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Alzheimer's disease (AD) is associated with neurodegeneration in vulnerable limbic and heteromodal regions of the cerebral cortex, detectable in vivo using magnetic resonance imaging. It is not clear whether abnormalities of cortical anatomy in AD can be reliably measured across different subject samples, how closely they track symptoms, and whether they are detectable prior to symptoms. An exploratory map of cortical thinning in mild AD was used to define regions of interest that were applied in a hypothesis-driven fashion to other subject samples. Results demonstrate a reliably quantifiable in vivo signature of abnormal cortical anatomy in AD, which parallels known regional vulnerability to AD neuropathology. Thinning in vulnerable cortical regions relates to symptom severity even in the earliest stages of clinical symptoms. Furthermore, subtle thinning is present in asymptomatic older controls with brain amyloid binding as detected with amyloid imaging. The reliability and clinical validity of AD-related cortical thinning suggests potential utility as an imaging biomarker. This “disease signature” approach to cortical morphometry, in which disease effects are mapped across the cortical mantle and then used to define ROIs for hypothesis-driven analyses, may provide a powerful methodological framework for studies of neuropsychiatric diseases., National Institute on Aging (K23-AG22509), National Institute on Aging (P50-AG05134), National Institute on Aging (P50-AG05681), National Institute on Aging (P01-AG03991), National Institute on Aging (R01-AG29411), National Institute on Aging (R21-AG29840), National Institute of Neurological Disorders and Stroke (U.S.) (grant R01-NS042861), National Center for Research Resources (U.S.) (P41RR14075), National Center for Research Resources (U.S.) (U24-RR021382), Alzheimer's Association, Howard Hughes Medical Institute, Mental Illness and Neuroscience Discovery (MIND) Institute

To perform well on any challenging task, it is necessary to evaluate your performance so that you can learn from errors. Recent theoretical and experimental work suggests that the neural sequellae of error commission in a dorsal anterior cingulate circuit index a type of contingency- or reinforcement-based learning, while activation in a rostral anterior cingulate circuit reflects appraisal of the affective or motivational significance of errors. Patients with schizophrenia show rigid, perseverative behaviour that is not optimally responsive to outcome. Findings of reduced anterior cingulate cortex (ACC) activity during error commission in schizophrenia suggest that difficulties in evaluating and modifying behaviour in response to errors may contribute to behavioural rigidity. Using event-related functional MRI and an antisaccade paradigm with concurrent monitoring of eye position, the present study examined error-related activation and its relation to task performance in the anatomic components of two ACC circuits that are theorized to make distinct contributions to error processing. Eighteen chronic-medicated schizophrenia patients and 15 healthy controls participated. Compared to controls, patients showed increased antisaccade error rates and decreased error-related activation in the reinforcement learning network--dorsal ACC, striatum and brainstem (possibly substantia nigra)--and also in the affective appraisal network--rostral ACC, insula and amygdala. These reductions remained when the effects of antipsychotic medication dose and error rate were statistically controlled. Activation in these networks was inversely related to error rate in both patient and control groups, but the slope of this relation was shallower in patients (i.e. across participants with schizophrenia, decrements in error rate were associated with smaller decrements in activation). This indicates that the blunted neural response to errors in schizophrenia was not simply a reflection of more frequent errors. Our findings demonstrate a blunted response to error commission that is associated with worse performance in two ACC circuits in schizophrenia. In the dACC circuit, the blunted response may reflect deficient modification of prepotent stimulus-response mappings in response to errors, and in the rACC network it may reflect diminished concern regarding behavioural outcomes. However, despite these deficits and in the absence of external feedback regarding errors, patients corrected their errors as frequently as controls suggesting intact error recognition and ability to institute corrective action. Impairments in evaluating and learning from errors in schizophrenia may contribute to behaviour that is rigid and perseverative rather than optimally guided by outcomes, and may compromise performance across a wide range of tasks.

