Stephen J. Johnston

Real-Time Self-Regulation of Emotion Networks in Patients with Depression

Many patients show no or incomplete responses to current pharmacological or psychological therapies for depression. Here we explored the feasibility of a new brain self-regulation technique that integrates psychological and neurobiological approaches through neurofeedback with functional magnetic resonance imaging (fMRI). In a proof-of-concept study, eight patients with depression learned to upregulate brain areas involved in the generation of positive emotions (such as the ventrolateral prefrontal cortex (VLPFC) and insula) during four neurofeedback sessions. Their clinical symptoms, as assessed with the 17-item Hamilton Rating Scale for Depression (HDRS), improved significantly. A control group that underwent a training procedure with the same cognitive strategies but without neurofeedback did not improve clinically. Randomised blinded clinical trials are now needed to exclude possible placebo effects and to determine whether fMRI-based neurofeedback might become a useful adjunct to current therapies for depression.

Real-Time Functional Magnetic Resonance Imaging Neurofeedback for Treatment of Parkinson's Disease

Self-regulation of brain activity in humans based on real-time feedback of functional magnetic resonance imaging (fMRI) signal is emerging as a potentially powerful, new technique. Here, we assessed whether patients with Parkinsons disease (PD) are able to alter local brain activity to improve motor function. Five patients learned to increase activity in the supplementary motor complex over two fMRI sessions using motor imagery. They attained as much activation in this target brain region as during a localizer procedure with overt movements. Concomitantly, they showed an improvement in motor speed (finger tapping) and clinical ratings of motor symptoms (37% improvement of the motor scale of the Unified Parkinsons Disease Rating Scale). Activation during neurofeedback was also observed in other cortical motor areas and the basal ganglia, including the subthalamic nucleus and globus pallidus, which are connected to the supplementary motor area (SMA) and crucial nodes in the pathophysiology of PD. A PD control group of five patients, matched for clinical severity and medication, underwent the same procedure but did not receive feedback about their SMA activity. This group attained no control of SMA activation and showed no motor improvement. These findings demonstrate that self-modulation of cortico-subcortical motor circuits can be achieved by PD patients through neurofeedback and may result in clinical benefits that are not attainable by motor imagery alone.

Upregulation of emotion areas through neurofeedback with a focus on positive mood

Real-time functional magnetic resonance imaging can be used to feed back signal changes from the brain to participants such that they can train to modulate activation levels in specific brain areas. Here we present the first study combining up-regulation of brain areas for positive emotions with psychometric measures to assess the effect of successful self-regulation on subsequent mood. We localized brain areas associated with positive emotions through presentation of standardized pictures with positive valence. Participants up-regulated activation levels in their target area during specific periods, alternating with rest. Participants attained reliable self-control of the target area by the last of three seven-minute runs. This training effect was supported by an extensive network outside the targeted brain region, including higher sensory areas, paralimbic and orbitofrontal cortex. Self-control of emotion areas was not accompanied by clear changes in self-reported emotions; trend-level improvements on depression scores were counteracted by increases on measures of fatigue, resulting in no overall mood improvement. It is possible that benefits of self-control of emotion networks may only appear in people who display abnormal emotional homeostasis. The use of only a single, short, training session, overlap between positive and negative emotion networks and aversive reactions to the scanning environment may have prevented the detection of subtle changes in mood.

The Brain’s Voices: Comparing Nonclinical Auditory Hallucinations and Imagery

Although auditory verbal hallucinations are often thought to denote mental illness, the majority of voice hearers do not satisfy the criteria for a psychiatric disorder. Here, we report the first functional imaging study of such nonclinical hallucinations in 7 healthy voice hearers comparing them with auditory imagery. The human voice area in the superior temporal sulcus was activated during both hallucinations and imagery. Other brain areas supporting both hallucinations and imagery included fronto temporal language areas in the left hemisphere and their contralateral homologues and the supplementary motor area (SMA). Hallucinations are critically distinguished from imagery by lack of voluntary control. We expected this difference to be reflected in the relative timing of prefrontal and sensory areas. Activity of the SMA indeed preceded that of auditory areas during imagery, whereas during hallucinations, the 2 processes occurred instantaneously. Voluntary control was thus represented in the relative timing of prefrontal and sensory activation, whereas the sense of reality of the sensory experience may be a product of the voice area activation. Our results reveal mechanisms of the generation of sensory experience in the absence of external stimulation and suggest new approaches to the investigation of the neurobiology of psychopathology.

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success.

