Speeded Near Infrared Spectroscopy (NIRS) Response Detection

The hemodynamic response measured by Near Infrared Spectroscopy (NIRS) is temporally delayed from the onset of the underlying neural activity. As a consequence, NIRS based brain-computer-interfaces (BCIs) and neurofeedback learning systems, may have a latency of several seconds in responding to a change in participants' behavioral or mental states, severely limiting the practical use of such systems. To explore the possibility of reducing this delay, we used a multivariate pattern classification technique (linear support vector machine, SVM) to decode the true behavioral state from the measured neural signal and systematically evaluated the performance of different feature spaces (signal history, history gradient, oxygenated or deoxygenated hemoglobin signal and spatial pattern). We found that the latency to decode a change in behavioral state can be reduced by 50% (from 4.8 s to 2.4 s), which will enhance the feasibility of NIRS for real-time applications

Applications of Multivariate Pattern Classification Analyses in Developmental Neuroimaging of Healthy and Clinical Populations

Analyses of functional and structural imaging data typically involve testing hypotheses at each voxel in the brain. However, it is often the case that distributed spatial patterns may be a more appropriate metric for discriminating between conditions or groups. Multivariate pattern analysis has been gaining traction in neuroimaging of adult healthy and clinical populations; studies have shown that information present in neuroimaging data can be used to decode intentions and perceptual states, as well as discriminate between healthy and diseased brains. While few studies to date have applied these methods in pediatric populations, in this review we discuss exciting potential applications for studying both healthy, and aberrant, brain development. We include an overview of methods and discussion of challenges and limitations

ÔØ Å ÒÙ× Ö ÔØ A quantitative comparison of NIRS and fMRI across multiple cognitive tasks ACCEPTED MANUSCRIPT A quantitative comparison of NIRS and fMRI across multiple cognitive tasks ACCEPTED MANUSCRIPT

Please cite this article as: Cui, Xu, Bray, Signe, Bryant, Daniel M., Glover, Gary H., Reiss, Allan L., A quantitative comparison of NIRS and fMRI across multiple cognitive tasks, NeuroImage (2010NeuroImage ( ), doi: 10.1016NeuroImage ( /j.neuroimage.2010 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT Abstract Near infrared spectroscopy (NIRS) is an increasingly popular technology for studying brain function. NIRS presents several advantages relative to functional magnetic resonance imaging (fMRI), such as measurement of concentration changes in both oxygenated-and deoxygenated hemoglobin, finer temporal resolution, and ease of administration, as well as disadvantages, most prominently inferior spatial resolution and decreased signal-to-noise ratio (SNR). While fMRI has become the gold standard for in vivo imaging of the human brain, in practice NIRS is a more convenient and less expensive technology than fMRI. It is therefore of interest to many researchers how NIRS compares to fMRI in studies of brain function. In the present study we scanned participants with simultaneous NIRS and fMRI on a battery of cognitive tasks, placing NIRS probes over both frontal and parietal brain regions. We performed detailed comparisons of the signals in both temporal and spatial domains. We found that NIRS signals have significantly weaker SNR, but are nonetheless often highly correlated with fMRI measurements. Both SNR and the distance between the scalp and the brain contributed to variability in the NIRS/fMRI correlations. In the spatial domain, we found that a photon path forming an ellipse between the NIRS emitter and detector correlated most strongly with the BOLD response. Taken together these findings suggest that, while NIRS can be an appropriate substitute for fMRI for studying brain activity related to cognitive tasks, care should be taken when designing studies with NIRS to ensure that: 1) the spatial resolution is adequate for answering the question of interest and 2) the design accounts for weaker SNR, especially in brain regions more distal from the scalp

Aberrant functional network recruitment of posterior parietal cortex in Turner syndrome.

Turner syndrome is a genetic disorder caused by the complete or partial absence of an X chromosome in affected women. Individuals with TS show characteristic difficulties with executive functions, visual-spatial and mathematical cognition, with relatively intact verbal skills, and congruent abnormalities in structural development of the posterior parietal cortex (PPC). The functionally heterogeneous PPC has recently been investigated using connectivity-based clustering methods, which sub-divide a given region into clusters of voxels showing similar structural or functional connectivity to other brain regions. In the present study, we extended this method to compare connectivity-based clustering between groups and investigate whether functional networks differentially recruit the PPC in TS. To this end, we parcellated the PPC into sub-regions based on temporal correlations with other regions of the brain. fMRI data were collected from 15 girls with TS and 14 typically developing (TD) girls, aged 7-14, while they performed a visual-spatial task. Temporal correlations between voxels in the PPC and a set of seed regions were calculated, and the PPC divided into clusters of voxels showing similar connectivity. It was found that in general the PPC parcellates similarly in TS and TD girls, but that regions in bilateral inferior parietal lobules, and posterior right superior parietal lobule, were reliably recruited by different networks in TS relative to TD participants. These regions showed weaker correlation in TS with a set of regions involved in visual processing. These results suggest that abnormal development of visuospatial functional networks in TS may relate to the well documented cognitive difficulties in this disorder

Including signals from multiple channels into the feature space improves accuracy and reduces delay in participant 1.

