Task-dependent individual differences in prefrontal connectivity

Corticostriatal causality analysis in children and adolescents with attention-deficit/hyperactivity disorder

AIM

The effective connectivity between the striatum and cerebral cortex has not been fully investigated in attention-deficit/hyperactivity disorder (ADHD). Our objective was to explore the interaction effects between diagnosis and age on disrupted corticostriatal effective connectivity and to represent the modulation function of altered connectivity pathways in children and adolescents with ADHD.

METHODS

We performed Granger causality analysis on 300 participants from a publicly available Attention-Deficit/Hyperactivity Disorder-200 dataset. By computing the correlation coefficients between causal connections between striatal subregions and other cortical regions, we estimated the striatal inflow and outflow connection to represent intermodulation mechanisms in corticostriatal pathways.

RESULTS

Interactions between diagnosis and age were detected in the superior occipital gyrus within the visual network, medial prefrontal cortex, posterior cingulate gyrus, and inferior parietal lobule within the default mode network, which is positively correlated with hyperactivity/impulsivity severity in ADHD. Main effect of diagnosis exhibited a general higher cortico-striatal causal connectivity involving default mode network, frontoparietal network and somatomotor network in ADHD compared with comparisons. Results from high-order effective connectivity exhibited a disrupted information pathway involving the default mode-striatum-somatomotor-striatum-frontoparietal networks in ADHD.

CONCLUSION

The interactions detected in the visual-striatum-default mode networks pathway appears to be related to the potential distraction caused by long-term abnormal information input from the retina in ADHD. Higher causal connectivity and weakened intermodulation may indicate the pathophysiological process that distractions lead to the impairment of motion planning function and the inhibition/control of this unplanned motion signals in ADHD.

Brain connectivity networks underlying resting heart rate variability in acute ischemic stroke

Acute strokes can affect heart rate variability (HRV), the mechanisms how are not well understood. We included 42 acute stroke patients (2-7 days after ischemic stroke, mean age 66 years, 16 women). For analysis of HRV, 20 matched controls (mean age 60.7, 10 women) were recruited. HRV was assessed at rest, in a supine position and individual breathing rhythmus for 5 min. The coefficient of variation (VC), the root mean square of successive differences (RMSSD), the powers of low (LF, 0.04-0.14 Hz) and high (HF, 0.15-0.50 Hz) frequency bands were extracted. HRV parameters were z-transformed related to age- and sex-matched normal subjects. Z-values < -1 indicate reduced HRV. Acute stroke lesions were marked on diffusion-weighted images employing MRIcroN and co-registered to a T1-weighted structural volume-dataset. Using independent component analysis (ICA), stroke lesions were related to HRV. Subsequently, we used the ICA-derived lesion pattern as a seed and estimated the connectivity between these brain regions and seven common functional networks, which were obtained from 50 age-matched healthy subjects (mean age 68.9, 27 women). Especially, LF and VC were frequently reduced in patients. ICA revealed one covarying lesion pattern for LF and one similar for VC, predominantly affecting the right hemisphere. Activity in brain areas corresponding to these lesions mainly impact on limbic (r = 0.55 ± 0.08) and salience ventral attention networks (0.61 ± 0.10) in the group with reduced LF power (z-score < -1), but on control and default mode networks in the group with physiological LF power (z-score > -1). No different connectivity could be found for the respective VC groups. Our results suggest that HRV alteration after acute stroke might be due to affecting resting-state brain networks.

The role of ipsilateral motor network in upper limb movement

The execution of voluntary movements is primarily governed by the cerebral hemisphere contralateral to the moving limb. Previous research indicates that the ipsilateral motor network, comprising the primary motor cortex (M1), supplementary motor area (SMA), and premotor cortex (PM), plays a crucial role in the planning and execution of limb movements. However, the precise functions of this network and its interplay in different task contexts have yet to be fully understood. Twenty healthy right-handed participants (10 females, mean age 26.1 ± 4.6 years) underwent functional MRI scans while performing biceps brachii representations such as bilateral, unilateral flexion, and bilateral flexion-extension. Ipsilateral motor evoked potentials (iMEPs) were obtained from the identical set of participants in a prior study using transcranial magnetic stimulation (TMS) targeting M1 while employing the same motor tasks. The voxel time series was extracted based on the region of interest (M1, SMA, ventral PM and dorsal PM). Directed functinal connectivity was derived from the extracted time series using time-resolved partial directed coherence. We found increased connectivity from left-PMv to both sides M1, as well as right-PMv to both sides SMA, in unilateral flexion compared to bilateral flexion. Connectivity from left M1 to left-PMv, and left-SMA to right-PMd, also increased in both unilateral flexion and bilateral flexion-extension compared to bilateral flexion. However, connectivity between PMv and right-M1 to left-PMd decreased during bilateral flexion-extension compared to unilateral flexion. Additionally, during bilateral flexion-extension, the connectivity from right-M1 to right-SMA had a negative relationship with the area ratio of iMEP in the dominant side. Our results provide corroborating evidence for prior research suggesting that the ipsilateral motor network is implicated in the voluntary movements and underscores its involvement in cognitive processes such as movement planning and coordination. Moreover, ipsilateral connectivity from M1 to SMA on the dominant side can modulate the degree of ipsilateral M1 activation during bilateral antagonistic contraction.

