Brain region binding of the D2/3 agonist [11C]-(+)-PHNO and the D2/3 antagonist [11C]raclopride in healthy humans

The D(2) receptors exist in either the high- or low-affinity state with respect to agonists, and while agonists bind preferentially to the high-affinity state, antagonists do not distinguish between the two states. [(11)C]-(+)-PHNO is a PET D(2) agonist radioligand and therefore provides a preferential measure of the D(2) (high) receptors. In contrast, [(11)C]raclopride is an antagonist radioligand and thus binds with equal affinity to the D(2) high- and low-affinity states. The aim was to compare the brain uptake, distribution and binding characteristics between [(11)C]-(+)-PHNO and [(11)C]raclopride in volunteers using a within-subject design. Both radioligands accumulated in brain areas rich in D(2)/D(3)-receptors. However, [(11)C]-(+)-PHNO showed preferential uptake in the ventral striatum and globus pallidus, while [(11)C]raclopride showed preferential uptake in the dorsal striatum. Mean binding potentials were higher in the putamen (4.3 vs. 2.8) and caudate (3.4 vs 2.1) for [(11)C]raclopride, equal in the ventral-striatum (3.4 vs. 3.3), and higher in the globus pallidus for [(11)C]-(+)-PHNO (1.8 vs. 3.3). Moreover [(11)C]-(+)-PHNO kinetics in the globus pallidus showed a slower washout than other regions. One explanation for the preferential binding of [(11)C]-(+)-PHNO in the globus pallidus and ventral-striatum could be the presence of a greater proportion of high- vs. low-affinity receptors in these areas. Alternatively, the observed distribution could also be explained by a preferential binding of D(3)-over-D(2) with [(11)C]-(+)-PHNO. This differential binding of agonist vs. antagonist radioligand, especially in the critically important region of the limbic striatum/pallidum, offers new avenues to investigate the role of the dopamine system in health and disease.

Group analysis and the subject factor in functional magnetic resonance imaging: analysis of fifty right-handed healthy subjects in a semantic language task

Before considering a given fMRI paradigm as a valid clinical tool, one should first assess the reliability of functional responses across subjects by establishing a normative database and defining a reference activation map that identifies major brain regions involved in the task at hand. However, the definition of such a reference map can be hindered by inter-individual functional variability. In this study, we analysed functional data obtained from 50 healthy subjects during a semantic language task to assess the influence of the number of subjects on the reference map and to characterise inter-individual functional variability. We first compared different group analysis approaches and showed that the extent of the activated network depends not only on the choice of the analysis approach but also on the statistical threshold used and the number of subjects included. This analysis suggested that, while the RFX analysis is suitable to detect confidently true positive activations, the other group approaches are useful for exploratory investigations in small samples. The application of quantitative measures at the voxel and regional levels suggested that while approximately 15-20 subjects were sufficient to reveal reliable and robust left hemisphere activations, >30 subjects were necessary for revealing more variable and weak right hemisphere ones. Finally, to visualise inter-individual variability, we combined two similarity indices that assess the percentages of true positive and false negative voxels in individual activation patterns relative to the group map. We suggest that these measures can be used for the estimation of the degree of 'normality' of functional responses in brain-damaged patients, where this question is often raised, and recommend the use of different quantifications to appreciate accurately the inter-individual functional variability that can be incorporated in group maps.

