Brain Activity is Influenced by How High Dimensional Data are Represented: An EEG Study of Scatterplot Diagnostic (Scagnostics) Measures.

Visualization and visual analytic tools amplify one's perception of data, facilitating deeper and faster insights that can improve decision making. For multidimensional data sets, one of the most common approaches of visualization methods is to map the data into lower dimensions. Scatterplot matrices (SPLOM) are often used to visualize bivariate relationships between combinations of variables in a multidimensional dataset.

Seeking the Amygdala: Novel Use of Diffusion Tensor Imaging to Delineate the Basolateral Amygdala.

The amygdaloid complex, including the basolateral nucleus (BLA), contributes crucially to emotional and cognitive brain functions, and is a major target of research in both humans and rodents. However, delineating structural amygdala plasticity in both normal and disease-related contexts using neuroimaging has been hampered by the difficulty of unequivocally identifying the boundaries of the BLA. This challenge is a result of the poor contrast between BLA and the surrounding gray matter, including other amygdala nuclei.

Superstorm Sandy exposure is associated with neurobehavioral phenotypes and brain structure alterations in childhood: A machine learning approach.

Introduction: Prenatal maternal stress (PNMS), including exposure to natural disasters, has been shown to serve as a risk factor for future child psychopathology and suboptimal brain development, particularly among brain regions shown to be sensitive to stress and trauma exposure. However, statistical approaches deployed in most studies are usually constrained by a limited number of variables for the sake of statistical power. Explainable machine learning, on the other hand, enables the study of high data dimension and offers novel insights into the prominent subset of behavioral phenotypes and brain regions most susceptible to PNMS.

Robust enhancement of motor sequence learning with 4 mA transcranial electric stimulation.

Background And Objectives: Motor learning experiments with transcranial direct current stimulation (tDCS) at 2 mA have produced mixed results. We hypothesize that tDCS boosts motor learning provided sufficiently high field intensity on the motor cortex.

Methods: In a single-blinded design, 108 healthy participants received either anodal (N = 36) or cathodal (N = 36) tDCS at 4 mA total, or no stimulation (N = 36) while they practiced a 12-min sequence learning task.

Online closed-loop real-time tES-fMRI for brain modulation: A technical report.

Recent studies suggest that transcranial electrical stimulation (tES) can be performed during functional magnetic resonance imaging (fMRI). The novel approach of using concurrent tES-fMRI to modulate and measure targeted brain activity/connectivity may provide unique insights into the causal interactions between the brain neural responses and psychiatric/neurologic signs and symptoms, and importantly, guide the development of new treatments. However, tES stimulation parameters to optimally influence the underlying brain activity may vary with respect to phase difference, frequency, intensity, and electrode's montage among individuals.

A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement.

Low-intensity transcranial electrical stimulation (tES), including alternating or direct current stimulation, applies weak electrical stimulation to modulate the activity of brain circuits. Integration of tES with concurrent functional MRI (fMRI) allows for the mapping of neural activity during neuromodulation, supporting causal studies of both brain function and tES effects. Methodological aspects of tES-fMRI studies underpin the results, and reporting them in appropriate detail is required for reproducibility and interpretability.

Identifiable Patterns of Trait, State, and Experience in Chronic Stroke Recovery.

Background: Considerable evidence indicates that the functional connectome of the healthy human brain is highly stable, analogous to a fingerprint.

Objective: We investigated the stability of functional connectivity across tasks and sessions in a cohort of individuals with chronic stroke using a supervised machine learning approach.

Methods: Twelve individuals with chronic stroke underwent functional magnetic resonance imaging (fMRI) seven times over 18 weeks.

White Matter Plasticity in Anxiety: Disruption of Neural Network Synchronization During Threat-Safety Discrimination.

Recent evidence highlighted the importance of white matter tracts in typical and atypical behaviors. White matter dynamically changes in response to learning, stress, and social experiences. Several lines of evidence have reported white matter dysfunction in psychiatric conditions, including depression, stress- and anxiety-related disorders.

fMRI and transcranial electrical stimulation (tES): A systematic review of parameter space and outcomes.

The combination of non-invasive brain stimulation interventions with human brain mapping methods have supported research beyond correlational associations between brain activity and behavior. Functional MRI (fMRI) partnered with transcranial electrical stimulation (tES) methods, i.e.

Methodology for tDCS integration with fMRI.

Understanding and reducing variability of response to transcranial direct current stimulation (tDCS) requires measuring what factors predetermine sensitivity to tDCS and tracking individual response to tDCS. Human trials, animal models, and computational models suggest structural traits and functional states of neural systems are the major sources of this variance. There are 118 published tDCS studies (up to October 1, 2018) that used fMRI as a proxy measure of neural activation to answer mechanistic, predictive, and localization questions about how brain activity is modulated by tDCS.