Neuroimaging in psychiatry: from bench to bedside

Frontal Functional Network Disruption Associated with Amyotrophic Lateral Sclerosis: An fNIRS-Based Minimum Spanning Tree Analysis

Recent evidence increasingly associates network disruption in brain organization with multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), a rare terminal disease. However, the comparability of brain network characteristics across different studies remains a challenge for conventional graph theoretical methods. One suggested method to address this issue is minimum spanning tree (MST) analysis, which provides a less biased comparison. Here, we assessed the novel application of MST network analysis to hemodynamic responses recorded by functional near-infrared spectroscopy (fNIRS) neuroimaging modality, during an activity-based paradigm to investigate hypothetical disruptions in frontal functional brain network topology as a marker of the executive dysfunction, one of the most prevalent cognitive deficit reported across ALS studies. We analyzed data recorded from nine participants with ALS and ten age-matched healthy controls by first estimating functional connectivity, using phase-locking value (PLV) analysis, and then constructing the corresponding individual and group MSTs. Our results showed significant between-group differences in several MST topological properties, including leaf fraction, maximum degree, diameter, eccentricity, and degree divergence. We further observed a global shift toward more centralized frontal network organizations in the ALS group, interpreted as a more random or dysregulated network in this cohort. Moreover, the similarity analysis demonstrated marginally significantly increased overlap in the individual MSTs from the control group, implying a reference network with lower topological variation in the healthy cohort. Our nodal analysis characterized the main local hubs in healthy controls as distributed more evenly over the frontal cortex, with slightly higher occurrence in the left prefrontal cortex (PFC), while in the ALS group, the most frequent hubs were asymmetrical, observed primarily in the right prefrontal cortex. Furthermore, it was demonstrated that the global PLV (gPLV) synchronization metric is associated with disease progression, and a few topological properties, including leaf fraction and tree hierarchy, are linked to disease duration. These results suggest that dysregulation, centralization, and asymmetry of the hemodynamic-based frontal functional network during activity are potential neuro-topological markers of ALS pathogenesis. Our findings can possibly support new bedside assessments of the functional status of ALS' brain network and could hypothetically extend to applications in other neurodegenerative diseases.

Magnetic resonance diffusion tensor imaging in psychiatry: a narrative review of its potential role in diagnosis

Diffusion tensor imaging (DTI) is an imaging technique that uses magnetic resonance. It measures the diffusion of water molecules in tissues, which can occur either without restriction (i.e., in an isotropic manner) or limited by some obstacles, such as cell membranes (i.e., in an anisotropic manner). Diffusion is most often measured in terms of, inter alia, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). DTI allows us to reconstruct, visualize, and evaluate certain qualities of white matter. To date, many studies have sought to associate various changes in the distribution of diffusion within the brain with mental diseases and disorders. A better understanding of white matter integrity disorders can help us recognize the causes of diseases, as well as help create objective methods of psychiatric diagnosis, identify biomarkers of mental illness, and improve pharmacotherapy. The aim of this work is to present the characteristics of DTI as well as current research on its use in schizophrenia, affective disorders, and other mental disorders.

Emotion Regulation in Schizophrenia: A Pilot Clinical Intervention as Assessed by EEG and Optical Imaging (Functional Near-Infrared Spectroscopy)

Previous research on Schizophrenia (S) revealed anomalies in brain responsiveness during emotion processing, as shown by neuroimaging and electroencephalography (EEG) measures. Nonetheless preserved capacities to explicitly evaluate the emotional significance of affective stimuli in term of valence have been found. The present study applied functional Near-Infrared Spectroscopy (fNIRS) and EEG to explore the spatial and temporal expressions of emotion processing in the brain before (T0) and after (T2) an emotional Neurofeedback (NF) training of patients, assigned to the control or the experimental group. Explicit measures revealed correct identifications of stimuli emotional valence before (T0) and after (T2) the treatment, while implicit measures (EEG and fNIRS) showed a modulation and increased competencies only after the NF (T2), with more balanced prefrontal activity.

Delineation of early and later adult onset depression by diffusion tensor imaging

Background

Due to a lack of evidence, there is no consistent age of onset to define early onset (EO) versus later onset (LO) major depressive disorder (MDD). Fractional anisotropy (FA), derived from diffusion tensor imaging (DTI), has been widely used to study neuropsychiatric disorders by providing information about the brain circuitry, abnormalities of which might facilitate the delineation of EO versus LO MDD.

