Concept: Functional neuroimaging
Internet addiction has become increasingly recognized as a mental disorder, though its neurobiological basis is unknown. This study used functional neuroimaging to investigate whole-brain functional connectivity in adolescents diagnosed with internet addiction. Based on neurobiological changes seen in other addiction related disorders, it was predicted that connectivity disruptions in adolescents with internet addiction would be most prominent in cortico-striatal circuitry.
A recent study demonstrates that intersubject variability in functional connectivity is heterogeneous across the cortex, with significantly higher variability in multimodal association cortex. Rather than being ‘noise’, intersubject variability is invaluable for understanding principles of brain evolution and ontogenetic development, and for interpreting statistical maps in task-based functional neuroimaging studies.
Objective To compare initial brain computed tomography (CT) scans with follow-up CT scans at one year in children with congenital Zika syndrome, focusing on cerebral calcifications.Design Case series study.Setting Barão de Lucena Hospital, Pernambuco state, Brazil.Participants 37 children with probable or confirmed congenital Zika syndrome during the microcephaly outbreak in 2015 who underwent brain CT shortly after birth and at one year follow-up.Main outcome measure Differences in cerebral calcification patterns between initial and follow-up scans.Results 37 children were evaluated. All presented cerebral calcifications on the initial scan, predominantly at cortical-white matter junction. At follow-up the calcifications had diminished in number, size, or density, or a combination in 34 of the children (92%, 95% confidence interval 79% to 97%), were no longer visible in one child, and remained unchanged in two children. No child showed an increase in calcifications. The calcifications at the cortical-white matter junction which were no longer visible at follow-up occurred predominately in the parietal and occipital lobes. These imaging changes were not associated with any clear clinical improvements.Conclusion The detection of cerebral calcifications should not be considered a major criterion for late diagnosis of congenital Zika syndrome, nor should the absence of calcifications be used to exclude the diagnosis.
Preoperative functional mapping in children younger than 5 years old remains a challenge. Awake functional MRI (fMRI) is usually not an option for these patients. Except for a description of passive fMRI in sedated patients and magnetoencephalography, no other noninvasive mapping method has been reported as a preoperative diagnostic tool in children. Therefore, invasive intraoperative direct cortical stimulation remains the method of choice. To the authors' knowledge, this is the first case of a young child undergoing preoperative functional motor cortex mapping with the aid of navigated transcranial magnetic stimulation (nTMS). In this 3-year-old boy with a rolandic ganglioglioma, awake preoperative mapping was performed using nTMS. A precise location of Broca area 4 could be established. The surgical approach was planned according to the preoperative findings. Intraoperative direct cortical stimulation verified the location of the nTMS hotspots, and complete resection of the precentral tumor was achieved. Navigated TMS is a precise tool for preoperative motor cortex mapping and is feasible even in very young pediatric patients. In children for whom performing the fMRI motor paradigm is challenging, nTMS is the only available option for functional mapping.
Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are highly heterogeneous and often present with overlapping symptomology, providing challenges in reliable classification and treatment. Single photon emission computed tomography (SPECT) may be advantageous in the diagnostic separation of these disorders when comorbid or clinically indistinct.
In resting-state functional magnetic resonance imaging (fMRI), the temporal correlation between spontaneous fluctuations of the blood oxygenation level dependent (BOLD) signal from different brain regions is used to assess functional connectivity. However, because the BOLD signal is an indirect measure of neuronal activity, its complex hemodynamic nature can complicate the interpretation of differences in connectivity that are observed across conditions or subjects. For example, prior studies have shown that caffeine leads to widespread reductions in BOLD connectivity but were not able to determine if neural or vascular factors were primarily responsible for the observed decrease. In this study, we used source-localized magnetoencephalography (MEG) in conjunction with fMRI to further examine the origins of the caffeine-induced changes in BOLD connectivity. We observed widespread and significant ( < 0.01) reductions in both MEG and fMRI connectivity measures, suggesting that decreases in the connectivity of resting-state neuro-electric power fluctuations were primarily responsible for the observed BOLD connectivity changes. The MEG connectivity decreases were most pronounced in the beta band. By demonstrating the similarity in MEG and fMRI based connectivity changes, these results provide evidence for the neural basis of resting-state fMRI networks and further support the potential of MEG as a tool to characterize resting-state connectivity.
