Emotional task-dependent low-frequency fluctuations and methylphenidate: Wavelet scaling analysis of 1/f-type fluctuations in fMRI of the cerebellar vermis

Stroop-related cerebellar and temporal activation is correlated with negative affect and alcohol use disorder severity

Impairment in cognitive control in alcohol use disorder (AUD) contributes to difficulty controlling alcohol use and, in many populations, difficulties with emotion regulation. However, the most reliable and robust marker of clinically-relevant deficits in cognitive control in AUD is unclear. Our aims were to measure relationships between BOLD signal during a Stroop task and AUD severity and change in BOLD signal and change in drinking over three weeks. We also aimed to explore the relationships between BOLD signal and subjective negative affect. Thirty-three individuals with AUD underwent a multisensory Stroop task during functional magnetic resonance imaging (fMRI), as well as a battery of neuropsychological tests and self-report assessments of negative affect and AUD severity. Greater activation in temporal gyrus and cerebellum during incongruent trials compared to congruent trials was observed, and percent signal change (incongruent minus congruent) in both clusters was positively correlated with AUD severity and self-reported negative affect. Neuropsychological task performance and self-reported impulsivity were not highly correlated with AUD severity. Hierarchical regression analyses indicated that percent signal change (incongruent minus congruent) in cerebellum was independently associated with negative affect after controlling for recent and chronic drinking. In a subset of individuals (n = 23) reduction in cerebellar percent signal change (incongruent minus congruent) was correlated with increases in percent days abstinent over 3 weeks. BOLD activation during this Stroop task may therefore be an important objective marker of AUD severity and negative affect. The potential importance of the cerebellum in emotion regulation and AUD severity is highlighted.

Infants' gaze exhibits a fractal structure that varies by age and stimulus salience

The development of selective visual attention is critical for effectively engaging with an ever-changing world. Its optimal deployment depends upon interactions between neural, motor, and sensory systems across multiple timescales and neurocognitive loci. Previous work illustrates the spatio-temporal dynamics of these processes in adults, but less is known about this emergent phenomenon early in life. Using data (n = 190; 421 visits) collected between 3 and 35 months of age, we examined the spatio-temporal complexity of young children's gaze patterns as they viewed stimuli varying in semantic salience. Specifically, we used detrended fluctuation analysis (DFA) to quantify the extent to which infants' gaze patterns exhibited scale invariant patterns of nested variability, an organizational feature thought to reflect self-organized and optimally flexible system dynamics that are not overly rigid or random. Results indicated that gaze patterns of even the youngest infants exhibited fractal organization that increased with age. Further, fractal organization was greater when children (a) viewed social stimuli compared to stimuli with degraded social information and (b) when they spontaneously gazed at faces. These findings suggest that selective attention is well-organized in infancy, particularly toward social information, and indicate noteworthy growth in these processes across the first years of life.

Experimental control of scaling behavior: what is not fractal?

The list of psychological processes thought to exhibit fractal behavior is growing. Although some might argue that the seeming ubiquity of fractal patterns illustrates their significance, unchecked growth of that list jeopardizes their relevance. It is important to identify when a single behavior is and is not fractal in order to make meaningful conclusions about the processes underlying those patterns. The hypothesis tested in the present experiment is that fractal patterns reflect the enactment of control. Participants performed two steering tasks: steering on a straight track and steering on a circular track. Although each task could be accomplished by holding the steering wheel at a constant angle, steering around a curve may require more constant control, at least from a psychological standpoint. Results showed that evidence for fractal behavior was strongest for the circular track; straight tracks showed evidence of two scaling regions. We argue from those results that, going forward, the goal of the fractal literature should be to bring scaling behavior under experimental control.

