Traditional Neuroimaging Methods Research Articles

Graph Analysis of the Visual Cortical Network during Naturalistic Movie Viewing Reveals Increased Integration and Decreased Segregation Following Mild TBI.

Traditional neuroimaging methods have identified alterations in brain activity patterns following mild traumatic brain injury (mTBI), particularly during rest, complex tasks, and normal vision. However, studies using graph theory to examine brain network changes in mTBI have produced varied results, influenced by the specific networks and task demands analyzed. In our study, we employed functional MRI to observe 17 mTBI patients and 54 healthy individuals as they viewed a simple, non-narrative underwater film, simulating everyday visual tasks. This approach revealed significant mTBI-related changes in network connectivity, efficiency, and organization. Specifically, the mTBI group exhibited higher overall connectivity and local network specialization, suggesting enhanced information integration without overwhelming the brain's processing capabilities. Conversely, these patients showed reduced network segregation, indicating a less compartmentalized brain function compared to healthy controls. These patterns were consistent across various visual cortex subnetworks, except in primary visual areas. Our findings highlight the potential of using naturalistic stimuli in graph-based neuroimaging to understand brain network alterations in mTBI and possibly other conditions affecting brain integration.

The impact of traditional neuroimaging methods on the spatial localization of cortical areas

Localizing human brain functions is a long-standing goal in systems neuroscience. Toward this goal, neuroimaging studies have traditionally used volume-based smoothing, registered data to volume-based standard spaces, and reported results relative to volume-based parcellations. A novel 360-area surface-based cortical parcellation was recently generated using multimodal data from the Human Connectome Project, and a volume-based version of this parcellation has frequently been requested for use with traditional volume-based analyses. However, given the major methodological differences between traditional volumetric and Human Connectome Project-style processing, the utility and interpretability of such an altered parcellation must first be established. By starting from automatically generated individual-subject parcellations and processing them with different methodological approaches, we show that traditional processing steps, especially volume-based smoothing and registration, substantially degrade cortical area localization compared with surface-based approaches. We also show that surface-based registration using features closely tied to cortical areas, rather than to folding patterns alone, improves the alignment of areas, and that the benefits of high-resolution acquisitions are largely unexploited by traditional volume-based methods. Quantitatively, we show that the most common version of the traditional approach has spatial localization that is only 35% as good as the best surface-based method as assessed using two objective measures (peak areal probabilities and "captured area fraction" for maximum probability maps). Finally, we demonstrate that substantial challenges exist when attempting to accurately represent volume-based group analysis results on the surface, which has important implications for the interpretability of studies, both past and future, that use these volume-based methods.

It's a matter of time: Reframing the development of cognitive control as a modification of the brain's temporal dynamics

Cognitive control is a process that unfolds over time and regulates thought and action in the service of achieving goals and managing unanticipated challenges. Prevailing accounts attribute the protracted development of this mental process to incremental changes in the functional organization of a cognitive control network. Here, we challenge the notion that cognitive control is linked to a topologically static network, and argue that the capacity to manage unanticipated challenges and its development should instead be characterized in terms of inter-regional functional coupling dynamics. Ongoing changes in temporal coupling have long represented a fundamental pillar in both empirical and theoretical-based accounts of brain function, but have been largely ignored by traditional neuroimaging methods that assume a fixed functional architecture. There is, however, a growing recognition of the importance of temporal coupling dynamics for brain function, and this has led to rapid innovations in analytic methods. Results in this new frontier of neuroimaging suggest that time-varying changes in connectivity strength and direction exist at the large scale and further, that network patterns, like cognitive control process themselves, are transient and dynamic.

Online fronto-cortical control of simple and attention-demanding locomotion in humans

Knowledge of online functional brain mechanisms of locomotion is scarce due to technical limitations of traditional neuroimaging methods. Using functional Near Infrared Spectroscopy (fNIRS) we evaluated task-related changes in oxygenated hemoglobin levels (HbO2) in real-time over the pre-frontal-cortex (PFC) regions during simple (Normal Walk; NW) and attention-demanding (Walking While Talking; WWT) locomotion tasks in a large cohort of non-demented older adults. Results revealed that the assessment of task-related changes in HbO2 was internally consistent. Imposing greater demands on the attention system during locomotion resulted in robust bilateral PFC increases in HbO2 levels during WWT compared to NW and the cognitive interference tasks. Elevated PFC oxygenation levels were maintained throughout the course of WWT but not during the NW condition. Increased oxygenation levels in the PFC were related to greater stride length and better cognitive performance but not to faster gait velocity in WWT. These findings elucidate online brain mechanisms of locomotion, and confer significant implications for risk assessment and intervention for major mobility outcomes.

