Future Trends in Functional MRI

While MRI became a standard workhorse in neurology/neurosurgery within a few years of installation of the first MRI unit, fMRI, in spite of being a powerful imaging tool, remains primarily a research tool, even though the first fMRI study was published 25 years ago. Scientifically, fMRI has made a major impact, judging by the number of PubMed citations and publications in high-impact journals. In cognitive neuroscience, fMRI is the most commonly used imaging technique in published peer-reviewed articles. fMRI is used clinically for preoperative brain mapping in neurosurgery to delineate the proximity of the lesion (tumor) to eloquent areas of the brain, with the aim of achieving adequate tumor resection with minimal functional damage to the brain. fMRI connectivity and activation maps have identified altered activation patterns and resting-state networks in psychiatric disorders like schizophrenia, bipolar disorder, autism, and Alzheimer’s disease, but fMRI is still not a standard diagnostic procedure in psychiatry. Diffusion imaging technique is being used for triaging stroke patients who are likely to respond to stroke therapy (embolectomy and/or clot lysis). Meanwhile, major collaborative fMRI studies are in progress in many institutions to collect normative data on connectivity, activation response, and behavioral response as well as correlation among them. Studies focused on specific neuropsychiatric disorders also have been initiated by the National Institutes of Health. All this is a reflection of the huge potential application of fMRI in clinical practice envisioned by the scientific community.

Functional MRI in Anesthesia and Resting-State Networks

This chapter reviews current knowledge of the effects of hypnotic anesthetic agents on brain resting-state networks (RSNs) that sustain consciousness. Although full exploration of the networks under anesthesia is not yet available, current evidence indicates that anesthetic agents with hypnotic properties dose-dependently modulate RSN functioning. Each anesthetic agent has specific effects that are not uniform within a given network and probably correlate with the specific clinical features observed when one agent or another is used. Observations made on RSNs during anesthesia are supplementary arguments to link the networks with specific aspects of consciousness and connectedness to the environment and to confirm their physiological functions. The precise link between observations made on RSNs during anesthesia and known biochemical targets of anesthetic agents, or their effects on systems that regulate the sleep–wake cycle, is not established yet. PET studies using radiolabeled probes that specifically target a neurotransmission system offer insights into the links. New technological advances and modes of functional data analysis, such as Granger causality and dynamic causal modeling, will help in obtaining a more in-depth exploration of the complex interactions between brain regions, their modulation by anesthesia, and their role in information processing by the brain. Effects of hypnosis on RSNs also have been studied. The hypnotic state is useful for performing surgical procedures and explorations without general anesthesia. The hypnotic state is associated with specific changes in the activity of RSNs that confirm hypnosis as a specific brain state, different from normal wakeful consciousness and anesthetic states.

Functional MRI in Pediatric Neurodevelopmental and Behavioral Disorders

This chapter addresses functional magnetic resonance imaging (fMRI) of brain in children with neurodevelopmental and behavioral disorders. Common challenges of pediatric fMRI studies are related to acquisition and processing. In children with disruptive behavior disorders, deficits in affective response, empathy, and decision-making have been reported. Resting-state fMRI studies in attention-deficit hyperactivity disorder (ADHD) have shown altered activity in default mode and cognitive control networks. Task-based fMRI studies in ADHD have implicated frontoparietal cognitive and attentional networks. The role of stimulants in restoring the altered brain function has been examined using fMRI studies. In children with autism spectrum disorder, fMRI studies using face-processing tasks, theory-of-mind tasks, imitation, and language processing (e.g., sentence comprehension), as well as studies of gaze aversion, interest in social faces, and faces with emotions have implicated cerebellum, amygdala, hippocampus, insula, fusiform gyrus, superior temporal sulcus, planum temporale, inferior frontal gyrus, basal ganglia, thalamus, cingulate cortex, corpus callosum, and brainstem. In addition, fMRI has been a valuable research tool for understanding neurobiological substrates in children with psychiatric disorders (e.g., psychosis, posttraumatic stress disorder, and anxiety disorders).

Functional MRI Approaches to Studying Cognition

Functional magnetic resonance imaging (fMRI) is a widely used technique for studying brain substrates of cognition. The objective of this chapter is to provide an overview of the basics of fMRI including fundamentals of MR physics and the blood oxygen level dependent (BOLD) contrast, paradigm design, data storage, image quality analysis, data pre-processing and data analytic strategies. We have discussed three illustrative examples from our published research works in schizophrenia, a neurodevelopmental disorder characterized by cognitive dysfunction and abnormalities of thought, perception and conation. We attempt to provide a broad understanding of the basic principles of fMRI research for clinicians and budding cognitive neuroscience researchers alike, without aiming to be exhaustive or in-depth in our coverage. We hope this primer in fMRI methods and applications would motivate the reader to peruse the additional resources cited at the end of the chapter while getting started in this exciting area of research.