This study examined how task (implicit vs. explicit) and semantic relationship (direct vs. indirect) modulated hemodynamic activity during lexico-semantic processing. Participants viewed directly related, indirectly related, and unrelated prime-target word-pairs as they performed (a) an implicit lexical decision (LD) task in which they decided whether each target was a real word or a nonword, and (b) an explicit relatedness judgment (RJ) task in which they determined whether each word-pair was related or unrelated in meaning. Task influenced both the polarity and neuroanatomical localization of hemodynamic modulation. Semantic relationship influenced the neuroanatomical localization of hemodynamic modulation. The implicit LD task was primarily associated with inferior prefrontal and ventral inferior temporal/fusiform hemodynamic response suppression to directly related (relative to unrelated) word-pairs, and with more widespread temporal-occipital response suppression to indirectly related (relative to unrelated) word-pairs. In contrast, the explicit RJ task was primarily associated with left inferior parietal hemodynamic response enhancement to both directly and indirectly related (relative to unrelated) word-pairs, as well as with additional left inferior prefrontal hemodynamic response enhancement to indirectly related (relative to unrelated) word-pairs. These findings are discussed in relation to the specific neurocognitive processes thought to underlie implicit and explicit semantic processes. Hum Brain Mapp, 2008. (c) 2007 Wiley-Liss, Inc.

In the present report, estimates of test–retest and between‐site reliability of fMRI assessments were produced in the context of a multicenter fMRI reliability study (FBIRN Phase 1, http://www.nbirn.net). Five subjects were scanned on 10 MRI scanners on two occasions. The fMRI task was a simple block design sensorimotor task. The impulse response functions to the stimulation block were derived using an FIR‐deconvolution analysis with FMRISTAT. Six functionally‐derived ROIs covering the visual, auditory and motor cortices, created from a prior analysis, were used. Two dependent variables were compared: percent signal change and contrast‐to‐noise‐ratio. Reliability was assessed with intraclass correlation coefficients derived from a variance components analysis. Test–retest reliability was high, but initially, between‐site reliability was low, indicating a strong contribution from site and site‐by‐subject variance. However, a number of factors that can markedly improve between‐site reliability were uncovered, including increasing the size of the ROIs, adjusting for smoothness differences, and inclusion of additional runs. By employing multiple steps, between‐site reliability for 3T scanners was increased by 123%. Dropping one site at a time and assessing reliability can be a useful method of assessing the sensitivity of the results to particular sites. These findings should provide guidance toothers on the best practices for future multicenter studies. Hum Brain Mapp, 2008. © 2007 Wiley‐Liss, Inc.

The functional organization of the human brain consists of a high degree of connectivity between interhemispheric homologous regions. The degree of homotopic organization is known to vary across the cortex and homotopic connectivity is high in regions that share cross-hemisphere structural connections or are activated by common input streams (e.g., the visual system). Damage to one or both regions, as well as damage to the connections between homotopic regions, could disrupt this functional organization. Here were introduce and test a computationally efficient technique, surface-based homotopic interhermispheric connectivity (sHIC), that leverages surface-based registration and processing techniques in an attempt to improve the spatial specificity and accuracy of cortical interhemispheric connectivity estimated with resting state functional connectivity. This technique is shown to be reliable both within and across subjects. sHIC is also characterized in a dataset of nearly 1000 subjects. We confirm previous results showing increased interhemispheric connectivity in primary sensory regions, and reveal a novel rostro-caudal functionally defined network level pattern of sHIC across the brain. In addition, we demonstrate a structural-functional relationship between sHIC and atrophy of the corpus callosum in multiple sclerosis (r = 0.2979, p = 0.0461). sHIC presents as a sensitive and reliable measure of cortical homotopy that may prove useful as a biomarker in neurologic disease. Hum Brain Mapp 37:2849-2868, 2016. © 2016 Wiley Periodicals, Inc.

