Cerebral vasomotion: a 0.1-Hz oscillation in reflected light imaging of neural activity

Cerebral artery-vein separation using 0.1-Hz oscillation in dual-wavelength optical imaging

We present a novel artery-vein separation method using 0.1-Hz oscillation at two wavelengths with optical imaging of intrinsic signals (OIS). The 0.1-Hz oscillation at a green light wavelength of 546 nm exhibits greater amplitude in arteries than in veins and is primarily caused by vasomotion, whereas the 0.1-Hz oscillation at a red light wavelength of 630 nm exhibits greater amplitude in veins than in arteries and is primarily caused by changes of deoxyhemoglobin concentration. This spectral feature enables cortical arteries and veins to be segmented independently. The arteries can be segmented on the 0.1-Hz amplitude image at 546 nm using matched filters of a modified dual Gaussian model combining with a single Gaussian model. The veins are a combination of vessels segmented on both amplitude images at the two wavelengths using multiscale matched filters of single Gaussian model. Our method can separate most of the thin arteries and veins from each other, especially the thin arteries with low contrast in raw gray images. In vivo OIS experiments demonstrate the separation ability of the 0.1-Hz based segmentation method in cerebral cortex of eight rats. Two validation studies were undertaken to evaluate the performance of the method by quantifying the arterial and venous length based on a reference standard. The results indicate that our 0.1-Hz method is very effective in separating both large and thin arteries and veins regardless of vessel crossover or overlapping to great extent in comparison with previous methods.

Measurements and modeling of transient blood flow perturbations induced by brief somatosensory stimulation

Proper interpretation of BOLD fMRI and other common functional imaging methods requires an understanding of neurovascular coupling. We used laser speckle-contrast optical imaging to measure blood-flow responses in rat somatosensory cortex elicited by brief (2 s) forepaw stimulation. Results show a large increase in local blood flow speed followed by an undershoot and possible late-time oscillations. The blood flow measurements were modeled using the impulse response of a simple linear network, a four-element windkessel. This model yielded excellent fits to the detailed time courses of activated regions. The four-element windkessel model thus provides a simple explanation and interpretation of the transient blood-flow response, both its initial peak and its late-time behavior.

Spatial homogeneity and task-synchrony of the trial-related hemodynamic signal

There is growing evidence that functional brain images in alert task-engaged subjects contain task-related but stimulus-independent signals in addition to stimulus-evoked responses. It is important to separate these different components when analyzing the neuroimaging signal. Using intrinsic-signal optical imaging combined with electrophysiology we had earlier reported a particular 'trial-related signal' in the primary visual cortex (V1) of alert monkeys performing periodic fixation tasks. This signal periodically modulated V1 tissue blood volume, in time with anticipated trial onsets. Unlike visually evoked blood volume changes, however, this signal was present even in total darkness. Further, it could not be predicted by concurrently recorded spiking or local field potentials. Here we use our earlier recording techniques to analyze the spatial distribution of this trial-related signal over our imaged area (10mm square, subdivided into a 16×16 grid, i.e. at 625 μm resolution). We show that the signal is spatially coherent and essentially homogeneous over the imaged region and fails to be predicted by concurrent electrode recordings even at the resolution of a single grid square at the electrode tip. As a corollary we show that the signal is critically linked to the animals' engagement in a task. Not only does the trial-related signal entrain accurately and precisely to any task timing at which the animal was willing to perform; the signal also loses the entrained trial-locked pattern dramatically, within a single trial, when the animal stops performing correctly. Thus the signal is very unlikely to be an ongoing task-independent vascular oscillation. These findings will help categorize the likely distinct varieties of non-stimulus-related signals evoked during behavioral tasks, and lead to a further understanding of the elements comprising the net neuroimaging response.

Orientation selective or not? - Measuring significance of tuning to a circular parameter

Orientation and direction tuning are among the most studied features of the visual system and are routinely measured during experiments to estimate the quality of neuronal responses. However, standard approaches to report orientation selectivity are only narrowly quantitative and strongly depend on the signal quality, while the more sophisticated ones are computationally exhaustive, making them difficult to use during ongoing experiments. We propose a fast and efficient method for reporting the reliability of coding applicable to any circular parameter. Similar to standard deviation in the linear statistics, reproducibility measures trial-to-trial variability of a circular response parameter. Reproducibility is a normalized measure easily transformed to p-values, which provide explicit information about significance of the estimated orientation preference. The proposed approach is applicable to a wide range of signal types. Here, we discuss examples from optical imaging and electrophysiological recordings, and provide a more thorough examination based on tuning curves modeled in silico.

The NIRS Analysis Package: noise reduction and statistical inference

Near infrared spectroscopy (NIRS) is a non-invasive optical imaging technique that can be used to measure cortical hemodynamic responses to specific stimuli or tasks. While analyses of NIRS data are normally adapted from established fMRI techniques, there are nevertheless substantial differences between the two modalities. Here, we investigate the impact of NIRS-specific noise; e.g., systemic (physiological), motion-related artifacts, and serial autocorrelations, upon the validity of statistical inference within the framework of the general linear model. We present a comprehensive framework for noise reduction and statistical inference, which is custom-tailored to the noise characteristics of NIRS. These methods have been implemented in a public domain Matlab toolbox, the NIRS Analysis Package (NAP). Finally, we validate NAP using both simulated and actual data, showing marked improvement in the detection power and reliability of NIRS.

Degeneration of cortical function in the Royal College of Surgeons rat

The purpose of the current study was to determine the progress of cortical functional degeneration in the Royal College of Surgeons (RCS) rat. Cortical responses were measured with optical imaging of intrinsic signals using gratings of various spatial frequencies. Subsequently, electrophysiological recordings were also taken across cortical layers in response to a pulse of broad-spectrum light. We found significant degeneration in the cortical processing of visual information as early as 4 weeks of age. These results show that degeneration in the cortical response of the RCS rat starts before development has been properly completed.

Dynamic linear model analysis of optical imaging data acquired from the human neocortex

The amount of light absorbed and scattered by neocortical tissue is altered by neuronal activity. Imaging of intrinsic optical signals (ImIOS), a technique for mapping these activity-evoked optical changes with an imaging detector, has the potential to be useful for both clinical and experimental investigations of the human neocortex. However, its usefulness for human studies is currently limited because intraoperatively acquired ImIOS data is noisy. To improve the reliability and usefulness of ImIOS for human studies, it is desirable to find appropriate methods for the removal of noise artifacts and its statistical analysis. Here we develop a Bayesian, dynamic linear modeling approach that appears to address these problems. A dynamic linear model (DLM) was constructed that included cyclic components to model the heartbeat and respiration artifacts, and a local linear component to model the activity-evoked response. The robustness of the model was tested on a set of ImIOS data acquired from the exposed cortices of six human subjects illuminated with either 535nm or 660nm light. The DLM adequately reduced noise artifacts in these data while reliably preserving their activity-evoked optical responses. To demonstrate how these methods might be used for intraoperative neurosurgical mapping, optical data acquired from a single human subject during direct electrical stimulation of the cortex were quantitatively analyzed. This example showed that the DLM can be used to provide quantitative information about human ImIOS data that is not available through qualitative analysis alone.

