Search

Significance: Time-domain functional near-infrared spectroscopy (TD-fNIRS) has been considered as the gold standard of noninvasive optical brain imaging devices. However, due to the high cost, complexity, and large form factor, it has not been as widely adopted as continuous wave NIRS systems. Aim: Kernel Flow is a TD-fNIRS system that has been designed to break through these limitations by maintaining the performance of a research grade TD-fNIRS system while integrating all of the components into a small modular device. Approach: The Kernel Flow modules are built around miniaturized laser drivers, custom integrated circuits, and specialized detectors. The modules can be assembled into a system with dense channel coverage over the entire head. Results: We show performance similar to benchtop systems with our miniaturized device as characterized by standardized tissue and optical phantom protocols for TD-fNIRS and human neuroscience results. Conclusions: The miniaturized design of the Kernel Flow system allows for broader applications of TD-fNIRS.

Highlights • fNIRS and looking responses to emotional faces were measured in 5- and 7-month-olds. • Emotional faces had varying identities within happy, angry, and fearful blocks. • Temporo-parietal and frontal activations were observed, particularly to happy faces. • Infants looked longer to the mouth region of angry faces. • No difference in behavior or neural activity observed between 5- and 7-month-olds., The processing of facial emotion is an important social skill that develops throughout infancy and early childhood. Here we investigate the neural underpinnings of the ability to process facial emotion across changes in facial identity in cross-sectional groups of 5- and 7-month-old infants. We simultaneously measured neural metabolic, behavioral, and autonomic responses to happy, fearful, and angry faces of different female models using functional near-infrared spectroscopy (fNIRS), eye-tracking, and heart rate measures. We observed significant neural activation to these facial emotions in a distributed set of frontal and temporal brain regions, and longer looking to the mouth region of angry faces compared to happy and fearful faces. No differences in looking behavior or neural activations were observed between 5- and 7-month-olds, although several exploratory, age-independent associations between neural activations and looking behavior were noted. Overall, these findings suggest more developmental stability than previously thought in responses to emotional facial expressions of varying identities between 5- and 7-months of age.

Data analysis methods for infant fNIRS data in global health are not standardised yet. This work proposes an analysis pipeline that improves the quality of the recovered HRF for use by other researchers in this field.

Typically developing infants rapidly acquire a sophisticated array of social skills within the first year of life. These social skills are largely learned within the context of day-to-day interactions with caregivers. While social neuroscience has made great gains in our knowledge of the underlying neural circuitry of social cognition and behavior, much of this work has focused on experiments that sacrifice ecological validity for experimental control. Functional near-infrared spectroscopy (fNIRS) is a promising methodology for measuring brain activity in the context of naturalistic social interactions. Here, we review what we have learned from fNIRS studies that have used traditional experimental stimuli to study social development during infancy. We then discuss recent infant fNIRS studies that have utilized more naturalistic social stimuli, followed by a discussion of applications of this methodology to the study of atypical social development, with a focus on infants at risk for autism spectrum disorder. We end with recommendations for applying fNIRS to studies of typically developing and at-risk infants in naturalistic social situations.

Children living in low‐resource settings are at risk for failing to reach their developmental potential. While the behavioral outcomes of growing up in such settings are well‐known, the neural mechanisms underpinning poor outcomes have not been well elucidated, particularly in the context of low‐ and middle‐income countries. In this study, we measure brain metabolic responses to social and nonsocial stimuli in a cohort of 6‐ and 36‐month‐old Bangladeshi children. Study participants in both cohorts lived in an urban slum and were exposed to a broad range of adversity early in life including extreme poverty, malnutrition, recurrent infections, and low maternal education. We observed brain regions that responded selectively to social stimuli in both ages indicating that these specialized brain responses are online from an early age. We additionally show that the magnitude of the socially selective response is related to maternal education, maternal stress, and the caregiving environment. Ultimately our results suggest that a variety of psychosocial hazards have a measurable relationship with the developing social brain.