Interaction Between Memory Load and Experimental Design on Brain Connectivity and Network Topology

The conventional approach to investigating functional connectivity in the block-designed study usually concatenates task blocks or employs residuals of task activation. While providing many insights into brain functions, the block design adds more manipulation in functional network analysis that may reduce the purity of the blood oxygenation level-dependent signal. Recent studies utilized one single long run for task trials of the same condition, the so-called continuous design, to investigate functional connectivity based on task functional magnetic resonance imaging. Continuous brain activities associated with the single-task condition can be directly utilized for task-related functional connectivity assessment, which has been examined for working memory, sensory, motor, and semantic task experiments in previous research. But it remains unclear how the block and continuous design influence the assessment of task-related functional connectivity networks. This study aimed to disentangle the separable effects of block/continuous design and working memory load on task-related functional connectivity networks, by using repeated-measures analysis of variance. Across 50 young healthy adults, behavioral results of accuracy and reaction time showed a significant main effect of design as well as interaction between design and load. Imaging results revealed that the cingulo-opercular, fronto-parietal, and default model networks were associated with not only task activation, but significant main effects of design and load as well as their interaction on intra- and inter-network functional connectivity and global network topology. Moreover, a significant behavior-brain association was identified for the continuous design. This work has extended the evidence that continuous design can be used to study task-related functional connectivity and subtle brain-behavioral relationships.

Altered Structural Brain Network Topology in Patients With Primary Craniocervical Dystonia

Purpose

Regional cortical thickness or volume analyses based upon structural MRI scans have been employed to study the pathophysiology of primary craniocervical dystonia (CCD). In the present study, brain connectivity network analyses based upon morphological distribution similarities among different brain areas were used to study the network disruption in individuals affected by CCD.

Methods

The T1 MRI scans were completed for 37 patients with CCD and 30 healthy controls, with individual brain structural networks being constructed based upon gray matter (GM) similarities in 90 regions within the brain. Area under the curve (AUC) values for each network parameter were determined, and the GRETNA program was used to conduct a graph theory-based measurement of nodal and global network properties. These properties were then compared between healthy controls and those with CCD. In addition, relationships between nodal properties and the severity of clinical dystonia were assessed through Spearman's correlation analyses.

Results

Relative to individuals in the control group, patients with CCD exhibited decreased local nodal properties in the right globus pallidus, right middle frontal gyrus, and right superior temporal pole. The degree of centrality as well as the node efficiency of the right globus pallidus were found to be significantly correlated with ocular dystonic symptom. The node efficiency of right middle frontal gyrus was significantly related to the total motor severity. No nodal properties were significantly correlated with oral dystonic motor scores. Among CCD patients, the right hemisphere exhibited more widespread decreases in connectivity associated with the motor related brain areas, associative cortex, and limbic system, particularly in the middle frontal gyrus, globus pallidus, and cingulate gyrus.

Conclusions

The assessment of morphological correlations between different areas in the brain may represent a sensitive approach for detecting alterations in brain structures and to understand the mechanistic basis for CCD at the network level. Based on the nodal properties identified in this study, the right middle frontal gyrus and globus pallidus were the most severely affected in patients with CCD. The widespread alterations in morphological connectivity, such as the cortico-cortical and cortico-subcortical networks, further support the network mechanism as a basis for CCD.

Dose-response relationship between iTBS and prefrontal activation during executive functioning: A fNIRS study

INTRODUCTION

Intermittent theta-burst stimulation (iTBS) is a non-invasive brain stimulation paradigm that has demonstrated promising therapeutic benefits for a variety of neuropsychiatric disorders. It has recently garnered widespread favor among researchers and clinicians, owing to its comparable potentiation effects as conventional high-frequency repetitive transcranial magnetic stimulation (rTMS), but administered in a much shorter time frame. However, there is still a lack of agreement over the optimal stimulation intensity, particularly when targeting the prefrontal regions. The objective of this study was to systematically investigate the influence of different stimulation intensities of iTBS, applied over the left dorsolateral prefrontal cortex (DLPFC), on brain activity and executive function in healthy adults.

METHODS

Twenty young healthy adults were enrolled in this randomized cross-over experiment. All participants received a single session iTBS over the left DLPFC at intensities of 50, 70, or 100% of their individual resting motor threshold (RMT), each on separate visits. Functional near-infrared spectroscopy (fNIRS) was used to measure changes of hemoglobin concentrations in prefrontal areas during the verbal fluency task (VFT) before and after stimulation.

RESULTS

After stimulation, iTBS to the left DLPFC with 70% RMT maintained the concentration change of oxyhemoglobin (HbO) in the target area during the VFT. In contrast, 50% [t ₍₁₇₎ = 2.203, P = 0.042, d = 0.523] and 100% iTBS [t ₍₁₇₎ = 2.947, P = 0.009, d = 0.547] significantly decreased change of HbO concentration, indicating an inverse U-shape relationship between stimulation intensity and prefrontal hemodynamic response in healthy young adults. Notably, improved VFT performance was only observed after 70% RMT stimulation [t ₍₁₇₎ = 2.511, P = 0.022, d = 0.592]. Moreover, a significant positive correlation was observed between task performance and the difference in HbO concentration change in the targeted area after 70% RMT stimulation (r = 0.496, P = 0.036) but not after 50 or 100% RMT stimulation.

CONCLUSION

The linear relationship between stimulation intensity and behavioral outcomes reported in previous conventional rTMS studies may not be translated to iTBS. Instead, iTBS at 70% RMT may be more efficacious than 100% RMT.

