Dynamic Functional Connectivity in Pediatric Mild Traumatic Brain Injury.

Resting-state fMRI can be used to identify recurrent oscillatory patterns of functional connectivity within the human brain, also known as dynamic brain states. Alterations in dynamic brain states are highly likely to occur following pediatric mild traumatic brain injury (pmTBI) due to the active developmental changes. The current study used resting-state fMRI to investigate dynamic brain states in 200 patients with pmTBI (ages 8-18 years, median = 14 years) at the subacute (∼1-week post-injury) and early chronic (∼ 4 months post-injury) stages, and in 179 age- and sex-matched healthy controls (HC). A k-means clustering analysis was applied to the dominant time-varying phase coherence patterns to obtain dynamic brain states. In addition, correlations between brain signals were computed as measures of static functional connectivity. Dynamic connectivity analyses showed that patients with pmTBI spend less time in a frontotemporal default mode/limbic brain state, with no evidence of change as a function of recovery post-injury. Consistent with models showing traumatic strain convergence in deep grey matter and midline regions, static interhemispheric connectivity was affected between the left and right precuneus and thalamus, and between the right supplementary motor area and contralateral cerebellum. Changes in static or dynamic connectivity were not related to symptom burden or injury severity measures, such as loss of consciousness and post-traumatic amnesia. In aggregate, our study shows that brain dynamics are altered up to 4 months after pmTBI, in brain areas that are known to be vulnerable to TBI. Future longitudinal studies are warranted to examine the significance of our findings in terms of long-term neurodevelopment.

Comparison of automated and manual quantification methods for neuromelanin-sensitive MRI in Parkinson's disease.

Neuromelanin-sensitive magnetic resonance imaging quantitative analysis methods have provided promising biomarkers that can noninvasively quantify degeneration of the substantia nigra in patients with Parkinson's disease. However, there is a need to systematically evaluate the performance of manual and automated quantification approaches. We evaluate whether spatial, signal-intensity, or subject specific abnormality measures using either atlas based or manually traced identification of the substantia nigra better differentiate patients with Parkinson's disease from healthy controls using logistic regression models and receiver operating characteristics. Inference was performed using bootstrap analyses to calculate 95% confidence interval bounds. Pairwise comparisons were performed by generating 10,000 permutations, refitting the models, and calculating a paired difference between metrics. Thirty-one patients with Parkinson's disease and 22 healthy controls were included in the analyses. Signal intensity measures significantly outperformed spatial and subject specific abnormality measures, with the top performers exhibiting excellent ability to differentiate patients with Parkinson's disease and healthy controls (balanced accuracy = 0.89; area under the curve = 0.81; sensitivity =0.86; and specificity = 0.83). Atlas identified substantia nigra metrics performed significantly better than manual tracing metrics. These results provide clear support for the use of automated signal intensity metrics and additional recommendations. Future work is necessary to evaluate whether the same metrics can best differentiate atypical parkinsonism, perform similarly in de novo and mid-stage cohorts, and serve as longitudinal monitoring biomarkers.

A cautionary tale on the effects of different covariance structures in linear mixed effects modeling of fMRI data.

With the steadily increasing abundance of longitudinal neuroimaging studies with large sample sizes and multiple repeated measures, questions arise regarding the appropriate modeling of variance and covariance. The current study examined the influence of standard classes of variance-covariance structures in linear mixed effects (LME) modeling of fMRI data from patients with pediatric mild traumatic brain injury (pmTBI; N = 181) and healthy controls (N = 162). During two visits, participants performed a cognitive control fMRI paradigm that compared congruent and incongruent stimuli. The hemodynamic response function was parsed into peak and late peak phases. Data were analyzed with a 4-way (GROUP×VISIT×CONGRUENCY×PHASE) LME using AFNI's 3dLME and compound symmetry (CS), autoregressive process of order 1 (AR1), and unstructured (UN) variance-covariance matrices. Voxel-wise results dramatically varied both within the cognitive control network (UN>CS for CONGRUENCY effect) and broader brain regions (CS>UN for GROUP:VISIT) depending on the variance-covariance matrix that was selected. Additional testing indicated that both model fit and estimated standard error were superior for the UN matrix, likely as a result of the modeling of individual terms. In summary, current findings suggest that the interpretation of results from complex designs is highly dependent on the selection of the variance-covariance structure using LME modeling.