Enhanced functional brain imaging by using adaptive filtering and a depth compensation algorithm in diffuse optical tomography

Reflectance diffuse optical tomography (rDOT) of brain function is limited by its high sensitivity to the superficial tissues (i.e., the scalp and skull) and by its severe decrease in measurement sensitivity with increased depth. Significant interference in rDOT results from spontaneous fluctuations that are embedded in both the superficial tissues and brain, such as arterial pulsation and vasomotion. In this study, first we investigate coherence and phase shift of the spontaneous fluctuations in the resting state, within the superficial tissues and at various depths of the brain, respectively. We demonstrate that the spontaneous fluctuations originating from arterial pulsations ( ∼ 1 Hz) are spatially global and temporally coherent, while the fluctuations originating from vasomotion ( ∼ 0.1 Hz) tend to have less coherence with increased depth. Second, adaptive cancellation of spontaneous fluctuations with a frequency-specific strategy is utilized and validated in both resting and activation (evoked by a finger-tapping task) states. Third, improved depth localization of motor activation in reconstructed rDOT images is achieved by combining adaptive cancellation with a depth compensation algorithm that we recently reported.

Fluctuating and sensory-induced vasodynamics in rodent cortex extend arteriole capacity

Neural activity in the brain is followed by localized changes in blood flow and volume. We address the relative change in volume for arteriole vs. venous blood within primary vibrissa cortex of awake, head-fixed mice. Two-photon laser-scanning microscopy was used to measure spontaneous and sensory evoked changes in flow and volume at the level of single vessels. We find that arterioles exhibit slow (<1 Hz) spontaneous increases in their diameter, as well as pronounced dilation in response to both punctate and prolonged stimulation of the contralateral vibrissae. In contrast, venules dilate only in response to prolonged stimulation. We conclude that stimulation that occurs on the time scale of natural stimuli leads to a net increase in the reservoir of arteriole blood. Thus, a "bagpipe" model that highlights arteriole dilation should augment the current "balloon" model of venous distension in the interpretation of fMRI images.

Spontaneous low-frequency oscillations in cerebral vessels: applications in carotid artery disease and ischemic stroke

The etiology behind and physiological significance of spontaneous oscillations in the low-frequency spectrum in both systemic and cerebral vessels remain unknown. Experimental studies have proposed that spontaneous oscillations in cerebral blood flow reflect impaired cerebral autoregulation (CA). Analysis of CA by measurement of spontaneous oscillations in the low-frequency spectrum in cerebral vessels might be a useful tool for assessing risk and investigating different treatment strategies in carotid artery disease (CAD) and stroke. We reviewed studies exploring spontaneous oscillations in the low-frequency spectrum in patients with CAD and ischemic stroke, conditions known to involve impaired CA. Several studies have reported changes in oscillations after CAD and stroke after surgery and over time compared with healthy controls. Phase shift in the frequency domain and correlation coefficients in the time domain are the most frequently used parameters for analyzing spontaneous oscillations in systemic and cerebral vessels. At present, there is no gold standard for analyzing spontaneous oscillations in the low-frequency spectrum, and simplistic models of CA have failed to predict or explain the spontaneous oscillation changes found in CAD and stroke studies. Near-infrared spectroscopy is suggested as a future complementary tool for assessing changes affecting the cortical arterial system.

High-speed vascular dynamics of the hemodynamic response

While a range of cellular mechanisms have been proposed to underlie control of neurovascular coupling, a comprehensive, reconciliatory model has yet to be determined. To fit with such a model, it is essential that candidate mechanisms exhibit reaction times, spatial ranges, and speeds of propagation that are consistent with the vascular manifestations of the 'hemodynamic response'. Understanding these vascular dynamics is therefore a critical step towards developing a robust model of neurovascular coupling. In this study, we utilize high-speed optical imaging of exposed rodent somatosensory cortex to explore and characterize the spatiotemporal dynamics of surface vessels during functional hyperemia. Our high-speed, high-resolution optical imaging approach allows us to study the hemodynamic response independently in individual vessels, and in discrete regions of the parenchyma with enough resolution to precisely characterize subtle spatial and temporal features of the response. Specifically, we explore when and where the first hemodynamic changes occur in response to stimuli, the direction and speed at which these changes propagate in arterioles and regions of the parenchyma, and the relative timing at which each of these compartments returns to its original baseline state. From these results, we are able to conclude that the hemodynamic response appears to initiate in the parenchyma and then spreads rapidly to surface arterioles. Following the initial onset we find evidence that the response spreads spatially outwards via the dilation of targeted arterioles. This propagation of vasodilation is independent of the direction of blood flow within each arteriole. We also find evidence of a decay phase that acts with a more uniform spatial dependence, rather than along targeted vessels, causing the periphery of the responding region to return to baseline first. We hypothesize that different underlying cellular mechanisms/signaling pathways are responsible for the response initiation and the response decay. Our results advance the fundamental understanding of the hemodynamic response, as well as our ability to evaluate potential cellular mechanisms for their involvement in neurovascular coupling.

Functional connectivity in blood oxygenation level-dependent and cerebral blood volume-weighted resting state functional magnetic resonance imaging in the rat brain

PURPOSE

To directly compare functional connectivity and spatiotemporal dynamics acquired with blood oxygenation level-dependent (BOLD) and cerebral blood volume (CBV)-weighted functional magnetic resonance imaging (fMRI) in anesthetized rats.

MATERIALS AND METHODS

A series of BOLD images were acquired in 10 rats followed by CBV-weighted images created by injection of ultrasmall iron oxide particles. Functional connectivity, spectral information, and spatiotemporal dynamics were compared for the BOLD and CBV-weighted resting state scans.

RESULTS

BOLD scans exhibited higher cross-correlation values compared to CBV-weighted scans, but the spatial patterns of correlation were similar. The BOLD spectrum contains power evenly distributed throughout the low-frequency range while the CBV power spectrum exhibited a high power peak localized to approximately 0.2 Hz. Both BOLD and CBV resting state scans showed similar propagating waves of activity along the cortex from the SII toward MI; however, these waves were detected more often in BOLD scans than in CBV scans.

CONCLUSION

While the power spectrum of the CBV signal is different from that of the BOLD signal, both connectivity maps and spatiotemporal dynamics are similar for the two modalities. Further experiments should address the relationship between spontaneous neural activity, local changes in metabolism, and hemodynamic fluctuations to elucidate the origins of the BOLD and CBV signals.

