Kevin Murphy, Ashley D Harris, Ana Diukova, John C Evans, David J Lythgoe, Fernando Zelaya and Richard G Wise.
Pulsed arterial spin labeling perfusion imaging at 3 T: estimating the number of subjects required in common designs of clinical trials. Magnetic Resonance Imaging 29(10):1382–1389, 2011.
Abstract Pulsed arterial spin labeling (PASL) is an increasingly common technique for noninvasively measuring cerebral blood flow (CBF) and has previously been shown to have good repeatability. It is likely to find a place in clinical trials and in particular the investigation of pharmaceutical agents active in the central nervous system. We aimed to estimate the sample sizes necessary to detect regional changes in CBF in common types of clinical trial design including (a) between groups, (b) a two-period crossover and (3) within-session single dosing. Whole brain CBF data were acquired at 3 T in two independent groups of healthy volunteers at rest; one of the groups underwent a repeat scan. Using these data, we were able to estimate between-groups, between-session and within-session variability along with regional mean estimates of CBF. We assessed the number of PASL tag?control image pairs that was needed to provide stable regional estimates of CBF and variability of regional CBF across groups. Forty tag?control image pairs, which take approximately 3 min to acquire using a single inversion label delay time, were adequate for providing stable CBF estimates at the group level. Power calculations based on the variance estimates of regional CBF measurements suggest that comparatively small cohorts are adequate. For example, detecting a 15% change in CBF, depending on the region of interest, requires from 7?15 subjects per group in a crossover design, 6?10 subjects in a within-session design and 20?41 subjects in a between-groups design. Such sample sizes make feasible the use of such CBF measurements in clinical trials of drugs. Pulsed arterial spin labeling (PASL) is an increasingly common technique for noninvasively measuring cerebral blood flow (CBF) and has previously been shown to have good repeatability. It is likely to find a place in clinical trials and in particular the investigation of pharmaceutical agents active in the central nervous system. We aimed to estimate the sample sizes necessary to detect regional changes in CBF in common types of clinical trial design including (a) between groups, (b) a two-period crossover and (3) within-session single dosing. Whole brain CBF data were acquired at 3 T in two independent groups of healthy volunteers at rest; one of the groups underwent a repeat scan. Using these data, we were able to estimate between-groups, between-session and within-session variability along with regional mean estimates of CBF. We assessed the number of PASL tag?control image pairs that was needed to provide stable regional estimates of CBF and variability of regional CBF across groups. Forty tag?control image pairs, which take approximately 3 min to acquire using a single inversion label delay time, were adequate for providing stable CBF estimates at the group level. Power calculations based on the variance estimates of regional CBF measurements suggest that comparatively small cohorts are adequate. For example, detecting a 15% change in CBF, depending on the region of interest, requires from 7?15 subjects per group in a crossover design, 6?10 subjects in a within-session design and 20?41 subjects in a between-groups design. Such sample sizes make feasible the use of such CBF measurements in clinical trials of drugs.
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Padmavathi Sundaram, Robert V Mulkern, William M Wells, Christina Triantafyllou, Tobias Loddenkemper, Ellen J Bubrick and Darren B Orbach.
An empirical investigation of motion effects in eMRI of interictal epileptiform spikes. Magnetic Resonance Imaging 29(10):1401–1409, 2011.
