Ata Akin

Extraction of cognitive activity related waveforms from functional near infrared signals

We address the problem of prototypical waveform extraction in cognitive experiments using functional near-infrared spectroscopy (fNIRS) signals. These waveform responses are evoked with visual stimuli provided in an oddball type experimental protocol. As the statistical signal-processing tool, we consider the linear signal space representation paradigm and use independent component analysis (ICA). The assumptions underlying ICA is discussed in the light of the signal measurement and generation mechanisms in the brain. The ICA-based waveform extraction is validated based both on its conformance to the parametric brain hemodynamic response (BHR) model and to the coherent averaging technique. We assess the intra-subject and inter-subject waveform and parameter variability.

Cerebrovascular dynamics in patients with migraine: near-infrared spectroscopy study.

Migraine is hypothesized to be a neurovascular coupling disorder where the cerebral vascular reactivity is malfunctioning and measuring hemodynamic changes during migraine without causing more disturbance has always been a challenge. Functional near infrared spectroscopy system (fNIRS) is being proposed as an inexpensive, rapid, safe and accurate alternative to fMRI, transcranial doppler sonography (TCD). We have developed NIROXCOPE 201, a novel device for fNIRS which offers 16 source-detector pairs distributed on a probe that is placed on the forehead. Measuring hemodynamic changes during migraine without causing more disturbance has always been a challenge. Using NIROXCOPE 201, we have attempted to investigate the cerebrovascular reactivity of migraine patients to a breath hold task which produces a metabolic perturbation. Six normals and six migraine patients performed four consecutive breath holding task. We calculated the peak and latencies of the initial dip and recovery phases for [Hb], [HbO(2)], [tHb], and [OXY] signals. [Hb], [tHb], and [OXY] ID and R amplitudes of normals are approximately a magnitude higher than migraine patients (P<0.01), while latencies showed no significant differences. Data suggests an altered neurovascular coupling in frontal cortex of migraine patients interictally. The application of NIROXCOPE 201 to patients suffering from other primary headache disorders will reveal diagnostic as well as therapeutic implications of the presented study.

Multilevel Statistical Inference From Functional Near-Infrared Spectroscopy Data During Stroop Interference

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for monitoring the concentration changes of oxy- and deoxy-hemoglobin (oxy-Hb and deoxy-Hb) in the brain. An important consideration in fNIRS-based neuroimaging modality is to conduct group-level analysis from a set of time series measured from a group of subjects. We investigate the feasibility of multilevel statistical inference for fNIRS. As a case study, we search for hemodynamic activations in the prefrontal cortex during Stroop interference. Hierarchical general linear model (GLM) is used for making this multilevel analysis. Activation patterns both at the subject and group level are investigated on a comparative basis using various classical and Bayesian inference methods. All methods showed consistent left lateral prefrontal cortex activation for oxy-Hb during interference condition, while the effects were much less pronounced for deoxy-Hb. Our analysis showed that mixed effects or Bayesian models are more convenient for faithful analysis of fNIRS data. We arrived at two important conclusions. First, fNIRS has the capability to identify activations at the group level, and second, the mixed effects or Bayesian model is the appropriate mechanism to pass from subject to group-level inference.

Multimodal investigation of fMRI and fNIRS derived breath hold BOLD signals with an expanded balloon model.

Multimodal investigation of blood oxygenation level-dependent (BOLD) signals, using both functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI), may give further insight to the underlying physiological principles and the detailed transient dynamics of the vascular response. Utilizing a breath hold task (BHT), we measured deoxy-hemoglobin (HbR) and oxy-hemoglobin (HbO) changes via fNIRS and blood oxygen level dependent (BOLD) changes by fMRI. Measurements were taken in four volunteers asynchronously and carefully aligned for comparative analysis. In order to describe the main stimulus in BHT, partial pressure of carbon dioxide (PaCO(2)) parameter was integrated into the balloon model as the driving function of cerebral blood flow (CBF) which led to the development of an expanded balloon model (EBM). During BHT, the increase in HbR was observed later than the BOLD peak and coincided temporally with its post-stimulus undershoot. Further investigation of these transients with a PaCO(2) integrated balloon model suggests that post-stimulus undershoot measured by fMRI is dominated by slow return of cerebral blood volume (CBV). This was confirmed by fNIRS measurements. In addition, the BOLD signal decreased with the increase of the initial level of PaCO(2) derived from EBM, indicating an effect of basal CBF level on the BOLD signal. In conclusion, a multimodal approach with an appropriate biophysical model gave a comprehensive description of the hemodynamic response during BHT.

Spectral Analysis of Event-Related Hemodynamic Responses in Functional Near Infrared Spectroscopy

The goal of this paper is to design experiments that confirm the evidence of cognitive responses in functional near infrared spectroscopy and to establish relevant spectral subbands. Hemodynamic responses of brain during single-event trials in an odd-ball experiment are measured by functional near infrared spectroscopy method. The frequency axis is partitioned into subbands by clustering the time-frequency power spectrum profiles of the brain responses. The predominant subbands are observed to confine the 0–30 mHz, 30–60 mHz, and 60–330 mHz ranges. We identify the group of subbands that shows strong evidence of protocol-induced periodicity as well as the bands where good correlation with an assumed hemodynamic response models is found.

