Iowa Brain-Behavior Modeling Toolkit: An Open-Source MATLAB Tool for Inferential and Predictive Modeling of Imaging-Behavior and Lesion-Deficit Relationships.

The traditional analytical framework taken by neuroimaging studies in general, and lesion-behavior studies in particular, has been inferential in nature and has focused on identifying and interpreting statistically significant effects within the sample under study. While this framework is well-suited for hypothesis testing approaches, achieving the modern goal of precision medicine requires a different framework that is predictive in nature and that focuses on maximizing the predictive power of models and evaluating their ability to generalize beyond the data that were used to train them. However, few tools exist to support the development and evaluation of predictive models in the context of neuroimaging or lesion-behavior research, creating an obstacle to the widespread adoption of predictive modeling approaches in the field.

Lesion and lesion network localization of dysnomia after epilepsy surgery.

Temporal lobe (TL) epilepsy surgery is an effective treatment option for patients with drug-resistant epilepsy. However, neurosurgery poses a risk for cognitive deficits - up to one third of patients have a decline in naming ability following TL surgery. In this study, we aimed to better understand the neural correlates associated with reduced naming performance after TL surgery, with the goal of informing surgical planning strategies to mitigate the risk of dysnomia.

Iowa Brain-Behavior Modeling Toolkit: An Open-Source MATLAB Tool for Inferential and Predictive Modeling of Imaging-Behavior and Lesion-Deficit Relationships.

The traditional analytical framework taken by neuroimaging studies in general, and lesion-behavior studies in particular, has been inferential in nature and has focused on identifying and interpreting statistically significant effects within the sample under study. While this framework is well-suited for hypothesis testing approaches, achieving the modern goal of precision medicine requires a different framework that is predictive in nature and that focuses on maximizing the predictive power of models and evaluating their ability to generalize beyond the data that were used to train them. However, few tools exist to support the development and evaluation of predictive models in the context of neuroimaging or lesion-behavior research, creating an obstacle to the widespread adoption of predictive modeling approaches in the field.

Generative whole-brain dynamics models from healthy subjects predict functional alterations in stroke at the level of individual patients.

Computational whole-brain models describe the resting activity of each brain region based on a local model, inter-regional functional interactions, and a structural connectome that specifies the strength of inter-regional connections. Strokes damage the healthy structural connectome that forms the backbone of these models and produce large alterations in inter-regional functional interactions. These interactions are typically measured by correlating the time series of the activity between two brain regions in a process, called resting functional connectivity.

Inferring the dynamical effects of stroke lesions through whole-brain modeling.

Understanding the effect of focal lesions (stroke) on brain structure-function traditionally relies on behavioral analyses and correlation with neuroimaging data. Here we use structural disconnection maps from individual lesions to derive a causal mechanistic generative whole-brain model able to explain both functional connectivity alterations and behavioral deficits induced by stroke. As compared to other models that use only the local lesion information, the similarity to the empirical fMRI connectivity increases when the widespread structural disconnection information is considered.

Indirect structural disconnection-symptom mapping.

In vivo tracking of white matter fibres catalysed a modern perspective on the pivotal role of brain connectome disruption in neuropsychological deficits. However, the examination of white matter integrity in neurological patients by diffusion-weighted magnetic resonance imaging bears conceptual limitations and is not widely applicable, as it requires imaging-compatible patients and resources beyond the capabilities of many researchers. The indirect estimation of structural disconnection offers an elegant and economical alternative.

Subcortical-cortical dynamical states of the human brain and their breakdown in stroke.

The mechanisms controlling dynamical patterns in spontaneous brain activity are poorly understood. Here, we provide evidence that cortical dynamics in the ultra-slow frequency range (<0.01-0.

Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions.

Functional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses.

Effective connectivity extracts clinically relevant prognostic information from resting state activity in stroke.

