Archana K. Singh

Virtual spatial registration of stand-alone fNIRS data to MNI space.

The registration of functional brain data to common stereotaxic brain space facilitates data sharing and integration across different subjects, studies, and even imaging modalities. Thus, we previously described a method for the probabilistic registration of functional near-infrared spectroscopy (fNIRS) data onto Montreal Neurological Institute (MNI) coordinate space that can be used even when magnetic resonance images of the subjects are not available. This method, however, requires the careful measurement of scalp landmarks and fNIRS optode positions using a 3D-digitizer. Here we present a novel registration method, based on simulations in place of physical measurements for optode positioning. First, we constructed a holder deformation algorithm and examined its validity by comparing virtual and actual deformation of holders on spherical phantoms and real head surfaces. The discrepancies were negligible. Next, we registered virtual holders on synthetic heads and brains that represent size and shape variations among the population. The registered positions were normalized to MNI space. By repeating this process across synthetic heads and brains, we statistically estimated the most probable MNI coordinate values, and clarified errors, which were in the order of several millimeters across the scalp, associated with this estimation. In essence, the current method allowed the spatial registration of completely stand-alone fNIRS data onto MNI space without the use of supplementary measurements. This method will not only provide a practical solution to the spatial registration issues in fNIRS studies, but will also enhance cross-modal communications within the neuroimaging community.

Exploring the false discovery rate in multichannel NIRS.

Near infrared spectroscopy (NIRS), an emerging non-invasive tool for functional neuroimaging, has evolved as a multichannel technique allowing simultaneous measurements through many channels ranging from below ten to above hundred. Simultaneous testing of such a large number of channels escalates the risk of Type I error, therefore multiplicity correction is unavoidable. To date, only a few studies have considered this issue using Bonferroni correction, which is an effective conservative solution, but may be too severe for neuroimaging. Its power varies in inverse proportion of the number of channels, which varies among NIRS studies depending on selected region of interest (ROI), thereby leading to a subjective inference. This problem may be well circumvented by a more contemporary approach, called false discovery rate (FDR) that is widely being adopted in functional neuroimaging. An FDR-based procedure controls the expected proportion of erroneously rejected hypotheses among the rejected hypotheses, which offers a more objective, powerful, and consistent measure of Type I error than Bonferroni correction and maintains a better balance between power and specificity. In this technical note, we examine FDR approach using examples from simulated and real NIRS data. The FDR-based procedure could yield 52% more power than Bonferroni correction in a 172-channel real NIRS study and proved to be more robust against the changing number of channels.

Virtual 10-20 measurement on MR images for inter-modal linking of transcranial and tomographic neuroimaging methods.

It is important to create a link between stereotaxic coordinates and head-surface-based positioning systems in order to share data between tomographic and transcranial brain mapping studies. In our previous studies, we established the probabilistic correspondence of the international 10-20 positions to the standard stereotaxic coordinate systems and made a reference database. However, its expansion required the physical marking of the 10-20 positions and the subsequent acquisition of MR images. To avoid such tedious procedures, we developed a virtual 10-20 measurement algorithm that can be applied to re-analyze any structural MR image that covers the whole head. As in the physical 10-20 measurements, with the reference points given, the algorithm automatically determines each 10-20 position step by step. Using the virtual 10-20 measurement method, we re-analyzed the MR images of 17 healthy subjects for whom we had determined 10-20 positions by physical marking in our previous study. The acquired 10-20 positions were normalized to the Montreal Neurological Institute (MNI) stereotactic coordinates and compared with the positions previously determined by physical measurements. 10-20 positions determined using the virtual and physical methods were roughly consistent. Average standard deviations for virtual and physical methods were 7.7 mm and 9.0 mm, respectively. There was a systematic shift in the virtual method, likely due to the absence of hair interference. We corrected the shift with affine transformation. The virtual 10-20 measurement method proved to be an effective alternative to physical marking. This method will serve as an essential tool for expanding the reference database and will further strengthen the link between tomographic and transcranial brain mapping methods.

