Effects of Salt Concentration on a Magnetic Nanoparticle-Based Aggregation Assay with a Tunable Dynamic Range.

Magnetic nanoparticles (MNPs) can be functionalized with antibodies to give them an affinity for a biomarker of interest. Functionalized MNPs (fMNPs) cluster in the presence of a multivalent target, causing a change in their magnetization. Target concentration can be proportional to the 3rd harmonic phase of the fMNP magnetization signal.

Evaluating the data quality of the Gazepoint GP3 low-cost eye tracker when used independently by study participants.

The portability of low-cost eye trackers makes them attractive for research outside of the laboratory. Such research may require independent eye-tracker use. The present work compared the data quality of the Gazepoint GP3 when used independently by research participants with expert eye-tracking users.

Using the force: STEM knowledge and experience construct shared neural representations of engineering concepts.

How does STEM knowledge learned in school change students' brains? Using fMRI, we presented photographs of real-world structures to engineering students with classroom-based knowledge and hands-on lab experience, examining how their brain activity differentiated them from their "novice" peers not pursuing engineering degrees. A data-driven MVPA and machine-learning approach revealed that neural response patterns of engineering students were convergent with each other and distinct from novices' when considering physical forces acting on the structures. Furthermore, informational network analysis demonstrated that the distinct neural response patterns of engineering students reflected relevant concept knowledge: learned categories of mechanical structures.

Assessing Feedback Response With a Wearable Electroencephalography System.

Event related potential (ERP) components, such as P3, N2, and FRN, are potential metrics for assessing feedback response as a form of performance monitoring. Most research studies investigate these ERP components using clinical or research-grade electroencephalography (EEG) systems. Wearable EEGs, which are an affordable alternative, have the potential to assess feedback response using ERPs but have not been sufficiently evaluated.

Decoding individual differences in STEM learning from functional MRI data.

Traditional tests of concept knowledge generate scores to assess how well a learner understands a concept. Here, we investigated whether patterns of brain activity collected during a concept knowledge task could be used to compute a neural 'score' to complement traditional scores of an individual's conceptual understanding. Using a novel data-driven multivariate neuroimaging approach-informational network analysis-we successfully derived a neural score from patterns of activity across the brain that predicted individual differences in multiple concept knowledge tasks in the physics and engineering domain.

Simultaneous EEG, eye-tracking, behavioral, and screen-capture data during online German language learning.

This article presents concurrent multimodal data, including EEG, eye-tracking, and behavioral data (cursor movements and clicks), acquired from individuals ( = 22) while engaging in several German language lessons using the web-based Duolingo interface. Lessons were restricted to visual learning only (excluding audio and speech components), including reading and writing vocabulary words and sentences, and matching vocabulary to images. EEG data was collected using the open-source OpenBCI device utilizing dry Ag-AgCl electrodes, while eye-tracking data was recorded using the Gazepoint GP3 system.

A Feasibility Study of Nonlinear Spectroscopic Measurement of Magnetic Nanoparticles Targeted to Cancer Cells.

Objective: Magnetic nanoparticles (MNPs) are an emerging platform for targeted diagnostics in cancer. An important component needed for translation of MNPs is the detection and quantification of targeted MNPs bound to tumor cells.

Method: This study explores the feasibility of a multifrequency nonlinear magnetic spectroscopic method that uses excitation and pickup coils and is capable of discriminating between quantities of bound and unbound MNPs in 0.

The role of visualization and 3-D printing in biological data mining.

Background: Biological data mining is a powerful tool that can provide a wealth of information about patterns of genetic and genomic biomarkers of health and disease. A potential disadvantage of data mining is volume and complexity of the results that can often be overwhelming. It is our working hypothesis that visualization methods can greatly enhance our ability to make sense of data mining results.

Extended arrays for nonlinear susceptibility magnitude imaging.