Progress in speech decoding from the electrocorticogram

Recent advances in neuroimaging methods have improved our ability to explore the neurological processes underlying speech and language. As a result of these investigations, it is now possible to decode aspects of speech directly from neural activity toward the development of neuroprosthetic devices for individuals with severe neuromuscular and communication disorders. Much of what is known about the neural correlates of speech articulation and perception is based on lesion and cortical electrical stimulation studies, as well as modern non-invasive neuroimaging. Though extremely important to the current understanding of brain function, traditional neuroimaging methods are primarily limited by the spatial and temporal resolution of the imaging technique. Electrical activity measured from the cortex, or electrocorticography (ECoG), offers several advantages over other neuroimaging modalities for characterization and real-time decoding of brain activity. Specifically, ECoG is well-suited for the study of speech and language owing to its unique spatial and temporal resolution capabilities that allow it to accurately capture the fast-changing dynamics of the large cortical networks underlying speech processing. This review presents the current progress of ECoG-based speech characterization and decoding studies, including an overview of prior neuroimaging studies, ECoG representations of speech production and perception, and a discussion of future directions.

Mapping human brain networks with cortico-cortical evoked potentials

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex.

Applying Functional Near Infrared (fNIR) Spectroscopy to Enhance MIS Research

This review paper introduces the emerging technology of optical brain imaging, also known as functional near infrared (fNIR) spectroscopy, and discusses its potential role in enhancing theory and methodology used in MIS research. We discuss basic fNIR principles including the technique’s safe and portable nature, which allows ambulatory brain activity assessment in real world environments. We then touch on the neural correlates that fNIR measures, and the cortical oxygenation changes in the dorsal and anterior regions of the prefrontal cortex. We compare fNIR with traditional neuroimaging methods such as fMRI and PET. We also list case studies, future directions, and potential approaches relevant to MIS. fNIR may be used to inform theory and improve assessments in MIS-based studies, including informing theory, by identifying neural correlates, studying constructs that could not easily if at all be measured with traditional methods, applying objective constructs that subjects are unaware of, and designing better surveys.

Neurometabolic, electrophysiological, and imaging abnormalities.

Sport-related concussions affect millions of athletes every year, but they generally present no anatomic alterations when examined using conventional magnetic resonance imaging or a computed tomography scan. Because the damage occurring after a head injury seems to be more functional than structural, these techniques are unable to detect subtle alterations. The absence of detectable structural alterations using traditional neuroimaging methods, the presence of persistent symptoms in some athletes, and the risk of developing neurodegenerative diseases emphasize the importance of assessing the impacts of a head injury with alternative neuroimaging techniques. Electrophysiological methods, magnetic resonance spectroscopy, and diffusion tensor imaging are useful techniques that are sensitive to the effects of a brain trauma, which provide complementary information to allow a more complete understanding of the multiple pathophysiological processes involved in concussive events. This report summarizes recent data using neurophysiological and neuroimaging techniques to better understand the acute and chronic effects of sport-related concussions.

Beyond Brain Mapping

One goal of social science in general, and of psychology in particular, is to understand and predict human behavior. Psychologists have traditionally used self-report measures and performance on laboratory tasks to achieve this end. However, these measures are limited in their ability to predict behavior in certain contexts. We argue that current neuroscientific knowledge has reached a point where it can complement other existing psychological measures in predicting behavior and other important outcomes. This brain-as-predictor approach integrates traditional neuroimaging methods with measures of behavioral outcomes that extend beyond the immediate experimental session. Previously, most neuroimaging experiments focused on understanding basic psychological processes that could be directly observed in the laboratory. However, recent experiments have demonstrated that brain measures can predict outcomes (e.g., purchasing decisions, clinical outcomes) over longer timescales in ways that go beyond what was previously possible with self-report data alone. This approach can be used to reveal the connections between neural activity in laboratory contexts and longer-term, ecologically valid outcomes. We describe this approach and discuss its potential theoretical implications. We also review recent examples of studies that have used this approach, discuss methodological considerations, and provide specific guidelines for using it in future research.