Method

In this study, 61 pairs of untreated, non-elderly, first-episode MDD patients and healthy controls (HCs) aged 18–45 years old received DTI scans. The voxel-based analysis method (VBM), classification analysis, using the Statistical Package for the Social Sciences (SPSS), and regression analyses were used to determine abnormal FA clusters and their correlations with age of onset and clinical symptoms.

Results

Classification analysis suggested in the best model that there were two subgroups of MDD patients, delineated by an age of onset of 30 years old, by which MDD patients could be divided into EO (18–29 years old) and LO (30–45 years old) groups. LO MDD was characterized by decreased FA, especially in the white matter (WM) of the fronto-occipital fasciculus and posterior limb of internal capsule, with a negative correlation with the severity of depressive symptoms; in marked contrast, EO MDD showed increased FA, especially in the WM of the corpus callosum, corticospinal midbrain and inferior fronto-occipital fasciculus, while FA of the WM near the midbrain had a positive correlation with the severity of depressive symptoms.

Conclusion

Specific abnormalities of the brain circuitry in EO vs. LO MDD were delineated by an age of onset of 30 years old, as demonstrated by distinct abnormal FA clusters with opposite correlations with clinical symptoms. This DTI study supported the evidence of an exact age for the delineation of MDD, which could have broad multidisciplinary importance.

Trial Registration

ClinicalTrials.gov NCT00703742

Genetic Testing and Neuroimaging: Trading off Benefit and Risk for Youth with Mental Illness

According to the World Health Organization, mental illness is one of the leading causes of disability worldwide. The first onset of mental illness usually occurs during childhood or adolescence. Neuroimaging and genetic testing have been invaluable in research on behavioral and intentional disorders, particularly with their potential to lead to improved diagnostic and predictive capabilities and to decrease the associated burdens of disease. The present study focused specifically the perspectives of mental health providers on the role of neuroimaging and genetic testing in clinical practice with children and adolescents. We interviewed 38 psychiatrists, psychologists, and allied mental health professionals who work primarily with youth about their receptivity towards either the use of neuroimaging or genetic testing. Interviews probed the role they foresee for these modalities for prediction, diagnosis, and treatment planning, and the benefits and risks they anticipate. Practitioners anticipated three major benefits associated with clinical introduction of imaging and genetic testing in the mental health care for youth: (1) improved understanding of illness, (2) more accurate diagnosis than available through conventional clinical examination, and (3) validation of treatment plans. They also perceived three major risks: (1) potential adverse impacts on employment and insurance as adolescents reach adulthood, (2) misuse or misinterpretation of the imaging or genetic data, and (3) infringements on self-esteem or self-motivation. Movement of brain imaging and genetic testing into clinical care will require a delicate balance of biology and respect for autonomy in the still-evolving cognitive and affective world of young individuals.

Brain magnetic resonance imaging: perception and expectations of neurologists, neurosurgeons and psychiatrists

Magnetic resonance imaging (MRI) has rapidly become an essential diagnostic tool in modern medicine. Understanding the objectives, perception and expectations of the different medical specialties towards MRI is therefore important to improve the quality of the examinations. Our aim was to better comprehend the reasons and expectations of neurologists, neurosurgeons and psychiatrists when requesting brain MRI scans for their patients, and also to perceive the degree of confidence of these specialists in the images and respective reports. Sixty-three specialists were recruited from two tertiary hospitals and answered a tailored questionnaire. Neurosurgeons were more concerned with the images themselves; neurologists lacked confidence in both MRI images and reports, and one third of the psychiatrists only read the report and were the most confident of the specialties in MRI findings. These results possibly reflect the idiosyncrasies of each of these medical specialties. This knowledge, driven by efficient communication between neuroradiologists and neurosurgeons, neurologists and psychiatrists, may contribute to improve the quality of MRI examinations and consequently patient care and management of health resources.

Multivariate pattern analysis of DTI reveals differential white matter in individuals with obsessive-compulsive disorder

Diffusion tensor imaging (DTI) studies have revealed group differences in white matter between patients with obsessive-compulsive disorder (OCD) and healthy controls. However, the results of these studies were based on average differences between the two groups, and therefore had limited clinical applicability. The objective of this study was to investigate whether fractional anisotropy (FA) of white matter can be used to discriminate between patients with OCD and healthy controls at the level of the individual. DTI data were acquired from 28 OCD patients and 28 demographically matched healthy controls, scanned using a 3T MRI system. Differences in FA values of white matter between OCD and healthy controls were examined using a multivariate pattern classification technique known as support vector machine (SVM). SVM applied to FA images correctly identified OCD patients with a sensitivity of 86% and a specificity of 82% resulting in a statistically significant accuracy of 84% (P ≤ 0.001). This discrimination was based on a distributed network including bilateral prefrontal and temporal regions, inferior fronto-occipital fasciculus, superior fronto-parietal fasciculus, splenium of corpus callosum and left middle cingulum bundle. The present study demonstrates subtle and spatially distributed white matter abnormalities in individuals with OCD, and provides preliminary support for the suggestion that that these could be used to aid the identification of individuals with OCD in clinical practice.