How to record a million synaptic weights in a hippocampal slice

A key step toward understanding the function of a brain circuit is to find its wiring diagram. New methods for optical stimulation and optical recording of neurons make it possible to map circuit connectivity on a very large scale. However, single synapses produce small responses that are difficult to measure on a large scale. Here I analyze how single synaptic responses may be detectable using relatively coarse readouts such as optical recording of somatic calcium. I model a network consisting of 10,000 input axons and 100 CA1 pyramidal neurons, each represented using 19 compartments with voltage-gated channels and calcium dynamics. As single synaptic inputs cannot produce a measurable somatic calcium response, I stimulate many inputs as a baseline to elicit somatic action potentials leading to a strong calcium signal. I compare statistics of responses with or without a single axonal input riding on this baseline. Through simulations I show that a single additional input shifts the distribution of the number of output action potentials. Stochastic resonance due to probabilistic synaptic release makes this shift easier to detect. With ∼80 stimulus repetitions this approach can resolve up to 35% of individual activated synapses even in the presence of 20% recording noise. While the technique is applicable using conventional electrical stimulation and extracellular recording, optical methods promise much greater scaling, since the number of synapses scales as the product of the number of inputs and outputs. I extrapolate from current high-speed optical stimulation and recording methods, and show that this approach may scale up to the order of a million synapses in a single two-hour slice-recording experiment.

The circuitry of the brain is defined by the connections (synapses) between its cells. Synapses are very small, so it is difficult to identify more than a few at a time using standard methods like electron microscopy or high-precision electrical recordings from cells. This study shows that it is possible to measure single synapses using low-precision methods such as optical recordings from neuronal cell bodies. I model optical or electrical stimulation of many inputs to trigger a visible response from neurons, and find single synapses by testing how this response is modulated when a single additional input synapse is triggered as well. I predict that it should be possible to record from as many as a million synapses using new optical recording and stimulation methods. It is believed that memories are encoded in synaptic connection patterns, so such connectivity data may give us a picture of how memories are encoded. We now know a great deal about how individual neurons behave, so a synapse-level wiring diagram would go a long way to fill out the picture of how neurons work together in the brain to interpret sensory information and plan actions.

High-pass GRAPPA: an image support reduction technique for improved partially parallel imaging

Partially parallel imaging (PPI) is a widely used technique in clinical applications. A limitation of this technique is the strong noise and artifact in the reconstructed images when high reduction factors are used. This work aims to increase the clinical applicability of PPI by improving its performance at high reduction factors. A new concept, image support reduction, is introduced. A systematic filter-design approach for image support reduction is proposed. This approach shows more advantages when used with an important existing PPI technique, GRAPPA. An improved GRAPPA method, high-pass GRAPPA (hp-GRAPPA), was developed based on this approach. The new technique does not involve changing the original GRAPPA kernel and performs reconstruction in almost the same amount of time. Experimentally, it is demonstrated that the reconstructed images using hp-GRAPPA have much lower noise/artifact level than those reconstructed using GRAPPA.

[Progress in visualization of MR diffusion tensor imaging]

MR diffusion tensor imaging (DT-MRI) is a new technology which reflects the direction of molecule diffusion better than traditional diffusion weighted imaging (DWI) does. DT-MRI has great advantages of showing the distribution of white matter fiber path and its spatial structures because the water molecules in brain white matters have the obvious anisotropic diffusion. This paper introduces the basics of diffusion tensor imaging, and reviews the visualization methods used with DT-MRI.

The resting frontal alpha asymmetry across the menstrual cycle: a magnetoencephalographic study

Gonadotropic hormones play an important role in the regulation of emotion. Previous studies have demonstrated that estrogen can modulate appetitive (approach/positive) and aversive (avoidance/negative) affective behaviors during the menstrual cycle. Frontal alpha asymmetry (a measure of relative difference of the alpha power between the two anterior hemispheres) has been associated with the trait and state reactivity of different affective styles. We studied the pattern change of frontal alpha asymmetry across the menstrual cycle. 16 healthy women participated in this resting magneto-encephalographic (MEG) study during the peri-ovulatory (OV) and menstrual (MC) phases. Our results showed significant interaction of resting MEG alpha activity between hemispheric side and menstrual phases. Difference in spontaneous frontal alpha asymmetry pattern across the menstrual cycle was also noted. Relatively higher right frontal activity was found during the OV phase; relatively higher left frontal activity was noted during the MC phase. The alteration of frontal alpha asymmetry might serve a sub-clinical correlate for hormonal modulation effect on dynamic brain organization for the predisposition and conceptualization of different affective styles across the menstrual cycle.