Infants are responsive to and show a preference for human vocalizations from very early in development. While previous studies have provided a strong foundation of understanding regarding areas of the infant brain that respond preferentially to social vs. non-social sounds, how the infant brain responds to sounds of varying social significance over time, and how this relates to behavior, is less well understood. The current study uniquely examined longitudinal brain responses to social sounds of differing social-communicative value in infants at 3 and 6 months of age using functional near-infrared spectroscopy (fNIRS). At 3 months, infants showed similar patterns of widespread activation in bilateral temporal cortices to communicative and non-communicative human non-speech vocalizations, while by 6 months infants showed more similar, and focal, responses to social sounds that carried increased social value (infant-directed speech and human non-speech communicative sounds). In addition, we found that brain activity at 3 months of age related to later brain activity and receptive language abilities as measured at 6 months. These findings suggest areas of consistency and change in auditory social perception between 3 and 6 months of age. Keywords: fNIRS, Infancy, Social perception, Brain development, Auditory stimuli

Highlights • Brain response distributed across regions in infants at high risk for autism. • Brain response localized to anterior regions in 6-month-old low risk infants. • Comparing groups, high risk infants had reduced response in anterior regions. • High risk infants had greater response than low risk infants in right posterior. • Brain response to speech predicted language outcomes in low risk infants only., Infants at high familial risk for autism spectrum disorder (ASD) are at increased risk for language impairments. Studies have demonstrated that atypical brain response to speech is related to language impairments in this population, but few have examined this relation longitudinally. We used functional near-infrared spectroscopy (fNIRS) to investigate the neural correlates of speech processing in 6-month-old infants at high (HRA) and low risk (LRA) for autism. We also assessed the relation between brain response to speech at 6-months and verbal developmental quotient (VDQ) scores at 24-months. LRA infants exhibited greater brain response to speech in bilateral anterior regions of interest (ROIs) compared to posterior ROIs, while HRA infants exhibited similar brain response across all ROIs. Compared to LRA infants, HRA+ infants who were later diagnosed with ASD had reduced brain response in bilateral anterior ROIs, while HRA- infants who were not later diagnosed with ASD had increased brain response in right posterior ROI. Greater brain response in left anterior ROI predicted VDQ scores for LRA infants only. Findings highlight the importance of studying HRA+ and HRA- infants separately, and implicate a different, more distributed neural system for speech processing in HRA infants that is not related to language functioning.

Greater relative right (versus left) frontal cortical activation to emotional faces as measured with alpha power in the electroencephalogram (EEG), has been considered a promising neural marker of increased vulnerability to psychopathology and emotional disorders. We set out to explore multichannel fNIRS as a tool to investigate infants' frontal asymmetry responses (hypothesizing greater right versus left frontal cortex activation) to emotional faces as influenced by maternal anxiety and depression symptoms during the postnatal period. We also explored activation differences in fronto-temporal regions associated with facial emotion processing. Ninety-one typically developing 5- and 7-month-old infants were shown photographs of women portraying happy, fearful and angry expressions. Hemodynamic brain responses were analyzed over two frontopolar and seven bilateral cortical regions subdivided into frontal, temporal and parietal areas, defined by age-appropriate MRI templates. Infants of mothers reporting higher negative affect had greater oxyhemoglobin (oxyHb) activation across all emotions over the left inferior frontal gyrus, a region implicated in emotional communication. Follow-up analyses indicated that associations were driven by maternal depression, but not anxiety symptoms. Overall, we found no support for greater right versus left frontal cortex activation in association with maternal negative affect. Findings point to the potential utility of fNIRS as a method for identifying altered neural substrates associated with exposure to maternal depression in infancy.