Exploring electroencephalography with a model inspired by quantum mechanics

An outstanding issue in cognitive neuroscience concerns how the brain is organized across different conditions. For instance, during the resting-state condition, the brain can be clustered into reliable and reproducible networks (e.g., sensory, default, executive networks). Interestingly, the same networks emerge during active conditions in response to various tasks. If similar patterns of neural activity have been found across diverse conditions, and therefore, different underlying processes and experiences of the environment, is the brain organized by a fundamental organizational principle? To test this, we applied mathematical formalisms borrowed from quantum mechanisms to model electroencephalogram (EEG) data. We uncovered a tendency for EEG signals to be localized in anterior regions of the brain during “rest”, and more uniformly distributed while engaged in a task (i.e., watching a movie). Moreover, we found analogous values to the Heisenberg uncertainty principle, suggesting a common underlying architecture of human brain activity in resting and task conditions. This underlying architecture manifests itself in the novel constant K_Brain, which is extracted from the brain state with the least uncertainty. We would like to state that we are using the mathematics of quantum mechanics, but not claiming that the brain behaves as a quantum object.

Fronto-cerebellar connectivity mediating cognitive processing speed

Processing speed is an important construct in understanding cognition. This study was aimed to control task specificity for understanding the neural mechanisms underlying cognitive processing speed. Forty young adult subjects performed attention tasks of two modalities (auditory and visual) and two levels of task rules (compatible and incompatible). Block-design fMRI captured BOLD signals during the tasks. Thirteen regions of interest were defined with reference to publicly available activation maps for processing speed tasks. Cognitive speed was derived from task reaction times, which yielded six sets of connectivity measures. Mixed-effect LASSO regression revealed six significant paths suggestive of a cerebello-frontal network predicting the cognitive speed. Among them, three are long range (two fronto-cerebellar, one cerebello-frontal), and three are short range (fronto-frontal, cerebello-cerebellar, and cerebello-thalamic). The long-range connections are likely to relate to cognitive control, and the short-range connections relate to rule-based stimulus-response processes. The revealed neural network suggests that automaticity, acting on the task rules and interplaying with effortful top-down attentional control, accounts for cognitive speed.

Neural primacy of the dorsolateral prefrontal cortex in patients with obsessive-compulsive disorder

The dorsolateral prefrontal cortex (DLPFC), a key structure in the executive system, has consistently emerged as a crucial element in the pathophysiology of obsessive-compulsive disorder (OCD). However, the neural primacy of the DLPFC remains elusive in this disorder. We investigated the causal interaction (measured by effective connectivity) between the DLPFC and the remaining brain areas using bivariate Granger causality analysis of resting-state fMRI collected from 88 medication-free OCD patients and 88 matched healthy controls. Additionally, we conducted seed-based functional connectivity (FC) analyses to identify network-level neural functional alterations using the bilateral DLPFC as seeds. OCD patients demonstrated reduced FC between the right DLPFC and right orbitofrontal cortex (OFC), and activity in the right OFC had an inhibitory effect on the right DLPFC. Additionally, we observed alterations in both feedforward and reciprocal influences between the inferior temporal gyrus (ITG) and the DLPFC in patients. Furthermore, activity in the cerebellum had an excitatory influence on the right DLPFC in OCD patients. These findings may help to elucidate the psychopathology of OCD by detailing the directional connectivity between the DLPFC and the rest of the brain, ultimately helping to identify regions that could serve as treatment targets in OCD.

The neurovascular basis of processing speed differences in humans: A model-systems approach using multiple sclerosis

Behavioral studies investigating fundamental cognitive abilities provide evidence that processing speed accounts for large proportions of performance variability between individuals. Processing speed decline is a hallmark feature of the cognitive disruption observed in healthy aging and in demyelinating diseases such as multiple sclerosis (MS), neuromyelitis optica, and Wilson's disease. Despite the wealth of evidence suggesting a central role for processing speed in cognitive decline, the neural mechanisms of this fundamental ability remain unknown. Intact neurovascular coupling, acute localized blood flow increases following neural activity, is essential for optimal neural function. We hypothesized that efficient coupling forms the neural basis of processing speed. Because MS features neural-glial-vascular system disruption, we used it as a model to test this hypothesis. To assess the integrity of the coupling system, we measured blood-oxygen-level-dependent (BOLD) signal in healthy controls (HCs) and MS patients using a 3T MRI scanner while they viewed radial checkerboards that flickered periodically at 8 ​Hz. To assess processing speed and cognitive function, we administered a battery of neuropsychological tests. While MS patients exhibited reduced ΔBOLD with reductions in processing speed, no such relationships were observed in HCs. To further investigate the mechanisms that underlie ΔBOLD-processing speed relationships, we assessed the physiologic components that constitute ΔBOLD signal (i.e., cerebral blood flow, ΔCBF; cerebral metabolic rate of oxygen, ΔCMRO₂; neurovascular coupling ratio) in speed-preserved and -impaired MS patients. While ΔCBF and ΔCMRO₂ showed no group-differences, the neurovascular coupling ratio was significantly reduced in speed-impaired MS patients compared to speed-preserved MS patients. Together, these results suggest that neurovascular uncoupling might underlie cognitive slowing in MS and might be the central pathogenic mechanism governing processing speed decline.

Enhancing neural efficiency of cognitive processing speed via training and neurostimulation: An fNIRS and TMS study

Speed of Processing (SoP) represents a fundamental limiting step in cognitive performance which may underlie General Intelligence. The measure of SoP is particularly sensitive to aging, neurological or cognitive diseases, and has become a benchmark for diagnosis, cognitive remediation, and enhancement. Neural efficiency of the Dorsolateral Prefrontal Cortex (DLPFC) is proposed to account for individual differences in SoP. However, the mechanisms by which DLPFC efficiency is shaped by training and whether it can be enhanced remain elusive. To address this, we monitored the brain activity of sixteen healthy participants using functional Near Infrared Spectroscopy (fNIRS) while practicing a common SoP task (Symbol Digit Substitution Task) across 4 sessions. Furthermore, in each session, participants received counterbalanced excitatory repetitive transcranial magnetic stimulation (rTMS) during mid-session breaks. Results indicate a significant involvement of the left-DLPFC in SoP, whose neural efficiency is consistently increased through task practice. Active neurostimulation, but not Sham, significantly enhanced the neural efficiency. These findings suggest a common mechanism by which neurostimulation may aid to accelerate learning.

