Functional near-infrared spectroscopy (fNIRS) is an emerging low-cost noninvasive neuroimaging technique that measures cortical bloodflow. While fNIRS has gained interest as a potential alternative to fMRI for use with clinical and pediatric populations, it remains unclear whether fNIRS has the necessary sensitivity to serve as a replacement for fMRI. The present study set out to examine whether fNIRS has the sensitivity to detect linear changes in activation and functional connectivity in response to cognitive load, and functional connectivity changes when transitioning from a task-free resting state to a task. Sixteen young adult subjects were scanned with a continuous-wave fNIRS system during a 10-min resting-state scan followed by a letter n-back task with three load conditions. Five optical probes were placed over frontal and parietal cortices, covering bilateral dorsolateral PFC (dlPFC), bilateral ventrolateral PFC (vlPFC), frontopolar cortex (FP), and bilateral parietal cortex. Activation was found to scale linearly with working memory load in bilateral prefrontal cortex. Functional connectivity increased with increasing n-back loads for fronto-parietal, interhemispheric dlPFC, and local connections. Functional connectivity differed between the resting state scan and the n-back scan, with fronto-parietal connectivity greater during the n-back, and interhemispheric vlPFC connectivity greater during rest. These results demonstrate that fNIRS is sensitive to both cognitive load and state, suggesting that fNIRS is well-suited to explore the full complement of neuroimaging research questions and will serve as a viable alternative to fMRI.

Functional near-infrared spectroscopy (fNIRS) is an optical neuroimaging technique of growing interest as a tool for investigation of cortical activity. Due to the on-head placement of optodes, artifacts arising from head motion are relatively less severe than for functional magnetic resonance imaging (fMRI). However, it is still necessary to remove motion artifacts. We present a novel motion correction procedure based on robust regression, which effectively removes baseline shift and spike artifacts without the need for any user-supplied parameters. Our simulations show that this method yields better activation detection performance than 5 other current motion correction methods. In our empirical validation on a working memory task in a sample of children 7-15 years, our method produced stronger and more extensive activation than any of the other methods tested. The new motion correction method enhances the viability of fNIRS as a functional neuroimaging modality for use in populations not amenable to fMRI.

Little research has been carried out on human performance in optimization problems, such as the Traveling Salesman problem (TSP). Studies by Polivanova (1974, Voprosy Psikhologii, 4, 41-51) and by MacGregor and Ormerod (1996, Perception & Psychophysics, 58, 527-539) suggest that: (1) the complexity of solutions to visually presented TSPs depends on the number of points on the convex hull; and (2) the perception of optimal structure is an innate tendency of the visual system, not subject to individual differences. Results are reported from two experiments. In the first, measures of the total length and completion speed of pathways, and a measure of path uncertainty were compared with optimal solutions produced by an elastic net algorithm and by several heuristic methods. Performance was also compared under instructions to draw the shortest or the most attractive pathway. In the second, various measures of performance were compared with scores on Raven's advanced progressive matrices (APM). The number of points on the convex hull did not determine the relative optimality of solutions, although both this factor and the total number of points influenced solution speed and path uncertainty. Subjects' solutions showed appreciable individual differences, which had a strong correlation with APM scores. The relation between perceptual organization and the process of solving visually presented TSPs is briefly discussed, as is the potential of optimization for providing a conceptual framework for the study of intelligence.

Noninvasive recording of fast optical signals presumably reflecting neuronal activity is a challenging task because of a relatively low signal-to-noise ratio. To improve detection of those signals in rapid object recognition tasks, we used the Independent Component Analysis (ICA) to reduce “global interference” (heartbeat and contribution of superficial layers). We recorded optical signals from the left prefrontal cortex in 10 right-handed participants with a continuous-wave instrument (DYNOT, NIRx, Brooklyn, NY). Visual stimuli were pictures of urban, landscape and seashore scenes with various vehicles as targets (target-to-non-target ratio 1:6) presented at ISI = 166 ms or 250 ms. Subjects mentally counted targets. Data were filtered at 2–30 Hz and artifactual components were identified visually (for heartbeat) and using the ICA weight matrix (for superficial layers). Optical signals were restored from the ICA components with artifactual components removed and then averaged over target and non-target epochs. After ICA processing, the event-related response was detected in 70–100% of subjects. The refined signal showed a significant decrease from baseline within 200–300 ms after targets and a slight increase after non-targets. The temporal profile of the optical signal corresponded well to the profile of a “differential ERP response”, the difference between targets and non-targets which peaks at 200 ms in similar object detection tasks. These results demonstrate that the detection of fast optical responses with continuous-wave instruments can be improved through the ICA method capable to remove noise, global interference and the activity of superficial layers. Fast optical signals may provide further information on brain processing during higher-order cognitive tasks such as rapid categorization of objects.