Decreased resting-state brain activity complexity in schizophrenia characterized by both increased regularity and randomness

Schizophrenia is characterized by heterogeneous pathophysiology. Using multiscale entropy (MSE) analysis, which enables capturing complex dynamics of time series, we characterized MSE patterns of blood-oxygen-level-dependent (BOLD) signals across different time scales and determined whether BOLD activity in patients with schizophrenia exhibits increased complexity (increased entropy in all time scales), decreased complexity toward regularity (decreased entropy in all time scales), or decreased complexity toward uncorrelated randomness (high entropy in short time scales followed by decayed entropy as the time scale increases). We recruited 105 patients with schizophrenia with an age of onset between 18 and 35 years and 210 age- and sex-matched healthy volunteers. Results showed that MSE of BOLD signals in patients with schizophrenia exhibited two routes of decreased BOLD complexity toward either regular or random patterns. Reduced BOLD complexity toward regular patterns was observed in the cerebellum and temporal, middle, and superior frontal regions, and reduced BOLD complexity toward randomness was observed extensively in the inferior frontal, occipital, and postcentral cortices as well as in the insula and middle cingulum. Furthermore, we determined that the two types of complexity change were associated differently with psychopathology; specifically, the regular type of BOLD complexity change was associated with positive symptoms of schizophrenia, whereas the randomness type of BOLD complexity was associated with negative symptoms of the illness. These results collectively suggested that resting-state dynamics in schizophrenia exhibit two routes of pathologic change toward regular or random patterns, which contribute to the differences in syndrome domains of psychosis in patients with schizophrenia.

Fractal analysis of spontaneous fluctuations of the BOLD signal in the human brain networks

PURPOSE

To investigate what extent brain regions are continuously interacting during resting-state, independent component analyses (ICA) was applied to analyze resting-state functional MRI (RS-fMRI) data. According to the analyzed results, it was surprisingly found that low frequency fluctuations (LFFs), which belong to the 1/f signal (a signal with power spectrum whose power spectral density is inversely proportional to the frequency), have been classified into groups using ICA; furthermore, the spatial distributions of these groups within the brain were found to resemble the spatial distributions of different networks, which manifests that the signal characteristics of RS LFFs are distinct across networks. In our work, we applied the 1/f model in the fractal analyses to further investigate this distinction.

MATERIALS AND METHODS

Twenty healthy participants got involved in this study. They were scanned to acquire the RS-fMRI data. The acquired data were first processed with ICA to obtain the networks of the resting brain. Afterward, the blood-oxygenation level dependent (BOLD) signals of these networks were processed with the fractal analyses for obtaining the fractal parameter α.

RESULTS

α was found to significantly vary across networks, which reveals that the fractal characteristic of LFFs differs across networks. According to prior literatures, this difference could be brought by the discrepancy of hemodynamic response amplitude (HRA) between networks. Hence, in our work, we also performed the computational simulation to discover the relationship between α and HRA. Based on the simulation results, HRA is highly linear-correlated with the fractal characteristics of LFFs which is revealed by α.

CONCLUSION

Our results support that the origin of RS-fMRI signals contains arterial fluctuations. Hence, in addition to the commonly used method such as synchrony analysis and power spectral analysis, another approach, the fractal analysis, is suggested for acquiring the information of hemodynamic responses by means of RS-fMRI data.

Complexity of low-frequency blood oxygen level-dependent fluctuations covaries with local connectivity

Very low-frequency blood oxygen level-dependent (BOLD) fluctuations have emerged as a valuable tool for describing brain anatomy, neuropathology, and development. Such fluctuations exhibit power law frequency dynamics, with largest amplitude at lowest frequencies. The biophysical mechanisms generating such fluctuations are poorly understood. Using publicly available data from 1,019 subjects of age 7-30, we show that BOLD fluctuations exhibit temporal complexity that is linearly related to local connectivity (regional homogeneity), consistently and significantly covarying across subjects and across gray matter regions. This relationship persisted independently of covariance with gray matter density or standard deviation of BOLD signal. During late neurodevelopment, BOLD fluctuations were unchanged with age in association cortex while becoming more random throughout the rest of the brain. These data suggest that local interconnectivity may play a key role in establishing the complexity of low-frequency BOLD fluctuations underlying functional magnetic resonance imaging connectivity. Stable low-frequency power dynamics may emerge through segmentation and integration of connectivity during development of distributed large-scale brain networks.

Predictors of postural stability in children with ADHD

OBJECTIVE

As children with ADHD who have more inattention problems are more frequently with fine motor problems, it is not clear whether postural balance problems are associated with different subtypes of ADHD. This study investigates the predictors of postural stability in children with ADHD considering the covariant factors of age, gender, and comorbidities.

METHOD

A total of 103 children with ADHD are studied using Poor Postural Stability Questionnaire filled out by their parents.