A cross-sectional group study of the effects of aging on brain metabolism as measured with (18)F-FDG-PET was performed using several different partial volume correction (PVC) methods: no correction (NoPVC), Meltzer (MZ), Muller-Gartner (MG), and the symmetric geometric transfer matrix (SGTM) using 99 subjects aged 65-87years from the Harvard Aging Brain study. Sensitivity to parameter selection was tested for MZ and MG. The various methods and parameter settings resulted in an extremely wide range of conclusions as to the effects of age on metabolism, from almost no changes to virtually all of cortical regions showing a decrease with age. Simulations showed that NoPVC had significant bias that made the age effect on metabolism appear to be much larger and more significant than it is. MZ was found to be the same as NoPVC for liberal brain masks; for conservative brain masks, MZ showed few areas correlated with age. MG and SGTM were found to be similar; however, MG was sensitive to a thresholding parameter that can result in data loss. CSF uptake was surprisingly high at about 15% of that in gray matter. The exclusion of CSF from SGTM and MG models, which is almost universally done, caused a substantial loss in the power to detect age-related changes. This diversity of results reflects the literature on the metabolism of aging and suggests that extreme care should be taken when applying PVC or interpreting results that have been corrected for partial volume effects. Using the SGTM, significant age-related changes of about 7% per decade were found in frontal and cingulate cortices as well as primary visual and insular cortices.

Serotonin (5-HT) is a neurotransmitter critically involved in a broad range of brain functions and implicated in the pathophysiology of neuropsychiatric illnesses including major depression, anxiety and sleep disorders. Despite being widely distributed throughout the brain, there is limited knowledge on the contribution of 5-HT to intrinsic brain activity. The dorsal raphe (DR) and median raphe (MR) nuclei are the source of most serotonergic neurons projecting throughout the brain and thus provide a compelling target for a seed-based probe of resting-state activity related to 5-HT. Here we implemented a novel multimodal neuroimaging approach for investigating resting-state functional connectivity (FC) between DR and MR and cortical, subcortical and cerebellar target areas. Using [(11)C]DASB positron emission tomography (PET) images of the brain serotonin transporter (5-HTT) combined with structural MRI from 49 healthy volunteers, we delineated DR and MR and performed a seed-based resting-state FC analysis. The DR and MR seeds produced largely similar FC maps: significant positive FC with brain regions involved in cognitive and emotion processing including anterior cingulate, amygdala, insula, hippocampus, thalamus, basal ganglia and cerebellum. Significant negative FC was observed within pre- and postcentral gyri for the DR but not for the MR seed. We observed a significant association between DR and MR FC and regional 5-HTT binding. Our results provide evidence for a resting-state network related to DR and MR and comprising regions receiving serotonergic innervation and centrally involved in 5-HT related behaviors including emotion, cognition and reward processing. These findings provide a novel advance in estimating resting-state FC related to 5-HT signaling, which can benefit our understanding of its role in behavior and neuropsychiatric illnesses.

© 2015 American College of Neuropsychopharmacology The amplitude of low-frequency fluctuations (ALFF) in the blood oxygenation level-dependent (BOLD) signal during resting-state fMRI reflects the magnitude of local low-frequency BOLD oscillations, rather than interregional connectivity. ALFF is of interest to studies of cognition because fluctuations in spontaneous intrinsic brain activity relate to, and possibly even constrain, task-evoked brain responses in healthy people. Lower ALFF has been reported in schizophrenia, but the cognitive correlates of these reductions remain unknown. Here, we assess relationships between ALFF and attention and working memory in order to establish the functional relevance of intrinsic BOLD oscillatory power alterations with respect to specific cognitive impairments in schizophrenia. As part of the multisite FBIRN study, resting-state fMRI data were collected from schizophrenia subjects (SZ; n=168) and healthy controls (HC; n=166). Voxelwise fractional ALFF (fALFF), a normalized ALFF measure, was regressed on neuropsychological measures of sustained attention and working memory in SZ and HC to identify regions showing either common slopes across groups or slope differences between groups (all findings p