Abstract We recently developed a functional neuroimaging technique called encephalographic magnetic resonance imaging (eMRI). Our method acquires rapid single-shot gradient-echo echo-planar MRI (repetition time=47 ms); it attempts to measure an MR signal more directly linked to neuronal electromagnetic activity than existing methods. To increase the likelihood of detecting such an MR signal, we recorded concurrent MRI and scalp electroencephalography (EEG) during fast (20?200 ms), localized, high-amplitude (>50 ?V on EEG) cortical discharges in a cohort of focal epilepsy patients. Seen on EEG as interictal spikes, these discharges occur in between seizures and induced easily detectable MR magnitude and phase changes concurrent with the spikes with a lag of milliseconds to tens of milliseconds. Due to the time scale of the responses, localized changes in blood flow or hemoglobin oxygenation are unlikely to cause the MR signal changes that we observed. While the precise underlying mechanisms are unclear, in this study, we empirically investigate one potentially important confounding variable ? motion. Head motion in the scanner affects both EEG and MR recording. It can produce brief ?spike-like? artifacts on EEG and induce large MR signal changes similar to our interictal spike-related signal changes. In order to explore the possibility that interictal spikes were associated with head motions (although such an association had never been reported), we had previously tracked head position in epilepsy patients during interictal spikes and explicitly demonstrated a lack of associated head motion. However, that study was performed outside the MR scanner, and the root-mean-square error in the head position measurement was 0.7 mm. The large inaccuracy in this measurement therefore did not definitively rule out motion as a possible signal generator. In this study, we instructed healthy subjects to make deliberate brief (<500 ms) head motions inside the MR scanner and imaged these head motions with concurrent EEG and MRI. We compared these artifactual MR and EEG data to genuine interictal spikes. While per-voxel MR and per-electrode EEG time courses for the motion case can mimic the corresponding time courses associated with a genuine interictal spike, head motion can be unambiguously differentiated from interictal spikes via scalp EEG potential maps. Motion induces widespread changes in scalp potential, whereas interictal spikes are localized and have a regional fall-off in amplitude. These findings make bulk head motion an unlikely generator of the large spike-related MR signal changes that we had observed. Further work is required to precisely identify the underlying mechanisms. We recently developed a functional neuroimaging technique called encephalographic magnetic resonance imaging (eMRI). Our method acquires rapid single-shot gradient-echo echo-planar MRI (repetition time=47 ms); it attempts to measure an MR signal more directly linked to neuronal electromagnetic activity than existing methods. To increase the likelihood of detecting such an MR signal, we recorded concurrent MRI and scalp electroencephalography (EEG) during fast (20?200 ms), localized, high-amplitude (>50 ?V on EEG) cortical discharges in a cohort of focal epilepsy patients. Seen on EEG as interictal spikes, these discharges occur in between seizures and induced easily detectable MR magnitude and phase changes concurrent with the spikes with a lag of milliseconds to tens of milliseconds. Due to the time scale of the responses, localized changes in blood flow or hemoglobin oxygenation are unlikely to cause the MR signal changes that we observed. While the precise underlying mechanisms are unclear, in this study, we empirically investigate one potentially important confounding variable ? motion. Head motion in the scanner affects both EEG and MR recording. It can produce brief ?spike-like? artifacts on EEG and induce large MR signal changes similar to our interictal spike-related signal changes. In order to explore the possibility that interictal spikes were associated with head motions (although such an association had never been reported), we had previously tracked head position in epilepsy patients during interictal spikes and explicitly demonstrated a lack of associated head motion. However, that study was performed outside the MR scanner, and the root-mean-square error in the head position measurement was 0.7 mm. The large inaccuracy in this measurement therefore did not definitively rule out motion as a possible signal generator. In this study, we instructed healthy subjects to make deliberate brief (<500 ms) head motions inside the MR scanner and imaged these head motions with concurrent EEG and MRI. We compared these artifactual MR and EEG data to genuine interictal spikes. While per-voxel MR and per-electrode EEG time courses for the motion case can mimic the corresponding time courses associated with a genuine interictal spike, head motion can be unambiguously differentiated from interictal spikes via scalp EEG potential maps. Motion induces widespread changes in scalp potential, whereas interictal spikes are localized and have a regional fall-off in amplitude. These findings make bulk head motion an unlikely generator of the large spike-related MR signal changes that we had observed. Further work is required to precisely identify the underlying mechanisms.
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Leif Hertz.
Astrocytic energy metabolism and glutamate formation — relevance for ¹³C-NMR spectroscopy and importance of cytosolic/mitochondrial trafficking. Magnetic Resonance Imaging 29(10):1319–1329, 2011.