Cerebrovascular reactivity to hypercapnia in migraine patients measured with near-infrared spectroscopy

Migraine pain is considered to manifest itself as a result of an impaired cerebrovascular reactivity. Hence, proper quantification and diagnosis of this problem without causing more disturbance has always been a challenge in investigating migraine pathogenesis. Functional near-infrared spectroscopy system (fNIRS) is being proposed as an inexpensive, rapid, safe and accurate technique to monitor cerebrovascular dynamics. We have developed NIROXCOPE 201, a novel multi source and detector device of fNIRS, and attempted to investigate the cerebrovascular reactivity of migraine patients to a breath hold task which produces a metabolic perturbation. Six normals and six migraine patients performed four consecutive breath holding task. A typical brain hemodynamic response (BHR) is observed both for controls and migraineurs with an initial phase, main response and a recovery phase. Hence, fitting to a sum of three sequentially arranged gaussian curves proved that amplitudes of [Hb] and [HbO2] signals acquired by fNIRS are approximately two to five times higher in controls than migraine patients (P<0.01) for all phases. Moreover, amplitude change between successive breath holds tends to converge to a steady value for controls whereas an uncontrolled percent change is observed for migraineurs. Our results confirm an impaired cerebrovascular reactivity in the frontal cortex of migraine patients interictally.

Association Among SNAP-25 Gene DdeI and MnlI Polymorphisms and Hemodynamic Changes During Methylphenidate Use A Functional Near-Infrared Spectroscopy Study

Objective: To investigate the interaction of treatment-related hemodynamic changes with genotype status for Synaptosomal associated protein 25 (SNAP-25) gene in participants with attention deficit hyperactivity disorder (ADHD) on and off single dose short-acting methylphenidate treatment with functional near-infrared spectroscopy (fNIRS). Method: A total of 15 right-handed adults and 16 right-handed children with DSM-IV diagnosis of ADHD were evaluated. Ten milligrams of short-acting methylphenidate was administered in a crossover design. Results: Participants with SNAP-25 DdeI T/T genotype had decreased right deoxyhemoglobin ([HHb]) with treatment. SNAP-25 MnlI genotype was also associated with right deoxyhemoglobin ([HbO2]) and [HHb] changes as well as left [HHb] change. When the combinations of these genotypes were taken into account, the participants with [DdeI C/C or T/C and MnlI G/G or T/G] genotype had increased right [HHb] with MPH use whereas the participants with [DdeI T/T and MnlI T/T] or [DdeI T/T and MnlI G/G or T/G] genotypes had decreased right prefrontal [HHb]. Conclusions: These results suggested that SNAP-25 polymorphism might be associated with methylphenidate induced brain hemodynamic changes in ADHD participants.

Constraining the general linear model for sensible hemodynamic response function waveforms

We propose a method to do constrained parameter estimation and inference from neuroimaging data using general linear model (GLM). Constrained approach precludes unrealistic hemodynamic response function (HRF) estimates to appear at the outcome of the GLM analysis. The permissible ranges of waveform parameters were determined from the study of a repertoire of plausible waveforms. These parameter intervals played the role of prior distributions in the subsequent Bayesian analysis of the GLM, and Gibbs sampling was used to derive posterior distributions. The method was applied to artificial null data and near infrared spectroscopy (NIRS) data. The results show that constraining the GLM eliminates unrealistic HRF waveforms and decreases false activations, without affecting the inference for “realistic” activations, which satisfy the constraints.

On Temporal Connectivity of PFC Via Gauss - Markov Modeling of fNIRS Signals

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults. The color-word matching Stroop task is performed to activate 16 different regions of PFC. There are three different types of stimuli in this task, which can be listed as incongruent stimulus (IS), congruent stimulus (CS), and neutral stimulus (NS), respectively. We introduce a new measure, called ¿information transfer metric¿ (ITM) for each time sample. The behavior of ITMs during IS are significantly different from the ITMs during CS and NS, which is consistent with the outcome of the previous research, which concentrated on fNIRS signal analysis via color-word matching Stroop task. Our analysis shows that the functional connectivity of PFC is highly relevant with the cognitive load, i.e., functional connectivity increases with the increasing cognitive load.

Wavelet denoising vs. ICA denoising for functional optical imaging

We performed a comparison between two source signal extraction algorithms, namely the Wavelet Denoising (WD) by Soft Thresholding and Independent Component Analysis (ICA) on a simulated functional optical imaging data. The simulated data are generated by combining a gamma function superimposed on a very low frequency sine wave as the source data and the additive noise components are chosen as having both Gaussian and non-Gaussian parts. We observed that ICA denoising outperforms significantly wavelet denoising scheme when the signal-to-noise ratio (SNR) decreases to below 0 dB.