A new approach to trace the dynamic patterns of task-based functional connectivity, by combining signal segmentation, dynamic time warping (DTW), and Quality Threshold (QT) clustering techniques, is presented. Electroencephalography (EEG) signals of 5 healthy subjects were recorded as they performed an auditory oddball and a visual modified oddball tasks. To capture the dynamic patterns of functional connectivity during the execution of each task, EEG signals are segmented into durations that correspond to the temporal windows of previously well-studied event-related potentials (ERPs). For each temporal window, DTW is employed to measure the functional similarities among channels. Unlike commonly used temporal similarity measures, such as cross correlation, DTW compares time series by taking into consideration that their alignment properties may vary in time. QT clustering analysis is then used to automatically identify the functionally connected regions in each temporal window. For each task, the proposed approach was able to establish a unique sequence of dynamic pattern (observed in all 5 subjects) for brain functional connectivity.

The mustached bat, Pteronotus parnellii, uses complex communication sounds ("calls") for social interactions. We recorded both event-related local field potentials (LFPs) and single/few-unit (SU) spike activity from the same electrode in the posterior region of the primary auditory cortex (AIp) during presentation of simple syllabic calls to awake bats. Temporal properties of the LFPs, which reflect activity within local neuronal clusters, and spike discharges from SUs were studied at 138 recording sites in six bats using seven variants each of 14 simple syllables presented at intensity levels of 40-90 dB SPL. There was no clear spatial selectivity to different call types within the AIp area. Rather, as shown previously, single units responded to multiple call types with similar values of the peak response rate in the peri-stimulus time histogram (PSTH). The LFPs and SUs, however, showed a rich temporal structure that was unique for each call type. Multidimensional scaling (MDS) of the averaged waveforms of call-evoked LFPs and PSTHs revealed that calls were better segregated in the two-dimensional space based on the LFP compared with the PSTH data. A representation within the "LFP-space" revealed that one of the dimensions correlated with the predominant and fundamental frequency of a call. The other dimension showed a high correlation with "harmonic complexity" ("fine" spectral structure of a call). We suggest that the temporal pattern of LFP and spiking activity reflects call-specific dynamics at any locus within the AIp area. This dynamic contributes to a distributed (population-based) representation of calls. Alternatively stated, the fundamental frequency and harmonic structure of calls, and not the recording location within the AIp, determines the temporal structure of the call-evoked LFP.

A role for astroglia in epileptogenesis has been hypothesised but is not established. Low doses of fluorocitrate specifically and reversibly disrupt astroglial metabolism by blocking aconitase, an enzyme integral to the tricarboxylic acid cycle. We used cerebral cortex injections of fluorocitrate, at a dose that we demonstrated to inhibit astroglial metabolism selectively, to determine whether astroglial disturbances lead to seizures. Rats were halothane-anesthetized, and 0.8 nmol of sodium fluorocitrate was injected into the cerebral cortex. Extradural electroencephalogram (EEG) electrodes were implanted, after which the anesthesia was ceased and the animals were observed. In all experiments, 14 of 15 fluorocitrate-treated animals exhibited epileptiform EEG discharges, with some animals exhibiting convulsive seizures. Discharges commenced as early as 30 min postfluorocitrate injection. Intraperitoneal octanol, but not halothane by inhalation, given to test the possible participation of gap junctions in EEG discharge generation, blocked or delayed the occurrence of discharges after fluorocitrate. These results indicate that focal cerebrocortical astroglial dysfunction leads to focal epileptiform discharges and sometimes to convulsive seizures and that the process possibly depends on effects mediated by gap junctions.

Near-infrared spectroscopy (NIRS) is a novel technology for low-cost noninvasive brain imaging suitable for use in virtually all subject and patient populations. Numerous studies of brain functional connectivity using fMRI, and recently NIRS, suggest new tools for the assessment of cognitive functions during task performance and the resting state (RS). We analyzed functional connectivity and its possible hemispheric asymmetry measuring coherence of optical signals at low frequencies (0.01-0.1 Hz) in the prefrontal cortex in 13 right-handed (RH) and 2 left-handed (LH) healthy subjects at rest (4-8 min) using a continuous-wave NIRS instrument CW5 (TechEn, Milford, MA). Two optical probes were placed bilaterally over the inferior frontal gyrus (IFG) and the middle frontal gyrus (MFG) using anatomical landmarks of the 10-20 system. As a result, 28 optical channels (14 for each hemisphere) were recorded for changes in oxygenated (HbO) and de-oxygenated (HbR) hemoglobin. Global physiological signals (respiratory and cardiac) were removed using Principal and Independent Component Analyses. Inter-channel coherences for HbO and HbR signals were calculated using Morlet wavelets along with correlation coefficients. Connectivity matrices showed specific patterns of connectivity which was higher within each anatomical region (IFG and MFG) and between hemispheres (e.g., left IFG <-> right IFG) than between IFG and MFG in the same hemisphere. Laterality indexes were calculated as t-values for the ‘left > right’ comparisons of intrinsic connectivity within each regional group of channels in each subject. Regardless of handedness, the group average laterality indexes were negative thus revealing significantly higher connectivity in the right hemisphere in the majority of RH subjects and in both LH subjects. The analysis of Granger Causality between hemispheres has also shown a greater flow of information from the right to the left hemisphere which may point to an important role of the right hemisphere in the resting state. These data encourage further exploration of the NIRS connectivity and its application for the analysis of hemispheric relationships within the functional architecture of the brain.