Abstract Glutamate plays a double role in 13C-nuclear magnetic resonance (NMR) spectroscopic determination of glucose metabolism in the brain. Bidirectional exchange between initially unlabeled glutamate and labeled α-ketoglutarate, formed from pyruvate via pyruvate dehydrogenase (PDH), indicates the rate of energy metabolism in the tricarboxylic acid (VTCA) cycle in neurons (VPDH, n) and, with additional computation, also in astrocytes (VPDH, g), as confirmed using the astrocyte-specific substrate [13C]acetate. Formation of new molecules of glutamate during increased glutamatergic activity occurs only in astrocytes by combined pyruvate carboxylase (VPC) and astrocytic PDH activity. VPDH, g accounts for ?15% of total pyruvate metabolism in the brain cortex, and VPC accounts for another ?10%. Since both PDH-generated and PC-generated pyruvates are needed for glutamate synthesis, ?20/25 (80%) of astrocytic pyruvate metabolism proceed via glutamate formation. Net transmitter glutamate [?-aminobutyric acid (GABA)] formation requires transfer of newly synthesized α-ketoglutarate to the astrocytic cytosol, α-ketoglutarate transamination to glutamate, amidation to glutamine, glutamine transfer to neurons, its hydrolysis to glutamate and glutamate release (or GABA formation). Glutamate?glutamine cycling, measured as glutamine synthesis rate (Vcycle), also transfers previously released glutamate/GABA to neurons after an initial astrocytic accumulation and measures predominantly glutamate signaling. An empirically established ?1/1 ratio between glucose metabolism and Vcycle may reflect glucose utilization associated with oxidation/reduction processes during glutamate production, which together with associated transamination processes are balanced by subsequent glutamate oxidation after cessation of increased signaling activity. Astrocytic glutamate formation and subsequent oxidative metabolism provide large amounts of adenosine triphosphate used for accumulation from extracellular clefts of neuronally released K+ and glutamate and for cytosolic Ca2+ homeostasis. Glutamate plays a double role in 13C-nuclear magnetic resonance (NMR) spectroscopic determination of glucose metabolism in the brain. Bidirectional exchange between initially unlabeled glutamate and labeled α-ketoglutarate, formed from pyruvate via pyruvate dehydrogenase (PDH), indicates the rate of energy metabolism in the tricarboxylic acid (VTCA) cycle in neurons (VPDH, n) and, with additional computation, also in astrocytes (VPDH, g), as confirmed using the astrocyte-specific substrate [13C]acetate. Formation of new molecules of glutamate during increased glutamatergic activity occurs only in astrocytes by combined pyruvate carboxylase (VPC) and astrocytic PDH activity. VPDH, g accounts for ?15% of total pyruvate metabolism in the brain cortex, and VPC accounts for another ?10%. Since both PDH-generated and PC-generated pyruvates are needed for glutamate synthesis, ?20/25 (80%) of astrocytic pyruvate metabolism proceed via glutamate formation. Net transmitter glutamate [?-aminobutyric acid (GABA)] formation requires transfer of newly synthesized α-ketoglutarate to the astrocytic cytosol, α-ketoglutarate transamination to glutamate, amidation to glutamine, glutamine transfer to neurons, its hydrolysis to glutamate and glutamate release (or GABA formation). Glutamate?glutamine cycling, measured as glutamine synthesis rate (Vcycle), also transfers previously released glutamate/GABA to neurons after an initial astrocytic accumulation and measures predominantly glutamate signaling. An empirically established ?1/1 ratio between glucose metabolism and Vcycle may reflect glucose utilization associated with oxidation/reduction processes during glutamate production, which together with associated transamination processes are balanced by subsequent glutamate oxidation after cessation of increased signaling activity. Astrocytic glutamate formation and subsequent oxidative metabolism provide large amounts of adenosine triphosphate used for accumulation from extracellular clefts of neuronally released K+ and glutamate and for cytosolic Ca2+ homeostasis.
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Cesare Magri, Nikos K Logothetis and Stefano Panzeri.
Investigating static nonlinearities in neurovascular coupling. Magnetic Resonance Imaging 29(10):1358–1364, 2011.