Cortical neural modulation by previous trial outcome differentiates fast- from slow-learning rats on a visuomotor directional choice task

To better understand the neural cortical underpinnings that explain behavioral differences in learning rate, we recorded single-unit activity in primary motor (M1) and secondary motor (M2) areas while rats learned to perform a directional (left or right) operant visuomotor association task. Analysis of neural activity during the early portion of the cue period showed that neural modulation in the motor cortex was most strongly associated with two task factors: the previous trial outcome (success or error) and the current trial's directional choice (left or right). Furthermore, the fast learners, defined as those who had steeper learning curves and required fewer learning sessions to reach criterion performance, encoded the previous trial outcome factor more strongly than the directional choice factor. Conversely, the slow learners encoded directional choice more strongly than previous trial outcome. These differences in task factor encoding were observed in both the percentage of neurons and the neural modulation depth. These results suggest that fast learning is accompanied by a stronger component of previous trial outcome in the modulation representation present in motor cortex, which therefore may be a contributing factor to behavioral differences in learning rate. NEW & NOTEWORTHY We chronically recorded neural activity as rats learned a visuomotor directional choice task from a naive state. Learning rates varied. Single-unit neural modulation of two motor areas revealed that the fast learners encoded previous trial outcome more strongly than directional choice, whereas the reverse was true for slow learners. This finding provides novel evidence that rat learning rate is strongly correlated with the strength of neural modulation by previous trial outcome in motor cortex.

Concussion: pathophysiology and clinical translation

The majority of the 3.8 million estimated annual traumatic brain injuries (TBI) in the United States are mild TBIs, or concussions, and they occur primarily in adolescents and young adults. A concussion is a brain injury associated with rapid brain movement and characteristic clinical symptoms, with no associated objective biomarkers or overt pathologic brain changes, thereby making it difficult to diagnose by neuroimaging or other objective diagnostic tests. Most concussion symptoms are transient and resolve within 1-2 weeks. Concussions share similar acute pathophysiologic perturbations to more severe TBI: there is a rapid release of neurotransmitters, which causes ionic disequilibrium across neuronal membranes. Re-establishing ionic homeostasis consumes energy and leads to dynamic changes in cerebral glucose uptake. The magnitude and duration of these changes are related to injury severity, with milder injuries showing faster normalization. Cerebral sex differences add further variation to concussion manifestation. Relative to the male brain, the female brain has higher overall cerebral blood flow, and demonstrates regional differences in glucose metabolism, inflammatory responses, and connectivity. Understanding the pathophysiology and clinical translation of concussion can move research towards management paradigms that will minimize the risk for prolonged recovery and repeat injury.

Resting-state connectivity and executive functions after pediatric arterial ischemic stroke

Background

The aim of this study was to compare the relationship between core executive functions and frontoparietal network connections at rest between children who had suffered an arterial ischemic stroke and typically developing peers.

Methods

Children diagnosed with arterial ischemic stroke more than two years previously and typically developing controls were included. Executive function (EF) measures comprised inhibition (Go-NoGo task), fluency (category fluency task), processing speed (processing speed tasks), divided attention, working memory (letter-number sequencing), conceptual reasoning (matrices) and EF in everyday life (questionnaire). High-resolution T1-weighted magnetic resonance (MR) structural images and resting-state functional MR imaging were acquired. Independent component analysis was used to identify the frontoparietal network. Functional connections were obtained through correlation matrices; associations between cognitive measures and functional connections through Pearson's correlations.

Results

Twenty participants after stroke (7 females; mean age 16.0 years) and 22 controls (13 females; mean age 14.8 years) were examined. Patients and controls performed within the normal range in all executive tasks. Patients who had had a stroke performed significantly less well in tests of fluency, processing speed and conceptual reasoning than controls. Resting-state functional connectivity between the left and right inferior parietal lobe was significantly reduced in patients after pediatric stroke. Fluency, processing speed and perceptual reasoning correlated positively with the interhemispheric inferior parietal lobe connection in patients and controls.

Conclusion

Decreased interhemispheric connections after stroke in childhood may indicate a disruption of typical interhemispheric interactions relating to executive functions. The present results emphasize the relationship between functional organization of the brain at rest and cognitive processes.

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Interhemispheric frontoparietal connectivity is reduced after pediatric stroke.

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Interhemispheric frontoparietal connectivity relates to executive functions.

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Connectivity-function relation occurs in children, adolescents and young adults.

Higher-order cognitive training effects on processing speed-related neural activity: a randomized trial

Higher-order cognitive training has shown to enhance performance in older adults, but the neural mechanisms underlying performance enhancement have yet to be fully disambiguated. This randomized trial examined changes in processing speed and processing speed-related neural activity in older participants (57-71 years of age) who underwent cognitive training (CT, N = 12) compared with wait-listed (WLC, N = 15) or exercise-training active (AC, N = 14) controls. The cognitive training taught cognitive control functions of strategic attention, integrative reasoning, and innovation over 12 weeks. All 3 groups worked through a functional magnetic resonance imaging processing speed task during 3 sessions (baseline, mid-training, and post-training). Although all groups showed faster reaction times (RTs) across sessions, the CT group showed a significant increase, and the WLC and AC groups showed significant decreases across sessions in the association between RT and BOLD signal change within the left prefrontal cortex (PFC). Thus, cognitive training led to a change in processing speed-related neural activity where faster processing speed was associated with reduced PFC activation, fitting previously identified neural efficiency profiles.