RESULTS

Linear regression analysis indicates that only oppositional-defiant behavior score is the predictor of seeking-movement subscale score. ADHD type does not predict the score of avoiding-postural-instability subscale, whereas separation anxiety score did so.

CONCLUSION

ADHD subtypes do not have distinct clinical profiles of the balance problems. Postural stability in children with ADHD depends on the comorbid psychiatric disorders rather than ADHD subtypes.

Randomness of resting-state brain oscillations encodes Gray's personality trait

Randomness of functional Magnetic Resonance Imaging (fMRI) resting-state time-series has recently been used as a biomarker for numerous disorders including Alzheimer's and Parkinson's disease as well as autism. To date, however, it remains unknown whether and to what degree personality traits are associated with the randomness of resting-state temporal dynamics. To investigate this question, we estimated the Hurst exponent - a measure of the randomness of a time-series - during resting-state fMRI in brain areas previously associated with trait Impulsivity as defined in Gray's Reinforcement Sensitivity Theory of Personality in 15 healthy individuals. The Hurst exponent in the ventral striatum as well as in the orbitofrontal cortex (OFC) was significantly associated with the measure of Gray's trait Impulsivity. Specifically, more random resting-state neural dynamics corresponded to higher Impulsivity scores both in the ventral striatum (r(15)=-.71; p=.003) and the OFC (r(15)=-.81; p<.001). In summary, we provide evidence for an association between individual differences in Gray's Impulsivity and randomness in key areas of the reward system which have previously been associated with this personality trait. Based on evidence from fMRI and electroencephalographical studies, we suggest that this association might arise from resting-state fluctuations constraining task-related neural responsiveness. Thereby, we outline a potential mechanism linking randomness of resting-state dynamics and personality.

A functional MRI study of working memory in adolescents and young adults at genetic risk for bipolar disorder: preliminary findings

OBJECTIVES

In this report, we seek to (i) identify a potential neuroimaging endophenotype for bipolar disorder (BD) in emotion regulatory and autonomic circuitry in young first-degree relatives of persons with BD; and (ii) replicate our previous work identifying the functional neuroanatomy of working memory (WM) in an older sample of relatives of persons with BD.

METHODS

Ten adolescent and young adult (age 13-24) unmedicated, non-ill, first-degree relatives of persons with BD (RELS) and 10 demographically comparable healthy controls performed a 2-back WM task and a 0-back control task during functional magnetic resonance imaging (fMRI). fMRI data were collected on a 1.5 Tesla scanner and analyzed using SPM-2. Mood was assessed on the day of scanning.

RESULTS

The groups did not differ on any demographic, neuropsychological, or in-scanner task performance variables. In contrast to controls, RELS showed (i) weak task-dependent modulation activity in the cerebellar vermis (CV), insula, and amygdala/parahippocampal region, and (ii) exaggerated modulation of activity in the frontopolar cortex and brainstem, even after controlling for potential confounders. Many of the group differences were driven by differences in activity in the low-level (0-back) baseline task.

CONCLUSIONS

Young, unmedicated RELS exhibited altered task-dependent modulation of frontopolar, CV, and insula activity during WM, especially during the low-level (0-back) baseline task. Results are largely consistent with our initial study of older adult RELS, suggesting these alterations may represent biomarkers of genetic risk for BD.

Dopamine D4 receptors modulate brain metabolic activity in the prefrontal cortex and cerebellum at rest and in response to methylphenidate

Methylphenidate (MP) is widely used to treat attention deficit hyperactivity disorder (ADHD). Variable number of tandem repeats polymorphisms in the dopamine D4 receptor (D(4)) gene have been implicated in vulnerability to ADHD and the response to MP. Here we examined the contribution of dopamine D4 receptors (D4Rs) to baseline brain glucose metabolism and to the regional metabolic responses to MP. We compared brain glucose metabolism (measured with micro-positron emission tomography and [(18)F]2-fluoro-2-deoxy-D-glucose) at baseline and after MP (10 mg/kg, i.p.) administration in mice with genetic deletion of the D(4). Images were analyzed using a novel automated image registration procedure. Baseline D(4)(-/-) mice had lower metabolism in the prefrontal cortex (PFC) and greater metabolism in the cerebellar vermis (CBV) than D(4)(+/+) and D(4)(+/-) mice; when given MP, D(4)(-/-) mice increased metabolism in the PFC and decreased it in the CBV, whereas in D(4)(+/+) and D(4)(+/-) mice, MP decreased metabolism in the PFC and increased it in the CBV. These findings provide evidence that D4Rs modulate not only the PFC, which may reflect the activation by dopamine of D4Rs located in this region, but also the CBV, which may reflect an indirect modulation as D4Rs are minimally expressed in this region. As individuals with ADHD show structural and/or functional abnormalities in these brain regions, the association of ADHD with D4Rs may reflect its modulation of these brain regions. The differential response to MP as a function of genotype could explain differences in brain functional responses to MP between patients with ADHD and healthy controls and between patients with ADHD with different D(4) polymorphisms.