Abstract Many statistical models of coupling between time changes of the band-limited power of neural signals and functional magnetic resonance imaging Blood Oxygenation Level Dependent (BOLD) signal time changes rely on linear convolution. The effect of nonlinear behaviors in single-trial relationships between neural signals and BOLD responses is rarely tested and included in models. Here we investigate whether using a static nonlinearity improves the prediction of single-trial BOLD responses from neural signals. A static nonlinearity is a nonlinear transformation of the convolution of neural responses which is implemented by the same nonlinear function for all time points. We evaluated this approach by applying it to simultaneous recordings of functional magnetic resonance imaging BOLD and band-limited neural signals (Local Field Potentials and Multi Unit Activity) from primary visual cortex of anaesthetized macaques. We found that using a simple polynomial static nonlinearity was sufficient to obtain highly significant improvements of the accuracy of single-trial BOLD prediction over the accuracy obtained with linear convolution. This suggests that static nonlinearities may be a useful tool for a compact and accurate statistical description of neurovascular coupling. Many statistical models of coupling between time changes of the band-limited power of neural signals and functional magnetic resonance imaging Blood Oxygenation Level Dependent (BOLD) signal time changes rely on linear convolution. The effect of nonlinear behaviors in single-trial relationships between neural signals and BOLD responses is rarely tested and included in models. Here we investigate whether using a static nonlinearity improves the prediction of single-trial BOLD responses from neural signals. A static nonlinearity is a nonlinear transformation of the convolution of neural responses which is implemented by the same nonlinear function for all time points. We evaluated this approach by applying it to simultaneous recordings of functional magnetic resonance imaging BOLD and band-limited neural signals (Local Field Potentials and Multi Unit Activity) from primary visual cortex of anaesthetized macaques. We found that using a simple polynomial static nonlinearity was sufficient to obtain highly significant improvements of the accuracy of single-trial BOLD prediction over the accuracy obtained with linear convolution. This suggests that static nonlinearities may be a useful tool for a compact and accurate statistical description of neurovascular coupling.
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Nora Höfner, Hans-Helge Albrecht, Antonino Mario Cassará, Gabriel Curio, Stefan Hartwig, Jens Haueisen, Ingo Hilschenz, Rainer Körber, Sven Martens, Hans-Jürgen Scheer, Jens Voigt, Lutz Trahms and Martin Burghoff.
Are brain currents detectable by means of low-field NMR? A phantom study. Magnetic Resonance Imaging 29(10):1365–1373, 2011.
Abstract A number of different methods have been developed in order to detect the spreading of neuronal currents by means of noninvasive imaging techniques. However, all of these are subjected to limitations in the temporal or spatial resolution. A new approach of neuronal current detection is based on the use of low-field nuclear magnetic resonance (LF-NMR) that records brain activity directly. In the following, we describe a phantom study in order to assess the feasibility of neuronal current detection using LF-NMR. In addition to that, necessary preliminary subject studies examining somatosensory evoked neuronal currents are presented. During the phantom study, the influences of two different neuronal time signals on 1H-NMR signals were observed. The measurements were carried out by using a head phantom with an integrated current dipole to simulate neuronal activity. Two LF-NMR methods based on a DC and an AC (resonant) mechanism were utilized to study the feasibility of detecting both types of magnetic brain signals. Measurements were made inside an extremely magnetically shielded room by using a superconducting quantum interference device magnetometer system. The measurement principles were validated applying currents of higher intensity than those typical of the neuronal currents. Through stepwise reduction of the amplitude of the current dipole strength, the resolution limits of the two measuring procedures were found. The results indicate that it is necessary to improve the signal-to-noise ratio of the measurement system by at least a factor of 38 in order to detect typical human neuronal activity directly by means of LF-NMR. In addition to that, ways of achieving this factor are discussed. A number of different methods have been developed in order to detect the spreading of neuronal currents by means of noninvasive imaging techniques. However, all of these are subjected to limitations in the temporal or spatial resolution. A new approach of neuronal current detection is based on the use of low-field nuclear magnetic resonance (LF-NMR) that records brain activity directly. In the following, we describe a phantom study in order to assess the feasibility of neuronal current detection using LF-NMR. In addition to that, necessary preliminary subject studies examining somatosensory evoked neuronal currents are presented. During the phantom study, the influences of two different neuronal time signals on 1H-NMR signals were observed. The measurements were carried out by using a head phantom with an integrated current dipole to simulate neuronal activity. Two LF-NMR methods based on a DC and an AC (resonant) mechanism were utilized to study the feasibility of detecting both types of magnetic brain signals. Measurements were made inside an extremely magnetically shielded room by using a superconducting quantum interference device magnetometer system. The measurement principles were validated applying currents of higher intensity than those typical of the neuronal currents. Through stepwise reduction of the amplitude of the current dipole strength, the resolution limits of the two measuring procedures were found. The results indicate that it is necessary to improve the signal-to-noise ratio of the measurement system by at least a factor of 38 in order to detect typical human neuronal activity directly by means of LF-NMR. In addition to that, ways of achieving this factor are discussed.