Process-specific prefrontal contributions to episodic encoding and retrieval of tastes: A functional NIRS study

The neural basis of memory subprocesses, encoding and retrieval, have been extensively examined in functional neuroimaging studies. However, the cortical substrates of taste memory, which form an important part of our episodic memory, have rarely been explored in humans. Previously, we have used functional near-infrared spectroscopy (fNIRS) and found activation of the lateral prefrontal cortex (LPFC) related to taste encoding. The method used in the current study allowed brain monitoring while participants tasted liquid taste-stimuli in upright positions. Here, using the same system, we examined the LPFC activity of 28 healthy volunteers during both the encoding and the retrieval of taste memory. The contrast between the retrieval and eyes-closed-resting conditions revealed activation in the bilateral LPFC. This activation was significantly larger than that for encoding in the bilateral frontopolar and right dorso-LPFC regions, particularly in the right hemisphere (N=28, P<0.05, FDR corrected), exhibiting right hemispheric dominance. Our findings are in line with the hemispheric encoding/retrieval asymmetry (HERA) model, which proposes a process-specific prefrontal contribution to memory function.

Structural atlas-based spatial registration for functional near-infrared spectroscopy enabling inter-study data integration

OBJECTIVE The use of functional near-infrared spectroscopy (fNIRS) is growing, leading to a need for methods to summarise data from multiple studies. However, this is difficult using the current channel-based methods when experiments do not share a common channel (CH) arrangement. Thus, we proposed and implemented a CH-independent analysis method for summarising fNIRS data. METHODS We defined sub-regions as spatial bins to organise fNIRS data. Sub-regions were defined on the standard brain surface based on macro- and micro-structural information. After probabilistically estimating CH location in standard stereotaxic brain space, the CH-based data were reorganised into these spatial bins to evaluate sub-region-based activation. RESULTS Sub-regions with sizes corresponding to fNIRS spatial resolution were defined. We demonstrated this method by integrating data from two of our fNIRS studies that shared the same region of interest but used different channel arrangements. CONCLUSIONS Using this method, data from multiple fNIRS studies with different CH arrangements can be integrated in standard brain space, while keeping in mind the brain structure-function relationship. SIGNIFICANCE The current method will facilitate an effective use of accumulating fNIRS data by allowing integration of data from multiple studies.

Prefrontal activity during flavor difference test: Application of functional near-infrared spectroscopy to sensory evaluation studies

Sensory evaluation (SE) of food attributes involves various levels of cognitive functions, yet not much has been studied about its neural basis. Using multi-channel functional near-infrared spectroscopy (fNIRS), we examined the activation of the anterior portion of the lateral prefrontal cortex (LPFC) of 12 healthy volunteers during the SE of tea samples. The experimental task used corresponded to the early phase of the same-different test, and required subjects to attentively taste tea samples and memorize their flavors. To isolate activation associated with the cognitive functions involved in the task, we contrasted the results with those achieved by a control (Ctl) task during which subjects held familiar tea samples in their mouths without actively evaluating their flavor. We probabilistically registered the fNIRS data to the Montreal Neurological Institute standard brain space to examine the results as they correspond with other published neuroimaging studies. We found significant activation in the left LPFC and in the right inferior frontal gyrus. The activation pattern was consistent with earlier studies on encoding of other sensory stimuli, with cortical regions supposed to be involved in semantic and perceptual processing. This research makes a start on characterizing the cognitive process employed during SE from the neuroimaging perspective.

Visual feature integration indicated by pHase-locked frontal-parietal EEG signals.

The capacity to integrate multiple sources of information is a prerequisite for complex cognitive ability, such as finding a target uniquely identifiable by the conjunction of two or more features. Recent studies identified greater frontal-parietal synchrony during conjunctive than non-conjunctive (feature) search. Whether this difference also reflects greater information integration, rather than just differences in cognitive strategy (e.g., top-down versus bottom-up control of attention), or task difficulty is uncertain. Here, we examine the first possibility by parametrically varying the number of integrated sources from one to three and measuring phase-locking values (PLV) of frontal-parietal EEG electrode signals, as indicators of synchrony. Linear regressions, under hierarchical false-discovery rate control, indicated significant positive slopes for number of sources on PLV in the 30–38 Hz, 175–250 ms post-stimulus frequency-time band for pairs in the sagittal plane (i.e., F3-P3, Fz-Pz, F4-P4), after equating conditions for behavioural performance (to exclude effects due to task difficulty). No such effects were observed for pairs in the transverse plane (i.e., F3-F4, C3-C4, P3-P4). These results provide support for the idea that anterior-posterior phase-locking in the lower gamma-band mediates integration of visual information. They also provide a potential window into cognitive development, seen as developing the capacity to integrate more sources of information.