Fractals in the nervous system: conceptual implications for theoretical neuroscience

This essay is presented with two principal objectives in mind: first, to document the prevalence of fractals at all levels of the nervous system, giving credence to the notion of their functional relevance; and second, to draw attention to the as yet still unresolved issues of the detailed relationships among power-law scaling, self-similarity, and self-organized criticality. As regards criticality, I will document that it has become a pivotal reference point in Neurodynamics. Furthermore, I will emphasize the not yet fully appreciated significance of allometric control processes. For dynamic fractals, I will assemble reasons for attributing to them the capacity to adapt task execution to contextual changes across a range of scales. The final Section consists of general reflections on the implications of the reviewed data, and identifies what appear to be issues of fundamental importance for future research in the rapidly evolving topic of this review.

Activation of the pre-supplementary motor area but not inferior prefrontal cortex in association with short stop signal reaction time--an intra-subject analysis

BACKGROUND

Our previous work described the neural processes of motor response inhibition during a stop signal task (SST). Employing the race model, we computed the stop signal reaction time (SSRT) to index individuals' ability in inhibitory control. The pre-supplementary motor area (preSMA), which shows greater activity in individuals with short as compared to those with long SSRT, plays a role in mediating response inhibition. In contrast, the right inferior prefrontal cortex (rIFC) showed greater activity during stop success as compared to stop error. Here we further pursued this functional differentiation of preSMA and rIFC on the basis of an intra-subject approach.

RESULTS

Of 65 subjects who participated in four sessions of the SST, we identified 30 individuals who showed a difference in SSRT but were identical in other aspects of stop signal performance between the first ("early") and last two ("late") sessions. By comparing regional brain activation between the two sessions, we confirmed greater preSMA but not rIFC activity during short as compared to long SSRT session within individuals. Furthermore, putamen, anterior cerebellum and middle/posterior cingulate cortex also showed greater activity in association with short SSRT.

CONCLUSION

These results are consistent with a role of medial prefrontal cortex in controlled action and inferior frontal cortex in orienting attention. We discussed these findings with respect to the process of attentional monitoring and inhibitory motor control during stop signal inhibition.

Generic aspects of complexity in brain imaging data and other biological systems

A key challenge for systems neuroscience is the question of how to understand the complex network organization of the brain on the basis of neuroimaging data. Similar challenges exist in other specialist areas of systems biology because complex networks emerging from the interactions between multiple non-trivially interacting agents are found quite ubiquitously in nature, from protein interactomes to ecosystems. We suggest that one way forward for analysis of brain networks will be to quantify aspects of their organization which are likely to be generic properties of a broader class of biological systems. In this introductory review article we will highlight four important aspects of complex systems in general: fractality or scale-invariance; criticality; small-world and related topological attributes; and modularity. For each concept we will provide an accessible introduction, an illustrative data-based example of how it can be used to investigate aspects of brain organization in neuroimaging experiments, and a brief review of how this concept has been applied and developed in other fields of biomedical and physical science. The aim is to provide a didactic, focussed and user-friendly introduction to the concepts of complexity science for neuroscientists and neuroimagers.