Background Non-invasive imaging techniques, such as fNIRS, allow us to shed light on the neural correlates of infant’s social-emotional development within the context of parent-infant interaction. On a behavioral level, numerous studies have investigated parent-infant interaction employing the still-face paradigm and found that the primary caregiver(s), often the mother, is an important coregulator of the infant’s physiological and behavioral stress response. However, limited information is available on how the infant’s brain reacts to the maternal cues during real-life interaction. Methods Therefore, the main aim of the current study was to design a fNIRS paradigm to study live mother-infant interaction and to explore the neural correlates of infant affect regulation during real-life dyadic interaction. To this end, a modified still-face paradigm was designed, which consists of live face-to-face mother-infant, and stranger-infant, interaction episodes, including stressful, “still-face” and non-stressful, “happy-face” interaction blocks, combined with infant fNIRS imaging. Results Hemodynamic brain responses were collected in n = 10 (6 females, mean age 230.2 ± 17.5 days), typically developing infants using the Hitachi ETG-4000 continuous-wave system (22 channels spanning the frontal cortex; 10 Hz system sampling frequency). Infants with usable data (n = 7) showed negative activations, indicated by a decrease in oxygenated hemoglobin, over the middle frontal gyrus in response to happy-face (reunion) interaction with their mothers compared to a female stranger; suggesting deactivation of brain regions associated with affect regulation. We also explored correlations between infant brain responses to maternal interaction and infant characteristics (temperament) as well as experiential/environmental factors (mothers’ self-reported depression symptoms). Conclusions Although the current results are very preliminary, they overall suggest that live design in infant populations is doable and offers unique opportunities to study the neural mechanisms underlying early caregiver(s)-child interaction in a more naturalistic context. Restrictions, and implications, of the methodology are critically discussed.

We investigated heart rate (HR) in infants at 3, 6, 9, and 12 months of age, at high (HRA) and low (LRC) familial risk for ASD, to identify potential endophenotypes of ASD risk related to attentional responses. HR was extracted from functional near-infrared spectroscopy recordings while infants listened to speech stimuli. Longitudinal analysis revealed that HRA infants and males generally had lower baseline HR than LRC infants and females. HRA infants showed decreased HR responses to early trials over development, while LRC infants showed increased responses. These findings suggest altered developmental trajectories in physiological responses to speech stimuli over the first year of life, with HRA infants showing less social orienting over time.

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. Results The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects. Comparison with existing methods Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10-20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system. Conclusions The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest.

Recording of event-related potentials (ERPs) is one of the best-suited technologies for examining brain function in human infants. Yet the existing software packages are not optimized for the unique requirements of analyzing artifact-prone ERP data from infants. We developed a new graphical user interface that enables an efficient implementation of a two-stage approach to the analysis of infant ERPs. In the first stage, video records of infant behavior are synchronized with ERPs at the level of individual trials to reject epochs with noncompliant behavior and other artifacts. In the second stage, the interface calls MATLAB and EEGLAB (Delorme & Makeig, Journal of Neuroscience Methods 134(1):9–21, 2004) functions for further preprocessing of the ERP signal itself (i.e., filtering, artifact removal, interpolation, and rereferencing). Finally, methods are included for data visualization and analysis by using bootstrapped group averages. Analyses of simulated and real EEG data demonstrated that the proposed approach can be effectively used to establish task compliance, remove various types of artifacts, and perform representative visualizations and statistical comparisons of ERPs. The interface is available for download from http://www.uta.fi/med/icl/methods/eeg.html in a format that is widely applicable to ERP studies with special populations and open for further editing by users. Electronic supplementary material The online version of this article (doi:10.3758/s13428-013-0404-4) contains supplementary material, which is available to authorized users.

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. We also quantify the effect of including vasculature on the forward model and list our assumptions that allow us to estimate light penetration depth in the head. We show that using the 10/5 system for the optical probe design allows for the measurement of 37% of the cortical surface on average, with a mean CNR in the visible region of 5.5 dB. Certain anatomical regions, such as the lateral occipital cortex, had a very high percentage above the CNR threshold, while other regions such as the cingulate cortex were not measurable. Vasculature blocked optical sensitivity over 1% of the cortex. Cortical coverage was positively correlated with intracranial volume and relative cerebrospinal fluid volume, and negatively correlated with relative scalp volume and skull volume. These contributions allow experimenters to understand how anatomical variation in a subject population may impact DOT or functional near-infrared spectroscopy measurements.