Abnormal Cerebrovascular Activity, Perfusion, and Glymphatic Clearance in Lewy Body Diseases.

Cerebrovascular activity is not only crucial to optimal cerebral perfusion, but also plays an important role in the glymphatic clearance of interstitial waste, including α-synuclein. This highlights a need to evaluate how cerebrovascular activity is altered in Lewy body diseases. This review begins by discussing how vascular risk factors and cardiovascular autonomic dysfunction may serve as upstream or direct influences on cerebrovascular activity. We then discuss how patients with Lewy body disease exhibit reduced and delayed cerebrovascular activity, hypoperfusion, and reductions in measures used to capture cerebrospinal fluid flow, suggestive of a reduced capacity for glymphatic clearance. Given the lack of an existing framework, we propose a model by which these processes may foster α-synuclein aggregation and neuroinflammation. Importantly, this review highlights several avenues for future research that may lead to treatments early in the disease course, prior to neurodegeneration. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Reduced and Delayed Cerebrovascular Reactivity in Patients with Parkinson's Disease.

BACKGROUND: Cerebrovascular dysfunction in Parkinson's disease (PD) is heterogeneous and may contribute to disease pathophysiology or progression. There is a need to understand the mechanisms by which cerebrovascular dysfunction is altered in participants with PD. OBJECTIVES: The objective of this study is to test the hypothesis that participants with PD exhibit a significant reduction in the ability of the cerebral vessels to dilate in response to vasoactive challenges relative to healthy controls (HC). METHODS: The current study uses a vasodilatory challenge while participants undergo functional magnetic resonance imaging to quantify the amplitude and delay of cerebrovascular reactivity in participants with PD relative to age and sex-matched HC. An analysis of covariance was used to evaluate differences in cerebrovascular reactivity amplitude and latency between PD participants and HC. RESULTS: A significant main effect of group was observed for whole-brain cerebrovascular reactivity amplitude (F(1, 28) = 4.38, p = 0.046, Hedge's g = 0.73) and latency (F(1, 28) = 16.35, p < 0.001, Hedge's g = 1.42). Participants with PD exhibited reduced whole-brain amplitude and increased latencies in cerebrovascular reactivity relative to HC. The evaluation of regional effects indicates that the largest effects were observed in the cuneus, precuneus, and parietal regions. CONCLUSIONS: PD participants exhibited reduced and delayed cerebrovascular reactivity. This dysfunction may play an important role in chronic hypoxia, neuroinflammation, and protein aggregation, mechanisms that could lead to disease progression. Cerebrovascular reactivity may serve as an important biomarker and target for future interventions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Multicompartmental models and diffusion abnormalities in paediatric mild traumatic brain injury.