A dynamic model of neurovascular coupling: implications for blood vessel dilation and constriction

Neurovascular coupling in response to stimulation of the rat barrel cortex was investigated using concurrent multichannel electrophysiology and laser Doppler flowmetry. The data were used to build a linear dynamic model relating neural activity to blood flow. Local field potential time series were subject to current source density analysis, and the time series of a layer IV sink of the barrel cortex was used as the input to the model. The model output was the time series of the changes in regional cerebral blood flow (CBF). We show that this model can provide excellent fit of the CBF responses for stimulus durations of up to 16 s. The structure of the model consisted of two coupled components representing vascular dilation and constriction. The complex temporal characteristics of the CBF time series were reproduced by the relatively simple balance of these two components. We show that the impulse response obtained under the 16-s duration stimulation condition generalised to provide a good prediction to the data from the shorter duration stimulation conditions. Furthermore, by optimising three out of the total of nine model parameters, the variability in the data can be well accounted for over a wide range of stimulus conditions. By establishing linearity, classic system analysis methods can be used to generate and explore a range of equivalent model structures (e.g., feed-forward or feedback) to guide the experimental investigation of the control of vascular dilation and constriction following stimulation.

Linear superposition of sensory-evoked and ongoing cortical hemodynamics

Modern non-invasive brain imaging techniques utilize changes in cerebral blood flow, volume and oxygenation that accompany brain activation. However, stimulus-evoked hemodynamic responses display considerable inter-trial variability even when identical stimuli are presented and the sources of this variability are poorly understood. One of the sources of this response variation could be ongoing spontaneous hemodynamic fluctuations. To investigate this issue, 2-dimensional optical imaging spectroscopy was used to measure cortical hemodynamics in response to sensory stimuli in anesthetized rodents. Pre-stimulus cortical hemodynamics displayed spontaneous periodic fluctuations and as such, data from individual stimulus presentation trials were assigned to one of four groups depending on the phase angle of pre-stimulus hemodynamic fluctuations and averaged. This analysis revealed that sensory evoked cortical hemodynamics displayed distinctive response characteristics and magnitudes depending on the phase angle of ongoing fluctuations at stimulus onset. To investigate the origin of this phenomenon, "null-trials" were collected without stimulus presentation. Subtraction of phase averaged "null trials" from their phase averaged stimulus-evoked counterparts resulted in four similar time series that resembled the mean stimulus-evoked response. These analyses suggest that linear superposition of evoked and ongoing cortical hemodynamic changes may be a property of the structure of inter-trial variability.

Time lag dependent multimodal processing of concurrent fMRI and near-infrared spectroscopy (NIRS) data suggests a global circulatory origin for low-frequency oscillation signals in human brain

Low frequency oscillations (LFOs), characterized by frequencies in the range 0.01-0.1 Hz are commonly observed in blood-related brain functional measurements such as near-infrared spectroscopy (NIRS) and functional magnetic resonance imaging (fMRI). While their physiological origin and implications are not fully understood, these signals are believed to reflect some types of neuronal signaling, systemic hemodynamics, and/or cerebral vascular auto-regulation processes. Here, we examine a new method of integrated processing of concurrent NIRS and fMRI data collected on six human subjects during a whole brain resting state acquisition. The method combines the high spatial resolution offered by fMRI (approximately 3mm) and the high temporal resolution offered by NIRS (approximately 80 ms) to allow for the quantitative assessment of temporal relationships between the LFOs observed at different spatial locations in fMRI data. This temporal relationship allowed us to infer that the origin of a large proportion of the LFOs is independent of the baseline neural activity. The spatio-temporal pattern of LFOs detected by NIRS and fMRI evolves temporally through the brain in a way that resembles cerebral blood flow dynamics. Our results suggest that a major component of the LFOs arise from fluctuations in the blood flow and hemoglobin oxygenation at a global circulatory system level.

Processing of functional maps of the cat visual cortex obtained using intrinsic optical signals

Functional structures of the primary visual cortex, particularly clearly apparent structures such as orientation columns, are studied by recording the brain's intrinsic optical signals. These reflect changes in local neuron metabolism and cerebral blood flow induced by functional loading. Despite the advantages of this method, mapping of neurons with weak signals can be hindered by noise generated by the global and local components of optical signals associated with physiological processes occurring in the body as well as equipment factors. This generates the need to correct functional optical maps to eliminate noise effects. The present report describes a new method of processing functional maps using approximations to identify and remove the global components of the optical signal and other interference from maps. The results are compared with data obtained by traditional map processing methods.

Separation of arteries and veins in the cerebral cortex using physiological oscillations by optical imaging of intrinsic signal

An automated method is presented for artery-vein separation in cerebral cortical images recorded with optical imaging of the intrinsic signal. The vessel-type separation method is based on the fact that the spectral distribution of intrinsic physiological oscillations varies from arterial regions to venous regions. In arterial regions, the spectral power is higher in the heartbeat frequency (HF), whereas in venous regions, the spectral power is higher in the respiration frequency (RF). The separation method was begun by extracting the vascular network and its centerline. Then the spectra of the optical intrinsic signals were estimated by the multitaper method. A standard F-test was performed on each discrete frequency point to test the statistical significance at the given level. Four periodic physiological oscillations were examined: HF, RF, and two other eigenfrequencies termed F1 and F2. The separation of arteries and veins was implemented with the fuzzy c-means clustering method and the region-growing approach by utilizing the spectral amplitudes and power-ratio values of the four eigenfrequencies on the vasculature. Subsequently, independent spectral distributions in the arteries, veins, and capillary bed were estimated for comparison, which showed that the spectral distributions of the intrinsic signals were very distinct between the arterial and venous regions.

Comparison of alpha-chloralose, medetomidine and isoflurane anesthesia for functional connectivity mapping in the rat

Functional connectivity measures based upon low-frequency blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) signal fluctuations have become a widely used tool for investigating spontaneous brain activity in humans. Still unknown, however, is the precise relationship between neural activity, the hemodynamic response and fluctuations in the MRI signal. Recent work from several groups had shown that correlated low-frequency fluctuations in the BOLD signal can be detected in the anesthetized rat - a first step toward elucidating this relationship. Building on this preliminary work, through this study, we demonstrate that functional connectivity observed in the rat depends strongly on the type of anesthesia used. Power spectra of spontaneous fluctuations and the cross-correlation-based connectivity maps from rats anesthetized with alpha-chloralose, medetomidine or isoflurane are presented using a high-temporal-resolution imaging sequence that ensures minimal contamination from physiological noise. The results show less localized correlation in rats anesthetized with isoflurane as compared with rats anesthetized with alpha-chloralose or medetomidine. These experiments highlight the utility of using different types of anesthesia to explore the fundamental physiological relationships of the BOLD signal and suggest that the mechanisms contributing to functional connectivity involve a complicated relationship between changes in neural activity, neurovascular coupling and vascular reactivity.