Neural hyperactivation in carriers of the Alzheimer's risk variant on the clusterin gene

Recent GWAS identified a risk variant for Alzheimers disease (AD) at a locus (rs11136000) of the clusterin gene (CLU). Here we use functional magnetic resonance imaging (fMRI) during working memory to probe the effect of the risk variant on brain activation in healthy individuals. Participants with the CLU risk genotype had higher activity than participants with the protective allele in frontal and posterior cingulate cortex and the hippocampus, particularly during high memory demand. These results inform pathophysiological models of the preclinical progression of AD.

Real-time fMRI brain-computer interface: development of a "motivational feedback" subsystem for the regulation of visual cue reactivity.

Here we present a novel neurofeedback subsystem for the presentation of motivationally relevant visual feedback during the self-regulation of functional brain activation. Our “motivational neurofeedback” approach uses functional magnetic resonance imaging (fMRI) signals elicited by visual cues (pictures) and related to motivational processes such as craving or hunger. The visual feedback subsystem provides simultaneous feedback through these images as their size corresponds to the magnitude of fMRI signal change from a target brain area. During self-regulation of cue-evoked brain responses, decreases and increases in picture size thus provide real motivational consequences in terms of cue approach vs. cue avoidance, which increases face validity of the approach in applied settings. Further, the outlined approach comprises of neurofeedback (regulation) and “mirror” runs that allow to control for non-specific and task-unrelated effects, such as habituation or neural adaptation. The approach was implemented in the Python programming language. Pilot data from 10 volunteers showed that participants were able to successfully down-regulate individually defined target areas, demonstrating feasibility of the approach. The newly developed visual feedback subsystem can be integrated into protocols for imaging-based brain-computer interfaces (BCI) and may facilitate neurofeedback research and applications into healthy and dysfunctional motivational processes, such as food craving or addiction.

Naive random subspace ensemble with linear classifiers for real-time classification of fMRI data

Functional magnetic resonance imaging (fMRI) provides a spatially accurate measure of brain activity. Real-time classification allows the use of fMRI in neurofeedback experiments. With limited labelled data available, a fixed pre-trained classifier may be inaccurate. We propose that streaming fMRI data may be classified using a classifier ensemble which is updated through naive labelling. Naive labelling is a protocol where in the absence of ground truth, updates are carried out using the label assigned by the classifier. We perform experiments on three fMRI datasets to demonstrate that naive labelling is able to improve upon a pre-trained initial classifier.

Eye movement patterns during the recognition of three-dimensional objects: Preferential fixation of concave surface curvature minima

This study used eye movement patterns to examine how high-level shape information is used during 3D object recognition. Eye movements were recorded while observers either actively memorized or passively viewed sets of novel objects, and then during a subsequent recognition memory task. Fixation data were contrasted against different algorithmically generated models of shape analysis based on: (1) regions of internal concave or (2) convex surface curvature discontinuity or (3) external bounding contour. The results showed a preference for fixation at regions of internal local features during both active memorization and passive viewing but also for regions of concave surface curvature during the recognition task. These findings provide new evidence supporting the special functional status of local concave discontinuities in recognition and show how studies of eye movement patterns can elucidate shape information processing in human vision.

ZNF804A Genotype Modulates Neural Activity during Working Memory for Faces

Background: Genetic susceptibility to schizophrenia (SZ) has been suggested to influence the cortical systems supporting working memory (WM) and face processing. Genetic imaging studies link the SZ risk variant rs1344706 on the ZNF804A gene to psychosis via alterations in functional brain connectivity during WM, but no work has looked at the effects of ZNF804A on WM with face-processing components. Methods: We therefore investigated healthy controls that were genotyped for rs1344706 with a face WM task during functional magnetic resonance imaging. We suggested that variation at the rs1344706 locus would be associated with similar alterations as patients previously tested using the same WM task for faces. Results: The rs1344706 risk allele was indeed associated with altered activation in the right dorsolateral prefrontal (rDLPFC) cortex. We established that the rDLPFC was activated in a task-dependent manner, suggesting that the differences in activation between rs1344706 genotype groups reflected alterations in task processing. Furthermore, we demonstrated that the rDLPFC region showed significant volumetric overlap with the rDLPFC which had previously been reported to be altered during task processing for patients with SZ. Conclusions: The findings support an association between rs1344706 and alterations in DLPFC activity during WM for faces. We further suggest that WM for faces may be a useful intermediate phenotype in the investigation of genetic susceptibility to psychosis.