Functional MRI methods and findings in schizophrenia

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Functional MRI imaging methods have allowed researchers to combine neurocognitive testing with structural neuroanatomical measures, consider cognitive and affective paradigms, and create computer-aided diagnosis techniques and algorithms. [1] [2] Functional MRI has several benefits, such as its non-invasive quality, relatively high spatial resolution, and decent temporal resolution. This is due the influential development in the scanner hardware, where it now allows for technicians to retrieve higher resolution images in a shorter amount of time. Additionally, there has been an improved motion correction and harmonization, which both aid in the generalizability and replication of findings in schizophrenia research. [3] Recent studies have used fMRI to explore specific brain networks, such as the salience network and default mode network, to understand their roles in schizophrenia-related symptoms. Alterations in these networks may affect self-referential thoughts and responses to external stimuli, potentially contributing to symptoms like hallucinations and disorganized thinking. [4] One particular method used in recent research is resting-state functional magnetic resonance imaging, rs-fMRI.

Contents

In a 'reformulation' of the binary-risk vulnerability model, researchers have suggested a multiple-hit hypothesis that utilizes several risk factors — some bestowing a greater probability than others — to identify at-risk individuals, often genetically predisposed to schizophrenia. [5] The process of defining clinical criteria of schizophrenia for early diagnosis has posed a great challenge for scientists. [6]

Methodology

According to the DSM-5, a schizophrenia diagnosis is given if an individual possesses two or more of the following symptoms over the course of a 1-month period: delusions, hallucinations, disorganized speech, grossly disorganized or catatonic behavior, or negative symptoms. Additionally, at least one of the following three characteristics: delusions, hallucinations, and disorganized speech, must be present. [7] A rapid increase of studies in schizophrenia has covered topics such as abnormal activity in "motor tasks, working memory attention, word fluency, emotion processing, and decision making." [8] Researchers also focus on identifying biomarkers through fMRI scans that could aid early diagnosis. For example, abnormalities in the anterior cingulate cortex and dorsolateral prefrontal cortex are considered potential indicators of schizophrenia risk. [9] In contrast to the abundance of research centered on positive symptoms of the disorder, fMRI research for schizophrenia primarily analyzes the 'failures' of the neural system and the resulting cognitive deficits, with an example being changes in functional connectivity. [3] [8] Another biomarker that can be found through fMRI scans is dysconnectivity within functioning of the cortico-striatal-thalamo-cortical networks. Because this characteristic is associated as an early signal for psychosis, it acts as a marker for predicting a schizophrenia diagnosis. [3] To confirm that a task activates identical regions in schizophrenia patients vs. controls, the given task typically begins easily so that both patients and healthy comparison subjects perform close to 100% accuracy; the task is then increased in difficulty to distinguish activation between two groups with varying abilities of individuals. [8] Eliminating confounding variables by using matched-controlled participants, which match the participant on race, age, sex, occupation...etc. Additionally, increasing datasets of participant groups helps the machine algorithms to improve generalizability across clinical and scanning settings.

The 'basic symptoms' approach

The 'basic symptoms' approach for schizophrenia, which emerged from "retrospective descriptions of the prodromal phase," represents a framework for a large portion of fMRI research, which evaluates changes in cognition and sensory perception that may affect higher-level information processes. [10] [11] The word 'basic' represents the earliest stages of the self-experienced symptoms of psychosis. These symptoms overall reveal the expression of neurobiological presses relating to it. This acts as an indicator for the onset of schizophrenia, and has potential in alerting researchers in earlier treatment. [12] Moreover, researchers oppose the tendency of researchers to attribute schizophrenia to higher-order processes like working memory, attention, and executive processing, instead choosing to inspect impairments in basic sensory and perceptual functions. [11] Deficits in basic sensory functions influence higher-order processes such as auditory emotion recognition, perceptual closure, object recognition, etc. [11] New research also suggests that disruptions in basic visual and auditory processing could contribute to impaired social perception in schizophrenia, making it difficult for individuals to interpret body language and facial expressions accurately. [13] In the visual system, for example, rudimentary deficits in the function of the magnocellular system result in impairments in higher-order processes like perceptual closure, object recognition, and reading. [11] On the other hand, fMRI data has also suggested the opposite. In one study, researchers found significantly differing activity between healthy and schizophrenic patients in the left dorsal parietal cortex and left ventrolateral prefrontal cortex; as these regions are essential components of a frontal-parietal executive system, hypo-activity in these regions for schizophrenia patients during working memory tasks were theorized to be associated with deficits in executive functioning. [14]