Aberrant temporal and spatial brain activity during rest in patients with chronic pain

In the absence of external stimuli, human hemodynamic brain activity displays slow intrinsic variations. To find out whether such fluctuations would be altered by persistent pain, we asked 10 patients with unrelenting chronic pain of different etiologies and 10 sex- and age-matched control subjects to rest with eyes open during 3-T functional MRI. Independent component analysis was used to identify functionally coupled brain networks. Time courses of an independent component comprising the insular cortices of both hemispheres showed stronger spectral power at 0.12 to 0.25 Hz in patients than in control subjects, with the largest difference at 0.16 Hz. A similar but weaker effect was seen in the anterior cingulate cortex, whereas activity of the precuneus and early visual cortex, used as a control site, did not differ between the groups. In the patient group, seed point-based correlation analysis revealed altered spatial connectivity between insulae and anterior cingulate cortex. The results imply both temporally and spatially aberrant activity of the affective pain-processing areas in patients suffering from chronic pain. The accentuated 0.12- to 0.25-Hz fluctuations in the patient group might be related to altered activity of the autonomic nervous system.

Respiratory and Mayer wave-related discharge patterns of raphé and pontine neurons change with vagotomy

Previous models have attributed changes in respiratory modulation of pontine neurons after vagotomy to a loss of pulmonary stretch receptor "gating" of an efference copy of inspiratory drive. Recently, our group confirmed that pontine neurons change firing patterns and become more respiratory modulated after vagotomy, although average peak and mean firing rates of the sample did not increase (Dick et al., J Physiol 586: 4265-4282, 2008). Because raphé neurons are also elements of the brain stem respiratory network, we tested the hypotheses that after vagotomy raphé neurons have increased respiratory modulation and that alterations in their firing patterns are similar to those seen for pontine neurons during withheld lung inflation. Raphé and pontine neurons were recorded simultaneously before and after vagotomy in decerebrated cats. Before vagotomy, 14% of 95 raphé neurons had increased activity during single respiratory cycles prolonged by withholding lung inflation; 13% exhibited decreased activity. After vagotomy, the average index of respiratory modulation (eta(2)) increased (0.05 +/- 0.10 to 0.12 +/- 0.18 SD; Student's paired t-test, P < 0.01). Time series and frequency domain analyses identified pontine and raphé neuron firing rate modulations with a 0.1-Hz rhythm coherent with blood pressure Mayer waves. These "Mayer wave-related oscillations" (MWROs) were coupled with central respiratory drive and became synchronized with the central respiratory rhythm after vagotomy (7 of 10 animals). Cross-correlation analysis identified functional connectivity in 52 of 360 pairs of neurons with MWROs. Collectively, the results suggest that a distributed network participates in the generation of MWROs and in the coordination of respiratory and vasomotor rhythms.

Evaluation of receptive field size from higher harmonics in visuotopic mapping using continuous stimulation optical imaging

The extraction and detection of specific responses from a large amount of background noise has been the subject of a considerable body of research in brain functional imaging, and more specifically in optical intrinsic signal imaging. Recent work by Kalatsky and Stryker (2003) showed that by combining different conditions and using periodic stimuli, recording times can be reduced. Spectral decomposition is then used to provide amplitude and phase information locked to the stimulus. A drawback of the above method is that by focusing only on a single harmonic, response information is limited. The shape of the hemodynamic response function (HRF) and the temporal variations in the neural responses cannot be assessed. In this work it is argued that additional information about neural responses can be gathered by using higher harmonics. Moving bars were used to generate visuotopic maps on large portions of the cat visual cortex. Up to four simultaneously bars moving repetitively across the visual field at different frequencies were used to sample the HRF in the Fourier domain. The HRF profile obtained with continuous stimulation was spatially homogeneous throughout the cortex and similar to the HRF profile obtained using episodic stimulation. Furthermore, by modeling the optical response as a convolution between HRF and neuronal responses, the ratio of the second harmonic to the first provided an estimation of the receptive field size. This was further validated by measuring spatial frequency selectivity. Therefore, the use of higher harmonics opens new avenues to estimate receptive field size from temporal signals.

Temporal dynamics of spontaneous MEG activity in brain networks

Functional MRI (fMRI) studies have shown that low-frequency (<0.1 Hz) spontaneous fluctuations of the blood oxygenation level dependent (BOLD) signal during restful wakefulness are coherent within distributed large-scale cortical and subcortical networks (resting state networks, RSNs). The neuronal mechanisms underlying RSNs remain poorly understood. Here, we describe magnetoencephalographic correspondents of two well-characterized RSNs: the dorsal attention and the default mode networks. Seed-based correlation mapping was performed using time-dependent MEG power reconstructed at each voxel within the brain. The topography of RSNs computed on the basis of extended (5 min) epochs was similar to that observed with fMRI but confined to the same hemisphere as the seed region. Analyses taking into account the nonstationarity of MEG activity showed transient formation of more complete RSNs, including nodes in the contralateral hemisphere. Spectral analysis indicated that RSNs manifest in MEG as synchronous modulation of band-limited power primarily within the theta, alpha, and beta bands-that is, in frequencies slower than those associated with the local electrophysiological correlates of event-related BOLD responses.

Astrocytic endfoot Ca2+ and BK channels determine both arteriolar dilation and constriction

Neuronal activity is thought to communicate to arterioles in the brain through astrocytic calcium (Ca(2+)) signaling to cause local vasodilation. Paradoxically, this communication may cause vasoconstriction in some cases. Here, we show that, regardless of the mechanism by which astrocytic endfoot Ca(2+) was elevated, modest increases in Ca(2+) induced dilation, whereas larger increases switched dilation to constriction. Large-conductance, Ca(2+)-sensitive potassium channels in astrocytic endfeet mediated a majority of the dilation and the entire vasoconstriction, implicating local extracellular K(+) as a vasoactive signal for both dilation and constriction. These results provide evidence for a unifying mechanism that explains the nature and apparent duality of the vascular response, showing that the degree and polarity of neurovascular coupling depends on astrocytic endfoot Ca(2+) and perivascular K(+).

Intrinsic signal optical imaging of brain function using short stimulus delivery intervals

Intrinsic signal optical imaging (ISOI) can be used to map cortical function and organization. Because its detected signal lasts 10+s consisting of three phases, trials are typically collected using a long (tens of seconds) stimulus delivery interval (SDI) at the expense of efficiency, even when interested in mapping only the first signal phase (e.g., ISOI initial dip). It is unclear how the activity profile can change when stimuli are delivered at shorter intervals, and whether a short SDI can be implemented to improve efficiency. The goals of the present study are twofold: characterize the ISOI activity profile when multiple stimuli are delivered at 4s intervals, and determine whether successful mapping can be attained from trials collected using an SDI of 4s (offering >10x increase in efficiency). Our results indicate that four stimuli delivered 4s apart evoke an activity profile different from the triphasic signal, consisting of signal dips in a series at the same frequency as the stimuli despite a strong rise in signal prior to the 2nd to 4th stimuli. Visualization of such signal dips is dependent on using a baseline immediately prior to every stimulus. Use of the 4-s SDI is confirmed to successfully map activity with a similar location in peak activity and increased areal extent and peak magnitude compared to using a long SDI. Additional experiments were performed to begin addressing issues such as SDI temporal jittering, response magnitude as a function of SDI duration, and application for successful mapping of cortical function topography.