Near-Infrared Spectroscopy (NIRS) measures the functional hemodynamic response occurring at the surface of the cortex. Large pial veins are located above the surface of the cerebral cortex. Following activation, these veins exhibit oxygenation changes but their volume likely stays constant. The back-reflection geometry of the NIRS measurement renders the signal very sensitive to these superficial pial veins. As such, the measured NIRS signal contains contributions from both the cortical region as well as the pial vasculature. In this work, the cortical contribution to the NIRS signal was investigated using (1) Monte Carlo simulations over a realistic geometry constructed from anatomical and vascular MRI and (2) multimodal NIRS-BOLD recordings during motor stimulation. A good agreement was found between the simulations and the modeling analysis of in vivo measurements. Our results suggest that the cortical contribution to the deoxyhemoglobin signal change ( Δ HbR) is equal to 16–22% of the cortical contribution to the total hemoglobin signal change ( Δ HbT). Similarly, the cortical contribution of the oxyhemoglobin signal change ( Δ HbO) is equal to 73–79% of the cortical contribution to the Δ HbT signal. These results suggest that Δ HbT is far less sensitive to pial vein contamination and therefore, it is likely that the Δ HbT signal provides better spatial specificity and should be used instead of Δ HbO or Δ HbR to map cerebral activity with NIRS. While different stimuli will result in different pial vein contributions, our finger tapping results do reveal the importance of considering the pial contribution.

Diffuse Optical Imaging (DOI) allows the recovery of the hemodynamic response associated with evoked brain activity. The signal is contaminated with systemic physiological interference which occurs in the superficial layers of the head as well as in the brain tissue. The back-reflection geometry of the measurement makes the DOI signal strongly contaminated by systemic interference occurring in the superficial layers. A recent development has been the use of signals from small source-detector separation (1 cm) optodes as regressors. Since those additional measurements are mainly sensitive to superficial layers in adult humans, they help in removing the systemic interference present in longer separation measurements (3 cm). Encouraged by those findings, we developed a dynamic estimation procedure to remove global interference using small optode separations and to estimate simultaneously the hemodynamic response. The algorithm was tested by recovering a simulated synthetic hemodynamic response added over baseline DOI data acquired from 6 human subjects at rest. The performance of the algorithm was quantified by the Pearson R2 coefficient and the mean square error (MSE) between the recovered and the simulated hemodynamic responses. Our dynamic estimator was also compared with a static estimator and the traditional adaptive filtering method. We observed a significant improvement (two-tailed paired t-test, p < 0.05) in both HbO and HbR recovery using our Kalman filter dynamic estimator compared to the traditional adaptive filter, the static estimator and the standard GLM technique.

Correcting for motion is an important consideration in infant functional near-infrared spectroscopy studies. We tested the performance of conventional motion correction methods and compared probe motion and data quality metrics for data collected at different infant ages (5, 7, and 12 months) and during different methods of stimulus presentation (video versus live). While 5-month-olds had slower maximum head speed than 7- or 12-month-olds, data quality metrics and hemodynamic response recovery errors were similar across ages. Data quality was also similar between video and live stimulus presentation. Motion correction algorithms, such as wavelet filtering and targeted principal component analysis, performed well for infant data using infant-specific parameters, and parameters may be used without fine-tuning for infant age or method of stimulus presentation. We recommend using wavelet filtering with [Formula: see text]; however, a range of parameters seemed acceptable. We do not recommend using trial rejection alone, because it did not improve hemodynamic response recovery as compared to no correction at all. Data quality metrics calculated from uncorrected data were associated with hemodynamic response recovery error, indicating that full simulation studies may not be necessary to assess motion correction performance.

Greater loss in structural integrity of the ipsilesional corticospinal tract (CST) is associated with poorer motor outcome in patients with hemiparetic stroke. Animal models of stroke have demonstrated that structural remodeling of white matter in the ipsilesional and contralesional hemispheres is associated with improved motor recovery. Accordingly, motor recovery in patients with stroke may relate to the relative strength of CST degeneration and remodeling. This study examined the relationship between microstructural status of brain white matter tracts, indexed by the fractional anisotropy (FA) metric derived from diffusion tensor imaging (DTI) data, and motor skill of the stroke-affected hand in patients with chronic stroke. Voxelwise analysis revealed that motor skill significantly and positively correlated with FA of the ipsilesional and contralesional CST in the patients. Additional voxelwise analyses showed that patients with poorer motor skill had reduced FA of bilateral CST compared to normal control subjects, whereas patients with better motor skill had elevated FA of bilateral CST compared to controls. These findings were confirmed using a DTI-tractography method applied to the CST in both hemispheres. The results of this study suggest that the level of motor skill recovery achieved in patients with hemiparetic stroke relates to microstructural status of the CST in both the ipsilesional and contralesional hemispheres, which may reflect the net effect of degeneration and remodeling of bilateral CST.

Functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) can be used to isolate an evoked response to a stimulus from significant background physiological fluctuations. Data analysis approaches typically use averaging or linear regression to remove this physiological baseline with varying degrees of success. Biophysical model-based analysis of the functional hemodynamic response has also been advanced previously with the Balloon and Windkessel models. In the present work, a biophysical model of systemic and cerebral circulation and gas exchange is applied to resting state NIRS neuroimaging data from 10 human subjects. The model further includes dynamic cerebral autoregulation, which modulates the cerebral arteriole compliance to control cerebral blood flow. This biophysical model allows for prediction, from noninvasive blood pressure measurements, of the background hemodynamic fluctuations in the systemic and cerebral circulations. Significantly higher correlations with the NIRS data were found using the biophysical model predictions compared to blood pressure regression and compared to transfer function analysis (multifactor ANOVA, p < 0.0001). This finding supports the further development and use of biophysical models for removing baseline activity in functional neuroimaging analysis. Future extensions of this work could model changes in cerebrovascular physiology that occur during development, aging, and disease.

Changes in heart rate are a useful physiological measure in infant studies. We present an algorithm for calculating the heart rate (HR) from oxyhemoglobin pulsation in functional near-infrared spectroscopy (fNIRS) signals. The algorithm is applied to data collected from 10 infants, and the HR derived from the fNIRS signals is compared against the HR as calculated by electrocardiography. We show high agreement between the two HR signals for all infants (r>0.90), and also compare stimulus-related HR responses as measured by the two methods and find good agreement despite high levels of movement in the infants. This algorithm can be used to measure changes in HR in infants participating in fNIRS studies without the need for additional HR sensors.

We have studied the effects on the exchange bias of decreasing the antiferromagnetic layer to the Angstro/spl uml/m-scale regime in order to shed light on the minimum required thickness of the antiferromagnet. We have deposited IrMn layers between 0.2 and 2 nm on spin valves and measured the exchange bias by examining hysteresis loops at 5 K using the giant magnetoresistance of the spin valves. The exchange bias persists for IrMn thicknesses down to 0.4 nm and has a maximum at 1.6 nm. Because the ultra-thin layers create an exchange field, the origin of at least one component of exchange biasing must have a similarly short length scale.

Near-Infrared Spectroscopy (NIRS) measures the functional hemodynamic response occuring at the surface of the cortex. Large pial veins are located above the surface of the cerebral cortex. Following activation, these veins exhibit oxygenation changes but their volume likely stays constant. The back-reflection geometry of the NIRS measurement renders the signal very sensitive to these superficial pial veins. As such, the measured NIRS signal contains contributions from both the cortical region as well as the pial vasculature. In this work, the cortical contribution to the NIRS signal was investigated using (1) Monte Carlo simulations over a realistic geometry constructed from anatomical and vascular MRI and (2) multimodal NIRS-BOLD recordings during motor stimulation. A good agreement was found between the simulations and the modeling analysis of in vivo measurements. Our results suggest that the cortical contribution to the deoxyhemoglobin signal change (ΔHbR) is equal to 16-22% of the cortical contribution to the total hemoglobin signal change (ΔHbT). Similarly, the cortical contribution of the oxyhemoglobin signal change (ΔHbO) is equal to 73-79% of the cortical contribution to the ΔHbT signal. These results suggest that ΔHbT is far less sensitive to pial vein contamination and therefore, it is likely that the ΔHbT signal provides better spatial specificity and should be used instead of ΔHbO or ΔHbR to map cerebral activity with NIRS. While different stimuli will result in different pial vein contributions, our finger tapping results do reveal the importance of considering the pial contribution.