Symptoms of hyperactivity and inattention can mediate deficits of postural stability in developmental dyslexia

Developmental dyslexia is a reading disorder associated with impaired postural control. However, such deficits are also found in attention deficit hyperactivity disorder (ADHD), which is present in a substantial subset of dyslexia diagnoses. Very few studies of balance in dyslexia have assessed ADHD symptoms, thereby motivating the hypothesis that such measures can account for the group differences observed. In this study, we assessed adults with dyslexia and similarly aged controls on a battery of cognitive, literacy and attention measures, alongside tasks of postural stability. Displacements of centre of mass to perturbations of posture were measured in four experimental conditions using digital optical motion capture. The largest group differences were obtained in conditions where cues to the support surface were reduced. Between-group differences in postural sway and in sway variability were largely accounted for by co-varying hyperactivity and inattention ratings, however. These results therefore suggest that postural instability in dyslexia is more strongly associated with symptoms of ADHD than to those specific to reading impairment.

Components of variance in a multicentre functional MRI study and implications for calculation of statistical power

This article firstly presents a theoretical analysis of the statistical power of a parallel-group, repeated-measures (two-session) and two-centre design suitable for a placebo-controlled pharmacological MRI study. For arbitrary effect size, power is determined by the pooled between-session error, the pooled measurement error, the ratio of centre measurement errors, the total number of subjects and the proportion of subjects studied at the centre with greatest measurement error. Secondly, an experiment is described to obtain empirical estimates of variance components in task-related and resting state functional magnetic resonance imaging. Twelve healthy volunteers were scanned at two centres during performance of blocked and event-related versions of an affect processing task (each repeated twice per session) and rest. In activated regions, variance components were estimated: between-subject (23% of total), between-centre (2%), between-paradigm (4%), within-session occasion (paradigm repeat; 2%) and residual (measurement) error (69%). The between-centre ratio of measurement errors was 0.8. A similar analysis for the Hurst exponent estimated in resting data showed negligible contributions of between-subject and between-centre variability; measurement error accounted for 99% of total variance. Substituting these estimates in the theoretical expression for power, incorporation of two centres in the design necessitates a modest (10%) increase in the total number of subjects compared with a single-centre study. Furthermore, considerable improvements in power can be attained by repetition of the task within each scanning session. Thus, theoretical models of power and empirical data indicate that between-centre variability can be small enough to encourage multicentre designs without major compensatory increases in sample size.

Monofractal and multifractal dynamics of low frequency endogenous brain oscillations in functional MRI

Fractal processes, like trees or coastlines, are defined by self-similarity or power law scaling controlled by a single exponent, simply related to the fractal dimension or Hurst exponent (H) of the process. Multifractal processes, like turbulence, have more complex behaviours defined by a spectrum of possible local scaling behaviours or singularity exponents (h). Here, we report two experiments that explore the relationships between instrumental and cognitive variables and the monofractal and multifractal parameters of functional magnetic resonance imaging (fMRI) data acquired in a no-task or resting state. First, we show that the Hurst exponent is greater in grey matter than in white matter regions, and it is maximal in grey matter when data were acquired with an echo time known to optimise BOLD contrast. Second, we show that latency of response in a fame decision/facial encoding task was negatively correlated with the Hurst exponent of resting state data acquired 30 min after task performance. This association was localised to a right inferior frontal cortical region activated by the fame decision task and indicated that people with shorter response latency had more persistent dynamics (higher values of H). Multifractal analysis revealed that faster responding participants had wider singularity spectra of resting fMRI time series in inferior frontal cortex. Endogenous brain oscillations measured by fMRI have monofractal and multifractal properties that can be related to instrumental and cognitive factors in a way, which indicates that these low frequency dynamics are relevant to neurocognitive function.

Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the 'resting' brain

Functional magnetic resonance imaging techniques using the blood oxygenation level-dependent (BOLD) contrast are widely used to map human brain function by relating local hemodynamic responses to neuronal stimuli compared to control conditions. There is increasing interest in spontaneous cerebral BOLD fluctuations that are prominent in the low-frequency range (<0.1 Hz) and show intriguing spatio-temporal correlations in functional networks. The nature of these signal fluctuations remains unclear, but there is accumulating evidence for a neural basis opening exciting new avenues to study human brain function and its connectivity at rest. Moreover, an increasing number of patient studies report disease-dependent variation in the amplitude and spatial coherence of low-frequency BOLD fluctuations (LFBF) that may afford greater diagnostic sensitivity and easier clinical applicability than standard fMRI. The main disadvantage of this emerging tool relates to physiological (respiratory, cardiac and vasomotion) and motion confounds that are challenging to disentangle requiring thorough preprocessing. Technical aspects of functional connectivity fMRI analysis and the neuroscientific potential of spontaneous LFBF in the default mode and other resting-state networks have been recently reviewed. This review will give an update on the current knowledge of the nature of LFBF, their relation to physiological confounds and potential for clinical diagnostic and pharmacological studies.