This study implements nonlinear susceptibility magnitude imaging (SMI) with multifrequency intermodulation and phase encoding. An imaging grid was constructed of cylindrical wells of 3.5-mm diameter and 4.

Modeling Neurovascular Coupling from Clustered Parameter Sets for Multimodal EEG-NIRS.

Despite significant improvements in neuroimaging technologies and analysis methods, the fundamental relationship between local changes in cerebral hemodynamics and the underlying neural activity remains largely unknown. In this study, a data driven approach is proposed for modeling this neurovascular coupling relationship from simultaneously acquired electroencephalographic (EEG) and near-infrared spectroscopic (NIRS) data. The approach uses gamma transfer functions to map EEG spectral envelopes that reflect time-varying power variations in neural rhythms to hemodynamics measured with NIRS during median nerve stimulation.

Correspondence of electroencephalography and near-infrared spectroscopy sensitivities to the cerebral cortex using a high-density layout.

This study investigates the correspondence of the cortical sensitivity of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). EEG forward model sensitivity to the cerebral cortex was calculated for 329 EEG electrodes following the 10-5 EEG positioning system using a segmented structural magnetic resonance imaging scan of a human subject. NIRS forward model sensitivity was calculated for the same subject using 156 NIRS source-detector pairs selected from 32 source and 32 detector optodes positioned on the scalp using a subset of the 10-5 EEG positioning system.

Nonlinear Susceptibility Magnitude Imaging of Magnetic Nanoparticles.

This study demonstrates a method for improving the resolution of susceptibility magnitude imaging (SMI) using spatial information that arises from the nonlinear magnetization characteristics of magnetic nanoparticles (mNPs). In this proof-of-concept study of nonlinear SMI, a pair of drive coils and several permanent magnets generate applied magnetic fields and a coil is used as a magnetic field sensor. Sinusoidal alternating current (AC) in the drive coils results in linear mNP magnetization responses at primary frequencies, and nonlinear responses at harmonic frequencies and intermodulation frequencies.

Spectroscopic AC Susceptibility Imaging (sASI) of Magnetic Nanoparticles.

This study demonstrates a method for alternating current (AC) susceptibility imaging (ASI) of magnetic nanoparticles (mNPs) using low cost instrumentation. The ASI method uses AC magnetic susceptibility measurement to create tomographic images using an array of drive coils, compensation coils and fluxgate magnetometers. Using a spectroscopic approach in conjunction with ASI, a series of tomographic images can be created for each frequency measurement and is termed sASI.

Algorithm to find high density EEG scalp coordinates and analysis of their correspondence to structural and functional regions of the brain.

Background: Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain.

New Method: An algorithm is introduced for automatic calculation of the International 10-20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes.

T1 magnetic resonance imaging head segmentation for diffuse optical tomography and electroencephalography.

Accurate segmentation of structural magnetic resonance images is critical for creating subject-specific forward models for functional neuroimaging source localization. In this work, we present an innovative segmentation algorithm that generates accurate head tissue layer thicknesses that are needed for diffuse optical tomography (DOT) data analysis. The presented algorithm is compared against other publicly available head segmentation methods.

Development of a magnetic nanoparticle susceptibility magnitude imaging array.

There are several emerging diagnostic and therapeutic applications of magnetic nanoparticles (mNPs) in medicine. This study examines the potential for developing an mNP imager that meets these emerging clinical needs with a low cost imaging solution that uses arrays of digitally controlled drive coils in a multiple-frequency, continuous-wave operating mode and compensated fluxgate magnetometers. The design approach is described and a mathematical model is developed to support measurement and imaging.

Effects of spatial pattern scale of brain activity on the sensitivity of DOT, fMRI, EEG and MEG.