Hierarchical control of false discovery rate for phase locking measures of EEG synchrony.

Computing phase-locking values (PLVs) between EEG signals is becoming a popular measure for quantifying functional connectivity, because it affords a more detailed picture of the synchrony relationships between channels at different times and frequencies. However, the accompanying increase in data dimensionality incurs a serious multiple testing problem for determining PLV significance. Standard methods for controlling Type I error, which treat all hypotheses as belonging to a single family, can fail to detect any significant discoveries. Instead, we propose a novel application of a hierarchical FDR method, which subsumes multiple families, for detecting significant PLV effects. For simulations and experimental data, we show that the proposed hierarchical FDR method is most powerful. This method revealed significant synchrony effects in the expected regions at an acceptable error rate of 5%, where other methods, including standard FDR correction failed to reveal any significant effects.

Establishment of 3D Co-Culture Models from Different Stages of Human Tongue Tumorigenesis: Utility in Understanding Neoplastic Progression

To study multistep tumorigenesis process, there is a need of in-vitro 3D model simulating in-vivo tissue. Present study aimed to reconstitute in-vitro tissue models comprising various stages of neoplastic progression of tongue tumorigenesis and to evaluate the utility of these models to investigate the role of stromal fibroblasts in maintenance of desmosomal anchoring junctions using transmission electron microscopy. We reconstituted in-vitro models representing normal, dysplastic, and malignant tissues by seeding primary keratinocytes on either fibroblast embedded in collagen matrix or plain collagen matrix in growth factor-free medium. The findings of histomorphometry, immunohistochemistry, and electron microscopy analyses of the three types of 3D cultures showed that the stratified growth, cell proliferation, and differentiation were comparable between co-cultures and their respective native tissues; however, they largely differed in cultures grown without fibroblasts. The immunostaining intensity of proteins, viz., desmoplakin, desmoglein, and plakoglobin, was reduced as the disease stage increased in all co-cultures as observed in respective native tissues. Desmosome-like structures were identified using immunogold labeling in these cultures. Moreover, electron microscopic observations revealed that the desmosome number and their length were significantly reduced and intercellular spaces were increased in cultures grown without fibroblasts when compared with their co-culture counterparts. Our results showed that the major steps of tongue tumorigenesis can be reproduced in-vitro. Stromal fibroblasts play a role in regulation of epithelial thickness, cell proliferation, differentiation, and maintenance of desmosomalanchoring junctions in in-vitro grown tissues. The reconstituted co-culture models could help to answer various biological questions especially related to tongue tumorigenesis.

Optimal detection of functional connectivity from high-dimensional EEG synchrony data.

Computing phase-locking values between EEG signals is a popular method for quantifying functional connectivity. However, this method involves large-scale, high-resolution datasets, which impose a serious multiple testing problem. Standard multiple testing methods fail to exploit the information from the complex dependence structure that varies across hypotheses in spectral, temporal, and spatial dimensions and result in a severe loss of power. They tend to control the false positives at the cost of hiding true positives. We introduce a new approach, called optimal discovery procedure (ODP) for identifying synchrony that is statistically significant. ODP maximizes the number of true positives for a given number of false positives, and thus offers a theoretical optimum for detecting significant synchrony in a multiple testing situation. We demonstrate the utility of this method with PLV data obtained from a visual search study. We also present simulation analysis to confirm the validity and relevance of using ODP in comparison with the standard FDR method for given configurations of true synchrony. We also compare the effectiveness of ODP with our previously published investigation of hierarchical FDR method (Singh and Phillips, 2010).