Neural Basis of Video Gaming: A Systematic Review

Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games.

Objectives: We aim to understand the relationship between the use of video games and their neural correlates, taking into account the whole variety of cognitive factors that they encompass.

Methods: A systematic review was conducted using standardized search operators that included the presence of video games and neuro-imaging techniques or references to structural or functional brain changes. Separate categories were made for studies featuring Internet Gaming Disorder and studies focused on the violent content of video games.

Results: A total of 116 articles were considered for the final selection. One hundred provided functional data and 22 measured structural brain changes. One-third of the studies covered video game addiction, and 14% focused on video game related violence.

Conclusions: Despite the innate heterogeneity of the field of study, it has been possible to establish a series of links between the neural and cognitive aspects, particularly regarding attention, cognitive control, visuospatial skills, cognitive workload, and reward processing. However, many aspects could be improved. The lack of standardization in the different aspects of video game related research, such as the participants' characteristics, the features of each video game genre and the diverse study goals could contribute to discrepancies in many related studies.

Cognitive Slowing in Gulf War Illness Predicts Executive Network Hyperconnectivity: Study in a Population-Representative Sample

Cognitive slowing is a prevalent symptom observed in Gulf War Illness (GWI). The present study assessed the extent to which functional connectivity between dorsolateral prefrontal cortex (DLPFC) and other task-relevant brain regions was predictive of GWI-related cognitive slowing. GWI patients (n = 54) and healthy veteran controls (n = 29) were assessed on performance of a processing speed task (the Digit Symbol Substitution Task; DSST) while undergoing functional magnetic resonance imaging (fMRI). GWI patients were slower on the DSST relative to controls. Bilateral DLPFC connectivity with task-relevant nodes was altered in GWI patients compared to healthy controls during DSST performance. Moreover, hyperconnectivity in these networks predicted GWI-related increases in reaction time on the DSST, whereas hypoconnectivity did not. These results suggest that GWI-related cognitive slowing reflects reduced efficiency in cortical networks.

Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data

The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078-0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p < 0.05). Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain's functioning at resting state.

Tutorial on platform for optical topography analysis tools

Optical topography/functional near-infrared spectroscopy (OT/fNIRS) is a functional imaging technique that noninvasively measures cerebral hemoglobin concentration changes caused by neural activities. The fNIRS method has been extensively implemented to understand the brain activity in many applications, such as neurodisorder diagnosis and treatment, cognitive psychology, and psychiatric status evaluation. To assist users in analyzing fNIRS data with various application purposes, we developed a software called platform for optical topography analysis tools (POTATo). We explain how to handle and analyze fNIRS data in the POTATo package and systematically describe domain preparation, temporal preprocessing, functional signal extraction, statistical analysis, and data/result visualization for a practical example of working memory tasks. This example is expected to give clear insight in analyzing data using POTATo. The results specifically show the activated dorsolateral prefrontal cortex is consistent with previous studies. This emphasizes analysis robustness, which is required for validating decent preprocessing and functional signal interpretation. POTATo also provides a self-developed plug-in feature allowing users to create their own functions and incorporate them with established POTATo functions. With this feature, we continuously encourage users to improve fNIRS analysis methods. We also address the complications and resolving opportunities in signal analysis.

The causal interaction within attention networks and emotion network: a fMRI study

fMRI studies have suggested that there are two different attention networks: the dorsal attention network (DAN) and the ventral attention network (VAN). The emotion network has also been discovered by some researches. The dorsal attention network controls goal-oriented top-down deployment of attention; the ventral attention network controls stimulus-driven bottom-up deployment of attention; the emotion network will feed back the stimulus especially fearful expressions from the environment. The interaction within these networks has been noticed but few studies have been carried out. The purpose of this study is to explore the interaction within these networks. The regions of interest were acquired by using the GLM analysis after which the granger causality among these ROIs was calculated. Connections among ROIs were considered as causal when their respective granger causality value is greater than the mean value of all granger causalities. According to the results, there is interaction within the three networks, which suggested that the ventral attention network may distract the dorsal attention network and that the emotion network may influence both attention networks.

Alterations in hippocampal connectivity across the psychosis dimension

Recent evidence demonstrates that hippocampal hyperactivity helps mediate psychosis. Using resting state functional magnetic resonance imaging (rsfMRI), we examined hippocampal connectivity alterations in individuals with psychosis (PS) versus healthy controls (HC). Because of its putative greater involvement in psychiatric disorders, we hypothesized that the anterior hippocampus network would show greater dysconnectivity in psychosis. We tested rsfMRI connectivity in 88 PS (including 21 with schizophrenia; 40 with schizoaffective disorder; 27 with psychotic bipolar I disorder) and 65 HC. Seed-based voxel-wise connectivity analyses were carried out using whole, anterior, and posterior hippocampal seeds. No significant differences in functional hippocampal connectivity were found across the three conventional diagnoses. PS were then contrasted with HC, showing strong reductions in anterior hippocampal connectivity to anterior neocortical regions, including medial frontal and anterior cingulate cortices, as well as superior temporal gyrus, precuneus, thalamus and cerebellum. Posterior hippocampal seeds also demonstrated decreased connectivity in PS, with fewer dysconnected regions and a posterior/cerebellar distribution. Whole hippocampal outcomes were consistent with anterior/posterior hippocampal connectivity changes. Connectivity alterations did not correlate with cognition, clinical symptoms, or medication effect variables. Our results suggest a psychosis network of decreased hippocampal connectivity with limbic and frontal contributions, independent of diagnostic categories.

