Early diffusion evidence of retrograde transsynaptic degeneration in the human visual system

We investigated whether diffusion tensor imaging (DTI) indices of white matter integrity would offer early markers of retrograde transsynaptic degeneration (RTD) in the visual system after stroke Objective: We investigated whether diffusion tensor imaging (DTI) indices of white matter integrity would offer early markers of retrograde transsynaptic degeneration (RTD) in the visual system after stroke. Methods: We performed a prospective longitudinal analysis of the sensitivity of DTI markers of optic tract health in 12 patients with postsynaptic visual pathway stroke, 12 stroke controls, and 28 healthy controls. We examined group differences in (1) optic tract fractional anisotropy (FA-asymmetry), (2) perimetric measures of visual impairment, and (3) the relationship between FA-asymmetry and perimetric assessment. Results: FA-asymmetry was higher in patients with visual pathway lesions than in control groups. These differences were evident 3 months from the time of injury and did not change significantly at 12 months. Perimetric measures showed evidence of impairment in participants with visual pathway stroke but not in control groups. A significant association was observed between FA-asymmetry and perimetric measures at 3 months, which persisted at 12 months. Conclusions: DTI markers of RTD are apparent 3 months from the time of injury. This represents the earliest noninvasive evidence of RTD in any species. Furthermore, these measures associate with measures of visual impairment. DTI measures offer a reproducible, noninvasive, and sensitive method of investigating RTD and its role in visual impairment

Stronger prediction of motor recovery and outcome post-stroke by cortico-spinal tract integrity than functional connectivity

<div><p>Objectives</p><p>To examine longitudinal changes in structural and functional connectivity post-stroke in patients with motor impairment, and define their importance for recovery and outcome at 12 months.</p><p>Methods</p><p>First-time stroke patients (N = 31) were studied at 1–2 weeks, 3 months, and 12 months post-injury with a validated motor battery and resting-state fMRI to measure inter-hemispheric functional connectivity (FC). Fractional anisotropy (FA) of the cortico-spinal tract (CST) was derived from diffusion tensor imaging as a measure of white matter organization. ANOVAs were used to test for changes in FC, FA, and motor performance scores over time, and regression analysis related motor outcome to clinical and neuroimaging variables.</p><p>Results</p><p>FA of the ipsilesional CST improved significantly from 3 to 12 months and was strongly correlated with motor performance. FA improved even in the absence of direct damage to the CST. Inter-hemispheric FC also improved over time, but did not correlate with motor performance at 12 months. Clinical variables (early motor score, education level, and age) predicted 80.4% of the variation of motor outcome, and FA increased the predictability to 84.6%. FC did not contribute to the prediction of motor outcome.</p><p>Conclusions</p><p>Stroke causes changes to the CST microstructure that can account for behavioral variability even in the absence of demonstrable lesion. Ipsilesional CST undergoes remodeling post-stroke, even past the three-month window when most of the motor recovery happens. FA of the CST, but not inter-hemispheric FC, can improve to the prediction of motor outcome based on early motor scores.</p></div

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\u27s structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions

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\u27s lesion on the structural connectome by embedding the lesion in a diffusion MRI streamline tractography atlas constructed using data from healthy individuals. We defined direct disconnections as the loss of direct structural connections between two regions, and indirect disconnections as increases in the shortest structural path length between two regions that lack direct structural connections. We then tested the hypothesis that functional connectivity disruptions would be more severe for disconnected regions than for regions with spared connections. On average, nearly 20% of all region pairs were estimated to be either directly or indirectly disconnected by the lesions in our sample, and extensive disconnections were associated primarily with damage to deep white matter locations. Importantly, both directly and indirectly disconnected region pairs showed more severe functional connectivity disruptions than region pairs with spared direct and indirect connections, respectively, although functional connectivity disruptions tended to be most severe between region pairs that sustained direct structural disconnections. Together, these results emphasize the widespread impacts of focal brain lesions on the structural connectome and show that these impacts are reflected by disruptions of the functional connectome. Further, they indicate that in addition to direct structural disconnections, lesion-induced increases in the structural shortest path lengths between indirectly structurally connected region pairs provide information about the remote functional disruptions caused by focal brain lesions

Distinct phase-amplitude couplings distinguish cognitive processes in human attention

Abstract Spatial attention is the cognitive function that coordinates the selection of visual stimuli with appropriate behavioral responses. Recent studies have reported that phase-amplitude coupling (PAC) of low and high frequencies covaries with spatial attention, but differ on the direction of covariation and the frequency ranges involved. We hypothesized that distinct phase-amplitude frequency pairs have differentiable contributions during tasks that manipulate spatial attention. We investigated this hypothesis with electrocorticography (ECoG) recordings from participants who engaged in a cued spatial attention task. To understand the contribution of PAC to spatial attention we classified cortical sites by their relationship to spatial variables or behavioral performance. Local neural activity in spatial sites was sensitive to spatial variables in the task, while local neural activity in behavioral sites correlated with reaction time. We found two PAC frequency clusters that covaried with different aspects of the task. During a period of cued attention, delta-phase/high-gamma (DH) PAC was sensitive to cue direction in spatial sites. In contrast, theta-alpha-phase/beta-low-gamma-amplitude (TABL) PAC robustly correlated with future reaction times in behavioral sites. Finally, we investigated the origins of TABL PAC and found it corresponded to behaviorally relevant, sharp waveforms, which were also coupled to a low frequency rhythm. We conclude that TABL and DH PAC correspond to distinct mechanisms during spatial attention tasks and that sharp waveforms are elements of a coupled dynamical process