The blood oxygenation level-dependent (BOLD) contrast is widely used in functional magnetic resonance imaging (fMRI) studies aimed at investigating neuronal activity. However, the BOLD signal reflects changes in blood volume and oxygenation rather than neuronal activity per se. Therefore, understanding the transformation of microscopic vascular behavior into macroscopic BOLD signals is at the foundation of physiologically informed noninvasive neuroimaging. Here, we use oxygen-sensitive two-photon microscopy to measure the BOLD-relevant microvascular physiology occurring within a typical rodent fMRI voxel and predict the BOLD signal from first principles using those measurements. The predictive power of the approach is illustrated by quantifying variations in the BOLD signal induced by the morphological folding of the human cortex. This framework is then used to quantify the contribution of individual vascular compartments and other factors to the BOLD signal for different magnet strengths and pulse sequences.

Since its inception two decades ago, functional magnetic resonance imaging (fMRI) has become a leading tool for noninvasive studies of the human brain. fMRI studies require both the rapid acquisition of many brain images over a sustained period of time and a high level of MRI system stability in order to detect small activity-related fluctuations in the MR signal. These rigorous requirements have driven many improvements in the performance of MRI systems. Quality assurance (QA) procedures are critical for identifying issues with system performance and ensuring that the desired level of system stability and image quality is achieved. In addition, ongoing QA of experimental data is important for detecting issues with not only the MRI system but also other key experimental elements such as task performance, movement artifacts, and stimulus presentation equipment. Given the large size of the datasets generated by fMRI studies, QA processes rely heavily on computer-based analyses coupled with the assessment of the QA metrics by a human expert. A well-designed QA process is especially critical for ensuring data quality and uniformity for fMRI studies involving multiple sites. These multicenter studies have a number of advantages, such as increased sample size, and are becoming more widely adopted.

© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved.Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both sourcebased morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects.

Longitudinal and multi-site clinical studies create the imperative to characterize and correct technological sources of variance that limit image reproducibility in high-resolution structural MRI studies, thus facilitating precise, quantitative, platform-independent, multi-site evaluation. In this work, we investigated the effects that imaging gradient non-linearity have on reproducibility of multi-site human MRI. We applied an image distortion correction method based on spherical harmonics description of the gradients and verified the accuracy of the method using phantom data. The correction method was then applied to the brain image data from a group of subjects scanned twice at multiple sites having different 1.5 T platforms. Within-site and across-site variability of the image data was assessed by evaluating voxel-based image intensity reproducibility. The image intensity reproducibility of the human brain data was significantly improved with distortion correction, suggesting that this method may offer improved reproducibility in morphometry studies. We provide the source code for the gradient distortion algorithm together with the phantom data.

To prospectively investigate the factors--including subject, brain hemisphere, study site, field strength, imaging unit vendor, imaging run, and examination visit--affecting the reproducibility of functional magnetic resonance (MR) imaging activations based on a repeated sensory-motor (SM) task.The institutional review boards of all participating sites approved this HIPAA-compliant study. All subjects gave informed consent. Functional MR imaging data were repeatedly acquired from five healthy men aged 20-29 years who performed the same SM task at 10 sites. Five 1.5-T MR imaging units, four 3.0-T units, and one 4.0-T unit were used. The subjects performed bilateral finger tapping on button boxes with a 3-Hz audio cue and a reversing checkerboard. In a block design, 15-second epochs of alternating baseline and tasks yielded 85 acquisitions per run. Functional MR images were acquired with block-design echo-planar or spiral gradient-echo sequences. Brain activation maps standardized in a unit-sphere for the left and right hemispheres of each subject were constructed. Areas under the receiver operating characteristic curve, intraclass correlation coefficients, multiple regression analysis, and paired Student t tests were used for statistical analyses.Significant factors were subject (P.005), k-space (P.005), and field strength (P = .02) for sensitivity and subject (P = .03) and k-space (P = .05) for specificity. At 1.5-T MR imaging, mean sensitivities ranged from 7% to 32% and mean specificities were higher than 99%. At 3.0 T, mean sensitivities and specificities ranged from 42% to 85% and from 96% to 99%, respectively. At 4.0 T, mean sensitivities and specificities ranged from 41% to 73% and from 95% to 99%, respectively. Mean areas under the receiver operating characteristic curve (+/- their standard errors) were 0.77 +/- 0.05 at 1.5 T, 0.90 +/- 0.09 at 3.0 T, and 0.95 +/- 0.02 at 4.0 T, with significant differences between the 1.5- and 3.0-T examinations and between the 1.5- and 4.0-T examinations (P.01 for both comparisons). Intraclass correlation coefficients ranged from 0.49 to 0.71.MR imaging at 3.0- and 4.0-T yielded higher reproducibility across sites and significantly better results than 1.5-T imaging. The effects of subject, k-space, and field strength on examination reproducibility were significant.

