Browsing by Author "Sokunbi, M.O."
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Item Open Access BOLD fMRI complexity predicts changes in brain processes, interactions and patterns, in health and disease(Elsevier, 2016-06-23) Sokunbi, M.O.The human brain is the most complex information processing system that exists in nature. Its information processing functionality exists at multiple levels of interactions which can be influenced by electrical, chemical and physical components governed by thresholds and saturation phenomena [1]. When these thresholds are exceeded, saturation is reached, giving rise to nonlinear behaviour [22]. The human brain like most dynamic systems in nature typically exhibit chaotic and complex behaviours with nonlinear dynamic properties [3].Item Open Access Children with ADHD exhibit lower fMRI spectral exponent than their typically developing counterparts(Organisation for Human Brain Mapping (OHBM), USA., 2018-06) Sokunbi, M.O.Complex interactions in nonlinear systems such as the human brain exhibit fractal processes which are outcomes of self-similar patterns over long time scales by a power law in the frequency domain. The spectral exponent (γ) of this power law can be observed as an estimator of relative health and disease especially in the case of 1/f power spectrum. The aim of this pilot study is to estimate the fractal behaviour (using spectral exponent) of resting state fMRI time series of children with ADHD when compared to age-matched and gender-matched typically developing children (TDC). We expect the spectral exponent of the children with ADHD to be significantly different from that of their typically developing counterparts. Our analysis shows that both the children with ADHD and TDC exhibited positive spectral exponent (γ) which implies that their fMRI time series depicts greater power at high frequencies. However, the children with ADHD exhibited significantly (p<0.05) lower spectral exponent (γ) than their typically developing counterparts in brain regions consistent with abnormalities in ADHD brain dynamics. Our results have shown that spectral exponent (γ) may be a useful tool in revealing abnormalities in ADHD brain dynamics.Item Open Access Development of a Technique for Restoring the Fidelity of Distorted Playback Audio Signal from Analog Cassette Tape(Science domain International, 2015-05-25) Atijosan, A.O.; Adeniran, S.A.; Sokunbi, M.O.; Badru, R.A.A simple yet elegant analog based technique for restoring the fidelity of playback audio signals emanating from magnetic cassette tapes is presented. The technique makes use of information from the high frequency bias signal in magnetic cassette tapes to correct for errors in the playback audio signal. Performance evaluation of the developed technique shows that the technique can correct for errors due to noise, scratches on the tape surface, clipping, and non-linear distortion. The developed technique will be valuable in restoring the fidelity of playback audio signal from magnetic cassette tapes stored in archives and private homes.Item Open Access Feedback of real-time fMRI signals: From concepts and principles to therapeutic interventions(Elsevier, 2016-08-25) Sokunbi, M.O.The feedback of real-time functional magnetic resonance imaging (rtfMRI) signals, dubbed “neurofeedback”, has found applications in the treatment of clinical disorders and enhancement of brain performance. However, knowledge of the basic underlying mechanism on which neurofeedback is based is rather limited. This article introduces the concepts, principles and characteristics of feedback control systems and its applications to electroencephalography (EEG) and rtfMRI signals. Insight into the underlying mechanisms of feedback systems may lead to the development of novel feedback protocols and subsystems for rtfMRI and enhance therapeutic solutions for clinical interventions.Item Open Access fMRI neurofeedback of higher visual areas and perceptual biases(Elsevier, 2016-03-26) Habes, I.; Rushton, S.; Johnston, S.J.; Sokunbi, M.O.; Barawi, K.; Brosnan, M.; Daly, T.The self-regulation of brain activation via neurofeedback training offers a method to study the relationship between brain areas and perception in a more direct manner than the conventional mapping of brain responses to different types of stimuli. The current proof-of-concept study aimed to demonstrate that healthy volunteers can self-regulate activity in the parahippocampal place area (PPA) over the fusiform face area (FFA). Both areas are involved in higher order visual processing and are activated during the imagery of scenes and faces respectively. Participants (N=9) were required to upregulate PPA relative to FFA activity, and all succeeded at the task, with imagery