Human functional MRI (fMRI) research primarily focuses on analyzing data averaged across groups, which limits the detail, specificity, and clinical utility of fMRI resting-state functional connectivity (RSFC) and task-activation maps. To push our understanding of functional brain organization to the level of individual humans, we assembled a novel MRI dataset containing 5 hr of RSFC data, 6 hr of task fMRI, multiple structural MRIs, and neuropsychological tests from each of ten adults. Using these data, we generated ten high-fidelity, individual-specific functional connectomes. This individual-connectome approach revealed several new types of spatial and organizational variability in brain networks, including unique network features and topologies that corresponded with structural and task-derived brain features. We are releasing this highly sampled, individual-focused dataset as a resource for neuroscientists, and we propose precision individual connectomics as a model for future work examining the organization of healthy and diseased individual human brains.
Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, concerns have recently been raised that the conclusions that are drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors and a lack of direct replication apply to many fields, but perhaps particularly to functional MRI. Here, we discuss these problems, outline current and suggested best practices, and describe how we think the field should evolve to produce the most meaningful and reliable answers to neuroscientific questions.
There is increasing interest in how the phase of local oscillatory activity within a brain area determines the long-range functional connectivity of that area. For example, increasing convergent evidence from a range of methodologies suggests that beta (20 Hz) oscillations may play a vital role in the function of the motor system [1-5]. The “communication through coherence” hypothesis posits that the precise phase of coherent oscillations in network nodes is a determinant of successful communication between them [6, 7]. Here we set out to determine whether oscillatory activity in the beta band serves to support this theory within the cortical motor network in vivo. We combined non-invasive transcranial alternating-current stimulation (tACS) [8-12] with resting-state functional MRI (fMRI)  to follow both changes in local activity and long-range connectivity, determined by inter-areal blood-oxygen-level-dependent (BOLD) signal correlation, as a proxy for communication in the human cortex. Twelve healthy subjects participated in three fMRI scans with 20 Hz, 5 Hz, or sham tACS applied separately on each scan. Transcranial magnetic stimulation (TMS) at beta frequency has previously been shown to increase local activity in the beta band  and to modulate long-range connectivity within the default mode network . We demonstrated that beta-frequency tACS significantly changed the connectivity pattern of the stimulated primary motor cortex (M1), without changing overall local activity or network connectivity. This finding is supported by a simple phase-precession model, which demonstrates the plausibility of the results and provides emergent predictions that are consistent with our empirical findings. These findings therefore inform our understanding of how local oscillatory activity may underpin network connectivity.
Autism (ASD) is vastly heterogeneous, particularly in early language development. While ASD language trajectories in the first years of life are highly unstable, by early childhood these trajectories stabilize and are predictive of longer-term outcome. Early neural substrates that predict/precede such outcomes are largely unknown, but could have considerable translational and clinical impact. Pre-diagnosis fMRI response to speech in ASD toddlers with relatively good language outcome was highly similar to non-ASD comparison groups and robustly recruited language-sensitive superior temporal cortices. In contrast, language-sensitive superior temporal cortices were hypoactive in ASD toddlers with poor language outcome. Brain-behavioral relationships were atypically reversed in ASD, and a multimodal combination of pre-diagnostic clinical behavioral measures and speech-related fMRI response showed the most promise as an ASD prognosis classifier. Thus, before ASD diagnoses and outcome become clinically clear, distinct functional neuroimaging phenotypes are already present that can shed insight on an ASD toddler’s later outcome. VIDEO ABSTRACT.