The underlying pathophysiology of paediatric mild traumatic brain injury and the time-course for biological recovery remains widely debated, with clinical care principally informed by subjective self-report. Similarly, clinical evidence indicates that adolescence is a risk factor for prolonged recovery, but the impact of age-at-injury on biomarkers has not been determined in large, homogeneous samples. The current study collected diffusion MRI data in consecutively recruited patients (n = 203; 8-18 years old) and age and sex-matched healthy controls (n = 170) in a prospective cohort design. Patients were evaluated subacutely (1-11 days post-injury) as well as at 4 months post-injury (early chronic phase). Healthy participants were evaluated at similar times to control for neurodevelopment and practice effects. Clinical findings indicated persistent symptoms at 4 months for a significant minority of patients (22%), along with residual executive dysfunction and verbal memory deficits. Results indicated increased fractional anisotropy and reduced mean diffusivity for patients, with abnormalities persisting up to 4 months post-injury. Multicompartmental geometric models indicated that estimates of intracellular volume fractions were increased in patients, whereas estimates of free water fractions were decreased. Critically, unique areas of white matter pathology (increased free water fractions or increased neurite dispersion) were observed when standard assumptions regarding parallel diffusivity were altered in multicompartmental models to be more biologically plausible. Cross-validation analyses indicated that some diffusion findings were more reproducible when ∼70% of the total sample (142 patients, 119 controls) were used in analyses, highlighting the need for large-sample sizes to detect abnormalities. Supervised machine learning approaches (random forests) indicated that diffusion abnormalities increased overall diagnostic accuracy (patients versus controls) by ∼10% after controlling for current clinical gold standards, with each diffusion metric accounting for only a few unique percentage points. In summary, current results suggest that novel multicompartmental models are more sensitive to paediatric mild traumatic brain injury pathology, and that this sensitivity is increased when using parameters that more accurately reflect diffusion in healthy tissue. Results also indicate that diffusion data may be insufficient to achieve a high degree of objective diagnostic accuracy in patients when used in isolation, which is to be expected given known heterogeneities in pathophysiology, mechanism of injury and even criteria for diagnoses. Finally, current results indicate ongoing clinical and physiological recovery at 4 months post-injury.

Test-Retest Reliability of a Semi-Structured Interview to Aid in Pediatric Traumatic Brain Injury Diagnosis.

OBJECTIVE: Retrospective self-report is typically used for diagnosing previous pediatric traumatic brain injury (TBI). A new semi-structured interview instrument (New Mexico Assessment of Pediatric TBI; NewMAP TBI) investigated test-retest reliability for TBI characteristics in both the TBI that qualified for study inclusion and for lifetime history of TBI. METHOD: One-hundred and eight-four mTBI (aged 8-18), 156 matched healthy controls (HC), and their parents completed the NewMAP TBI within 11 days (subacute; SA) and 4 months (early chronic; EC) of injury, with a subset returning at 1 year (late chronic; LC). RESULTS: The test-retest reliability of common TBI characteristics [loss of consciousness (LOC), post-traumatic amnesia (PTA), retrograde amnesia, confusion/disorientation] and post-concussion symptoms (PCS) were examined across study visits. Aside from PTA, binary reporting (present/absent) for all TBI characteristics exhibited acceptable (≥0.60) test-retest reliability for both Qualifying and Remote TBIs across all three visits. In contrast, reliability for continuous data (exact duration) was generally unacceptable, with LOC and PCS meeting acceptable criteria at only half of the assessments. Transforming continuous self-report ratings into discrete categories based on injury severity resulted in acceptable reliability. Reliability was not strongly affected by the parent completing the NewMAP TBI. CONCLUSIONS: Categorical reporting of TBI characteristics in children and adolescents can aid clinicians in retrospectively obtaining reliable estimates of TBI severity up to a year post-injury. However, test-retest reliability is strongly impacted by the initial data distribution, selected statistical methods, and potentially by patient difficulty in distinguishing among conceptually similar medical concepts (i.e., PTA vs. confusion).

Fronto-Parietal gray matter and white matter efficiency differentially predict intelligence in males and females.

While there are minimal sex differences in overall intelligence, males, on average, have larger total brain volume and corresponding regional brain volumes compared to females, measures that are consistently related to intelligence. Limited research has examined which other brain characteristics may differentially contribute to intelligence in females to facilitate equal performance on intelligence measures. Recent reports of sex differences in the neural characteristics of the brain further highlight the need to differentiate how the structural neural characteristics relate to intellectual ability in males and females. The current study utilized a graph network approach in conjunction with structural equation modeling to examine potential sex differences in the relationship between white matter efficiency, fronto-parietal gray matter volume, and general cognitive ability (GCA). Participants were healthy adults (n = 244) who completed a battery of cognitive testing and underwent structural neuroimaging. Results indicated that in males, a latent factor of fronto-parietal gray matter was significantly related to GCA when controlling for total gray matter volume. In females, white matter efficiency and total gray matter volume were significantly related to GCA, with no specificity of the fronto-parietal gray matter factor over and above total gray matter volume. This work highlights that different neural characteristics across males and females may contribute to performance on intelligence measures. Hum Brain Mapp 37:4006-4016, 2016. © 2016 Wiley Periodicals, Inc.

Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence.

The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence.

Sex differences in the relationship between white matter connectivity and creativity.

Creative cognition emerges from a complex network of interacting brain regions. This study investigated the relationship between the structural organization of the human brain and aspects of creative cognition tapped by divergent thinking tasks. Diffusion weighted imaging (DWI) was used to obtain fiber tracts from 83 segmented cortical regions. This information was represented as a network and metrics of connectivity organization, including connectivity strength, clustering and communication efficiency were computed, and their relationship to individual levels of creativity was examined. Permutation testing identified significant sex differences in the relationship between global connectivity and creativity as measured by divergent thinking tests. Females demonstrated significant inverse relationships between global connectivity and creative cognition, whereas there were no significant relationships observed in males. Node specific analyses revealed inverse relationships across measures of connectivity, efficiency, clustering and creative cognition in widespread regions in females. Our findings suggest that females involve more regions of the brain in processing to produce novel ideas to solutions, perhaps at the expense of efficiency (greater path lengths). Males, in contrast, exhibited few, relatively weak positive relationships across these measures. Extending recent observations of sex differences in connectome structure, our findings of sexually dimorphic relationships suggest a unique topological organization of connectivity underlying the generation of novel ideas in males and females.

Parkinson's disease cerebrovascular reactivity pattern: A feasibility study.

A mounting body of research points to cerebrovascular dysfunction as a fundamental element in the pathophysiology of Parkinson's disease (PD). In the current feasibility study, blood-oxygen-level-dependent (BOLD) MRI was used to measure cerebrovascular reactivity (CVR) in response to hypercapnia in 26 PD patients and 16 healthy controls (HC), and aimed to find a multivariate pattern specific to PD. Whole-brain maps of CVR amplitude (i.e., magnitude of response to CO2) and latency (i.e., time to reach maximum amplitude) were computed, which were further analyzed using scaled sub-profile model principal component analysis (SSM-PCA) with leave-one-out cross-validation. A meaningful pattern based on CVR latency was identified, which was named the PD CVR pattern (PD-CVRP). This pattern was characterized by relatively increased latency in basal ganglia, sensorimotor cortex, supplementary motor area, thalamus and visual cortex, as well as decreased latency in the cerebral white matter, relative to HC. There were no significant associations with clinical measures, though sample size may have limited our ability to detect significant associations. In summary, the PD-CVRP highlights the importance of cerebrovascular dysfunction in PD, and may be a potential biomarker for future clinical research and practice.

Changes in intrinsic functional brain networks following blast-induced mild traumatic brain injury.

OBJECTIVE: Blast-induced mild traumatic brain injuries (mTBI) commonly go undetected by computed tomography and conventional magnetic resonance imaging (MRI). This study was used to investigate functional brain network abnormalities in a group of blast-induced mTBI subjects using independent component analysis (ICA) of resting state functional MRI (fMRI) data. METHODS: Twenty-eight resting state networks of 13 veterans who sustained blast-induced mTBI were compared with healthy controls across three fMRI domains: blood oxygenation level-dependent spatial maps, time course spectra and functional connectivity. RESULTS: The mTBI group exhibited hyperactivity in the temporo-parietal junctions and hypoactivity in the left inferior temporal gyrus. Abnormal frequencies in default-mode (DMN), sensorimotor, attentional and frontal networks were detected. In addition, functional connectivity was disrupted in six network pairs: DMN-basal ganglia, attention-sensorimotor, frontal-DMN, attention-sensorimotor, attention-frontal and sensorimotor-sensorimotor. CONCLUSIONS: The results suggest white matter disruption across certain attentional networks. Additionally, given their elevated activity relative to controls', the temporo-parietal junctions of blast mTBI subjects may be compensating for diffuse axonal injury in other cortical regions.