Resting-state fMRI

The 'disconnectivity hypothesis' is a key theory describing the failure of mechanisms underlying schizophrenia, specifically the failure to integrate information properly. [15] The dysconnectivity hypothesis suggests that disruptions in communication between the brain’s frontal and temporal regions may underlie symptoms like auditory hallucinations and impaired memory, as these areas are critical for integrating sensory input and memory. [16] Functional connectivity, which fMRI evaluates, is the activity coordination between brain regions. It is measured as "temporal correlations of low-frequency oscillations in the BOLD signal between anatomically distinct brain areas" and can reveal resting state networks. [17] The cause for the correlations in fMRI measurements is theorized to be "correlated firing rates of interconnected neurons." [18] Resting-state functional magnetic resonance imaging (rs-fMRI) has become a powerful tool to examine networks' functional connectivity throughout the brain, such as the default mode network (DMN). [19] Through resting-state fMRI, scientists have observed that schizophrenia is associated with altered connectivity patterns in the default mode, central executive, and salience networks. These networks’ dysconnectivity could impact attention, emotion regulation, and self-referential thought processes. [20] Although there are benefits to the resting state fMRI, it is important to note its limitations. fMRI scans measures the blood oxygen level-dependent response (BOLD) when patients partake in specific tasks. Therefore, when a brain region is activated, it takes in more oxygen, which measures and differentiates activity in various neurotransmitter systems. Failure to achieve this causes ambiguity in the areas that are affected, leaving researchers to only see general areas for treatment. [3]

Abnormal brain connectivity has long been theorized as a fundamental cause of psychosis in schizophrenia. [21] rs-fMRI can help evaluate regional interactions at rest and whether there are altered, reduced, or hyperactive connections in psychiatric disorders like schizophrenia. During resting-state fMRI experiments, participants are instructed to relax and stay awake but not think of anything. It is important to note that resting-state networks can change between eyes open and eyes closed conditions. [22] Researchers then measure spontaneous brain activation. [17] There are several advantages to studying the resting state of brain networks — the primary reason is that spontaneous neural activity accounts for most of the brain's activity in contrast to task-based neural activity. [22] Additionally, rs-fMRI eliminates confounding effects such as differing performances between healthy subjects and patients in tasks; rs-fMRI also requires less movement than task-based fMRI studies. [22] Seed-based analysis/ROI approaches to analyzing functional connectivity are common in rs-fMRI for schizophrenia. A seed (region of interest) is first selected, and BOLD time series are then extracted from the seed and all other voxels. After preprocessing, the temporal correlation between the seed and other brain voxels is determined, and the software produces a functional connectivity map. [17] Seed-based comparisons in rs-fMRI have revealed functional disconnectivity in schizophrenia patients in numerous studies, using different ROIs for their seeds — in general, schizophrenia patients show reduced connectivity. [17] Recent studies using resting-state fMRI (rs-fMRI) have identified significant disruptions in functional connectivity across multiple brain networks in schizophrenia, including the default mode, frontotemporal, and cerebellar networks. These findings provide additional support for the dysconnectivity hypothesis, which suggests that impaired coordination between brain regions contributes to the cognitive and behavioral symptoms of schizophrenia. [23] [24] This information is compatible with experiment findings suggesting reduced activation in the amygdala in schizophrenia patients during sadness mood induction, for example. [25]

Related Research Articles

<span class="mw-page-title-main">Schizophrenia</span> Mental disorder with psychotic symptoms

Schizophrenia is a mental disorder characterized variously by hallucinations, delusions, disorganized thinking and behavior, and flat or inappropriate affect. Symptoms develop gradually and typically begin during young adulthood and are never resolved. There is no objective diagnostic test; diagnosis is based on observed behavior, a psychiatric history that includes the person's reported experiences, and reports of others familiar with the person. For a diagnosis of schizophrenia, the described symptoms need to have been present for at least six months or one month. Many people with schizophrenia have other mental disorders, especially mood disorders, anxiety disorders, and obsessive–compulsive disorder.

<span class="mw-page-title-main">Functional magnetic resonance imaging</span> MRI procedure that measures brain activity by detecting associated changes in blood flow

Functional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases.