A map of periodicity orthogonal to frequency representation in the cat auditory cortex

Harmonic sounds, such as voiced speech sounds and many animal communication signals, are characterized by a pitch related to the periodicity of their envelopes. While frequency information is extracted by mechanical filtering of the cochlea, periodicity information is analyzed by temporal filter mechanisms in the brainstem. In the mammalian auditory midbrain envelope periodicity is represented in maps orthogonal to the representation of sound frequency. However, how periodicity is represented across the cortical surface of primary auditory cortex (AI) remains controversial. Using optical recording of intrinsic signals, we here demonstrate that a periodicity map exists in primary AI of the cat. While pure tone stimulation confirmed the well-known frequency gradient along the rostro-caudal axis of AI, stimulation with harmonic sounds revealed segregated bands of activation, indicating spatially localized preferences to specific periodicities along a dorso-ventral axis, nearly orthogonal to the tonotopic gradient. Analysis of the response locations revealed an average gradient of - 100 degrees +/- 10 degrees for the periodotopic, and -12 degrees +/- 18 degrees for the tonotopic map resulting in a mean angle difference of 88 degrees . The gradients were 0.65 +/- 0.08 mm/octave for periodotopy and 1.07 +/- 0.16 mm/octave for tonotopy indicating that more cortical territory is devoted to the representation of an octave along the tonotopic than along the periodotopic gradient. Our results suggest that the fundamental importance of pitch, as evident in human perception, is also reflected in the layout of cortical maps and that the orthogonal spatial organization of frequency and periodicity might be a more general cortical organization principle.

Interaction between nitric oxide synthase inhibitor induced oscillations and the activation flow coupling response

The role of nitric oxide (NO) in the activation-flow coupling (AFC) response to periodic electrical forepaw stimulation was investigated using signal averaged laser Doppler (LD) flowmetry. LD measures of calculated cerebral blood flow (CBF) were obtained both prior and after intra-peritoneal administration of the non-selective nitric oxide synthase (NOS) inhibitor, N(G)-nitro-L-arginine (L-NNA) (40 mg/kg). Characteristic baseline low frequency vasomotion oscillations (0.17 Hz) were observed after L-NNA administration. These LD(CBF) oscillations were synchronous within but not between hemispheres. L-NNA reduced the magnitude of the AFC response (p<0.05) for longer stimuli (1 min) with longer inter-stimulus intervals (2 min). In contrast, the magnitude of the AFC response for short duration stimuli (4 s) with short inter-stimulus intervals (20 s) was augmented (p<0.05) after L-NNA. An interaction occurred between L-NNA induced vasomotion oscillations and the AFC response with the greatest increase occurring at the stimulus harmonic closest to the oscillatory frequency. Nitric oxide may therefore modulate the effects of other vasodilators involved in vasomotion oscillations and the AFC response.

Single-trial classification of NIRS signals during emotional induction tasks: towards a corporeal machine interface

Background

Corporeal machine interfaces (CMIs) are one of a few available options for restoring communication and environmental control to those with severe motor impairments. Cognitive processes detectable solely with functional imaging technologies such as near-infrared spectroscopy (NIRS) can potentially provide interfaces requiring less user training than conventional electroencephalography-based CMIs. We hypothesized that visually-cued emotional induction tasks can elicit forehead hemodynamic activity that can be harnessed for a CMI.

Methods

Data were collected from ten able-bodied participants as they performed trials of positively and negatively-emotional induction tasks. A genetic algorithm was employed to select the optimal signal features, classifier, task valence (positive or negative emotional value of the stimulus), recording site, and signal analysis interval length for each participant. We compared the performance of Linear Discriminant Analysis and Support Vector Machine classifiers. The latency of the NIRS hemodynamic response was estimated as the time required for classification accuracy to stabilize.

Results

Baseline and activation sequences were classified offline with accuracies upwards of 75.0%. Feature selection identified common time-domain discriminatory features across participants. Classification performance varied with the length of the input signal, and optimal signal length was found to be feature-dependent. Statistically significant increases in classification accuracy from baseline rates were observed as early as 2.5 s from initial stimulus presentation.

Conclusion

NIRS signals during affective states were shown to be distinguishable from baseline states with classification accuracies significantly above chance levels. Further research with NIRS for corporeal machine interfaces is warranted.

Bimodal modulation and continuous stimulation in optical imaging to map direction selectivity

In the visual system, neurons with similar functional properties such as orientation and direction selectivity are clustered together to form modules. Optical imaging recordings in combination with episodic paradigms have been previously used to estimate direction selectivity, a fundamental property of visual neurons. The major drawback of the episodic approach is that the extraction of the signal from various forms of physiological noise is difficult, leading to a poor estimation of direction. Recent work, based on periodic stimulation and Fourier decomposition improved the extraction of periodic stimulus responses from noise and thus, reduced the recording time considerably. Given the success of this new paradigm in mapping orientation, the present study evaluated its reliability to measure direction selectivity in the visual cortex of anesthetized cats. Here, a model that exploits the harmonics of the Fourier decomposition is proposed where the first harmonic is related to direction responses, and the second to orientation. As expected, the first harmonic was absent when a static stimulus was presented. Contrarily, the first harmonic was present when moving stimuli were presented and the amplitude was greater with random dots kinematograms than with drifting gratings. The phase of the first harmonic showed a good agreement with direction preference measured by episodic paradigm. The ratio of the first/the second harmonic amplitude, related to a direction index, was weaker in fracture. It was also weaker in areas of the ventral pathway (areas 17 and 21a) where direction selectivity is known to be reduced. These results indicate that a periodic paradigm can be easily used to measure specific parameters in optical signals, particularly in situations when short acquisition periods are needed.

Setting the frame: the human brain activates a basic low-frequency network for language processing

Low-frequency fluctuations (LFFs) are a major source of variation in fMRI data. This has been established in numerous experiments-particularly in the resting state. Here we investigate LFFs in a task-dependent setting. We hypothesized that LFFs may contain information about cognitive networks that are specific to the overall task domain without being time locked to stimulus onsets. We analyzed data of 6 fMRI experiments, 4 of which belonged to the language domain. After regressing out specifics of the experimental design and low-pass filtering (<0.1 Hz), we found that the 4 language experiments produced a correlational pattern that was not present in the 2 nonlanguage studies. Specifically, a region in the posterior part of the left superior temporal sulcus/gyrus was consistently correlated with both the left Brodmann's area 44 and the left frontal operculum in all 4 language studies, whereas this correlation was not found in the 2 other experiments. This finding indicates the existence of a basic network that acts as a general framework for language processing. In contrast to networks obtained by a conventional conjunction analysis of activation maps, this network is independent of experimental specifics such as stimulus onsets and exists in the low-frequency range.