Near-Infrared Spectroscopy (NIRS) allows the recovery of cortical oxy- and deoxyhemoglobin changes associated with evoked brain activity. NIRS is a back-reflection measurement making it very sensitive to the superficial layers of the head, i.e. the skin and the skull, where systemic interference occurs. As a result, the NIRS signal is strongly contaminated with systemic interference of superficial origin. A recent approach to overcome this problem has been the use of additional short source-detector separation optodes as regressors. Since these additional measurements are mainly sensitive to superficial layers in adult humans, they can be used to remove the systemic interference present in longer separation measurements, improving the recovery of the cortical hemodynamic response function (HRF). One question that remains to answer is whether or not a short separation measurement is required in close proximity to each long separation NIRS channel. Here, we show that the systemic interference occurring in the superficial layers of the human head is inhomogeneous across the surface of the scalp. As a result, the improvement obtained by using a short separation optode decreases as the relative distance between the short and the long measurement is increased. NIRS data was acquired on 6 human subjects both at rest and during a motor task consisting of finger tapping. The effect of distance between the short and the long channel was first quantified by recovering a synthetic hemodynamic response added over the resting-state data. The effect was also observed in the functional data collected during the finger tapping task. Together, these results suggest that the short separation measurement must be located as close as 1.5 cm from the standard NIRS channel in order to provide an improvement which is of practical use. In this case, the improvement in Contrast-to-Noise Ratio (CNR) compared to a standard General Linear Model (GLM) procedure without using any small separation optode reached 50% for HbO and 100% for HbR. Using small separations located farther than 2 cm away resulted in mild or negligible improvements only.

The brain processes involved in the restoration of motor skill after hemiparetic stroke are not fully understood. The current study compared cortical activity in chronic stroke patients who successfully recovered hand motor skill and normal control subjects during performance of kinematically matched unskilled and skilled hand movements using functional magnetic resonance imaging. We found that cortical activation during performance of the unskilled movement was increased in the patients relative to controls in the contralesional primary sensorimotor cortex. Performance of the skilled movement elicited increased activation in the patients relative to controls in the contralesional primary sensorimotor cortex, ventral premotor cortex, supplementary motor area/cingulate, and occipitoparietal cortex. Further, the activation change in the contralesional occipitoparietal cortex was greater in the patients relative to controls with the increase in motor skill challenge. Kinematic differences, mirror movements, and residual motor deficits did not account for the enhanced activation in the contralesional cortices in the patients. These results suggest that activation in the contralesional cortical network was enhanced as a function of motor skill challenge in stroke patients with good motor recovery. The findings of the current study suggest that successful recovery of motor skill after hemiparetic stroke involves participation of the contralesional cortical network.

Damage to the corticospinal tract (CST) in stroke patients has been associated with functional reorganization in the ipsilesional and contralesional sensorimotor cortices. However, it is unknown whether a quantitative relationship exists between the extent of structural damage to the CST and functional reorganization in stroke patients. The purpose of the current study was to examine the relationship between structural CST damage and motor task-related cortical activity in chronic hemiparetic stroke patients. In ten chronic hemiparetic stroke patients with heterogeneous lesions, CST damage was quantified using conventional structural magnetic resonance imaging and tractography based on diffusion tensor imaging. Cortical activity was measured using functional magnetic resonance imaging during repetitive flexion/extension movements of the digits. We found that the two measures of CST damage were strongly correlated. Moreover, greater CST damage was significantly and linearly correlated with increased activation during affected hand movement in the hand area of the contralesional primary sensorimotor cortex (M1/S1) and in the ipsilesional M1/S1 ventral to the hand area. To our knowledge, this is the first demonstration of a quantitative relationship between the extent of structural damage to the CST and functional reorganization in stroke patients. This relationship was observed in stroke patients with heterogeneous lesions, suggesting that CST damage is a factor relevant to the variation in functional reorganization in the clinical population.