<span class="mw-page-title-main">Caudate nucleus</span> Structure of the striatum in the basal ganglia of the brain

The caudate nucleus is one of the structures that make up the corpus striatum, which is part of the basal ganglia in the human brain. Although the caudate nucleus has long been associated with motor processes because of its role in Parkinson's disease, it also plays important roles in nonmotor functions, such as procedural learning, associative learning, and inhibitory control of action. The caudate is also one of the brain structures that compose the reward system, and it functions as part of the cortico-basal ganglia-thalamo-cortical loop.

<span class="mw-page-title-main">Functional neuroimaging</span>

Functional neuroimaging is the use of neuroimaging technology to measure an aspect of brain function, often with a view to understanding the relationship between activity in certain brain areas and specific mental functions. It is primarily used as a research tool in cognitive neuroscience, cognitive psychology, neuropsychology, and social neuroscience.

Functional integration is the study of how brain regions work together to process information and effect responses. Though functional integration frequently relies on anatomic knowledge of the connections between brain areas, the emphasis is on how large clusters of neurons – numbering in the thousands or millions – fire together under various stimuli. The large datasets required for such a whole-scale picture of brain function have motivated the development of several novel and general methods for the statistical analysis of interdependence, such as dynamic causal modelling and statistical linear parametric mapping. These datasets are typically gathered in human subjects by non-invasive methods such as EEG/MEG, fMRI, or PET. The results can be of clinical value by helping to identify the regions responsible for psychiatric disorders, as well as to assess how different activities or lifestyles affect the functioning of the brain.

<span class="mw-page-title-main">Neuroimaging</span> Set of techniques to measure and visualize aspects of the nervous system

Neuroimaging is the use of quantitative (computational) techniques to study the structure and function of the central nervous system, developed as an objective way of scientifically studying the healthy human brain in a non-invasive manner. Increasingly it is also being used for quantitative research studies of brain disease and psychiatric illness. Neuroimaging is highly multidisciplinary involving neuroscience, computer science, psychology and statistics, and is not a medical specialty. Neuroimaging is sometimes confused with neuroradiology.

<span class="mw-page-title-main">Posterior cingulate cortex</span> Caudal part of the cingulate cortex of the brain

The posterior cingulate cortex (PCC) is the caudal part of the cingulate cortex, located posterior to the anterior cingulate cortex. This is the upper part of the "limbic lobe". The cingulate cortex is made up of an area around the midline of the brain. Surrounding areas include the retrosplenial cortex and the precuneus.

<span class="mw-page-title-main">Dorsolateral prefrontal cortex</span> Area of the prefrontal cortex of primates

The dorsolateral prefrontal cortex is an area in the prefrontal cortex of the primate brain. It is one of the most recently derived parts of the human brain. It undergoes a prolonged period of maturation which lasts into adulthood. The DLPFC is not an anatomical structure, but rather a functional one. It lies in the middle frontal gyrus of humans. In macaque monkeys, it is around the principal sulcus. Other sources consider that DLPFC is attributed anatomically to BA 9 and 46 and BA 8, 9 and 10.

Connectomics is the production and study of connectomes: comprehensive maps of connections within an organism's nervous system. More generally, it can be thought of as the study of neuronal wiring diagrams with a focus on how structural connectivity, individual synapses, cellular morphology, and cellular ultrastructure contribute to the make up of a network. The nervous system is a network made of billions of connections and these connections are responsible for our thoughts, emotions, actions, memories, function and dysfunction. Therefore, the study of connectomics aims to advance our understanding of mental health and cognition by understanding how cells in the nervous system are connected and communicate. Because these structures are extremely complex, methods within this field use a high-throughput application of functional and structural neural imaging, most commonly magnetic resonance imaging (MRI), electron microscopy, and histological techniques in order to increase the speed, efficiency, and resolution of these nervous system maps. To date, tens of large scale datasets have been collected spanning the nervous system including the various areas of cortex, cerebellum, the retina, the peripheral nervous system and neuromuscular junctions.

<span class="mw-page-title-main">Default mode network</span> Large-scale brain network active when not focusing on an external task

In neuroscience, the default mode network (DMN), also known as the default network, default state network, or anatomically the medial frontoparietal network (M-FPN), is a large-scale brain network primarily composed of the dorsal medial prefrontal cortex, posterior cingulate cortex, precuneus and angular gyrus. It is best known for being active when a person is not focused on the outside world and the brain is at wakeful rest, such as during daydreaming and mind-wandering. It can also be active during detailed thoughts related to external task performance. Other times that the DMN is active include when the individual is thinking about others, thinking about themselves, remembering the past, and planning for the future. The DMN creates a coherent "internal narrative" control to the construction of a sense of self.