Investigation of the prefrontal cortex in response to duration-variable anagram tasks using functional near-infrared spectroscopy

We hypothesize that nonlinearity between short-term anagram tasks and corresponding hemodynamic responses can be observed by functional near-infrared spectroscopy (fNIRS) in the prefrontal cortex (PFC). The PFC of six human subjects in response to anagram tasks is investigated using multichannel fNIRS. Concentration changes of oxyhemoglobin and deoxyhemoglobin in the PFC are measured with variable anagram durations and at two difficulty levels (four- and six-letter anagrams). The durations to perform the selected anagram tasks range from several seconds to more than one minute. The dorsolateral PFC areas exhibit consistent and strong hemodynamic deactivation during and shortly after task execution. The superposition principle of a linear system is employed to investigate nonlinear hemodynamic features among three task duration subgroups: D1 = 2.0 sec, D2 = 4.0 sec, and D3 = 8.0 sec. Such analysis shows clear nonlinearity in hemodynamic responses on the PFC with task durations shorter than 4 sec. Our observation of significant deactivation in early hemodynamic responses in the PFC is consistent with multiple fNIRS studies and several reports given in the field of functional magnetic resonance imaging. A better understanding of nonlinearity in fNIRS signals will have potential for us to investigate brain adaptation and to extrapolate neuronal activities from hemodynamic signals.

A model for transient oxygen delivery in cerebral cortex

Popular hemodynamic brain imaging methods, such as blood oxygen-level dependent functional magnetic resonance imaging (BOLD fMRI), would benefit from a detailed understanding of the mechanisms by which oxygen is delivered to the cortex in response to brief periods of neural activity. Tissue oxygen responses in visual cortex following brief visual stimulation exhibit rich dynamics, including an early decrease in oxygen concentration, a subsequent large increase in concentration, and substantial late-time oscillations (“ringing”). We introduce a model that explains the full time-course of these observations made by Thompson et al. (2003). The model treats oxygen transport with a set of differential equations that include a combination of flow and diffusion in a three-compartment (intravascular, extravascular, and intracellular) system. Blood flow in this system is modeled using the impulse response of a lumped linear system that includes an inertive element; this provides a simple biophysical mechanism for the ringing. The model system is solved numerically to produce excellent fits to measurements of tissue oxygen. The results give insight into the dynamics of cerebral oxygen transfer, and can serve as the starting point to understand BOLD fMRI measurements.

Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans

Functional imaging of the human brain is an increasingly important technique for clinical and cognitive neuroscience research, with functional MRI (fMRI) of the blood oxygen level-dependent (BOLD) response and electroencephalography or magnetoencephalography (MEG) recordings of neural oscillations being 2 of the most popular approaches. However, the neural and physiological mechanisms that generate these responses are only partially understood and sources of interparticipant variability in these measures are rarely investigated. Here, we test the hypothesis that the properties of these neuroimaging metrics are related to individual levels of cortical inhibition by combining magnetic resonance spectroscopy to quantify resting GABA concentration in the visual cortex, MEG to measure stimulus-induced visual gamma oscillations and fMRI to measure the BOLD response to a simple visual grating stimulus. Our results demonstrate that across individuals gamma oscillation frequency is positively correlated with resting GABA concentration in visual cortex (R = 0.68; P < 0.02), BOLD magnitude is inversely correlated with resting GABA (R = -0.64; P < 0.05) and that gamma oscillation frequency is strongly inversely correlated with the magnitude of the BOLD response (R = -0.88; P < 0.001). Our results are therefore supportive of recent theories suggesting that these functional neuroimaging metrics are dependent on the excitation/inhibition balance in an individual's cortex and have important implications for the interpretation of functional imaging results, particularly when making between-group comparisons in clinical research.

Anticipatory haemodynamic signals in sensory cortex not predicted by local neuronal activity

Haemodynamic signals underlying functional brain imaging (for example, functional magnetic resonance imaging (fMRI)) are assumed to reflect metabolic demand generated by local neuronal activity, with equal increases in haemodynamic signal implying equal increases in the underlying neuronal activity. Few studies have compared neuronal and haemodynamic signals in alert animals to test for this assumed correspondence. Here we present evidence that brings this assumption into question. Using a dual-wavelength optical imaging technique that independently measures cerebral blood volume and oxygenation, continuously, in alert behaving monkeys, we find two distinct components to the haemodynamic signal in the alert animals' primary visual cortex (V1). One component is reliably predictable from neuronal responses generated by visual input. The other component-of almost comparable strength-is a hitherto unknown signal that entrains to task structure independently of visual input or of standard neural predictors of haemodynamics. This latter component shows predictive timing, with increases of cerebral blood volume in anticipation of trial onsets even in darkness. This trial-locked haemodynamic signal could be due to an accompanying V1 arterial pumping mechanism, closely matched in time, with peaks of arterial dilation entrained to predicted trial onsets. These findings (tested in two animals) challenge the current understanding of the link between brain haemodynamics and local neuronal activity. They also suggest the existence of a novel preparatory mechanism in the brain that brings additional arterial blood to cortex in anticipation of expected tasks.

Low-frequency oscillations in the cerebellar cortex of the tottering mouse

The tottering mouse is an autosomal recessive disorder involving a missense mutation in the gene encoding P/Q-type voltage-gated Ca2+ channels. The tottering mouse has a characteristic phenotype consisting of transient attacks of dystonia triggered by stress, caffeine, or ethanol. The neural events underlying these episodes of dystonia are unknown. Flavoprotein autofluorescence optical imaging revealed transient, low-frequency oscillations in the cerebellar cortex of anesthetized and awake tottering mice but not in wild-type mice. Analysis of the frequencies, spatial extent, and power were used to characterize the oscillations. In anesthetized mice, the dominant frequencies of the oscillations are between 0.039 and 0.078 Hz. The spontaneous oscillations in the tottering mouse organize into high power domains that propagate to neighboring cerebellar cortical regions. In the tottering mouse, the spontaneous firing of 83% (73/88) of cerebellar cortical neurons exhibit oscillations at the same low frequencies. The oscillations are reduced by removing extracellular Ca2+ and blocking L-type Ca2+ channels. The oscillations are likely generated intrinsically in the cerebellar cortex because they are not affected by blocking AMPA receptors or by electrical stimulation of the parallel fiber-Purkinje cell circuit. Furthermore, local application of an L-type Ca2+ agonist in the tottering mouse generates oscillations with similar properties. The beam-like response evoked by parallel fiber stimulation is reduced in the tottering mouse. In the awake tottering mouse, transcranial flavoprotein imaging revealed low-frequency oscillations that are accentuated during caffeine-induced attacks of dystonia. During dystonia, oscillations are also present in the face and hindlimb electromyographic (EMG) activity that become significantly coherent with the oscillations in the cerebellar cortex. These low-frequency oscillations and associated cerebellar cortical dysfunction demonstrate a novel abnormality in the tottering mouse. These oscillations are hypothesized to be involved in the episodic movement disorder in this mouse model of episodic ataxia type 2.