Recent resting-state functional MRI studies in stroke patients have identified two robust biomarkers of acute brain dysfunction: a reduction of inter-hemispheric functional connectivity between homotopic regions of the same network, and an abnormal increase of ipsi-lesional functional connectivity between task-negative and task-positive resting-state networks. Whole-brain computational modelling studies, at the individual subject level, using undirected effective connectivity derived from empirically measured functional connectivity, have shown a reduction of measures of integration and segregation in stroke as compared to healthy brains. Here we employ a novel method, first, to infer whole-brain directional effective connectivity from zero-lagged and lagged covariance matrices, then, to compare it to empirically measured functional connectivity for predicting stroke versus healthy status, and patient performance (zero, one, multiple deficits) across neuropsychological tests.

Mental health in the UK Biobank: A roadmap to self-report measures and neuroimaging correlates.

The UK Biobank (UKB) is a highly promising dataset for brain biomarker research into population mental health due to its unprecedented sample size and extensive phenotypic, imaging, and biological measurements. In this study, we aimed to provide a shared foundation for UKB neuroimaging research into mental health with a focus on anxiety and depression. We compared UKB self-report measures and revealed important timing effects between scan acquisition and separate online acquisition of some mental health measures.

Intermittent Theta Burst Stimulation (iTBS) for Treatment of Chronic Post-Stroke Aphasia: Results of a Pilot Randomized, Double-Blind, Sham-Controlled Trial.

BACKGROUND Research indicates intermittent theta burst stimulation (iTBS) is a potential treatment of post-stroke aphasia. MATERIAL AND METHODS In this double-blind, sham-controlled trial (NCT01512264) participants were randomized to receive 3 weeks of sham (G₀), 1 week of iTBS/2 weeks of sham (G₁), 2 weeks of iTBS/1 week of sham (G₂), or 3 weeks of iTBS (G₃). FMRI localized residual language function in the left hemisphere; iTBS was applied to the maximum fMRI activation in the residual language cortex in the left frontal lobe.

Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions.

Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain's structural connectome, few dedicated tools exist to facilitate this endeavor.

Damage to the shortest structural paths between brain regions is associated with disruptions of resting-state functional connectivity after stroke.

Focal brain lesions disrupt resting-state functional connectivity, but the underlying structural mechanisms are unclear. Here, we examined the direct and indirect effects of structural disconnections on resting-state functional connectivity in a large sample of sub-acute stroke patients with heterogeneous brain lesions. We estimated the impact of each patient's lesion on the structural connectome by embedding the lesion in a diffusion MRI streamline tractography atlas constructed using data from healthy individuals.

Structural Disconnections Explain Brain Network Dysfunction after Stroke.

Stroke causes focal brain lesions that disrupt functional connectivity (FC), a measure of activity synchronization, throughout distributed brain networks. It is often assumed that FC disruptions reflect damage to specific cortical regions. However, an alternative explanation is that they reflect the structural disconnection (SDC) of white matter pathways.

Cortical excitability affects mood state in patients with idiopathic generalized epilepsies (IGEs).

Previously, we demonstrated an association between cortical hyperexcitability and mood disturbance in healthy adults. Studies have documented hyperexcitability in patients with idiopathic generalized epilepsies (IGEs; long-interval intracortical inhibition [LICI]) and high prevalence of mood comorbidities. This study aimed to investigate the influences of cortical excitability and seizure control on mood state in patients with IGEs.

Cortical excitability and seizure control influence attention performance in patients with idiopathic generalized epilepsies (IGEs).

We recently found that higher cortical excitability is associated with poorer attention performance in healthy adults. While patients with idiopathic generalized epilepsies (IGEs), previously termed genetic generalized epilepsies, are known to demonstrate increased cortical excitability and cognitive deficits, a relationship between these variables in IGEs has not been investigated. Therefore, we aimed to characterize the effects of cortical excitability and seizure control on cognitive performance in IGEs.

A feasibility study of combined intermittent theta burst stimulation and modified constraint-induced aphasia therapy in chronic post-stroke aphasia.

Purpose: The purpose of this feasibility study was to assess whether combined intermittent theta burst suppression (iTBS) applied to the ipsilesional hemisphere and modified constraint-induced aphasia therapy (mCIAT) are safe and logistically feasible within the time interval associated with iTBS induced long-term potentiation in patients with post-stroke aphasia. We also wanted to determine whether combining priming with iTBS and CIAT improves language functions after treatment.