Microbiome-gut-brain dysfunction in prodromal and symptomatic Lewy body diseases.

Lewy body diseases, such as Parkinson's disease and dementia with Lewy bodies, vary in their clinical phenotype but exhibit the same defining pathological feature, α-synuclein aggregation. Microbiome-gut-brain dysfunction may play a role in the initiation or progression of disease processes, though there are multiple potential mechanisms. We discuss the need to evaluate gastrointestinal mechanisms of pathogenesis across Lewy body diseases, as disease mechanisms likely span across diagnostic categories and a 'body first' clinical syndrome may better account for the heterogeneity of clinical presentations across the disorders. We discuss two primary hypotheses that suggest that either α-synuclein aggregation occurs in the gut and spreads in a prion-like fashion to the brain or systemic inflammatory processes driven by gastrointestinal dysfunction contribute to the pathophysiology of Lewy body diseases. Both of these hypotheses posit that dysbiosis and intestinal permeability are key mechanisms and potential treatment targets. Ultimately, this work can identify early interventions targeting initial disease pathogenic processes before the development of overt motor and cognitive symptoms.

Gut-brain pathogenesis of post-acute COVID-19 neurocognitive symptoms.

Approximately one third of non-hospitalized coronavirus disease of 2019 (COVID-19) patients report chronic symptoms after recovering from the acute stage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Some of the most persistent and common complaints of this post-acute COVID-19 syndrome (PACS) are cognitive in nature, described subjectively as "brain fog" and also objectively measured as deficits in executive function, working memory, attention, and processing speed. The mechanisms of these chronic cognitive sequelae are currently not understood. SARS-CoV-2 inflicts damage to cerebral blood vessels and the intestinal wall by binding to angiotensin-converting enzyme 2 (ACE2) receptors and also by evoking production of high levels of systemic cytokines, compromising the brain's neurovascular unit, degrading the intestinal barrier, and potentially increasing the permeability of both to harmful substances. Such substances are hypothesized to be produced in the gut by pathogenic microbiota that, given the profound effects COVID-19 has on the gastrointestinal system, may fourish as a result of intestinal post-COVID-19 dysbiosis. COVID-19 may therefore create a scenario in which neurotoxic and neuroinflammatory substances readily proliferate from the gut lumen and encounter a weakened neurovascular unit, gaining access to the brain and subsequently producing cognitive deficits. Here, we review this proposed PACS pathogenesis along the gut-brain axis, while also identifying specific methodologies that are currently available to experimentally measure each individual component of the model.

Longitudinal hippocampal subfields, CSF biomarkers, and cognition in patients with Parkinson disease.

Objective: Hippocampal atrophy is an indicator of emerging dementia in PD, though it is unclear whether cerebral spinal fluid (CSF) Abeta-42, t-tau, or alpha-syn predict hippocampal subfield atrophy in a de novo cohort of PD patients. To examine whether levels of CSF alpha-synuclein (alpha-syn), beta-amyloid 1-42 (Abeta-42), or total-tau (t-tau) are associated with hippocampal subfield volumes over time. Methods: We identified a subset of Parkinson's Progression Markers Initiative (PPMI) de novo PD patients with longitudinal T1-weighted imaging (baseline plus at least two additional visits across 12, 24, and 48 months) and CSF biomarkers available at baseline. We performed cross-sectional, regression, and linear mixed model analyses to evaluate the baseline and longitudinal CSF biomarkers, hippocampal subfields, and cognition. A false discovery rate (FDR) was used to correct for multiple comparisons. Results: 88 PD-CN and 21 PD-MCI had high quality longitudinal data. PD-MCI patients exhibited reduced bilateral CA1 volumes relative to PD-CN, though there were no significant differences in CSF biomarkers between these groups. Relationships between CSF biomarkers and hippocampal subfields changed over time, with a general pattern that lower CSF Abeta-42, higher t-tau and higher alpha-syn were associated with smaller hippocampal subfields, primarily in the right hemisphere. Conclusion: We replicated prior reports that demonstrated reduced CA1 volumes in PD-MCI in a de novo PD cohort. CSF biomarkers were associated with individual subfields, with evidence that the increased CSF t-tau was associated with smaller subiculum volumes at baseline and over time, though there was no clear indication that the subfields associated with cognition (CA1 and HATA) were associated with CSF biomarkers.