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Steffen Stoewer, Jozien Goense, Georgios A Keliris, Andreas Bartels, Nikos K Logothetis, John Duncan and Natasha Sigala.
Realignment strategies for awake-monkey fMRI data. Magnetic Resonance Imaging 29(10):1390–1400, 2011.
Abstract Functional magnetic resonance imaging (fMRI) experiments with awake nonhuman primates (NHPs) have recently seen a surge of applications. However, the standard fMRI analysis tools designed for human experiments are not optimal for NHP data collected at high fields. One major difference is the experimental setup. Although real head movement is impossible for NHPs, MRI image series often contain visible motion artifacts. Animal body movement results in image position changes and geometric distortions. Since conventional realignment methods are not appropriate to address such differences, algorithms tailored specifically for animal scanning become essential. We have implemented a series of high-field NHP specific methods in a software toolbox, fMRI Sandbox (http://kyb.tuebingen.mpg.de/~stoewer/), which allows us to use different realignment strategies. Here we demonstrate the effect of different realignment strategies on the analysis of awake-monkey fMRI data acquired at high field (7 T). We show that the advantage of using a nonstandard realignment algorithm depends on the amount of distortion in the dataset. While the benefits for less distorted datasets are minor, the improvement of statistical maps for heavily distorted datasets is significant. Functional magnetic resonance imaging (fMRI) experiments with awake nonhuman primates (NHPs) have recently seen a surge of applications. However, the standard fMRI analysis tools designed for human experiments are not optimal for NHP data collected at high fields. One major difference is the experimental setup. Although real head movement is impossible for NHPs, MRI image series often contain visible motion artifacts. Animal body movement results in image position changes and geometric distortions. Since conventional realignment methods are not appropriate to address such differences, algorithms tailored specifically for animal scanning become essential. We have implemented a series of high-field NHP specific methods in a software toolbox, fMRI Sandbox (http://kyb.tuebingen.mpg.de/~stoewer/), which allows us to use different realignment strategies. Here we demonstrate the effect of different realignment strategies on the analysis of awake-monkey fMRI data acquired at high field (7 T). We show that the advantage of using a nonstandard realignment algorithm depends on the amount of distortion in the dataset. While the benefits for less distorted datasets are minor, the improvement of statistical maps for heavily distorted datasets is significant.
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Fahad Sultan, Mark Augath, Yusuke Murayama, Andreas S Tolias and Nikos Logothetis.
esfMRI of the upper STS: further evidence for the lack of electrically induced polysynaptic propagation of activity in the neocortex. Magnetic Resonance Imaging 29(10):1374–1381, 2011.
Abstract Combining electrical stimulation with fMRI (esfMRI) has proven to be an important tool to study the global effects of electrical stimulation on neural networks in the brain. Here we extend our previous studies to stimulating the upper superior temporal sulcus (STS) in the anesthetized monkey. Our results show that stimulating area V5/MT and surrounding areas leads to positive BOLD responses in the majority of cortical areas known to receive direct/monosynaptic connections from the stimulation site. We confirm our previous results from stimulating primary visual cortex that the propagation of electrically induced activity is limited in its transsynaptic propagation to the first synapse also for extrastriate areas. Combining electrical stimulation with fMRI (esfMRI) has proven to be an important tool to study the global effects of electrical stimulation on neural networks in the brain. Here we extend our previous studies to stimulating the upper superior temporal sulcus (STS) in the anesthetized monkey. Our results show that stimulating area V5/MT and surrounding areas leads to positive BOLD responses in the majority of cortical areas known to receive direct/monosynaptic connections from the stimulation site. We confirm our previous results from stimulating primary visual cortex that the propagation of electrically induced activity is limited in its transsynaptic propagation to the first synapse also for extrastriate areas.