Genetic Testing and Neuroimaging for Youth at Risk for Mental Illness: Trading off Benefit and Risk

BACKGROUND

According to the World Health Organization, mental illness is one of the leading causes of disability worldwide. The first onset of mental illness usually occurs during childhood or adolescence, with nearly 12 million diagnosed cases in the United States alone. Neuroimaging and genetic testing have been invaluable in research on behavioral, affective, and attentional disorders, particularly with their potential predictive capabilities, and ability to improve diagnosis and to decrease the associated burdens of disease. The present study focused specifically the perspectives of mental health providers on the role of neuroimaging and genetic testing in clinical practice with children and adolescents.

METHODS

We interviewed 38 psychiatrists, psychologists, and allied mental health professionals who work primarily with youth about their receptivity toward either the use of neuroimaging or genetic testing. Interviews probed the role they foresee for these modalities for prediction, diagnosis, treatment planning, and the benefits and risks they anticipate.

RESULTS

Practitioners anticipated three major benefits associated with clinical introduction of imaging and genetic testing in the mental health care for youth: (1) improved understanding of the brain and mental illness, (2) more accurate diagnosis than available through conventional clinical examination, and (3) legitimization of treatment plans. They also perceived three major risks: (1) misuse or misinterpretation of the imaging or genetic data, (2) potential adverse impacts on employment and insurance as adolescents reach adulthood, and (3) infringements on self-esteem or self-motivation.

LIMITATIONS

The nature of the interview questions focused on the future of neuroimaging and genetic testing testing research in the context of clinical neuroscience. Therefore, the responses from interview participants are based on anticipated rather than actual experience.

CONCLUSIONS

Continued expansion of brain imaging and genetic testing into clinical care will require a delicate balance of brain biology and respect for autonomy in the still-evolving cognitive and affective world of young individuals.

Functional magnetic resonance imaging (FMRI) neurofeedback: implementations and applications

Neurofeedback (NFB) allows subjects to learn how to volitionally influence the neuronal activation in the brain by employing real-time neural activity as feedback. NFB has already been performed with electroencephalography (EEG) since the 1970s. Functional MRI (fMRI), offering a higher spatial resolution, has further increased the spatial specificity. In this paper, we briefly outline the general principles behind NFB, the implementation of fMRI-NFB studies, the feasibility of fMRI-NFB, and the application of NFB as a supplementary therapy tool.

Neurobiological narratives: experiences of mood disorder through the lens of neuroimaging

Many scientists, healthcare providers, policymakers and patients are awaiting in anticipation the application of biomedical technologies such as functional neuroimaging for the prediction, diagnosis and treatment of mental disorders. The potential efficacy of such applications is controversial, and functional neuroimaging is not yet routinely used in psychiatric clinics. However, commercial ventures and enthusiastic reporting indicate a pressing need to engage with the social and ethical issues raised by clinical translation. There has been little investigation of how individuals living with mental illness view functional neuroimaging, or of the potential psychological impacts of its clinical use. We conducted 12 semi-structured interviews with adults diagnosed with major depression or bipolar disorder, probing their experiences with mental health care and their perspectives on the prospect of receiving neuroimaging for prediction, diagnosis and planning treatment. The participants discussed the potential role of neuroimages in (i) mitigating stigma; (ii) supporting morally loaded explanations of mental illness due to an imbalance of brain chemistry; (iii) legitimising psychiatric symptoms, which may have previously been de-legitimised since they lacked objective representation, through objective representations of disorder; and (iv) reifying DSM-IV-TR disorder categories and links to identity. We discuss these anticipated outcomes in the context of participant lived experience and attitudes to biologisation of mental illness, and argue for bringing these voices into upstream ethics discussion.

