a neuro-functional biomarker for monitoring the acute effects of methylphenidate in ADHD children. fNIRS-based examinations were applicable to ADHD children as young as 6 years old, and thus would con-tribute to early clinical diagnosis and treatment of ADHD children.
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    • "Finally, Beauregard and Lévesque [117] scanned 15 unmedicated ADHD children randomly assigned to an experimental group that received NF, and five other ADHD children assigned to the control group who did not receive NF. Subjects from both groups were scanned 1 week before the beginning of training and 1 week after, while they performed a Counting Stroop task. Prior to training , the Counting Stroop task was associated with significant focus of activation in the left superior parietal lobule for both groups but no activation in the anterior cingulate cortex (ACC). "
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    ABSTRACT: Autism is a highly varied developmental disorder typically characterized by deficits in reciprocal social interaction, difficulties with verbal and nonverbal communication, and restricted interests and repetitive behaviors. Although a wide range of behavioral, pharmacological, and alternative medicine strategies have been reported to ameliorate specific symptoms for some individuals, there is at present no cure for the condition. Nonetheless, among the many incompatible observations about aspects of the development, anatomy, and functionality of the autistic brain, it is widely agreed that it is characterized by widespread aberrant connectivity. Such disordered connectivity, be it increased, decreased, or otherwise compromised, may complicate healthy synchronization and communication among and within different neural circuits, thereby producing abnormal processing of sensory inputs necessary for normal social life. It is widely accepted that the innate properties of brain electrical activity produce pacemaker elements and linked networks that oscillate synchronously or asynchronously, likely reflecting a type of functional connectivity. Using phase coherence in multiple frequency EEG bands as a measure of functional connectivity, studies have shown evidence for both global hypoconnectivity and local hyperconnectivity in individuals with ASD. However, the nature of the brain's experience-dependent structural plasticity suggests that these abnormal patterns may be reversed with the proper type of treatment. Indeed, neurofeedback (NF) training, an intervention based on operant conditioning that results in self-regulation of brain electrical oscillations, has shown promise in addressing marked abnormalities in functional and structural connectivity. It is hypothesized that neurofeedback produces positive behavioral changes in ASD children by normalizing the aberrant connections within and between neural circuits. NF exploits the brain's plasticity to normalize aberrant connectivity patterns apparent in the autistic brain. By grounding this training in known anatomical (e.g., mirror neuron system) and functional markers (e.g., mu rhythms) of autism, NF training holds promise to support current treatments for this complex disorder. The proposed hypothesis specifically states that neurofeedback-induced alpha mu (8-12Hz) rhythm suppression or desynchronization, a marker of cortical activation, should induce neuroplastic changes and lead to normalization in relevant mirroring networks that have been associated with higher-order social cognition. []
    Medical Hypotheses 12/2012; 79(6):790-8. DOI:10.1016/j.mehy.2012.08.031 · 1.07 Impact Factor
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