The causes of schizophrenia that underlie the development of schizophrenia, a psychiatric disorder, are complex and not clearly understood. A number of hypotheses including the dopamine hypothesis, and the glutamate hypothesis have been put forward in an attempt to explain the link between altered brain function and the symptoms and development of schizophrenia.

<span class="mw-page-title-main">Resting state fMRI</span> Type of functional magnetic resonance imaging

Resting state fMRI is a method of functional magnetic resonance imaging (fMRI) that is used in brain mapping to evaluate regional interactions that occur in a resting or task-negative state, when an explicit task is not being performed. A number of resting-state brain networks have been identified, one of which is the default mode network. These brain networks are observed through changes in blood flow in the brain which creates what is referred to as a blood-oxygen-level dependent (BOLD) signal that can be measured using fMRI.

The biological basis of personality is a collection of brain systems and mechanisms that underlie human personality. Human neurobiology, especially as it relates to complex traits and behaviors, is not well understood, but research into the neuroanatomical and functional underpinnings of personality are an active field of research. Animal models of behavior, molecular biology, and brain imaging techniques have provided some insight into human personality, especially trait theories.

Functional magnetic resonance spectroscopy of the brain (fMRS) uses magnetic resonance imaging (MRI) to study brain metabolism during brain activation. The data generated by fMRS usually shows spectra of resonances, instead of a brain image, as with MRI. The area under peaks in the spectrum represents relative concentrations of metabolites.

The dorsal nexus is an area within the dorsal medial prefrontal cortex that serves as an intersection point for multiple brain networks. Research suggests it plays a role in the maintenance and manipulation of information, as well as supporting the control of cognitive functions such as behavior, memory, and conflict resolution. Abnormally increased connectivity between these networks through the dorsal nexus has been associated with certain types of depression. The activity generated by this abnormally high level of connectivity during a depressive state can be identified through magnetic resonance imaging (MRI) and positron emission tomography (PET).

<span class="mw-page-title-main">Hypofrontality</span> State of decreased cerebral blood flow

Hypofrontality is a state of decreased cerebral blood flow (CBF) in the prefrontal cortex of the brain. Hypofrontality is symptomatic of several neurological medical conditions, such as schizophrenia, attention deficit hyperactivity disorder (ADHD), bipolar disorder, and major depressive disorder. This condition was initially described by Ingvar and Franzén in 1974, through the use of xenon blood flow technique with 32 detectors to image the brains of patients with schizophrenia. This finding was confirmed in subsequent studies using the improved spatial resolution of positron emission tomography with the fluorodeoxyglucose (18F-FDG) tracer. Subsequent neuroimaging work has shown that the decreases in prefrontal CBF are localized to the medial, lateral, and orbital portions of the prefrontal cortex. Hypofrontality is thought to contribute to the negative symptoms of schizophrenia.

Dynamic functional connectivity (DFC) refers to the observed phenomenon that functional connectivity changes over a short time. Dynamic functional connectivity is a recent expansion on traditional functional connectivity analysis which typically assumes that functional networks are static in time. DFC is related to a variety of different neurological disorders, and has been suggested to be a more accurate representation of functional brain networks. The primary tool for analyzing DFC is fMRI, but DFC has also been observed with several other mediums. DFC is a recent development within the field of functional neuroimaging whose discovery was motivated by the observation of temporal variability in the rising field of steady state connectivity research.

Network neuroscience is an approach to understanding the structure and function of the human brain through an approach of network science, through the paradigm of graph theory. A network is a connection of many brain regions that interact with each other to give rise to a particular function. Network Neuroscience is a broad field that studies the brain in an integrative way by recording, analyzing, and mapping the brain in various ways. The field studies the brain at multiple scales of analysis to ultimately explain brain systems, behavior, and dysfunction of behavior in psychiatric and neurological diseases. Network neuroscience provides an important theoretical base for understanding neurobiological systems at multiple scales of analysis.

Susan Whitfield-Gabrieli is an American scientist, psychologist/neuroscientist, academic and researcher. She is a professor of psychology, the Founding Director of the Biomedical Imaging Center at Northeastern University, Researcher in the Department of Psychiatry at Massachusetts General Hospital, Harvard Medical School and a Research Affiliate of McGovern Institute for Brain Research at Massachusetts Institute of Technology.

Alan Anticevic is a Croatian neuroscientist known for his contributions to the fields of cognitive neuroscience, computational psychiatry, and neuroimaging studies of severe psychiatric illnesses.

References

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