Spontaneous activity patterns in human motor cortex replay evoked activity patterns for hand movements

Spontaneous brain activity, measured with resting state fMRI (R-fMRI), is correlated among regions that are co-activated by behavioral tasks. It is unclear, however, whether spatial patterns of spontaneous activity within a cortical region correspond to spatial patterns of activity evoked by specific stimuli, actions, or mental states. The current study investigated the hypothesis that spontaneous activity in motor cortex represents motor patterns commonly occurring in daily life. To test this hypothesis 15 healthy participants were scanned while performing four different hand movements. Three movements (Grip, Extend, Pinch) were ecological involving grip and grasp hand movements; one control movement involving the rotation of the wrist was not ecological and infrequent (Shake). They were also scanned at rest before and after the execution of the motor tasks (resting-state scans). Using the task data, we identified movement-specific patterns in the primary motor cortex. These task-defined patterns were compared to resting-state patterns in the same motor region. We also performed a control analysis within the primary visual cortex. We found that spontaneous activity patterns in the primary motor cortex were more like task patterns for ecological than control movements. In contrast, there was no difference between ecological and control hand movements in the primary visual area. These findings provide evidence that spontaneous activity in human motor cortex forms fine-scale, patterned representations associated with behaviors that frequently occur in daily life

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 (\u3c0.01-0.1 Hz) requires intact cortical-subcortical communication. Using functional magnetic resonance imaging (fMRI) at rest, we identify Dynamic Functional States (DFSs), transient but recurrent clusters of cortical and subcortical regions synchronizing at ultra-slow frequencies. We observe that shifts in cortical clusters are temporally coincident with shifts in subcortical clusters, with cortical regions flexibly synchronizing with either limbic regions (hippocampus/amygdala), or subcortical nuclei (thalamus/basal ganglia). Focal lesions induced by stroke, especially those damaging white matter connections between basal ganglia/thalamus and cortex, provoke anomalies in the fraction times, dwell times, and transitions between DFSs, causing a bias toward abnormal network integration. Dynamical anomalies observed 2 weeks after stroke recover in time and contribute to explaining neurological impairment and long-term outcome

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. We show that adding information about the structural disconnections produced by a patient’s lesion to a whole-brain model previously trained on structural and functional data from a large cohort of healthy subjects enables the prediction of the resting functional connectivity of the patient and fits the model directly to the patient’s data (Pearson correlation = 0.37; mean square error = 0.005). Furthermore, the model dynamics reproduce functional connectivity-based measures that are typically abnormal in stroke patients and measures that specifically isolate these abnormalities. Therefore, although whole-brain models typically involve a large number of free parameters, the results show that, even after fixing those parameters, the model reproduces results from a population very different than that on which the model was trained. In addition to validating the model, these results show that the model mechanistically captures the relationships between the anatomical structure and the functional activity of the human brain

Abnormal white matter blood-oxygen-level-dependent signals in chronic mild traumatic brain injury

Concussion, or mild traumatic brain injury (mTBI), can cause persistent behavioral symptoms and cognitive impairment, but it is unclear if this condition is associated with detectable structural or functional brain changes. At two sites, chronic mTBI human subjects with persistent post-concussive symptoms (three months to five years after injury) and age- and education-matched healthy human control subjects underwent extensive neuropsychological and visual tracking eye movement tests. At one site, patients and controls also performed the visual tracking tasks while blood-oxygen-level-dependent (BOLD) signals were measured with functional magnetic resonance imaging. Although neither neuropsychological nor visual tracking measures distinguished patients from controls at the level of individual subjects, abnormal BOLD signals were reliably detected in patients. The most consistent changes were localized in white matter regions: anterior internal capsule and superior longitudinal fasciculus. In contrast, BOLD signals were normal in cortical regions, such as the frontal eye field and intraparietal sulcus, that mediate oculomotor and attention functions necessary for visual tracking. The abnormal BOLD signals accurately differentiated chronic mTBI patients from healthy controls at the single-subject level, although they did not correlate with symptoms or neuropsychological performance. We conclude that subjects with persistent post-concussive symptoms can be identified years after their TBI using fMRI and an eye movement task despite showing normal structural MRI and DTI

Brain aerobic glycolysis and resilience in Alzheimer disease

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (Aβ) deposition in individuals with symptomatic and preclinical Alzheimer disease (AD). Brain AG decreases with age, but the functional significance of this decrease with regard to the development of AD symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption, and glucose utilization-from which we derive AG-we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG. In contrast, amyloid positivity without cognitive impairment was associated with preservation of youthful brain AG, which was even higher than that seen in cognitively unimpaired, amyloid negative adults. Similar findings were not seen for blood flow nor oxygen consumption. Finally, in cognitively unimpaired adults, white matter hyperintensity burden was found to be specifically associated with decreased youthful brain AG. Our results suggest that AG may have a role in the resilience and/or response to early stages of amyloid pathology and that age-related white matter disease may impair this process