<p>A) accuracy, B) onset delay, and C) offset delay. We ordered all 48 channels by decreasing CNR, and then included one additional channel in each round in that order. For this participant the accuracy peaked at 9 channels and then declined due to overfitting. With 9 channels, the onset delay is reduced to 1.2s and the offset delay is reduced to 0.7s.</p

Classification results with feature spaces including oxy-Hb only (blue), deoxy-Hb only (green), both oxy-Hb and deoxy-Hb (red), CBSI corrected oxy-Hb (cyan), and total (oxy-Hb+deoxy-Hb, pink).

<p>A) accuracy, B) onset delay, and C) offset delay. Compared to the oxy-Hb only feature space, incorporating both oxy-Hb and deoxy-Hb improves the accuracy by 2.4% and reduces the onset delay by 0.3s. The total Hb signal gave the worst classification results; due to poor accuracy, we did not calculate the onset and offset delay for total-Hb.</p

Classification results for the baseline classifier (top row) and a classifier with signal history included in the feature space (bottom row).

<p>The rectangular blue waveform indicates the onset and offset of finger tapping. A,C) The time series of oxy-Hb concentration change in channel 13 in participant 1 is plotted. The time points which are classified as active are plotted in red, and inactive in black. B,D) The time series and classification result of trial 11 is shown in more detail. The feature space of the baseline classifier is simply the amplitude of oxy-Hb in channel 13 (i.e. one dimensional), which essentially classifies based on a single threshold. It's evident from panels A and B that the classified active state (red) is delayed from the true active state (between the vertical blue lines). The onset classification delay in trial 11 is about 6s, and the offset delay is 1.6s. With 2s history of the oxy-Hb signal in channel 13 incorporated into the feature space (C and D, 21-dimensional feature space), the delay is reduced to 4s (onset) and 0.2s (offset).</p

Including first and second order gradients doesn't improve classification performance.

<p>A) accuracy, B) onset delay, and C) offset delay are nearly identical with classifiers based on amplitude, and first or second order gradients.</p

Classification results for all participants.

<p>A) accuracy, B) onset delay C) offset delay. The largest boost in accuracy and drop in delay occurs when history is included in the feature space. For some participants (#1 and #6), including deoxy-Hb or including signals from other channels also improved the performance. Comparing the classifier with the full feature space (history of oxy-Hb and deoxy-Hb, and other channels) to the baseline classifier, the average increase in accuracy is 7.7% (p = 0.004, one sample T test, degree of freedom = 5), the average reduction in onset delay is 2.4s (p = 0.02), and the average reduction in offset delay is 1.3s (p = 0.003).</p

Manipulating visual scanpaths during facial emotion perception modulates functional brain activation in schizophrenia patients and controls

Individuals with schizophrenia exhibit deficits in facial emotion processing, which have been associated with abnormalities in visual gaze behaviour and functional brain activation. However, the relationship between gaze behaviour and brain activation in schizophrenia remains unexamined. Studies in healthy individuals and other clinical samples indicate a relationship between gaze behaviour and functional activation in brain regions implicated in facial emotion processing deficits in schizophrenia (e.g., fusiform gyrus), prompting the question of whether a similar relationship exists in schizophrenia. This study examined whether manipulating visual scanpaths during facial emotion perception would modulate functional brain activation in a sample of 23 schizophrenia patients and 26 community controls. Participants underwent functional magnetic resonance imaging while viewing pictures of emotional faces. During the typical viewing condition, a fixation cue directed participants’ gaze primarily to the eyes and mouth, whereas during the atypical viewing condition gaze was directed to peripheral features. Both viewing conditions elicited a robust response throughout face-processing regions. Typical viewing led to greater activation in visual association cortex including the right inferior occipital gyrus/occipital face area, whereas atypical viewing elicited greater activation in primary visual cortex and regions involved in attentional control. There were no between-group activation differences in response to faces or interaction between group and gaze manipulation. The results indicate that gaze behaviour modulates functional activation in early face-processing regions in individuals with and without schizophrenia, suggesting that abnormal gaze behaviour in schizophrenia may contribute to activation abnormalities during facial emotion perception