Prospective Study of Gray Matter Atrophy Following Pediatric Mild Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: The clinical and physiologic time course for recovery following pediatric mild traumatic brain injury (pmTBI) remains actively debated. The primary objective of the current study was to prospectively examine structural brain changes (cortical thickness and subcortical volumes) and age-at-injury effects. A priori study hypotheses predicted reduced cortical thickness and hippocampal volumes up to 4 months postinjury, which would be inversely associated with age at injury. METHODS: Prospective cohort study design with consecutive recruitment. Study inclusion adapted from American Congress of Rehabilitation Medicine (upper threshold) and Zurich Concussion in Sport Group (minimal threshold) and diagnosed by Emergency Department and Urgent Care clinicians. Major neurologic, psychiatric, or developmental disorders were exclusionary. Clinical (Common Data Element) and structural (3 T MRI) evaluations within 11 days (subacute visit [SA]) and at 4 months (early chronic visit [EC]) postinjury. Age- and sex-matched healthy controls (HC) to control for repeat testing/neurodevelopment. Clinical outcomes based on self-report and cognitive testing. Structural images quantified with FreeSurfer (version 7.1.1). RESULTS: A total of 208 patients with pmTBI (age = 14.4 ± 2.9; 40.4% female) and 176 HC (age = 14.2 ± 2.9; 42.0% female) were included in the final analyses (>80% retention). Reduced cortical thickness (right rostral middle frontal gyrus; d = -0.49) and hippocampal volumes (d = -0.24) observed for pmTBI, but not associated with age at injury. Hippocampal volume recovery was mediated by loss of consciousness/posttraumatic amnesia. Significantly greater postconcussive symptoms and cognitive deficits were observed at SA and EC visits, but were not associated with the structural abnormalities. Structural abnormalities slightly improved balanced classification accuracy above and beyond clinical gold standards (∆+3.9%), with a greater increase in specificity (∆+7.5%) relative to sensitivity (∆+0.3%). DISCUSSION: Current findings indicate that structural brain abnormalities may persist up to 4 months post-pmTBI and are partially mediated by initial markers of injury severity. These results contribute to a growing body of evidence suggesting prolonged physiologic recovery post-pmTBI. In contrast, there was no evidence for age-at-injury effects or physiologic correlates of persistent symptoms in our sample.

Electric field distribution predicts efficacy of accelerated intermittent theta burst stimulation for late-life depression.

Introduction: Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention for late-life depression (LLD) but may have lower rates of response and remission owing to age-related brain changes. In particular, rTMS induced electric field strength may be attenuated by cortical atrophy in the prefrontal cortex. To identify clinical characteristics and treatment parameters associated with response, we undertook a pilot study of accelerated fMRI-guided intermittent theta burst stimulation (iTBS) to the right dorsolateral prefrontal cortex in 25 adults aged 50 or greater diagnosed with LLD and qualifying to receive clinical rTMS. Methods: Participants underwent baseline behavioral assessment, cognitive testing, and structural and functional MRI to generate individualized targets and perform electric field modeling. Forty-five sessions of iTBS were delivered over 9 days (1800 pulses per session, 50-min inter-session interval). Assessments and testing were repeated after 15 sessions (Visit 2) and 45 sessions (Visit 3). Primary outcome measure was the change in depressive symptoms on the Inventory of Depressive Symptomatology-30-Clinician (IDS-C-30) from Visit 1 to Visit 3. Results: Overall there was a significant improvement in IDS score with the treatment (Visit 1: 38.6; Visit 2: 31.0; Visit 3: 21.3; mean improvement 45.5%) with 13/25 (52%) achieving response and 5/25 (20%) achieving remission (IDS-C-30 < 12). Electric field strength and antidepressant effect were positively correlated in a subregion of the ventrolateral prefrontal cortex (VLPFC) (Brodmann area 47) and negatively correlated in the posterior dorsolateral prefrontal cortex (DLPFC). Conclusion: Response and remission rates were lower than in recently published trials of accelerated fMRI-guided iTBS to the left DLPFC. These results suggest that sufficient electric field strength in VLPFC may be a contributor to effective rTMS, and that modeling to optimize electric field strength in this area may improve response and remission rates. Further studies are needed to clarify the relationship of induced electric field strength with antidepressant effects of rTMS for LLD.