Previous research indicates that long-term meditation practice is associated with altered resting electroencephalogram patterns, suggestive of long lasting changes in brain activity. We hypothesized that meditation practice might also be associated with changes in the brain’s physical structure. Magnetic resonance imaging was used to assess cortical thickness in 20 participants with extensive Insight meditation experience, which involves focused attention to internal experiences. Brain regions associated with attention, interoception and sensory processing were thicker in meditation participants than matched controls, including the prefrontal cortex and right anterior insula. Between-group diierences in prefrontal cortical thickness were most pronounced in older participants, suggesting that meditation might oiset age-related cortical thinning. Finally, the thickness of two regions correlated with meditation experience. These data provide the ¢rst structural evidence for experience-dependent cortical plasticity associated with meditation practice. NeuroReport 16:1893^1897 � c 2005 Lippincott Williams & Wilkins.

Functional magnetic resonance imaging (fMRI) was used to study memory-associated activation of medial temporal lobe (MTL) regions in 32 nondemented elderly individuals with mild cognitive impairment (MCI). Subjects performed a visual encoding task during fMRI scanning and were tested for recognition of stimuli afterward. MTL regions of interest were identified from each individual's structural MRI, and activation was quantified within each region. Greater extent of activation within the hippocampal formation and parahippocampal gyrus (PHG) was correlated with better memory performance. There was, however, a paradoxical relationship between extent of activation and clinical status at both baseline and follow-up evaluations. Subjects with greater clinical impairment, based on the Clinical Dementia Rating Sum of Boxes, recruited a larger extent of the right PHG during encoding, even after accounting for atrophy. Moreover, those who subsequently declined over the 2.5 years of clinical follow-up (44% of the subjects) activated a significantly greater extent of the right PHG during encoding, despite equivalent memory performance. We hypothesize that increased activation in MTL regions reflects a compensatory response to accumulating AD pathology and may serve as a marker for impending clinical decline.

This study describes the neural circuitry underlying temporally separated components of working memory (WM) performance-stimulus encoding, maintenance of information during a delay, and the response to a probe. While other studies have applied event-related fMRI to separate epochs of WM tasks, this study differs in that it employs a methodology that does not make any a priori assumptions about the shape of the hemodynamic response (HDR). This is important because no one model of the HDR is valid across the range of activated brain regions and stimulus types. Systematic modeling inaccuracies may lead to the misattribution of activity to adjacent events. Twelve healthy subjects performed a numerical version of the Sternberg Item Recognition Paradigm adapted for rapid presentation event-related fMRI. This paradigm emphasized maintenance rather than manipulative WM processes and used a subcapacity WM load. WM trials with different delay lengths were compared to fixation. The HDR of the entire WM trial for each trial type was estimated using a finite impulse response (FIR). Regional activity associated with the Encode, Delay, and Probe epochs was identified using contrasts that were based on the FIR estimates and by examining the HDRs. Each epoch was associated with a distinct but overlapping pattern of regional activity. Activation of the dorsolateral prefrontal cortex, thalamus, and basal ganglia was exclusively associated with the probe. This suggests that frontostriatal neural circuitry participates in selecting an appropriate response based on the contents of WM.