Removal of spatial biological artifacts in functional maps by local similarity minimization

Functional maps obtained by various technologies, including optical imaging techniques, f-MRI, PET, and others, may be contaminated with biological artifacts such as vascular patterns or large patches of parenchyma. These artifacts originate mostly from changes in the microcirculation that result from either activity-dependent changes in volume or from oximetric changes that do not co-localize with neuronal activity per se. Standard methods do not always suffice to reduce such artifacts, in which case conspicuous spatial artifacts mask details of the underlying activity patterns. Here we propose a simple algorithm that efficiently removes spatial biological artifacts contaminating high-resolution functional maps. We validated this procedure by applying it to cortical maps resulting from optical imaging, based either on voltage-sensitive dye signals or on intrinsic signals. To remove vascular spatial patterns we first constructed a template of typical artifacts (vascular/cardiac pulsation/vasomotion), using principle components derived from baseline information obtained in the absence of stimulation. Next, we modified this template by means of local similarity minimization (LSM), achieved by measuring neighborhood similarity between contaminated data and the artifact template and then abolishing the similarity. LSM thus removed spatial patterns originating from the cortical vasculature components, including large fields of capillary parenchyma, helping to unveil details of neuronal activity patterns that were otherwise masked by these vascular artifacts. Examples obtained from our imaging experiments with anaesthetized cats and behaving monkeys showed that the LSM method is both general and reproducible, and is often superior to other available procedures.

Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest

Recent studies have demonstrated large amplitude spontaneous fluctuations in functional-MRI (fMRI) signals in humans in the resting state. Importantly, these spontaneous fluctuations in blood-oxygenation-level-dependent (BOLD) signal are often synchronized over distant parts of the brain, a phenomenon termed functional-connectivity. Functional-connectivity is widely assumed to reflect interregional coherence of fluctuations in activity of the underlying neuronal networks. Despite the large body of human imaging literature on spontaneous activity and functional-connectivity in the resting state, the link to underlying neural activity remains tenuous. Through simultaneous fMRI and intracortical neurophysiological recording, we demonstrate correlation between slow fluctuations in BOLD signals and concurrent fluctuations in the underlying locally measured neuronal activity. This correlation varied with time-lag of BOLD relative to neuronal activity, resembling a traditional hemodynamic response function with peaks at approximately 6 s lag of BOLD signal. The correlations were reliably detected when the neuronal signal consisted of either the spiking rate of a small group of neurons, or relative power changes in the multi-unit activity band, and particularly in the local field potential gamma band. Analysis of correlation between the voxel-by-voxel fMRI time-series and the neuronal activity measured within one cortical site showed patterns of correlation that slowly traversed cortex. BOLD fluctuations in widespread areas in visual cortex of both hemispheres were significantly correlated with neuronal activity from a single recording site in V1. To the extent that our V1 findings can be generalized to other cortical areas, fMRI-based functional-connectivity between remote regions in the resting state can be linked to synchronization of slow fluctuations in the underlying neuronal signals.

Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the 'resting' brain

Functional magnetic resonance imaging techniques using the blood oxygenation level-dependent (BOLD) contrast are widely used to map human brain function by relating local hemodynamic responses to neuronal stimuli compared to control conditions. There is increasing interest in spontaneous cerebral BOLD fluctuations that are prominent in the low-frequency range (<0.1 Hz) and show intriguing spatio-temporal correlations in functional networks. The nature of these signal fluctuations remains unclear, but there is accumulating evidence for a neural basis opening exciting new avenues to study human brain function and its connectivity at rest. Moreover, an increasing number of patient studies report disease-dependent variation in the amplitude and spatial coherence of low-frequency BOLD fluctuations (LFBF) that may afford greater diagnostic sensitivity and easier clinical applicability than standard fMRI. The main disadvantage of this emerging tool relates to physiological (respiratory, cardiac and vasomotion) and motion confounds that are challenging to disentangle requiring thorough preprocessing. Technical aspects of functional connectivity fMRI analysis and the neuroscientific potential of spontaneous LFBF in the default mode and other resting-state networks have been recently reviewed. This review will give an update on the current knowledge of the nature of LFBF, their relation to physiological confounds and potential for clinical diagnostic and pharmacological studies.

In vitro and in vivo noise analysis for optical neural recording

Laser diodes (LD) are commonly used for optical neural recordings in chronically recorded animals and humans, primarily due to their brightness and small size. However, noise introduced by LDs may counteract the benefits of brightness when compared to low-noise light-emitting diodes (LEDs). To understand noise sources in optical recordings, we systematically compared instrument and physiological noise profiles in two recording paradigms. A better understanding of noise sources can help improve optical recordings and make them more practical with fewer averages. We stimulated lobster nerves and a rat cortex, then compared the root mean square (RMS) noise and signal-to-noise ratios (SNRs) of data obtained with LED, superluminescent diode (SLD), and LD illumination for different numbers of averages. The LED data exhibited significantly higher SNRs in fewer averages than LD data in all recordings. In the absence of tissue, LED noise increased linearly with intensity, while LD noise increased sharply in the transition to lasing and settled to noise levels significantly higher than the LED's, suggesting that speckle noise contributed to the LD's higher noise and lower SNRs. Our data recommend low coherence and portable light sources for in vivo chronic neural recording applications.

Lessons from fMRI about mapping cortical columns

Recently developed fMRI can map small functional structures noninvasively and repeatedly without any depth limitation. However, there has been a persistent concern as to whether the high-resolution fMRI signals actually mark the sites of increased neural activity. To examine this outstanding issue, the authors used iso-orientation columns of isoflurane-anesthetized cats as a biological model and confirmed the neural correlation of fMRI iso-orientation maps by comparing them with intrinsic optical imaging maps. The results suggest that highest fMRI signals indeed indicate the sites of increased neuronal activity. Now fMRI can be used to determine plastic and/or developmental change of functional columnar structure possibly on a layer-to-layer basis. In this review, the authors focus mainly on what technical aspects should be considered when mapping functional cortical columns, including imaging techniques and experimental design.