Vestibular Stimulation for ADHD: randomized controlled trial of Comprehensive Motion Apparatus

OBJECTIVE

This research evaluates effects of vestibular stimulation by Comprehensive Motion Apparatus (CMA) in ADHD.

METHOD

Children ages 6 to 12 (48 boys, 5 girls) with ADHD were randomized to thrice-weekly 30-min treatments for 12 weeks with CMA, stimulating otoliths and semicircular canals, or a single-blind control of equal duration and intensity, each treatment followed by a 20-min typing tutorial.

RESULTS

In intent-to-treat analysis (n = 50), primary outcome improved significantly in both groups (p = .0001, d = 1.09 to 1.30), but treatment difference not significant (p = .7). Control children regressed by follow-up (difference p = .034, d = 0.65), but overall difference was not significant (p = .13, d = .47). No measure showed significant treatment differences at treatment end, but one did at follow-up. Children with IQ-achievement discrepancy > or = 1 SD showed significantly more CMA advantage on three measures.

CONCLUSION

This study illustrates the importance of a credible control condition of equal duration and intensity in trials of novel treatments. CMA treatment cannot be recommended for combined-type ADHD without learning disorder.

The role of abnormal neural oscillations in the pathophysiology of co-occurring Tourette syndrome and attention-deficit/hyperactivity disorder

OBJECTIVE

To examine the role of aberrant neural oscillatory activity in the pathophysiology of co-occurring Tourette Syndrome (TS) and Attention-Deficit/Hyperactivity Disorder (ADHD).

METHOD

Neural oscillations refer to periodic variations in the recording of neural activity. The temporal synchronization of oscillations represents a mechanism of neural communication implicated in normal brain functioning as well as psychopathology. We reviewed physiological, imaging, and neuropsychological evidence that tics and symptoms of ADHD may result from abnormal oscillatory activity in the brain.

RESULTS

Structural and functional abnormalities in the cortical-striatal-thalamo-cortical circuits may result in the disruption of oscillatory activity within the basal ganglia of individuals with TS and lead to transient hyperpolarization of selected thalamocortical regions. Extended to TS plus ADHD this or similar mechanisms, in turn, would lead to the dysrhythmia of particular vulnerable cortical regions and give rise to various deficits in motor control (TS + ADHD) as well as impulsivity and attention (ADHD). Compensatory systems within the prefrontal cortex could be activated and trained to modulate the misguided striatal and thalamocortical oscillations.

CONCLUSIONS

Although it is highly likely that abnormal neural oscillations have a prominent role in co-occurrence of TS + ADHD, its final relevance in this case deserves further differentiated research (i.e. oscillatory networks disentangled from other neuropsychiatric disorders).

Efficiency and cost of economical brain functional networks

Brain anatomical networks are sparse, complex, and have economical small-world properties. We investigated the efficiency and cost of human brain functional networks measured using functional magnetic resonance imaging (fMRI) in a factorial design: two groups of healthy old (N = 11; mean age = 66.5 years) and healthy young (N = 15; mean age = 24.7 years) volunteers were each scanned twice in a no-task or "resting" state following placebo or a single dose of a dopamine receptor antagonist (sulpiride 400 mg). Functional connectivity between 90 cortical and subcortical regions was estimated by wavelet correlation analysis, in the frequency interval 0.06-0.11 Hz, and thresholded to construct undirected graphs. These brain functional networks were small-world and economical in the sense of providing high global and local efficiency of parallel information processing for low connection cost. Efficiency was reduced disproportionately to cost in older people, and the detrimental effects of age on efficiency were localised to frontal and temporal cortical and subcortical regions. Dopamine antagonism also impaired global and local efficiency of the network, but this effect was differentially localised and did not interact with the effect of age. Brain functional networks have economical small-world properties-supporting efficient parallel information transfer at relatively low cost-which are differently impaired by normal aging and pharmacological blockade of dopamine transmission.