The objective of this work is to quantify how patterns of cortical activity at different spatial scales are measured by noninvasive functional neuroimaging sensors. We simulated cortical activation patterns at nine different spatial scales in a realistic head model and propagated this activity to magnetoencephalography (MEG), electroencephalography (EEG), diffuse optical tomography (DOT), and functional magnetic resonance imaging (fMRI) sensors in arrangements that are typically used in functional neuroimaging studies. We estimated contrast transfer functions (CTF), correlation distances in sensor space, and the minimum resolvable spatial scale of cortical activity for each modality.

Continuous correction of differential path length factor in near-infrared spectroscopy.

In continuous-wave near-infrared spectroscopy (CW-NIRS), changes in the concentration of oxyhemoglobin and deoxyhemoglobin can be calculated by solving a set of linear equations from the modified Beer-Lambert Law. Cross-talk error in the calculated hemodynamics can arise from inaccurate knowledge of the wavelength-dependent differential path length factor (DPF). We apply the extended Kalman filter (EKF) with a dynamical systems model to calculate relative concentration changes in oxy- and deoxyhemoglobin while simultaneously estimating relative changes in DPF.

Compliant head probe for positioning electroencephalography electrodes and near-infrared spectroscopy optodes.

A noninvasive head probe that combines near-infrared spectroscopy (NIRS) and electroencephalography (EEG) for simultaneous measurement of neural dynamics and hemodynamics in the brain is presented. It is composed of a compliant expandable mechanism that accommodates a wide range of head size variation and an elastomeric web that maintains uniform sensor contact pressure on the scalp as the mechanism expands and contracts. The design is intended to help maximize optical and electrical coupling and to maintain stability during head movement.

Measuring cerebral hemodynamics with a modified magnetoencephalography system.

Magnetoencephalography (MEG) systems are designed to noninvasively measure magnetic fields produced by neural electrical currents. This project examines the possibility of measuring hemodynamics with an MEG system that has been modified with dc electromagnets to measure magnetic susceptibility while maintaining the capability of measuring neural dynamics. A forward model is presented that simulates the interaction of an applied magnetic field with changes in magnetic susceptibility in the brain associated with hemodynamics.

Creation of a human head phantom for testing of electroencephalography equipment and techniques.

We have designed and fabricated an anatomically accurate human head phantom that is capable of generating realistic electric scalp potential patterns. This phantom was developed for performance evaluation of new electroencephalography (EEG) caps, hardware, and measurement techniques that are designed for environments high in electromagnetic and mechanical noise. The phantom was fabricated using conductive composite materials that mimic the electrical and mechanical properties of scalp, skull, and brain.

Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe.

We quantify the variability in diffuse optical tomography (DOT) sensitivity over the cortical surface in eight young adult subjects. We use the 10/5 electroencephalography system as a basis for our whole-head optical high-density probe design. The contrast-to-noise ratio (CNR) is calculated along with the percentage of the cortex that is above a CNR = 0 dB threshold.

Modeling habituation in rat EEG-evoked responses via a neural mass model with feedback.

Habituation is a generic property of the neural response to repeated stimuli. Its strength often increases as inter-stimuli relaxation periods decrease. We propose a simple, broadly applicable control structure that enables a neural mass model of the evoked EEG response to exhibit habituated behavior.

Effect of deep breathing on extracted oxygen and cerebral hemoglobin levels.

This study examines the relationship between oxygen expired and functional near infrared spectroscopy (fNIRS) measured hemoglobin levels in the brain. Analysis of these two signals during normal versus deep breathing provides insight into the dynamics of cerebral physiology. Intersubject variation suggests the existence of two distinct groups with respect to oxygen extraction and hemoglobin levels.

An investigation of the NOCSAE linear impactor test method based on in vivo measures of head impact acceleration in American football.

The performance characteristics of football helmets are currently evaluated by simulating head impacts in the laboratory using a linear drop test method. To encourage development of helmets designed to protect against concussion, the National Operating Committee for Standards in Athletic Equipment recently proposed a new headgear testing methodology with the goal of more closely simulating in vivo head impacts. This proposed test methodology involves an impactor striking a helmeted headform, which is attached to a nonrigid neck.