Following general screening of Neurofeedback training for ASD, here you will find further scientific screening addressing the brain patterns that have been shown by research to improve symptoms in ASD following Neurofeedback training.
Due to the complexity of ASD, e.g., the vast array of brain regions and mechanisms associated with the pathology, several neurofeedback (NFT) protocols are investigated.
The number of global brain abnormalities prompts issues in neural connectivity within the form of both hyper and hypoconnectivty. For example, there is short-range overconnectivity, predominantly within the left insula, frontal and pericentral brain regions [3,11,12], and impaired long-range connectivity between the frontal lobe and other cortical regions [7,3]. I
t is suggested that early developmental neuroinflammatory reactions disrupt frontal microcircuitry, provoking brain overgrowth which hinders connectivity between various information processing mechanisms, e.g., diminished connectivity between the frontal lobe and other systems. At the same time, this brain expansion that results in neuropil space reduction prompts excessive connectivity within the frontal lobes.
These structural and functional changes induce developmental stunting as they prohibit further growth in cerebral connectivity and specialisation. Problematic, as the frontal regions are vital in linguistic, cognitive, emotional control and social processes . Supporting research has presented that impaired information flow between frontal and posterior regions slows down response time and negatively impacts executive processing in both visual and spatial domains (especially information involving facial perceptions and working memory) .
Coben et al. 2007 demonstrated that children with autism displayed greater alpha and beta coherence but less interhemispheric and intra-hemispheric asymmetry . Thus, they theorised that normalising connectivity should improve autistic symptoms.
The results demonstrated that personalised protocols based on connectivity-guided neurofeedback led to improved connectivity and a 45% reduction in autistic symptoms.
These findings have been replicated. For example, Coby and Padolsky 2007 obtained a 40% reduction in autistic symptoms and hypercoherence, followed by an enhancement in neuropsychological functions after 20 sessions .
Neurofeedback appears promising in connectivity, as it uses operant conditioning to exercise and strengthen desired network connections and diminish undesired connections.
Low frequency bands: Decrease theta & increase SMR
Low-frequency waves are also targeted in neurofeedback, as attenuated cortical excitability with excessive slow-wave activity (within the frontal regions) and a diminished alpha power band are observed in ASD . Kouijzer et al. carried out several studies in this domain after past research demonstrated that increasing low beta and decreasing theta attenuates ASD symptomology and promotes brain flexibility via; 1. enhancing medial prefrontal brain activation and 2. enhancing the flexibility of the default mode network’s activation, which improves executive functions .
The team found that inhibiting theta and increasing beta activation reduced the heightened theta/beta ratio and improved ASD symptomology.
What is significant about the improvements is that they were not observed in the age, sex and IQ-matched control group.
Additionally, the improvements in executive functioning that occurred immediately after the neurofeedback treatment either persisted or further improved 12 months after training .
Functions that further improved following NFT treatment entailed motor response inhibition and sustained auditory selective attention. Additionally, improvements in social behaviour (social interaction skills, communicative abilities and typical behaviour) were maintained 12 months onwards. Supporting studies have demonstrated similar promising results [4,18]:
However, Mekkawy found no improvements in five patients (mean age of 10.7yrs) and suggested that earlier intervention may enhance NFT-treatment outcome .
Underlying mechanisms that support effective executive functioning and social behaviour include the default mode network, which entails the anterior cingulate cortex (ACC). In addition to generating significant levels of theta activity, the ACC regulates cognitive and emotional processes. During rest, the ACC has a high default metabolism, whereas when other brain regions are activated during cognitive tasks, the ACC deactivates .
Kennedy et al. found that ASD subjects did not deactivate their ACC to allow for the activation of other task-related brain regions . Thus, learning to reduce ACC theta activity via NFT allows for increased ACC flexibility, i.e., for the ACC to activate and deactivate appropriately in response to other cognitive and executive demands, which enhances performance.
Mu rhythm training
As previously mentioned, social deficits in ASD are suggested to involve the human mirror neuron system. In normal conditions, mu power around the sensorimotor cortex is suppressed during the observation, imagination and execution of body movements. Mu suppression is accompanied by the activation of regions linked to the hMNS. In ASD however, it has been observed that mu rhythm is absent during the observation of body movements unless the observed or imitated person is familiar to the individual with ASD. This finding was promising as it suggested that mu-rhythm is malleable in ASD .
Datko et al. performed 20 hours of mu-rhythm neurofeedback targeting the sensorimotor cortex in children. When assessing the results via fMRI, the ASD group displayed increased activation in brain regions containing the hMNS, e.g., the inferior parietal lobe (IPL). The IPL is involved in sensorimotor integration, perception and performance of goal-directed actions. Thus, increased IPL activation suggests that Neurofeedback treatment enhanced visuomotor integration during imitation. These brain changes were accompanied by behavioural improvements.
Previous studies on mu rhythm training have presented similar positive outcomes [20,21]. The overall results suggest that mu-training increased hMNS activation and thereby induced positive changes in behaviour.
Criticisms of Neurofeedback in Autism
Holtmann et al. 2011, critiqued that research presenting positive ASD-neurofeedback outcomes may not be demonstrating improvements in ASD but in its comorbid disorder, ADHD . Nonetheless, the team stated that due to the high number of individuals with ASD and comorbid ADHD (at the time of the paper, 40-50% of ASD individuals had ADHD), ADHD treatment should be obligatory as it impacts ASD presentation. However, in recent years, meta-analyses have been used to assess the efficacy of neurofeedback on ASD.
Van Hoogdalem et al. 2021 analysed 587 articles (containing 443 participants) and found that 94% of the nonrandomised controlled trials produced positive neurofeedback results on ASD. When only randomised controls were assessed, the efficacy of neurofeedback training increased .
Similar to Kouijzer et al. 2009 and Pineda et al. 2014, Datko et al. 2017 found no corresponding changes in their control group, indicating that the benefits of sensorimotor mu-NFT specifically benefit ASD. These findings are significant as they demonstrate that some NFT protocols specifically target maladaptive alterations found only in ASD, disproving Holtmann et al. 2011.
Targeting ASD symptoms
While the therapeutic potential of NFT on autism requires more research, there is a significant amount of research on NFT’s therapeutic effects on the symptoms associated with autism. Bar ADHD which has numerous amounts of literature validating NFTs efficacy, 40% of individuals with ASD have comorbid anxiety  that comprises both typical and autism-related anxiety .
Examples of autism-related anxiety are concerns about sensory stimuli, worries concerning change or unpredictable situations and uncommon but specific phobias. The following are examples of neurofeedback’s impact on anxiety:
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