of scenes being the most commonly reported mental strategy. A control group (N=8) underwent the same imagery and testing procedure, albeit without neurofeedback, in a mock MR scanner to account for any non-specific training effects. The upregulation of PPA activity occurred concurrently with activation of prefrontal and parietal areas, which have been associated with ideation and mental image generation. We tested whether successful upregulation of the PPA relative to FFA had consequences on perception by assessing bistable perception of faces and houses in a binocular rivalry task (before and after the scanning sessions) and categorisation of faces and scenes presented in transparent composite images (during scanning, interleaved with the self-regulation blocks). Contrary to our expectations, upregulation of the PPA did not alter the duration of face or house perception in the rivalry task and response speed and accuracy in the categorisation task. This conclusion was supported by the results of another control experiment (N=10 healthy participants) that involved intensive exposure to category-specific stimuli and did not show any behavioural or perceptual changes. We conclude that differential self-regulation of higher visual areas can be achieved, but that perceptual biases under conditions of stimulus rivalry are relatively robust against such internal modulation of localised brain activity. This study sets the basis for future investigations of perceptual and behavioural consequences of localised self-regulation of neural activity.Item Open Access Fractal analysis of resting state fMRI signals in adults with ADHD(2013-06) Sokunbi, M.O.; Fung, W.; Sawlani, V.; Donev, R.; Linden, D.E.J.; Thome, J.The fractal concept developed by Mandelbrot provides a useful tool for examining a variety of naturally occurring phenomena. Fractals are signals that display scale-invariant or self-similar behaviour. They can be found everywhere in nature including fractional Gaussian noise (fGn). Resting state fMRI signals can be modelled as fGn which makes them appropriate for fractal analysis. The Hurst exponent, H, is a measure of fractal processes and has values ranging between 0 and 1. Fractional Gaussian noise with 0Item Open Access Functional MRI entropy measurements of age-related brain changes(2011-06) Sokunbi, M.O.; Staff, R.T.; Waiter, G.D.; Cameron, G.G.; Ahearn, T.S.; Murray, A.D.As we age there is a decline in cognitive abilities such as processing speed, memory, executive function and reasoning. The basis for this decline is not well understood. In this study, the physiological complexity of resting state fMRI signals in a group of healthy volunteers was investigated. Twenty volunteers ranging from age 25 to 60 years underwent functional magnetic resonance imaging (fMRI). Physiological complexity was measured by calculating approximate entropy (ApEn) maps for all volunteers. Maps were statistically analysed globally and regionally with Statistical Package for Social Sciences (SPSS) and Statistical Parametric Mapping (SPM8) software respectively. Comparing the older participants (> 40 years) with the younger ones, the older group exhibited significantly lower signal ApEn in areas of white matter, grey matter, frontal lobe, sub-lobar, brainstem, limbic lobe and temporal lobe. Decline in fMRI brain complexity is a feature of normal ageing beyond the age of 40 years.Item Open Access Fuzzy approximate entropy analysis of resting state fMRI signal complexity across the adult life span(Elsevier, 2015-10-21) Sokunbi, M.O.; Cameron, G.G.; Ahearn, T.S.; Murray, A.D.; Staff, R.T.In this study, we present a method for measuring functional magnetic resonance imaging (fMRI) signal complexity using fuzzy approximate entropy (fApEn) and compare it with the established sample entropy (SampEn). Here we use resting state fMRI dataset of 86 healthy adults (41 males) with age ranging from 19 to 85 years. We expect the complexity of the resting state fMRI signals measured to be consistent with the Goldberger/Lipsitz model for robustness where healthier (younger) and more robust systems exhibit more complexity in their physiological output and system complexity decrease with age. The mean whole brain fApEn demonstrated significant negative correlation (r = -0.472, p<0.001) with age. In comparison, SampEn produced a non-significant negative correlation (r = -0.099, p=0.367). fApEn also demonstrated a significant (p<0.05) negative correlation with age regionally (frontal, parietal, limbic, temporal and cerebellum parietal lobes). There was no significant correlation regionally between the SampEn maps and age. These results support the Goldberger/Lipsitz model for robustness and have shown that fApEn is potentially a sensitive