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Silvia Mangia, Federico De Martino, Timo Liimatainen, Michael Garwood and Shalom Michaeli.
Magnetization transfer using inversion recovery during off-resonance irradiation. Magnetic Resonance Imaging 29(10):1346–1350, 2011.
Abstract Estimation of magnetization transfer (MT) parameters in vivo can be compromised by an inability to drive the magnetization to a steady state using allowable levels of radiofrequency (RF) irradiation, due to safety concerns (tissue heating and specific absorption rate (SAR)). Rather than increasing the RF duration or amplitude, here we propose to circumvent the SAR limitation by sampling the formation of the steady state in separate measurements made with the magnetization initially along the -z and +z axis of the laboratory frame, i.e. with or without an on-resonance inversion pulse prior to the off-resonance irradiation. Results from human brain imaging demonstrate that this choice provides a tremendous benefit in the fitting procedure used to estimate MT parameters. The resulting parametric maps are characterized by notably increased tissue specificity as compared to those obtained with the standard MT acquisition in which magnetization is initially along the +z axis only. Estimation of magnetization transfer (MT) parameters in vivo can be compromised by an inability to drive the magnetization to a steady state using allowable levels of radiofrequency (RF) irradiation, due to safety concerns (tissue heating and specific absorption rate (SAR)). Rather than increasing the RF duration or amplitude, here we propose to circumvent the SAR limitation by sampling the formation of the steady state in separate measurements made with the magnetization initially along the -z and +z axis of the laboratory frame, i.e. with or without an on-resonance inversion pulse prior to the off-resonance irradiation. Results from human brain imaging demonstrate that this choice provides a tremendous benefit in the fitting procedure used to estimate MT parameters. The resulting parametric maps are characterized by notably increased tissue specificity as compared to those obtained with the standard MT acquisition in which magnetization is initially along the +z axis only.
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Dirk Ostwald and Andrew P Bagshaw.
Information theoretic approaches to functional neuroimaging. Magnetic Resonance Imaging 29(10):1417–1428, 2011.
Abstract Information theory is a probabilistic framework that allows the quantification of statistical non-independence between signals of interest. In contrast to other methods used for this purpose, it is model free, i.e., it makes no assumption about the functional form of the statistical dependence or the underlying probability distributions. It thus has the potential to unveil important signal characteristics overlooked by classical data analysis techniques. In this review, we discuss how information theoretic concepts have been applied to the analysis of functional brain imaging data such as functional magnetic resonance imaging and magneto/electroencephalography. We review studies from a number of imaging domains, including the investigation of the brain's functional specialization and integration, neurovascular coupling and multimodal imaging. We demonstrate how information theoretical concepts can be used to answer neurobiological questions and discuss their limitations as well as possible future developments of the framework to advance our understanding of brain function. Information theory is a probabilistic framework that allows the quantification of statistical non-independence between signals of interest. In contrast to other methods used for this purpose, it is model free, i.e., it makes no assumption about the functional form of the statistical dependence or the underlying probability distributions. It thus has the potential to unveil important signal characteristics overlooked by classical data analysis techniques. In this review, we discuss how information theoretic concepts have been applied to the analysis of functional brain imaging data such as functional magnetic resonance imaging and magneto/electroencephalography. We review studies from a number of imaging domains, including the investigation of the brain's functional specialization and integration, neurovascular coupling and multimodal imaging. We demonstrate how information theoretical concepts can be used to answer neurobiological questions and discuss their limitations as well as possible future developments of the framework to advance our understanding of brain function.
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Silvia De Santis, Andrea Gabrielli, Marco Palombo, Bruno Maraviglia and Silvia Capuani.
Non-Gaussian diffusion imaging: a brief practical review. Magnetic Resonance Imaging 29(10):1410–1416, 2011.