Intrinsic signal imaging of deprivation-induced contraction of whisker representations in rat somatosensory cortex

In classical sensory cortical map plasticity, the representation of deprived or underused inputs contracts within cortical sensory maps, whereas spared inputs expand. Expansion of spared inputs occurs preferentially into nearby cortical columns representing temporally correlated spared inputs, suggesting that expansion involves correlation-based learning rules at cross-columnar synapses. It is unknown whether deprived representations contract in a similar anisotropic manner, which would implicate similar learning rules and sites of plasticity. We briefly deprived D-row whiskers in 20-day-old rats, so that each deprived whisker had deprived (D-row) and spared (C- and E-row) neighbors. Intrinsic signal optical imaging revealed that D-row deprivation weakened and contracted the functional representation of deprived D-row whiskers in L2/3 of somatosensory (S1) cortex. Spared whisker representations did not strengthen or expand, indicating that D-row deprivation selectively engages the depression component of map plasticity. Contraction of deprived whisker representations was spatially uniform, with equal withdrawal from spared and deprived neighbors. Single-unit electrophysiological recordings confirmed these results, and showed substantial weakening of responses to deprived whiskers in layer 2/3 of S1, and modest weakening in L4. The observed isotropic contraction of deprived whisker representations during D-row deprivation is consistent with plasticity at intracolumnar, rather than cross-columnar, synapses.

Spatio-temporal characteristics of low-frequency BOLD signal fluctuations in isoflurane-anesthetized rat brain

We studied the spatio-temporal characteristics of the resting state low-frequency fluctuations in fMRI-BOLD signal in isoflurane-anesthetized rats. fMRI-BOLD measurements at 9.4 T were made during normal and exsanguinated condition previously known to alter cerebral blood flow (CBF) fluctuations in anesthetized rats. fMRI signal time series were low pass filtered and studied by spectral analysis. During normal conditions, baseline mean arterial pressure (MAP) was 110+/-10 mm Hg and low-frequency fluctuations in BOLD signal were observed in the frequency range of 0.01 to 0.125 Hz. Following blood withdrawal (exsanguination), MAP decreased to 68+/-7 mm Hg, resulting in an increase in the amplitude of the low-frequency fluctuations in BOLD signal time series and an increase in power at several frequencies between 0.01 and 0.125 Hz. Spatially, the BOLD fluctuations were confined to the cortex and thalamus spanning both hemispheres with sparse presence in the caudate putamen and hippocampus during both normal and exsanguinated states. Spatial distribution of the low-frequency fluctuations in BOLD signal, from cross-correlation analysis, indicates substantial inter-hemispheric synchrony similar to that observed in the conscious human brain. The behavior of the resting state BOLD signal fluctuations similar to CBF fluctuations during exsanguination indicates a myogenic dependence. Also, a high inter-hemispheric synchrony combined with different phase characteristics of the low-frequency BOLD fluctuations particularly in the hippocampus relative to the cortex emphasizes distinct functional networks.

Pial arteriolar vasomotion changes during cortical activation in rats

The oscillatory pattern of pial arterioles, i.e. vasomotion, has been described since early 1980s, but the impact of neural activation on such oscillations has never been formally examined. Sciatic nerve stimulation, a well characterized model for studying neurovascular coupling (NVC), leads to a neural activity-related increase of pial arteriolar diameter in the contralateral hindlimb somatosensory cortex. Exploiting such an experimental model, the aim of the present study was to explore vasomotion and its changes during NVC with a novel analytical approach. Indeed, to characterize oscillations, we evaluated the total spectral power in the range 0.02-2.00 Hz and subdivided this frequency interval into seven 50% overlapping frequency bands. Results indicated that only arterioles overlying the stimulated hindlimb cortex showed a significant increase of total power, unlike arterioles overlaying the whisker barrel cortex, used as control for the vascular response specificity. The total power increase was sustained mainly by marked increments in the low frequency range, with two peaks at 0.03 and 0.08 Hz, and by a wide increase in the high frequency range (0.60-2.00 Hz) in the averaged spectrum. These activity-related spectral changes suggest: (i) that it is possible to assess the vascular responses by using total power; (ii) the existence of at least three distinct mechanisms involved in the control of NVC, two with a feedback frequency loop in the low frequency range and another one in the high range; (iii) a potential involvement of vasomotion in NVC. Moreover, these findings highlight the oscillatory nature of the mechanisms controlling NVC.

Physiological noise in near-infrared spectroscopy: implications for optical brain computer interfacing

Near-infrared spectroscopy is a non-invasive optical method used to detect functional activation of the cerebral cortex. Cognitive, visual, auditory and motor tasks are among the functions that have been investigated by this technique in the context of optical brain computer interfacing. In order to determine whether the optical response is due to a stimulus, it is essential to identify and reduce the effects of physiological noise. This paper characterizes noise typically present in optical responses and reports signal processing approaches used to overcome such noise.

Optical brain imaging in vivo: techniques and applications from animal to man

Optical brain imaging has seen 30 years of intense development, and has grown into a rich and diverse field. In-vivo imaging using light provides unprecedented sensitivity to functional changes through intrinsic contrast, and is rapidly exploiting the growing availability of exogenous optical contrast agents. Light can be used to image microscopic structure and function in vivo in exposed animal brain, while also allowing noninvasive imaging of hemodynamics and metabolism in a clinical setting. This work presents an overview of the wide range of approaches currently being applied to in-vivo optical brain imaging, from animal to man. Techniques include multispectral optical imaging, voltage sensitive dye imaging and speckle-flow imaging of exposed cortex, in-vivo two-photon microscopy of the living brain, and the broad range of noninvasive topography and tomography approaches to near-infrared imaging of the human brain. The basic principles of each technique are described, followed by examples of current applications to cutting-edge neuroscience research. In summary, it is shown that optical brain imaging continues to grow and evolve, embracing new technologies and advancing to address ever more complex and important neuroscience questions.

Critical spatial frequencies for illusory contour processing in early visual cortex

Single neurons in primate V2 and cat A18 exhibit identical orientation tuning for sinewave grating and illusory contour stimuli. This cue invariance is also manifested in similar orientation maps to these stimuli, but in V1/A17 the illusory contour maps appear reversed. We hypothesized that this map reversal depends upon the spatial frequencies of the inducers in the illusory contours, relative to the spatial selectivities of these brain areas. We employed intrinsic signal optical imaging to measure orientation maps in cat A17/18 to illusory contours with inducers at spatial frequencies from 0.15 to 1.6 cpd. A17 illusory contour maps were indeed reversed compared with grating-driven maps for inducer spatial frequencies <1.3 cpd, whereas A18 maps were invariant. Simulations based on known neurophysiology demonstrated that map reversal can arise from linear filtering, and map invariance can be explained by a nonlinear (filter-rectify-filter) mechanism. The simulation also correctly predicted that A17 could show invariant maps when the inducer spatial frequency is sufficiently high (1.6 cpd), and that A18 maps could reverse at lower inducer frequencies (0.18 cpd). Thus, the map reversal or invariance to illusory contours depends critically on the relationship of the inducer spatial frequencies to the spatial filtering properties of neurons in each brain area.