Functional MRI Studies of Cognitive Evaluation in the Elderly

Over the last century, life expectancy has improved significantly in the United States—from 47 years for men and 49 years for women in 1900 to 76 years and 81 years, respectively, in 2017. Older people have altered mental function that can vary from subtle cognitive changes to dementia. Additionally in elderly patients cognitive function seems to worsen after a medical illness, hospital admission or major surgery. The cognitive neuroscience of aging is an emerging field of research. Clinically, older patients can show alteration in working memory, executive function, multitasking, speed of response, etc. Anatomically, age-related changes in the brain are primarily in the frontal lobe. However, in neuropathological diseases affecting cognition in elderly (Alzheimer’s disease, Huntington’s disease, etc.), the changes are primarily in the temporal lobe. fMRI activation studies have revealed consistent changes in activation pattern with age. In younger persons, many activation-induced responses are lateralized—verbal activation is lateralized to the left and spatial memory activation is right lateralized. In the elderly, these activations induce a bilateral response. This is an age-related compensatory response. fMRI connectivity studies give a global perspective on mental function. The default mode network (DMN) is active in the resting “no task” state of the brain; with a task, activity decreases in the DMN. The elderly have less resting DMN activity than younger people, and their ability to decrease DMN activity during a task (which is essential for shifting attention and focusing on a task) is also less.

Functional MRI in Psychiatric Disorders

sSince its introduction to clinical research, functional magnetic resonance imaging (fMRI) has had a pivotal role in understanding the systems-level neural substrates of psychiatric disorders. fMRI is a powerful tool for the field of psychiatry because it is well suited to studying large-scale neural systems and distributed neuropathology, which are thought to underlie many of the behavioral symptoms in psychiatric conditions. This chapter highlights key fMRI findings in four major types of psychiatric disorders: schizophrenia, mood disorders (including major depressive disorder and bipolar disorder), obsessive-compulsive disorder, and posttraumatic stress disorder.

Functional MRI in Neurosurgery and Neurology

The relationship between neuroimaging and the care of patients with neurosurgical and neurological disorders has long been a close one. The integration of these fields dates back to neuroimaging’s earliest days in the 20th century. However, no single imaging technique has had the enduring impact on clinical medicine that magnetic resonance imaging (MRI) has. The impact of MRI has resulted not only from an enhanced understanding of structural abnormalities but also the functional implications of those abnormalities. Beyond this, advances in functional neuroimaging have improved our understanding not only of the functional correlates of lesion disorders but also of non-lesion conditions including developmental, degenerative and movement disorders as well as predicting rehabilitation potential following stroke or traumatic brain injury. The advent of functional MRI (fMRI), which capitalizes on the relationship between cerebral blood flow and neuronal activity, combines all of these advantages together with the ability to define regions of brain activity, or function, and has further revolutionized the clinical care of patients with neurosurgical and neurological disorders. Here, we discuss current fMRI techniques as well as their clinical application to the care of patients with neurosurgical and neurological disorders. We also briefly review other functional imaging modalities beyond fMRI.

Functional MRI in the Intensive Care Unit

Magnetic resonance imaging (MRI) technology has revolutionized medical and scientific imaging, has had an important effect on research, and has become a great source of valuable information on the functioning of the major organs of the human body. The role of fMRI (functional MRI) in the intensive care unit is growing, and different fMRI techniques have been used to assess the brain, the lung, and the abdomen of patients. fMRI has been used to assess the brain of an acutely comatose or delirious patient and to detect subtle pathological changes in traumatic brain injury from the acute phase to the chronic phase. Pulmonary MRI is used for the assessment of regional functional changes (perfusion, ventilation, and oxygen diffusion) in patients with airway diseases and, due to better spatial and temporal resolution, for regional functional assessment and for evaluation of the possibility of morphologic changes in a single examination. Cardiac MRI has shown high reproducibility and accuracy, allowing detailed functional assessment and characterization of myocardial tissue and providing information on surrogate outcome measures and complications. Functional imaging techniques also have been applied to the study of the liver and the kidney.

Functional MRI in Pain Management

Functional MRI (fMRI) studies in pain management examine the potential clinical role of fMRI in the diagnosis and treatment of acute and chronic pain conditions. In this chapter, the unique spatial and temporal properties of the brain’s response to pain are discussed first, because they provide the basis for potential clinical applications of fMRI. The second section considers several specific clinical roles that could be filled by fMRI. These include: detecting acute pain using a combination of machine learning and task-based fMRI, detecting chronic pain using functional connectivity MRI (fcMRI), predicting the development of chronic pain using fcMRI, monitoring the treatment of pain using fMRI, and treating pain directly using fMRI-based biofeedback. The possibility of translating fMRI findings to less expensive, more mobile technologies that could facilitate widespread clinical implementation is also discussed.

Functional MRI Data Analysis

Functional MRI (fMRI) data analysis aims to characterize neuronal dynamics by using observations of the hemodynamic phenomena associated with neuronal activity. These observations are indirect and highly “noisy” and commonly require different models for data interpretation. Many techniques have been developed in recent years for analyzing fMRI data. Despite advances in fMRI, there are some limitations that have to be considered in obtaining successful characterization of neuronal activity from fMRI data. In this chapter, the fundamentals of fMRI data analysis are described. Initially, the basis of the hemodynamic phenomena associated with neuronal activity is presented. This is followed by a description of the principal models used to perform fMRI data analysis. Finally, some of the most critical aspects of fMRI data analysis are covered.