Functional Connectivity in MRI Is Driven by Spontaneous BOLD Events

Functional brain signals are frequently decomposed into a relatively small set of large scale, distributed cortical networks that are associated with different cognitive functions. It is generally assumed that the connectivity of these networks is static in time and constant over the whole network, although there is increasing evidence that this view is too simplistic. This work proposes novel techniques to investigate the contribution of spontaneous BOLD events to the temporal dynamics of functional connectivity as assessed by ultra-high field functional magnetic resonance imaging (fMRI). The results show that: 1) spontaneous events in recognised brain networks contribute significantly to network connectivity estimates; 2) these spontaneous events do not necessarily involve whole networks or nodes, but clusters of voxels which act in concert, forming transiently synchronising sub-networks and 3) a task can significantly alter the number of localised spontaneous events that are detected within a single network. These findings support the notion that spontaneous events are the main driver of the large scale networks that are commonly detected by seed-based correlation and ICA. Furthermore, we found that large scale networks are manifestations of smaller, transiently synchronising sub-networks acting dynamically in concert, corresponding to spontaneous events, and which do not necessarily involve all voxels within the network nodes oscillating in unison.

Characteristics of canonical intrinsic connectivity networks across tasks and monozygotic twin pairs

Intrinsic connectivity networks (ICNs) are becoming more prominent in the analyses of in vivo brain activity as the field of neurometrics has revealed their importance for augmenting traditional cognitive neuroscience approaches. Consequently, tools that assess the coherence, or connectivity, and morphology of ICNs are being developed to support inferences and assumptions about the dynamics of the brain. Recently, we reported trait-like profiles of ICNs showing reliability over time and reproducibility across different contexts. This study further examined the trait-like and familial nature of ICNs by utilizing two divergent task paradigms in twins. The study aimed to identify stable network phenotypes that exhibited sensitivity to individual differences and external perturbations in task demands. Analogous ICNs were detected in each task and these ICNs showed consistency in morphology and intranetwork coherence across tasks, whereas the ICN timecourse dynamics showed sensitivity to task demands. Specifically, the timecourse of an arm/hand sensorimotor network showed the strongest correlation with the timeline of a hand imitation task, and the timecourse of a language-processing network showed the strongest temporal association with a verb generation task. The area V1/simple visual stimuli network exhibited the most consistency in morphology, coherence, and timecourse dynamics within and across tasks. Similarly, this network exhibited familiality in all three domains as well. Hence, this experiment is a proof of principle that the morphology and coherence of ICNs can be consistent both within and across tasks, that ICN timecourses can be differentially and meaningfully modulated by a task, and that these domains can exhibit familiality.

Functional ultrasound imaging of intrinsic connectivity in the living rat brain with high spatiotemporal resolution

Long-range coherences in spontaneous brain activity reflect functional connectivity. Here we propose a novel, highly resolved connectivity mapping approach, using ultrafast functional ultrasound (fUS), which enables imaging of cerebral microvascular haemodynamics deep in the anaesthetized rodent brain, through a large thinned-skull cranial window, with pixel dimensions of 100 μm × 100 μm in-plane. The millisecond-range temporal resolution allows unambiguous cancellation of low-frequency cardio-respiratory noise. Both seed-based and singular value decomposition analysis of spatial coherences in the low-frequency (<0.1 Hz) spontaneous fUS signal fluctuations reproducibly report, at different coronal planes, overlapping high-contrast, intrinsic functional connectivity patterns. These patterns are similar to major functional networks described in humans by resting-state fMRI, such as the lateral task-dependent network putatively anticorrelated with the midline default-mode network. These results introduce fUS as a powerful novel neuroimaging method, which could be extended to portable systems for three-dimensional functional connectivity imaging in awake and freely moving rodents.

Correspondence of executive function related functional and anatomical alterations in aging brain

Neurocognitive aging studies have focused on age-related changes in neural activity or neural structure but few studies have focused on relationships between the two. The present study quantitatively reviewed 24 studies of age-related changes in fMRI activation across a broad spectrum of executive function tasks using activation likelihood estimation (ALE) and 22 separate studies of age-related changes in gray matter using voxel-based morphometry (VBM). Conjunction analyses between functional and structural alteration maps were constructed. Overlaps were only observed in the conjunction of dorsolateral prefrontal cortex (DLPFC) gray matter reduction and functional hyperactivation but not hypoactivation. It was not evident that the conjunctions between gray matter and activation were related to task performance. Theoretical implications of these results are discussed.

Shorter term aerobic exercise improves brain, cognition, and cardiovascular fitness in aging

Physical exercise, particularly aerobic exercise, is documented as providing a low cost regimen to counter well-documented cognitive declines including memory, executive function, visuospatial skills, and processing speed in normally aging adults. Prior aging studies focused largely on the effects of medium to long term (>6 months) exercise training; however, the shorter term effects have not been studied. In the present study, we examined changes in brain blood flow, cognition, and fitness in 37 cognitively healthy sedentary adults (57–75 years of age) who were randomized into physical training or a wait-list control group. The physical training group received supervised aerobic exercise for 3 sessions per week 1 h each for 12 weeks. Participants' cognitive, cardiovascular fitness and resting cerebral blood flow (CBF) were assessed at baseline (T1), mid (T2), and post-training (T3). We found higher resting CBF in the anterior cingulate region in the physical training group as compared to the control group from T1 to T3. Cognitive gains were manifested in the exercise group's improved immediate and delayed memory performance from T1 to T3 which also showed a significant positive association with increases in both left and right hippocampal CBF identified earlier in the time course at T2. Additionally, the two cardiovascular parameters, VO₂ max and rating of perceived exertion (RPE) showed gains, compared to the control group. These data suggest that even shorter term aerobic exercise can facilitate neuroplasticity to reduce both the biological and cognitive consequences of aging to benefit brain health in sedentary adults.