Long-term seizure monitoring using a 256 contact dense array system

Adapting a 256 contact dense array system to perform multiday long-term EEG and video monitoring requires additional technical attention compared to standard long-term monitoring (LTM). Areas of concern are patient comfort, electrode maintenance, and increased time for record review.

Fast slice-selective radio-frequency excitation pulses for mitigating B+1 inhomogeneity in the human brain at 7 Tesla

A novel radio-frequency (RF) pulse design algorithm is presented that generates fast slice-selective excitation pulses that mitigate B+1 inhomogeneity present in the human brain at high field. The method is provided an estimate of the B+1 field in an axial slice of the brain and then optimizes the placement of sinc-like "spokes" in kz via an L1-norm penalty on candidate (kx, ky) locations; an RF pulse and gradients are then designed based on these weighted points. Mitigation pulses are designed and demonstrated at 7T in a head-shaped water phantom and the brain; in each case, the pulses mitigate a significantly nonuniform transmit profile and produce nearly uniform flip angles across the field of excitation (FOX). The main contribution of this work, the sparsity-enforced spoke placement and pulse design algorithm, is derived for conventional single-channel excitation systems and applied in the brain at 7T, but readily extends to lower field systems, nonbrain applications, and multichannel parallel excitation arrays.

Probabilistic framework for brain connectivity from functional MR images

This paper unifies our earlier work on detection of brain activation (Rajapakse and Piyaratna, 2001) and connectivity (Rajapakse and Zhou, 2007) in a probabilistic framework for analyzing effective connectivity among activated brain regions from functional magnetic resonance imaging (fMRI) data. Interactions among brain regions are expressed by a dynamic Bayesian network (DBN) while contextual dependencies within functional images are formulated by a Markov random field. The approach simultaneously considers both the detection of brain activation and the estimation of effective connectivity and does not require a priori model of connectivity. Experimental results show that the present approach outperforms earlier fMRI analysis techniques on synthetic functional images and robustly derives brain connectivity from real fMRI data.

Sensorimotor rhythm-based brain-computer interface (BCI): model order selection for autoregressive spectral analysis

People can learn to control EEG features consisting of sensorimotor rhythm amplitudes and can use this control to move a cursor in one or two dimensions to a target on a screen. Cursor movement depends on the estimate of the amplitudes of sensorimotor rhythms. Autoregressive models are often used to provide these estimates. The order of the autoregressive model has varied widely among studies. Through analyses of both simulated and actual EEG data, the present study examines the effects of model order on sensorimotor rhythm measurements and BCI performance. The results show that resolution of lower frequency signals requires higher model orders and that this requirement reflects the temporal span of the model coefficients. This is true for both simulated EEG data and actual EEG data during brain-computer interface (BCI) operation. Increasing model order, and decimating the signal were similarly effective in increasing spectral resolution. Furthermore, for BCI control of two-dimensional cursor movement, higher model orders produced better performance in each dimension and greater independence between horizontal and vertical movements. In sum, these results show that autoregressive model order selection is an important determinant of BCI performance and should be based on criteria that reflect system performance.

Fully optimized discrimination of physiological responses to auditory stimuli

The use of multivariate measurements to characterize brain activity (electrical, magnetic, optical) is widespread. The most common approaches to reduce the complexity of such observations include principal and independent component analyses (PCA and ICA), which are not well suited for discrimination tasks. We addressed two questions: first, how do the neurophysiological responses to elongated phonemes relate to tone and phoneme responses in normal children, and, second, how discriminable are these responses. We employed fully optimized linear discrimination analysis to maximally separate the multi-electrode responses to tones and phonemes, and classified the response to elongated phonemes. We find that discrimination between tones and phonemes is dependent upon responses from associative regions of the brain apparently distinct from the primary sensory cortices typically emphasized by PCA or ICA, and that the neuronal correlates corresponding to elongated phonemes are highly variable in normal children (about half respond with neural correlates of tones and half as phonemes). Our approach is made feasible by the increase in computational power of ordinary personal computers and has significant advantages for a wide range of neuronal imaging modalities.