new method for the complexity analysis of fMRI data.Item Open Access Inter-individual Differences in fMRI Entropy Measurements in Old Age(IEEE, 2011-08-22) Sokunbi, M.O.; Staff, R.T.; Waiter, G.D.; Ahearn, T.S.; Fox, H.C.; Deary, I.J.; Whalley, L.J.; Murray, A.D.We investigated the association between individual differences in cognitive performance in old age and the approximate entropy (ApEn) measured from functional magnetic resonance imaging (fMRI) data acquired from 40 participants of the Aberdeen Birth Cohort 1936 (ABC1936), while undergoing a visual information processing task: inspection time (IT). Participants took a version of the Moray House Test (MHT) No. 12 at age 11, a valid measure of childhood intelligence. The same individuals completed a test of non-verbal reasoning (Raven’s Standard Progressive Matrices [RPM]) aged about 68 years. The IT, MHT and RPM scores were used as indicators of cognitive performance. Our results show that higher regional signal entropy is associated with better cognitive performance. This finding was independent of ability in childhood but not independent of current cognitive ability. ApEn is used for the first time to identify a potential source of individual differences in cognitive ability using fMRI data.Item Open Access Motion during Acquisition is Associated with fMRI Brain Entropy(IEEE, 2019-04-01) de Vries, Clarisse F.; Staff, Roger T.; Waiter, Gordon D.; Sokunbi, M.O.; Sandu, Anca L.; Murray, Alison D.Measures of fMRI brain entropy have been used to investigate age and disease related neural changes. However, it is unclear if movement in the scanner is associated with brain entropy after geometric correction for movement. As age and disease can affect motor control, quantifying and correcting for the influence of movement will avoid false findings. This work examines the influence of head motion on fMRI brain entropy. Resting-state and task-based fMRI data from 281 individuals born in Aberdeen between 1950 and 1956 were analysed. The images were realigned, followed by nuisance regression of the head motion parameters. The images were either high-pass filtered (0.008 Hz) or band-pass (0.008 Hz – 0.1 Hz) filtered in order to compare the two methods; fuzzy approximate entropy (fApEn) and fuzzy sample entropy (fSampEn) were calculated for every voxel. Motion was quantified as the mean displacement and mean rotation in three dimensions. Greater mean motion was correlated with decreased entropy for all four methods of calculating entropy. Different movement characteristics produce different patterns of associations, which appear to be artefact. However, across all motion metrics, entropy calculation methods and scan conditions, a number of regions consistently show a significant negative association: the right cerebellum crus, left precentral gyrus (primary motor cortex), the left postcentral gyrus (primary somatosensory cortex), and the opercular part of the left inferior frontal gyrus. The robustness of our findings at these locations suggests that decreased entropy in specific brain regions may be a marker for decreased motor control.Item Open Access Neurofeedback of visual food cue reactivity: a potential avenue to alter incentive sensitization and craving.(Springer, 2016-05-27) Ihssen, N.; Sokunbi, M.O.; Lawrence, A.D.; Lawrence, N.S.; Linden, D.E.J.FMRI-based neurofeedback transforms functional brain activation in real-time into sensory stimuli that participants can use to self-regulate brain responses, which can aid the modification of mental states and behavior. Emerging evidence supports the clinical utility of neurofeedback-guided up-regulation of hypoactive networks. In contrast, down-regulation of hyperactive neural circuits appears more difficult to achieve. There are conditions though, in which down-regulation would be clinically useful, including dysfunctional motivational states elicited by salient reward cues, such as food or drug craving. In this proof-of-concept study, 10 healthy females (mean age = 21.40 years, mean BMI = 23.53) who had fasted for 4 h underwent a novel 'motivational neurofeedback' training in which they learned to down-regulate brain activation during exposure to appetitive food pictures. FMRI feedback was given from individually determined target areas and through decreases/increases in food picture size, thus providing salient motivational consequences in terms of cue approach/avoidance. Our preliminary findings suggest that motivational neurofeedback is associated with functionally specific activation decreases in diverse cortical/subcortical regions, including key motivational areas. There was also preliminary evidence for a reduction of hunger after neurofeedback and an association between down-regulation