A prospective study of physician-observed concussion during a varsity university hockey season: metabolic changes in ice hockey players. Part 4 of 4

Despite negative neuroimaging findings using traditional neuroimaging methods such as MRI and CT, sports-related concussions have been shown to cause neurometabolic changes in both the acute and subacute phases of head injury. However, no prospective clinical study has used an independent physician-observer design in the monitoring of these changes. The objective of this study was to evaluate the effects of repetitive concussive and sub-concussive head impacts on neurometabolic concentrations in a prospective study of two Canadian Interuniversity Sports (CIS) ice hockey teams using MR spectroscopy (MRS). Forty-five ice hockey players (25 men and 20 women) participated in this study. All participants underwent pre- and postseason MRI, including spectroscopy imaging, using a 3-T MRI machine. The linear combination model was used to quantify the following ratios: glutamate/creatine-phosphocreatine (Cr), myoinositol/Cr, and N-acetylaspartate (NAA)/Cr. Individuals sustaining a medically diagnosed concussion were sent for MRI at 72 hours, 2 weeks, and 2 months after injury. No statistically significant differences were observed between athletes who were diagnosed with a concussion and athletes who were not clinically diagnosed as sustaining a concussion. Although no statistically significant longitudinal metabolic changes were observed among athletes who were diagnosed with a concussion, the results demonstrated a predictable pattern of initial impairment, followed by a gradual return to ratios that were similar to, but lower than, baseline ratios. No significant pre- to postseason changes were demonstrated among men who were not observed to sustain a concussion. However, a substantively significant decrease in the NAA/Cr ratio was noted among the female hockey players (t((13)) = 2.58, p = 0.02, η(2) = 0.34). A key finding in this study, from the standpoint of future research design, is the demonstration of substantively significant metabolic changes among the players who were not diagnosed with a concussion. In addition, it may explain why there are few statistically significant differences demonstrated between players who were diagnosed with a concussion and players who were not diagnosed with a concussion (that is, the potency of the independent variable was diminished by the fact that the group of players not diagnosed with a concussion might be better described as a subgroup of the players who may have sustained a concussion but were not observed and diagnosed with a concussion). This result suggests that definitions of concussion may need to be revisited within sports with high levels of repetitive subconcussive head impacts. Future analysis of these data will examine the relationships between the modes of MRI (diffusion tensor imaging, MRS, and susceptibility-weighted MR imaging) used in this study, along with other more sensitive evaluative techniques. This type of intermodal comparison may improve the identification of concussions that were previously dependent on the unreliable self-reporting of recognized concussion symptomatology by the athlete or on poorly validated neuropsychological tests.

Task complexity relates to activation of cortical motor areas during uni- and bimanual performance: A functional NIRS study

Hand motor tasks are frequently used to assess impaired motor function in neurology and neurorehabilitation. Assessments can be varied by means of hand laterality, i.e. unimanual or bimanual performance, as well as by means of task complexity, i.e. different degrees ranging from simple to complex sequence tasks. The resulting functional activation in human primary motor cortex (M1) has been studied intensively by traditional neuroimaging methods.Previous studies using functional near-infrared spectroscopy (fNIRS) investigated simple hand motor tasks. However, it is unknown whether fNIRS can also detect changes in response to increasing task complexity. Our hypothesis was to show that fNIRS could detect activation changes in relation to task complexity in uni- and bimanual tasks.Sixteen healthy right-handed subjects performed five finger-tapping tasks: unimanual left and right, simple and complex tasks as well as bimanual complex tasks. We found significant differences in oxy-hemoglobin (O2Hb) and deoxy-hemoglobin (HHb) concentration in the right hemisphere over M1. Largest O2Hb concentration changes were found during complex (0.351±0.051 μmol/l) and simple (0.275±0.054 μmol/l) right hand tasks followed by bimanual (0.249±0.047 μmol/l), complex (0.154±0.034 μmol/l) and simple (0.110±0.034 μmol/l) left hand tasks. Largest HHb concentration changes were found during bimanual (−0.138±0.006 μmol/l) tasks, followed by simple right hand (−0.12±0.016 μmol/l), complex left (−0.0875±0.007 μmol/l), complex right (−0.0863±0.005 μmol/l) and simple left (−0.0674±0.005 μmol/l) hand tasks.We report for the first time that fNIRS detects oxygenation changes in relation to task complexity during finger-tapping. The study aims to contribute to the establishment of fNIRS as a neuroimaging method to assess hand motor function in clinical settings where traditional neuroimaging methods cannot be applied.