Uncovering interactions in the frequency domain

Oscillatory activity plays a critical role in regulating biological processes at levels ranging from subcellular, cellular, and network to the whole organism, and often involves a large number of interacting elements. We shed light on this issue by introducing a novel approach called partial Granger causality to reliably reveal interaction patterns in multivariate data with exogenous inputs and latent variables in the frequency domain. The method is extensively tested with toy models, and successfully applied to experimental datasets, including (1) gene microarray data of HeLa cell cycle; (2) in vivo multi-electrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of a sheep; and (3) in vivo LFPs recorded from distributed sites in the right hemisphere of a macaque monkey.

Group independent component analysis of language fMRI from word generation tasks

Language fMRI has been used to study brain regions involved in language processing and has been applied to pre-surgical language mapping. However, in order to provide clinicians with optimal information, the sensitivity and specificity of language fMRI needs to be improved. Type II error of failing to reach statistical significance when the language activations are genuinely present may be particularly relevant to pre-surgical planning, by falsely indicating low surgical risk in areas where no activations are shown. Furthermore, since the execution of language paradigms involves cognitive processes other than language function per se, the conventional general linear model (GLM) method may identify non-language-specific activations. In this study, we assessed an exploratory approach, independent component analysis (ICA), as a potential complementary method to the inferential GLM method in language mapping applications. We specifically investigated whether this approach might reduce type II error as well as generate more language-specific maps. Fourteen right-handed healthy subjects were studied with fMRI during two word generation tasks. A similarity analysis across tasks was proposed to select components of interest. Union analysis was performed on the language-specific components to increase sensitivity, and conjunction analysis was performed to identify language areas more likely to be essential. Compared with GLM, ICA identified more activated voxels in the putative language areas, and signals from other sources were isolated into different components. Encouraging results from one brain tumor patient are also presented. ICA may be used as a complementary tool to GLM in improving pre-surgical language mapping.

BrainTV: a novel approach for online mapping of human brain functions

Our understanding of the brain's functional organisation has greatly benefited from occasional exploratory sessions during electrophysiological studies, trying various manipulations of an animal's environment to trigger responses in particular neurons. Famous examples of such exploration have unveiled various unexpected response properties, such as those of mirror neurons. This approach, which relies on the possibility to test online the reactivity of precise neural populations has no equivalent so far in humans. The present study proposes and applies a radically novel framework for mapping human brain functions in ecological situations based on a combination of a) exploratory sessions, using real-time electrophysiology to formulate hypotheses about the functional role of precise cortical regions and b) controlled experimental protocols specifically adapted to test these hypotheses. Using this two-stage approach with an epileptic patient candidate for surgery and implanted with intracerebral electrodes, we were able to precisely map high-level auditory functions in the patients' superior temporal lobe. We propose that this procedure constitutes at the least a useful complement of electrical cortical stimulations to map eloquent brain areas in epileptic patients before their surgery, but also a path of discovery for human functional brain mapping.