Abstract The departure from purely mono-exponential decay of the signal, as observed from brain tissue following a diffusion-sensitized sequence, has prompted the search for alternative models to characterize these unconventional water diffusion dynamics. Several approaches have been proposed in the last few years. While multi-exponential models have been applied to characterize brain tissue, several unresolved controversies about the interpretations of the results have motivated the search for alternative models that do not rely on the Gaussian diffusion hypothesis. In this brief review, diffusional kurtosis imaging (DKI) and anomalous diffusion imaging (ADI) techniques are addressed and compared with diffusion tensor imaging. Theoretical and experimental issues are briefly described to allow readers to understand similarities, differences and limitations of these two non-Gaussian models. However, since the ultimate goal is to improve specificity, sensitivity and spatial localization of diffusion MRI for the detection of brain diseases, special attention will be paid on the clinical feasibility of the proposed techniques as well as on the context of brain pathology investigations. The departure from purely mono-exponential decay of the signal, as observed from brain tissue following a diffusion-sensitized sequence, has prompted the search for alternative models to characterize these unconventional water diffusion dynamics. Several approaches have been proposed in the last few years. While multi-exponential models have been applied to characterize brain tissue, several unresolved controversies about the interpretations of the results have motivated the search for alternative models that do not rely on the Gaussian diffusion hypothesis. In this brief review, diffusional kurtosis imaging (DKI) and anomalous diffusion imaging (ADI) techniques are addressed and compared with diffusion tensor imaging. Theoretical and experimental issues are briefly described to allow readers to understand similarities, differences and limitations of these two non-Gaussian models. However, since the ultimate goal is to improve specificity, sensitivity and spatial localization of diffusion MRI for the detection of brain diseases, special attention will be paid on the clinical feasibility of the proposed techniques as well as on the context of brain pathology investigations.
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Limin Chen, Arabinda Mishra, Allen T Newton, Victoria L Morgan, Elizabeth A Stringer, Baxter P Rogers and John C Gore.
Fine-scale functional connectivity in somatosensory cortex revealed by high-resolution fMRI. Magnetic Resonance Imaging 29(10):1330–1337, 2011.
Abstract High-resolution functional magnetic resonance imaging (fMRI) at high field (9.4 T) has been used to measure functional connectivity between subregions within the primary somatosensory (SI) cortex of the squirrel monkey brain. The hand?face region within the SI cortex of the squirrel monkey has been previously well mapped with functional imaging and electrophysiological and anatomical methods, and the orderly topographic map of the hand region is characterized by a lateral to medial representation of individual digits in four subregions of areas 3a, 3b, 1 and 2. With submillimeter resolution, we are able to detect not only the separate islands of activation corresponding to vibrotactile stimulations of single digits but also, in subsequent acquisitions, the degree of correlation between voxels within the SI cortex in the resting state. The results suggest that connectivity patterns are very similar to stimulus-driven distributions of activity and that connectivity varies on the scale of millimeters within the same primary region. Connectivity strength is not a reflection of global larger-scale changes in blood flow and is not directly dependent on distance between regions. Preliminary electrophysiological recordings agree well with the fMRI data. In human studies at 7 T, high-resolution fMRI may also be used to identify the same subregions and assess responses to sensory as well as painful stimuli, and to measure connectivity dynamically before and after such stimulations. High-resolution functional magnetic resonance imaging (fMRI) at high field (9.4 T) has been used to measure functional connectivity between subregions within the primary somatosensory (SI) cortex of the squirrel monkey brain. The hand?face region within the SI cortex of the squirrel monkey has been previously well mapped with functional imaging and electrophysiological and anatomical methods, and the orderly topographic map of the hand region is characterized by a lateral to medial representation of individual digits in four subregions of areas 3a, 3b, 1 and 2. With submillimeter resolution, we are able to detect not only the separate islands of activation corresponding to vibrotactile stimulations of single digits but also, in subsequent acquisitions, the degree of correlation between voxels within the SI cortex in the resting state. The results suggest that connectivity patterns are very similar to stimulus-driven distributions of activity and that connectivity varies on the scale of millimeters within the same primary region. Connectivity strength is not a reflection of global larger-scale changes in blood flow and is not directly dependent on distance between regions. Preliminary electrophysiological recordings agree well with the fMRI data. In human studies at 7 T, high-resolution fMRI may also be used to identify the same subregions and assess responses to sensory as well as painful stimuli, and to measure connectivity dynamically before and after such stimulations.
