The hemodynamic initial-dip consists of both volumetric and oxymetric changes reflecting localized spiking activity.

The initial-dip is a transient decrease frequently observed in functional neuroimaging signals, immediately after stimulus onset, believed to originate from a rise in deoxy-hemoglobin (HbR) caused by local neural activity. It has been shown to be more spatially specific than the hemodynamic response, and is believed to represent focal neuronal activity. However, despite being observed in various neuroimaging modalities (such as fMRI, fNIRS, etc), its origins are disputed, and its precise neuronal correlates are unknown. Here we show that the initial-dip is dominated by a decrease in total-hemoglobin (HbT). We also find a biphasic response in deoxy-Hb (HbR), with an early decrease and later rebound. Both the HbT-dip and HbR-rebound were strongly correlated to highly localized spiking activity. However, HbT decreases were always large enough to counter the spiking-induced increase in HbR. We find that the HbT-dip counters spiking induced HbR increases, imposing an upper-limit to HbR concentration in the capillaries. Building on our results, we explore the possibility of active venule dilation (purging) as a possible mechanism for the HbT dip.

Correction: Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals.

[This corrects the article DOI: 10.1371/journal.pone.0159959.].

Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals.

Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS) for developing Brain-Computer Interface (BCI) by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classification of multi-channel fNIRS signals using support-vector machines (SVM), so as to determine its feasibility as an online neurofeedback system. Towards this goal, we used left versus right hand movement execution and movement imagery as study paradigms in a series of experiments. In the first two experiments, activations in the motor cortex during movement execution and movement imagery were used to develop subject-dependent models that obtained high classification accuracies thereby indicating the robustness of our classification method. In the third experiment, a generalized classifier-model was developed from the first two experimental data, which was then applied for subject-independent neurofeedback training. Application of this method in new participants showed mean classification accuracy of 63% for movement imagery tasks and 80% for movement execution tasks. These results, and their corresponding offline analysis reported in this study demonstrate that SVM based real-time subject-independent classification of fNIRS signals is feasible. This method has important applications in the field of hemodynamic BCIs, and neuro-rehabilitation where patients can be trained to learn spatio-temporal patterns of healthy brain activity.

Simultaneous epidural functional near-infrared spectroscopy and cortical electrophysiology as a tool for studying local neurovascular coupling in primates.

Simultaneous measurements of intra-cortical electrophysiology and hemodynamic signals in primates are essential for relating human neuroimaging studies with intra-cortical electrophysiology in monkeys. Previously, technically challenging and resourcefully demanding techniques such as fMRI and intrinsic-signal optical imaging have been used for such studies. Functional near-infrared spectroscopy is a relatively less cumbersome neuroimaging method that uses near-infrared light to detect small changes in concentrations of oxy-hemoglobin (HbO), deoxy-hemoglobin (HbR) and total hemoglobin (HbT) in a volume of tissue with high specificity and temporal resolution. FNIRS is thus a good candidate for hemodynamic measurements in primates to acquire local hemodynamic signals during electrophysiological recordings. To test the feasibility of using epidural fNIRS with concomitant extracellular electrophysiology, we recorded neuronal and hemodynamic activity from the primary visual cortex of two anesthetized monkeys during visual stimulation. We recorded fNIRS epidurally, using one emitter and two detectors. We performed simultaneous cortical electrophysiology using tetrodes placed between the fNIRS sensors. We observed robust and reliable responses to the visual stimulation in both [HbO] and [HbR] signals, and quantified the signal-to-noise ratio of the epidurally measured signals. We also observed a positive correlation between stimulus-induced modulation of [HbO] and [HbR] signals and strength of neural modulation. Briefly, our results show that epidural fNIRS detects single-trial responses to visual stimuli on a trial-by-trial basis, and when coupled with cortical electrophysiology, is a promising tool for studying local hemodynamic signals and neurovascular coupling.