Predictability modulates motor-auditory interactions in self-triggered audio-visual apparent motion

We studied an effect of predictability in an audio-visual apparent motion task using magnetoencephalography. The synchronous sequences of audio-visual stimuli were self-triggered by subjects. The task was to detect the direction of the apparent motion in experimental blocks in which the motion either started from the side selected by subjects (predictable condition) or was random (unpredictable condition). Magnetic fields yielded three patterns of activity in the motor, auditory, and visual areas. Comparison of the dipole strength between predictable and unpredictable conditions revealed a significant difference of the preparatory motor activity in the time interval from -450 to -100 ms before self-triggering the stimulus. Perception of the audio-visual apparent motion was also modulated by predictability. However, the modulation was found only for the auditory activity but not for the visual one. The effect of predictability was selective and modulated only the auditory component N1 (100 ms after stimulus), which reflects initial evaluation of stimulus meaning. Importantly, the preparatory motor activity correlates with the following auditory activity mainly in the same hemisphere. Similar modulation by predictability of the motor and auditory activities suggests interactions between these two systems within an action-perception cycle. The mechanism of these interactions can be understood as an effect of anticipation of the own action outcomes on the preparatory motor and perceptual activity.

Correction of B0 susceptibility induced distortion in diffusion-weighted images using large-deformation diffeomorphic metric mapping

Geometric distortion caused by B0 inhomogeneity is one of the most important problems for diffusion-weighted images (DWI) using single-shot, echo planar imaging (SS-EPI). In this study, large-deformation, diffeomorphic metric mapping (LDDMM) algorithm has been tested for the correction of geometric distortion in diffusion tensor images (DTI). Based on data from nine normal subjects, the amount of distortion caused by B0 susceptibility in the 3-T magnet was characterized. The distortion quality was validated by manually placing landmarks in the target and DTI images before and after distortion correction. The distortion was found to be up to 15 mm in the population-averaged map and could be more than 20 mm in individual images. Both qualitative demonstration and quantitative statistical results suggest that the highly elastic geometric distortion caused by spatial inhomogeneity of the B0 field in DTI using SS-EPI can be effectively corrected by LDDMM. This postprocessing method is especially useful for correcting existent DTI data without phase maps.

Phased array 3D MR spectroscopic imaging of the brain at 7 T

Ultra-high-field 7 T magnetic resonance (MR) scanners offer the potential for greatly improved MR spectroscopic imaging due to increased sensitivity and spectral resolution. Prior 7 T human single-voxel MR Spectroscopy (MRS) studies have shown significant increases in signal-to-noise ratio (SNR) and spectral resolution as compared to lower magnetic fields but have not demonstrated the increase in spatial resolution and multivoxel coverage possible with 7 T MR spectroscopic imaging. The goal of this study was to develop specialized radiofrequency (RF) pulses and sequences for three-dimensional (3D) MR spectroscopic imaging (MRSI) at 7 T to address the challenges of increased chemical shift misregistration, B1 power limitations, and increased spectral bandwidth. The new 7 T MRSI sequence was tested in volunteer studies and demonstrated the feasibility of obtaining high-SNR phased-array 3D MRSI from the human brain.

[Spatial recognition in cats: effects of parahippocampal lesions]

To determine the contribution of the posterior parahippocampal region to spatial form of one-trial memory in cats, we trained 8 cats to remember the spatial positions of either two different trial-unique objects overlying two of three feeders in a feeder test tray (object-place trials) or simply two of the three feeders (place trials). Four cats then received electrolytic lesions restricted to the posterior parahippocampal region (experimental group) including mainly parahippocampal cortex, parasubiculum and presubiculum. Four other cats comprised sham-operated control group. This group was found to be completely unaffected postoperatively in both types of trials, whereas experimental group showed impaired performance in both types of trials equally. Thus, one-trial memory for object-place association and one-trial memory for two different places in cats appear to be critically dependent on the posterior parahippocampal region.