Revisiting Hemispheric Asymmetry in Mood Regulation: Implications for rTMS for Major Depressive Disorder.

Hemispheric differences in emotional processing have been observed for over half a century, leading to multiple theories classifying differing roles for the right and left hemisphere in emotional processing. Conventional acceptance of these theories has had lasting clinical implications for the treatment of mood disorders. The theory that the left hemisphere is broadly associated with positively valenced emotions, while the right hemisphere is broadly associated with negatively valenced emotions, drove the initial application of repetitive transcranial magnetic stimulation (rTMS) for the treatment of major depressive disorder (MDD). Subsequent rTMS research has led to improved response rates while adhering to the same initial paradigm of administering excitatory rTMS to the left prefrontal cortex (PFC) and inhibitory rTMS to the right PFC. However, accumulating evidence points to greater similarities in emotional regulation between the hemispheres than previously theorized, with potential implications for how rTMS for MDD may be delivered and optimized in the near future. This review will catalog the range of measurement modalities that have been used to explore and describe hemispheric differences, and highlight evidence that updates and advances knowledge of TMS targeting and parameter selection. Future directions for research are proposed that may advance precision medicine and improve efficacy of TMS for MDD.

Specific White Matter Tracts and Diffusion Properties Predict Conversion From Mild Cognitive Impairment to Alzheimer's Disease.

Identifying biomarkers that can assess the risk of developing Alzheimer's Disease (AD) remains a significant challenge. In this study, we investigated the integrity levels of brain white matter in 34 patients with mild cognitive impairment (MCI) who later converted to AD and 53 stable MCI patients. We used diffusion tensor imaging (DTI) and automated fiber quantification to obtain the diffusion properties of 20 major white matter tracts. To identify which tracts and diffusion measures are most relevant to AD conversion, we used support vector machines (SVMs) to classify the AD conversion and non-conversion MCI patients based on the diffusion properties of each tract individually. We found that diffusivity measures from seven white matter tracts were predictive of AD conversion with axial diffusivity being the most predictive diffusion measure. Additional analyses revealed that white matter changes in the central and parahippocampal terminal regions of the right cingulate hippocampal bundle, central regions of the right inferior frontal occipital fasciculus, and posterior and anterior regions of the left inferior longitudinal fasciculus were the best predictors of conversion from MCI to AD. An SVM based on these white matter tract regions achieved an accuracy of 0.75. These findings provide additional potential biomarkers of AD risk in MCI patients.

Distant histories of mild traumatic brain injury exacerbate age-related differences in white matter properties.

We examined associations of distant histories of mild traumatic brain injury (mTBI) with non-linear and linear trajectories of white matter (WM) properties across a wide age range (23-77). Diffusion tensor imaging (DTI) data obtained from 171 Veterans with histories of clinically diagnosed mTBIs and 115 controls were subjected to tractography, isolating 20 major WM tracts. Non-linear and linear effects of age on each tract's diffusion properties were examined in terms of their interactions with group (mTBI and control). The non-linear model revealed 7 tracts in which the mTBI group's DTI metrics rapidly deviated from control trajectories in middle and late adulthoods, despite the injuries having occurred in the late 20s, on average. In contrast, no interactions between prior injuries and age were detected when examining linear trajectories. Distant mTBIs may thus accelerate normal age-related trajectories of WM degeneration much later in life. As such, life-long histories of head trauma should be assessed in all patients in their mid-to-late adulthoods, whether neurologically healthy or presenting with seemingly unrelated neuropathology.