Neuroimaging in mental health care: voices in translation

Images of brain function, popularly called "neuroimages," have become a mainstay of contemporary communication about neuroscience and mental health. Paralleling media coverage of neuroimaging research and the high visibility of clinics selling scans is pressure from sponsors to move basic research about brain function along the translational pathway. Indeed, neuroimaging may offer benefits to mental health care: early or tailored intervention, opportunities for education and planning, and access to resources afforded by objectification of disorder. However, risks of premature technology transfer, such as misinterpretation, misrepresentation, and increased stigmatization, could compromise patient care. The insights of stakeholder groups about neuroimaging for mental health care are a largely untapped resource of information and guidance for translational efforts. We argue that the insights of key stakeholders-including researchers, healthcare providers, patients, and families-have an essential role to play upstream in professional, critical, and ethical discourse surrounding neuroimaging in mental health. Here we integrate previously orthogonal lines of inquiry involving stakeholder research to describe the translational landscape as well as challenges on its horizon.

Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging

Magnetic resonance imaging studies have reported significant functional and structural differences between depressed patients and controls. Little attention has been given, however, to the abnormalities in anatomical connectivity in depressed patients. In the present study, we aim to investigate the alterations in connectivity of whole-brain anatomical networks in those suffering from major depression by using machine learning approaches. Brain anatomical networks were extracted from diffusion magnetic resonance images obtained from both 22 first-episode, treatment-naive adults with major depressive disorder and 26 matched healthy controls. Using machine learning approaches, we differentiated depressed patients from healthy controls based on their whole-brain anatomical connectivity patterns and identified the most discriminating features that represent between-group differences. Classification results showed that 91.7% (patients=86.4%, controls=96.2%; permutation test, p<0.0001) of subjects were correctly classified via leave-one-out cross-validation. Moreover, the strengths of all the most discriminating connections were increased in depressed patients relative to the controls, and these connections were primarily located within the cortical-limbic network, especially the frontal-limbic network. These results not only provide initial steps toward the development of neurobiological diagnostic markers for major depressive disorder, but also suggest that abnormal cortical-limbic anatomical networks may contribute to the anatomical basis of emotional dysregulation and cognitive impairments associated with this disease.

Picturing neuroscience research through a human rights lens: imaging first-episode schizophrenic treatment-naive individuals

In this paper we examine imaging research involving first-episode schizophrenic treatment-naive individuals (FESTNIs) through a legal human rights lens; in particular, the lens of the Additional Protocol to the Convention on Human Rights and Biomedicine Concerning Biomedical Research. We identify a number of ethical and legal hot spots highlighted by the Protocol, and offer a series of recommendations designed to ensure the human rights compatibility of this research. Subsequently, we argue that the lack of reporting on design elements related to ethical concerns frustrates commitments at the heart of the human rights approach, namely, transparency and openness to international scrutiny. To redress this problem, we introduce two norms for the first time: ethical transparency, and ethical reproducibility. When concluding, we offer a set of reporting guidelines designed to operationalize these norms in the context of imaging research involving FESTNIs. Though we will not make this case here, we believe that parallel reporting guidelines should be incorporated into other areas of research involving human subjects.

Simulation of near-infrared light absorption considering individual head and prefrontal cortex anatomy: implications for optical neuroimaging

Functional near-infrared spectroscopy (fNIRS) is an established optical neuroimaging method for measuring functional hemodynamic responses to infer neural activation. However, the impact of individual anatomy on the sensitivity of fNIRS measuring hemodynamics within cortical gray matter is still unknown. By means of Monte Carlo simulations and structural MRI of 23 healthy subjects (mean age: 25.0±2.8 years), we characterized the individual distribution of tissue-specific NIR-light absorption underneath 24 prefrontal fNIRS channels. We, thereby, investigated the impact of scalp-cortex distance (SCD), frontal sinus volume as well as sulcal morphology on gray matter volumes (V(gray)) traversed by NIR-light, i.e. anatomy-dependent fNIRS sensitivity. The NIR-light absorption between optodes was distributed describing a rotational ellipsoid with a mean penetration depth of (23.6±0.7) mm considering the deepest 5% of light. Of the detected photon packages scalp and bone absorbed (96.4±9.7)% and V(gray) absorbed (3.1±1.8)% of the energy. The mean V(gray) volume (1.1±0.4) cm3 was negatively correlated (r=-.76) with the SCD and frontal sinus volume (r=-.57) and was reduced by 41.5% in subjects with relatively large compared to small frontal sinus. Head circumference was significantly positively correlated with the mean SCD (r=.46) and the traversed frontal sinus volume (r=.43). Sulcal morphology had no significant impact on V(gray). Our findings suggest to consider individual SCD and frontal sinus volume as anatomical factors impacting fNIRS sensitivity. Head circumference may represent a practical measure to partly control for these sources of error variance.