success and the degree of hunger reduction. Decreasing neural cue responses by motivational neurofeedback may provide a useful extension of existing behavioral methods that aim to modulate cue reactivity. Our pilot findings indicate that reduction of neural cue reactivity is not achieved by top-down regulation but arises in a bottom-up manner, possibly through implicit operant shaping of target area activity.Item Open Access Nonlinear complexity analysis of brain fMRI signals in schizophrenia(PLoS ONE, 2014-05-13) Sokunbi, M.O.; Gradin, V.B.; Waiter, G.D.; Cameron, G.G.; Ahearn, T.S.; Murray, A.D.; Steele, D.J.; Staff, R.T.We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.Item Open Access Real-time fMRI brain-computer interface: Development of a motivational feedback subsystem for the regulation of visual cue reactivity(Frontiers Media, 2014-11-25) Sokunbi, M.O.; Linden, D.E.J.; Habes, I.; Johnston, S.; Ihssen, N.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.Item Open Access Resting state fMRI entropy probes complexity of brain activity in adults with ADHD(Elsevier, 2013-10-15) Sokunbi, M.O.; Fung, W.; Sawlani, V.; Choppin, S.; Linden, D.E.J.; Thome, J.In patients with attention deficit hyperactivity disorder (ADHD), quantitative neuroimaging techniques have revealed abnormalities in various brain regions, including the frontal cortex, striatum, cerebellum, and occipital cortex. Nonlinear signal processing techniques such as sample entropy have been used to probe the regularity of brain magnetoencephalography signals in patients with ADHD. In the present study, we extend this technique to analyse the complex output patterns of the 4 dimensional resting state functional magnetic resonance imaging signals in adult patients with ADHD. After adjusting for the effect of age, we found whole brain entropy differences (P=0.002) between groups and negative correlation (r=-0.45) between symptom scores and mean whole brain entropy values, indicating lower complexity in patients. In the regional analysis, patients showed reduced entropy in frontal and occipital regions bilaterally and a significant negative correlation between the symptom scores and the entropy maps at a family-wise error corrected cluster level of P<0.05 (P=0.001, initial threshold). Our findings support the hypothesis of abnormal frontal-striatal-cerebellar circuits in ADHD and the suggestion that sample entropy is a useful tool in revealing abnormalities in the brain dynamics of patients with psychiatric disorders.Item Open Access Sample entropy reveals high discriminative power between young and elderly adults in short fMRI data sets(Frontiers Media, 2014-07-23) Sokunbi, M.O.Some studies have placed Sample entropy on the same data length constraint of 10m–20m (m: pattern length) as approximate entropy, even though Sample entropy is largely independent of data length and displays relative consistency over a broader range of possible parameters (r, tolerance value; m, pattern length; N, data length) under circumstances where approximate entropy does not. This is particularly erroneous for some fMRI experiments where the working data length is less than 100 volumes (when m = 2). We therefore investigated whether Sample entropy is able to effectively discriminate fMRI data with data length, N less than 10m (where m = 2) and r = 0.30, from a small group of 10 younger and 10 elderly adults, and the whole cohort of 43 younger and 43 elderly adults, that are significantly (p < 0.001) different in age. Ageing has been defined as a loss of entropy; where signal complexity decreases with age. For the small group analysis, the results of the whole brain analyses show that Sample entropy portrayed a good discriminatory ability for data lengths, 85 ≤ N ≤ 128, with an accuracy of 85% at N = 85 and 80% at N = 128, at q < 0.05. The regional analyses show that Sample entropy discriminated more brain regions at N = 128 than N = 85 and some regions common to both data lengths. As data length, N increased from 85 to 128, the noise level decreased. This was reflected in the accuracy of the whole brain analyses and the number of brain regions discriminated in the regional analyses. The whole brain analyses suggest that Sample entropy is relatively independent of data length, while the regional analyses show that fMRI data with length of 85 volumes is consistent with our hypothesis of a loss of entropy with ageing. In the whole cohort analysis, Sample entropy discriminated regionally between the younger and elderly adults only at N = 128. The whole cohort analysis at N = 85 was indicative of the ageing process but this indication was not significant (p > 0.05).Item Open Access Targeting the affective brain-a randomized controlled trial of real-time fMRI neurofeedback in patients with depression.