Is Granger causality a viable technique for analyzing fMRI data?

Multivariate neural data provide the basis for assessing interactions in brain networks. Among myriad connectivity measures, Granger causality (GC) has proven to be statistically intuitive, easy to implement, and generate meaningful results. Although its application to functional MRI (fMRI) data is increasing, several factors have been identified that appear to hinder its neural interpretability: (a) latency differences in hemodynamic response function (HRF) across different brain regions, (b) low-sampling rates, and (c) noise. Recognizing that in basic and clinical neuroscience, it is often the change of a dependent variable (e.g., GC) between experimental conditions and between normal and pathology that is of interest, we address the question of whether there exist systematic relationships between GC at the fMRI level and that at the neural level. Simulated neural signals were convolved with a canonical HRF, down-sampled, and noise-added to generate simulated fMRI data. As the coupling parameters in the model were varied, fMRI GC and neural GC were calculated, and their relationship examined. Three main results were found: (1) GC following HRF convolution is a monotonically increasing function of neural GC; (2) this monotonicity can be reliably detected as a positive correlation when realistic fMRI temporal resolution and noise level were used; and (3) although the detectability of monotonicity declined due to the presence of HRF latency differences, substantial recovery of detectability occurred after correcting for latency differences. These results suggest that Granger causality is a viable technique for analyzing fMRI data when the questions are appropriately formulated.

Top-down regulation of default mode activity in spatial visual attention

Dorsal anterior cingulate and bilateral anterior insula form a task control network (TCN) whose primary function includes initiating and maintaining task-level cognitive set and exerting top-down regulation of sensorimotor processing. The default mode network (DMN), comprising an anatomically distinct set of cortical areas, mediates introspection and self-referential processes. Resting-state data show that TCN and DMN interact. The functional ramifications of their interaction remain elusive. Recording fMRI data from human subjects performing a visual spatial attention task and correlating Granger causal influences with behavioral performance and blood oxygen level-dependent (BOLD) activity we report three main findings. First, causal influences from TCN to DMN, i.e., TCN → DMN, are positively correlated with behavioral performance. Second, causal influences from DMN to TCN, i.e., DMN → TCN, are negatively correlated with behavioral performance. Third, stronger DMN → TCN are associated with less elevated BOLD activity in TCN, whereas the relationship between TCN → DMN and DMN BOLD activity is unsystematic. These results suggest that, during visual spatial attention, top-down signals from TCN to DMN regulate the activity in DMN to enhance behavioral performance, whereas signals from DMN to TCN, acting possibly as internal noise, interfere with task control, leading to degraded behavioral performance.

Isolating age-group differences in working memory load-related neural activity: assessing the contribution of working memory capacity using a partial-trial fMRI method

Previous studies examining age-group differences in working memory load-related neural activity have yielded mixed results. When present, age-group differences in working memory capacity are frequently proposed to underlie these neural effects. However, direct relationships between working memory capacity and working memory load-related activity have only been observed in younger adults. These relationships remain untested in healthy aging. Therefore, the present study examined patterns of working memory load-related activity in 22 younger and 20 older adults and assessed the contribution of working memory capacity to these load-related effects. Participants performed a partial-trial delayed response item recognition task during functional magnetic resonance imaging. In this task, participants encoded either 2 or 6 letters, maintained them during a delay, and then indicated whether a probe was present in the memory set. Behavioral results revealed faster and more accurate responses to load 2 versus 6, with age-group differences in this load condition effect for the accuracy measure. Neuroimaging results revealed one region (medial superior frontal gyrus) that showed age-group differences in load-related activity during the retrieval period, with less (greater) neural activity for the low versus high load condition in younger (older) adults. Furthermore, for older adults, load-related activity did not vary as a function of working memory capacity. Thus, working memory-related activity varies with healthy aging, but these patterns are not due solely to working memory capacity. Neurocognitive aging theories that feature capacity will need to account for these results.

Reduced specificity of functional connectivity in the aging brain during task performance

The importance of studying connectivity in the aging brain is increasingly recognized. Recent studies have shown that connectivity within the default mode network is reduced with age and have demonstrated a clear relation of these changes with cognitive functioning. However, research on age-related changes in other functional networks is sparse and mainly focused on prespecified functional networks. Using functional magnetic resonance imaging, we investigated age-related changes in functional connectivity during a visual oddball task in a range of functional networks. It was found that compared with young participants, elderly showed a decrease in connectivity between areas belonging to the same functional network. This was found in the default mode network and the somatomotor network. Moreover, in all identified networks, elderly showed increased connectivity between areas within these networks and areas belonging to different functional networks. Decreased connectivity within functional networks was related to poorer cognitive functioning in elderly. The results were interpreted as a decrease in the specificity of functional networks in older participants.