The kinematics of motor task performance affect brain activity. However, few functional magnetic resonance imaging (fMRI) motor studies have accounted for on-line kinematics because there are currently few MRI-compatible devices to record motor performance. We built a device based on Micro-Electro-Mechanical System (MEMS) gyroscopes that measures the angular velocity of one segment of each of the 10 fingers while a subject performs a finger motor task during fMRI. Finger position, acceleration, and jerk were computed from the angular velocity measurements. The signal-to-noise ratio (SNR) of the MEMS sensors (range: 27.10-34.36 dB) allowed for clear detection of velocity of finger motion during fMRI motor task performance, and showed good stability over time. We demonstrate that use of the MEMS-based device, while negligibly increasing radiofrequency (RF) noise in the scanning environment, did not cause MR image artifacts nor alter fMRI statistical activation maps. Further, we show that signal from the MEMS sensors was not affected by the high static magnetic field (3 T). Increasing the RF power transmitted during fMRI by using a body coil, as compared to a head coil, decreased the sensor's SNR from 30.7 to 24.2 dB, though this loss in SNR did not interfere with the ability to measure velocity of finger motion. We demonstrate the utility of the MEMS-based device in fMRI motor studies through two experiments that examined the relationship between finger movement kinematics and fMRI activation in the healthy and injured brain. On-line acquisition of motor performance during fMRI, through the use of the MEMS-based device, promises to allow for a more detailed understanding of the relationship between movement kinematics and activation in the healthy and injured brain.

This work uses the giant magnetoresistance (GMR) of spin valves with pico-scale IrMn layers to determine the exchange biasing effects. The samples were prepared by magnetron sputtering. This paper focuses on the results for the 5 K measurements of the GMR, exchange field and coercive field. The coercive field and exchange field are measured as a function of IrMn thickness and it was found that for IrMn layers /spl les/12 /spl Aring/, the coercive field is larger than the exchange field.

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. We found that CTF decreases as the spatial extent of cortical activity decreases, and that correlations between nearby sensors depend on the spatial extent of cortical activity. For cortical activity on the intermediate spatial scale of 6.7 cm(2), the correlation distances (r>0.5) were 1.0 cm for fMRI, 2.0 cm for DOT, 12.8 for EEG, 9.5 cm for MEG magnetometers and 9.7 cm for MEG gradiometers. The resolvable spatial pattern scale was found to be 1.43 cm(2) for MEG magnetometers, 0.88 cm(2) for MEG gradiometers, 376 cm(2) for EEG, 0.75 cm(2) for DOT, and 0.072 cm(2) for fMRI. These findings show that sensitivity to cortical activity varies substantially as a function of spatial scale within and between the different imaging modalities. This information should be taken into account when interpreting neuroimaging data and when choosing the number of nodes for network analyses in sensor space.

Microscopic models of exchange bias focus on the formation of domains in the antiferromagnet or the ferromagnet, or on a small induced moment in the antiferromagnet. Previous giant magnetoresistance (GMR) measurements, however, reveal exchange bias and training effects in CoFe-based spin valves with antiferromagnetic IrMn layers as thin as 0.4 nm. Polarized neutron reflectometry studies of a related spin valve with a 1.6 nm IrMn layer were carried out for several points along the GMR hysteresis curve to probe separately the free and pinned CoFe layers. These measurements confirm that the two ferromagnetic CoFe layers are aligned in parallel in saturating fields. During the first field cyle, regions of high resistance correspond to an antiparallel alignment of the CoFe layers as expected. Significant changes in this antiparallel structure are observed during the second field sweep, and a magnetic spiral forms and persists in the pinned CoFe layer. High-field saturation seems to reduce the effectiveness of ...

The spin dependent mean free path in Co90Fe10 is determined as a function of temperature down to 5K using two different spin valve structures. At 5K the spin dependent mean free path for one structure was measured to be 9.4±1.4nm, decreasing by a factor of 3 by 350K. For the other structure, it is 7.5±0.5nm at 5K and decreased by a factor of 1.5 by 350K. In both cases, the spin dependent mean free path approaches the typical thickness of ferromagnetic layers in spin valves at room temperature and, thus, has an impact on the choice of design parameters for the development of new spintronic devices.