Background Previous studies have shown that the activity of the amygdala is elevated in people experiencing clinical and subclinical levels of anxiety and depression (negative affect). It has been proposed that a reduction in inhibitory input to the amygdala from the prefrontal cortex and resultant over-activity of the amygdala underlies this association. Prior studies have found relationships between negative affect and 1) amygdala over-activity and 2) reduced amygdala-prefrontal connectivity. However, it is not known whether elevated amygdala activity is associated with decreased amygdala-prefrontal connectivity during negative affect states. Methods Here we used resting-state arterial spin labeling (ASL) and blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) in combination to test this model, measuring the activity (regional cerebral blood flow, rCBF) and functional connectivity (correlated fluctuations in the BOLD signal) of one subregion of the amygdala with strong connections with the prefrontal cortex, the basolateral nucleus (BLA), and subsyndromal anxiety levels in 38 healthy subjects. Results BLA rCBF was strongly correlated with anxiety levels. Moreover, both BLA rCBF and anxiety were inversely correlated with the strength of the functional coupling of the BLA with the caudal ventromedial prefrontal cortex. Lastly, BLA perfusion was found to be a mediator of the relationship between BLA-prefrontal connectivity and anxiety. Conclusions These results show that both perfusion of the BLA and a measure of its functional coupling with the prefrontal cortex directly index anxiety levels in healthy subjects, and that low BLA-prefrontal connectivity may lead to increased BLA activity and resulting anxiety. Thus, these data provide key evidence for an often-cited circuitry model of negative affect, using a novel, multi-modal imaging approach.

We have developed a model of BOLD-fMRI from first principles using from two-photon microscopic measurements of cerebrovascular physiology. The model was validated against experimental BOLD measurements at several levels.

To examine alterations in brain activation associated with pharmacologically induced memory impairment, we used functional MRI (fMRI) to study the effects of lorazepam and scopolamine on a face–name associative encoding paradigm. Ten healthy young subjects were scanned on four occasions, 2 weeks apart; they were administered i.v. saline during two placebo-scanning sessions and then alternately administered i.v. lorazepam (1 mg) or scopolamine (0.4 mg) in a double-blind, randomized, cross-over design. Both the extent and magnitude of activation within anatomic regions of interest (ROIs) were examined to determine the reproducibility of activation in the placebo sessions and the regional specificity of the pharmacologic effects. Activation within all ROIs was consistent across the two placebo scans during the encoding of novel face–name pairs (compared with visual fixation). With the administration of either lorazepam or scopolamine, significant decreases were observed in both the extent and magnitude of activation within the hippocampal, fusiform, and inferior prefrontal ROIs, but no significant alterations in activation in the striate cortex were found. Both medications impaired performance on postscan memory measures, and significant correlations between memory performance and extent of activation were found in hippocampal and fusiform ROIs. These findings suggest that pharmacologic effects can be detected with fMRI by using a reproducible experimental paradigm and that medications that impair memory also diminish activation in specific brain regions thought to subserve complex memory processes.

Exploratory (i.e., voxelwise) spatial methods are commonly used in neuroimaging to identify areas that show an effect when a region-of-interest (ROI) analysis cannot be performed because no strong a priori anatomical hypothesis exists. However, noise at a single voxel is much higher than noise in a ROI making noise management critical to successful exploratory analysis. This work explores how preprocessing choices affect the bias and variability of voxelwise kinetic modeling analysis of brain positron emission tomography (PET) data. These choices include the use of volume- or cortical surface-based smoothing, level of smoothing, use of voxelwise partial volume correction (PVC), and PVC masking threshold. PVC was implemented using the Muller-Gartner method with the masking out of voxels with low gray matter (GM) partial volume fraction. Dynamic PET scans of an antagonist serotonin-4 receptor radioligand ([11C]SB207145) were collected on sixteen healthy subjects using a Siemens HRRT PET scanner. Kinetic modeling was used to compute maps of non-displaceable binding potential (BPND) after preprocessing. The results showed a complicated interaction between smoothing, PVC, and masking on BPND estimates. Volume-based smoothing resulted in large bias and intersubject variance because it smears signal across tissue types. In some cases, PVC with volume smoothing paradoxically caused the estimated BPND to be less than when no PVC was used at all. When applied in the absence of PVC, cortical surface-based smoothing resulted in dramatically less bias and the least variance of the methods tested for smoothing levels 5 mm and higher. When used in combination with PVC, surface-based smoothing minimized the bias without significantly increasing the variance. Surface-based smoothing resulted in 2–4 times less intersubject variance than when volume smoothing was used. This translates into more than 4 times fewer subjects needed in a group analysis to achieve similarly powered statistical tests. Surface-based smoothing has less bias and variance because it respects cortical geometry by smoothing the PET data only along the cortical ribbon and so does not contaminate the GM signal with that of white matter and cerebrospinal fluid. The use of surface-based analysis in PET should result in substantial improvements in the reliability and detectability of effects in exploratory PET analysis, with or without PVC.