(Nature, 2018-06-23) Mehler, David M. A.; Sokunbi, M.O.; Habes, I.; Barawi, K.; Subramanian, L.; Range, M.; Evans, J.; Hood, K.; Lührs, M.; Keedwell, P.; Goebel, R.; Linden, D.E.J.Functional magnetic resonance imaging neurofeedback (fMRI-NF) training of areas involved in emotion processing can reduce depressive symptoms by over 40% on the Hamilton Depression Rating Scale (HDRS). However, it remains unclear if this efficacy is specific to feedback from emotion-regulating regions. We tested in a single-blind, randomized, controlled trial if upregulation of emotion areas (NFE) yields superior efficacy compared to upregulation of a control region activated by visual scenes (NFS). Forty-three moderately to severely depressed medicated patients were randomly assigned to five sessions augmentation treatment of either NFE or NFS training. At primary outcome (week 12) no significant group mean HDRS difference was found (B = −0.415 [95% CI −4.847 to 4.016], p = 0.848) for the 32 completers (16 per group). However, across groups depressive symptoms decreased by 43%, and 38% of patients remitted. These improvements lasted until follow-up (week 18). Both groups upregulated target regions to a similar extent. Further, clinical improvement was correlated with an increase in self-efficacy scores. However, the interpretation of clinical improvements remains limited due to lack of a sham-control group. We thus surveyed effects reported for accepted augmentation therapies in depression. Data indicated that our findings exceed expected regression to the mean and placebo effects that have been reported for drug trials and other sham-controlled high-technology interventions. Taken together, we suggest that the experience of successful self-regulation during fMRI-NF training may be therapeutic. We conclude that if fMRI-NF is effective for depression, self-regulation training of higher visual areas may provide an effective alternative.Item Open Access Using real-time fMRI brain-computer interfacing to treat eating disorders(Elsevier, 2018-03-07) Sokunbi, M.O.Real-time functional magnetic resonance imaging based brain-computer interfacing (fMRI neurofeedback) has shown encouraging outcomes in the treatment of psychiatric and behavioural disorders. However, its use in the treatment of eating disorders is very limited. Here, we give a brief overview of how to design and implement fMRI neurofeedback intervention for the treatment of eating disorders, considering the basic and essential components. We also attempt to develop potential adaptations of fMRI neurofeedback intervention for the treatment of anorexia nervosa, bulimia nervosa and binge eating disorder.Item Embargo Using real-time fMRI to influence effective connectivity in the developing emotion regulation network(Elsevier, 2016-01-15) Cohen Kadosh, K.; Luo, Q.; de Burca, C.; Sokunbi, M.O.; Feng, J.; Linden, D.E.J.; Lau, J.Y.F.For most people, adolescence is synonymous with emotional turmoil and it has been shown that early difficulties with emotion regulation can lead to persistent problems for some people. This suggests that intervention during development might reduce long-term negative consequences for those individuals. Recent research has highlighted the suitability of real-time fMRI-based neurofeedback (NF) in training emotion regulation (ER) networks in adults. However, its usefulness in directly influencing plasticity in the maturing ER networks remains unclear. Here, we used NF to teach a group of 17 7–16 year-olds to up-regulate the bilateral insula, a key ER region. We found that all participants learned to increase activation during the up-regulation trials in comparison to the down-regulation trials. Importantly, a subsequent Granger causality analysis of Granger information flow within the wider ER network found that during up-regulation trials, bottom-up driven Granger information flow increased from the amygdala to the bilateral insula and from the left insula to the mid-cingulate cortex, supplementary motor area and the inferior parietal lobe. This was reversed during the down-regulation trials, where we observed an increase in top-down driven Granger information flow to the bilateral insula from mid-cingulate cortex, pre-central gyrus and inferior parietal lobule. This suggests that: 1) NF training had a differential effect on up-regulation vs down-regulation network connections, and that 2) our training was not only superficially concentrated on surface effects but also relevant with regards to the underlying neurocognitive bases. Together these findings highlight the feasibility of using NF in children and adolescents and its possible use for shaping key social cognitive networks during development.