Single-step nonlinear diffusion tensor estimation in the presence of microscopic and macroscopic motion

Patient motion can cause serious artifacts in diffusion tensor imaging (DTI), diminishing the reliability of the estimated diffusion tensor information. Studies in this field have so far been limited mainly to the correction of miniscule physiological motion. In order to correct for gross patient motion it is not sufficient to correct for misregistration between successive shots; the change in the diffusion-encoding direction must also be accounted for. This becomes particularly important for multishot sequences, whereby-in the presence of motion-each shot is encoded with a different diffusion weighting. In this study a general mathematical framework to correct for gross patient motion present in a multishot and multicoil DTI scan is presented. A signal model is presented that includes the effect of rotational and translational motion in the patient frame of reference. This model was used to create a nonlinear least-squares formulation, from which the diffusion tensors were obtained using a nonlinear conjugate gradient algorithm. Applications to both phantom simulations and in vivo studies showed that in the case of gross motion the proposed algorithm performs superiorly compared to conventional methods used for tensor estimation.

[Assessment of cerebral ischemia by oxygen pulse-based near-infrared optical topography]

BACKGROUND

SPECT and angiography are used to assess the cerebral blood flow dynamics; however, they have several drawbacks such as physical stress on the patients and considerable invasiveness. In order to overcome these drawbacks, we proposed and verified an alternative method of involving optical topography (OT).

MATERIALS AND METHODS

We used a 48-channel OT system with the 2 faces of 3 x 5 probe-holders on the patient's head, covering the bilateral fronto-temporal areas. The study was conducted with 11 normal volunteers and 30 patients with cerebral ischemia (ICA or MCA stenosis). All measurements were performed at a constant frequency of 10 Hz. In a block fashion, the subjects inhaled room air followed by oxygen for 2 minutes and then room air again, and SpO2 were monitored at the subjects' finger tips. In some cases, IMP-SPECT was performed.

RESULTS

The level of oxyhemoglobin measured by OT in the normal brain regions showed a trapezoid increase in accordance with oxygen inhalation, and similar results were obtained for SpO2. In the ischemic regions, the oxyhemoglobin increase was delayed and/or its height was lower. These observations suggest that the transmission of the systemic SpO2 wave pattern was delayed and its extent was lower in the ischemic region; this phenomenon can be utilized to detect the tissue ischemia. Principal component analysis was performed based on the SpO2 wave pattern. No lateralities were observed in 81.8% of the normal cases. However, in the ischemic cases, the weights of the principal components in the ischemic regions were reduced, and these findings agreed with the SPECT findings regarding of ischemia in 76.2% of the cases.

DISCUSSIONS AND CONCLUSIONS

Our results suggested that the regional attenuation of the oxhemoglobin wave demonstrated by principal component analysis reflects the ischemic state of cerebral blood flow. This novel method uses oxyhemoglobin as an OT. It can be clinically utilized as a real-time noninvasive method for the assessment of cerebral ischemia.

Mapping resting-state functional connectivity using perfusion MRI

Resting-state, low-frequency (<0.08 Hz) fluctuations of blood oxygenation level-dependent (BOLD) magnetic resonance signal have been shown to exhibit high correlation among functionally connected regions. However, correlations of cerebral blood flow (CBF) fluctuations during the resting state have not been extensively studied. The main challenges of using arterial spin labeling perfusion magnetic resonance imaging to detect CBF fluctuations are low sensitivity, low temporal resolution, and contamination from BOLD. This work demonstrates CBF-based quantitative functional connectivity mapping by combining continuous arterial spin labeling (CASL) with a neck labeling coil and a multi-channel receiver coil to achieve high perfusion sensitivity. In order to reduce BOLD contamination, the CBF signal was extracted from the CASL signal time course by high frequency filtering. This processing strategy is compatible with sinc interpolation for reducing the timing mismatch between control and label images and has the flexibility of choosing an optimal filter cutoff frequency to minimize BOLD fluctuations. Most subjects studied showed high CBF correlation in bilateral sensorimotor areas with good suppression of BOLD contamination. Root-mean-square CBF fluctuation contributing to bilateral correlation was estimated to be 29+/-19% (N=13) of the baseline perfusion, while BOLD fluctuation was 0.26+/-0.14% of the mean intensity (at 3 T and 12.5 ms echo time).