Causal interactions in attention networks predict behavioral performance

Lesion and functional brain imaging studies have suggested that there are two anatomically nonoverlapping attention networks. The dorsal frontoparietal network controls goal-oriented top-down deployment of attention; the ventral frontoparietal network mediates stimulus-driven bottom-up attentional reorienting. The interaction between the two networks and its functional significance has been considered in the past but no direct test has been carried out. We addressed this problem by recording fMRI data from human subjects performing a trial-by-trial cued visual spatial attention task in which the subject had to respond to target stimuli in the attended hemifield and ignore all stimuli in the unattended hemifield. Correlating Granger causal influences between regions of interest with behavioral performance, we report two main results. First, stronger Granger causal influences from the dorsal attention network (DAN) to the ventral attention network (VAN), i.e., DAN→VAN, are generally associated with enhanced performance, with right intraparietal sulcus (IPS), left IPS, and right frontal eye field being the main sources of behavior-enhancing influences. Second, stronger Granger causal influences from VAN to DAN, i.e., VAN→DAN, are generally associated with degraded performance, with right temporal-parietal junction being the main sources of behavior-degrading influences. These results support the hypothesis that signals from DAN to VAN suppress and filter out unimportant distracter information, whereas signals from VAN to DAN break the attentional set maintained by the dorsal attention network to enable attentional reorienting.

Prediction of Task-Related BOLD fMRI with Amplitude Signatures of Resting-State fMRI

Blood oxygen contrast-functional magnetic resonance imaging (fMRI) signals are a convolution of neural and vascular components. Several studies indicate that task-related (T-fMRI) or resting-state (R-fMRI) responses linearly relate to hypercapnic task responses. Based on the linearity of R-fMRI and T-fMRI with hypercapnia demonstrated by different groups using different study designs, we hypothesized that R-fMRI and T-fMRI signals are governed by a common physiological mechanism and that resting-state fluctuation of amplitude (RSFA) should be linearly related to T-fMRI responses. We tested this prediction in a group of healthy younger humans where R-fMRI, T-fMRI, and hypercapnic (breath hold, BH) task measures were obtained form the same scan session during resting state and during performance of motor and BH tasks. Within individual subjects, significant linear correlations were observed between motor and BH task responses across voxels. When averaged over the whole brain, the subject-wise correlation between the motor and BH tasks showed a similar linear relationship within the group. Likewise, a significant linear correlation was observed between motor-task activity and RSFA across voxels and subjects. The linear rest-task (R-T) relationship between motor activity and RSFA suggested that R-fMRI and T-fMRI responses are governed by similar physiological mechanisms. A practical use of the R-T relationship is its potential to estimate T-fMRI responses in special populations unable to perform tasks during fMRI scanning. Using the R-T relationship determined from the first group of 12 healthy subjects, we predicted the T-fMRI responses in a second group of 7 healthy subjects. RSFA in both the lower and higher frequency ranges robustly predicted the magnitude of T-fMRI responses at the subject and voxel levels. We propose that T-fMRI responses are reliably predictable to the voxel level in situations where only R-fMRI measures are possible, and may be useful for assessing neural activity in task non-compliant clinical populations.

Reduced speech perceptual acuity for stop consonants in individuals who stutter

PURPOSE

In individuals who stutter (IWS), speech fluency can be enhanced by altered auditory feedback, although it has adverse effects in control speakers. This indicates abnormalities in the auditory feedback loop in stuttering. Current motor control theories on stuttering propose an impaired processing of internal forward models that might be related to a blurred auditory-to-motor translation. Although speech sound perception is an essential skill to form internal models, perceptual acuity has not been studied in IWS so far. The authors tested the stability of phoneme percepts by analyzing participants' ability to identify voiced and voiceless stop consonants.

METHOD

Two syllable continua were generated by systematic modification of the voice onset time. The authors determined speech perceptual acuity by means of discriminatory power in 25 IWS and 24 matched control participants by determining the phoneme boundaries and by quantifying the interval of voice onset times for which phonemes were perceived ambiguously.

RESULTS

In IWS, discriminatory performance was weaker and less stable over time when compared with control participants. In addition, phoneme boundaries were located at longer voice onset times in IWS.

CONCLUSION

Persistent developmental stuttering is associated with less reliable phonological percepts, supporting current theories regarding the sensory-motor interaction in human speech.

Resting state fMRI: a personal history

The goal of this review is to describe, from a personal perspective, the development and emergence of the resting state fMRI. In particular, various concepts derived from the resting state data are discussed in detail, including connectivity, amplitude of the fluctuations, analysis techniques, and use in clinical populations. We also briefly summarize our efforts in creating an open data sharing platform as well as both a journal and a conference dedicated to brain connectivity. All three projects are aimed at significantly increasing the impact of resting state fMRI developments and enabling large, collaborative science projects.

Functional connectivity in vergence and saccade eye movement tasks assessed using Granger Causality analysis

Throughout the day, the human visual system acquires information using saccade and vergence eye movements. Previously, functional MRI (fMRI) experiments have shown both shared neural resources and spatial differentiation between these two systems. FMRI experiments can reveal which regions are activated within an experimental task but do not yield insight into how regions of interest (ROIs) interact with each other. This study investigated the number and direction of influences among ROIs using a Granger Causality Analysis (GCA)--a statistical technique used to identify if an ROI is significantly influencing or 'connected' to another ROI. Two stimulus protocols were used: first, a simple block design of fixation versus random eye movements; and second, a more cognitively demanding task using random versus predictable movements. Each protocol used saccadic movements and was then repeated using vergence movements. Eight subjects participated in each of the four experiments. Results show that when prediction was evoked, more connections between ROIs were observed compared to the simple tracking experiment. More connections were also observed during the vergence prediction task compared to the saccade prediction task. Differences within the number of connections may be due to the type of oculomotor eye movements, as well as to the amount of higher-level executive cognitive demand.