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Giovanni Giulietti, Paul E Summers, Diana Ferraro, Carlo A Porro, Bruno Maraviglia and Federico Giove.
Semiautomated segmentation of the human spine based on echoplanar images. Magnetic Resonance Imaging 29(10):1429–1436, 2011.
Abstract The number of functional magnetic resonance imaging (fMRI) studies performed on the human spinal cord (SC) has considerably increased in recent years. The lack of a validated processing pipeline is, however, a significant obstacle to the spread of SC fMRI. One component likely to be involved in any such pipeline is the process of SC masking, analogous to brain extraction in cerebral fMRI. In general, SC masking has been performed manually, with the incumbent costs of being very time consuming and operator dependent.To overcome these drawbacks, we have developed a tailored semiautomatic method for segmenting echoplanar images (EPI) of human spine that is able to identify the spinal canal and the SC. The method exploits both temporal and spatial features of the EPI series and was tested and optimized on EPI images of cervical spine acquired at 3 T. The dependence of algorithm performance on the degree of EPI image distortion was assessed by computing the displacement warping field that best matched the EPI to the corresponding high-resolution T2 images. Segmentation accuracy was above 80%, a significant improvement over values obtained with similar approaches, but not exploiting temporal information. Geometric distortion was found to explain about 50% of the variance of algorithm classification efficiency. The number of functional magnetic resonance imaging (fMRI) studies performed on the human spinal cord (SC) has considerably increased in recent years. The lack of a validated processing pipeline is, however, a significant obstacle to the spread of SC fMRI. One component likely to be involved in any such pipeline is the process of SC masking, analogous to brain extraction in cerebral fMRI. In general, SC masking has been performed manually, with the incumbent costs of being very time consuming and operator dependent.To overcome these drawbacks, we have developed a tailored semiautomatic method for segmenting echoplanar images (EPI) of human spine that is able to identify the spinal canal and the SC. The method exploits both temporal and spatial features of the EPI series and was tested and optimized on EPI images of cervical spine acquired at 3 T. The dependence of algorithm performance on the degree of EPI image distortion was assessed by computing the displacement warping field that best matched the EPI to the corresponding high-resolution T2 images. Segmentation accuracy was above 80%, a significant improvement over values obtained with similar approaches, but not exploiting temporal information. Geometric distortion was found to explain about 50% of the variance of algorithm classification efficiency.
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Yusuke Murayama, Mark Augath and Nikos K Logothetis.
Activation of SC during electrical stimulation of LGN: retinal antidromic stimulation or corticocollicular activation?. Magnetic Resonance Imaging 29(10):1351–1357, 2011.
Abstract We have recently used combined electrostimulation, neurophysiology, microinjection and functional magnetic resonance imaging (fMRI) to study the cortical activity patterns elicited during stimulation of cortical afferents in monkeys. We found that stimulation of a site in lateral geniculate nucleus (LGN) increases the fMRI signal in the regions of primary visual cortex receiving input from that site, but suppresses it in the retinotopically matched regions of extrastriate cortex. Intracortical injection experiments showed that such suppression is due to synaptic inhibition. During these experiments, we have consistently observed activation of superior colliculus (SC) following LGN stimulation. Since LGN does not directly project to SC, the current study investigated the origin of SC activation. By examining experimental manipulations inactivating the primary visual cortex, we present here evidence that the robust SC activation, which follows the stimulation of LGN, is due to the activation of corticocollicular pathway. We have recently used combined electrostimulation, neurophysiology, microinjection and functional magnetic resonance imaging (fMRI) to study the cortical activity patterns elicited during stimulation of cortical afferents in monkeys. We found that stimulation of a site in lateral geniculate nucleus (LGN) increases the fMRI signal in the regions of primary visual cortex receiving input from that site, but suppresses it in the retinotopically matched regions of extrastriate cortex. Intracortical injection experiments showed that such suppression is due to synaptic inhibition. During these experiments, we have consistently observed activation of superior colliculus (SC) following LGN stimulation. Since LGN does not directly project to SC, the current study investigated the origin of SC activation. By examining experimental manipulations inactivating the primary visual cortex, we present here evidence that the robust SC activation, which follows the stimulation of LGN, is due to the activation of corticocollicular pathway.
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