Methods: Twelve participants received fMRI (semantic decision/tone decision task) and neuropsychological testing of language skills at three time points - before starting the iTBS/mCIAT intervention (T1), immediately after completing 2-week long course of intervention (T2), and at 3-months follow-up (T3).

Linking left hemispheric tissue preservation to fMRI language task activation in chronic stroke patients.

The preservation of near-typical function in distributed brain networks is associated with less severe deficits in chronic stroke patients. However, it remains unclear how task-evoked responses in networks that support complex cognitive functions such as semantic processing relate to the post-stroke brain anatomy. Here, we used recently developed methods for the analysis of multimodal MRI data to investigate the relationship between regional tissue concentration and functional MRI activation evoked during auditory semantic decisions in a sample of 43 chronic left hemispheric stroke patients and 43 age, handedness, and sex-matched controls.

Relationship Between Alpha Rhythm and the Default Mode Network: An EEG-fMRI Study.

Purpose: Reports of the relationship between the default mode network (DMN) and alpha power are conflicting. Our goal was to assess this relationship by analyzing concurrently obtained EEG/functional MRI data using hypothesis-independent methods.

Methods: We collected functional MRI and EEG data during eyes-closed rest in 20 participants aged 19 to 37 (10 females) and performed independent component analysis on the functional MRI data and a Hamming-windowed fast Fourier transform on the EEG data.

Cortical excitability and neuropsychological functioning in healthy adults.

Evidence from clinical populations, such as epilepsy and attention deficit/hyperactivity disorder, suggests a relationship between hyperexcitability and cognitive impairment, but this relationship has not been demonstrated in healthy individuals. Here, we investigate the relationship between cortical excitability and cognitive functioning in healthy adults. Single- and paired-pulse TMS was applied to 20 healthy adults to measure cortical excitability and long-interval intracortical inhibition (LICI).

Damage to white matter bottlenecks contributes to language impairments after left hemispheric stroke.

Damage to the white matter underlying the left posterior temporal lobe leads to deficits in multiple language functions. The posterior temporal white matter may correspond to a bottleneck where both dorsal and ventral language pathways are vulnerable to simultaneous damage. Damage to a second putative white matter bottleneck in the left deep prefrontal white matter involving projections associated with ventral language pathways and thalamo-cortical projections has recently been proposed as a source of semantic deficits after stroke.

The canonical semantic network supports residual language function in chronic post-stroke aphasia.

Current theories of language recovery after stroke are limited by a reliance on small studies. Here, we aimed to test predictions of current theory and resolve inconsistencies regarding right hemispheric contributions to long-term recovery. We first defined the canonical semantic network in 43 healthy controls.

Age-Dependent Cortical Thinning of Peripheral Visual Field Representations in Primary Visual Cortex.

The cerebral cortex changes throughout the lifespan, and the cortical gray matter in many brain regions becomes thinner with advancing age. Effects of aging on cortical thickness (CT) have been observed in many brain regions, including areas involved in basic perceptual functions such as processing visual inputs. An important property of early visual cortices is their topographic organization-the cortical structure of early visual areas forms a topographic map of retinal inputs.

Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation.

Psychophysical and neurobiological evidence suggests that central and peripheral vision are specialized for different functions. This specialization of function might be expected to lead to differences in the large-scale functional interactions of early cortical areas that represent central and peripheral visual space. Here, we characterize differences in whole-brain functional connectivity among sectors in primary visual cortex (V1) corresponding to central, near-peripheral, and far-peripheral vision during resting fixation.

Cortical thickness in human V1 associated with central vision loss.

Better understanding of the extent and scope of visual cortex plasticity following central vision loss is essential both for clarifying the mechanisms of brain plasticity and for future development of interventions to retain or restore visual function. This study investigated structural differences in primary visual cortex between normally-sighted controls and participants with central vision loss due to macular degeneration (MD). Ten participants with MD and ten age-, gender-, and education-matched controls with normal vision were included.