A neural model is described of how the brain may autonomously learn a body-centered representation of a three-dimensional (3-D) target position by combining information about retinal target position, eye position, and head position in real time. Such a body-centered spatial representation enables accurate movement commands to the limbs to be generated despite changes in the spatial relationships between the eyes, head, body, and limbs through time. The model learns a vector representation—otherwise known as a parcellated distributed representation—of target vergence with respect to the two eyes, and of the horizontal and vertical spherical angles of the target with respect to a cyclopean egocenter. Such a vergence-spherical representation has been reported in the caudal midbrain and medulla of the frog, as well as in psychophysical movement studies in humans. A head-centered vergence-spherical representation of foveated target position can be generated by two stages of opponent processing that combine corollary discharges of outflow movement signals to the two eyes. Sums and differences of opponent signals define angular and vergence coordinates, respectively. The head-centered representation interacts with a binocular visual representation of nonfoveated target position to learn a visuomotor representation of both foveated and nonfoveated target position that is capable of commanding yoked eye movements. This head-centered vector representation also interacts with representations of neck movement commands to learn a body-centered estimate of target position that is capable of Commanding coordinated arm movements. Learning occurs during head movements made while gaze remains fixed on a foveated target. An initial estimate is stored and a VOR-mediated gating signal prevents the stored estimate from being reset during a gaze-maintaining head movement. As the head moves, new estimates are compared with the stored estimate to compute difference vectors which act as error signals that drive the learning process, as well as control the on-line merging of multimodal information.

Schizophrenia patients show significant subcortical brain abnormalities. We examined these abnormalities using automated image analysis software and provide effect size estimates for prospective multi-scanner schizophrenia studies. Subcortical and intracranial volumes were obtained using FreeSurfer 5.0.0 from high-resolution structural imaging scans from 186 schizophrenia patients (mean age±S.D.=38.9±11.6, 78% males) and 176 demographically similar controls (mean age±S.D.=37.5±11.2, 72% males). Scans were acquired from seven 3-Tesla scanners. Univariate mixed model regression analyses compared between-group volume differences. Weighted mean effect sizes (and number of subjects needed for 80% power at α=0.05) were computed based on the individual single site studies as well as on the overall multi-site study. Schizophrenia patients have significantly smaller intracranial, amygdala, and hippocampus volumes and larger lateral ventricle, putamen and pallidum volumes compared with healthy volunteers. Weighted mean effect sizes based on single site studies were generally larger than effect sizes computed based on analysis of the overall multi-site sample. Prospectively collected structural imaging data can be combined across sites to increase statistical power for meaningful group comparisons. Even when using similar scan protocols at each scanner, some between-site variance remains. The multi-scanner effect sizes provided by this study should help in the design of future multi-scanner schizophrenia imaging studies.

Among brain functions, language is one of the most lateralized. Cortical language areas are also some of the most asymmetrical in the brain. An open question is whether the asymmetry in function is linked to the asymmetry in anatomy. To address this question, we measured anatomical asymmetry in 34 participants shown with fMRI to have language dominance of the left hemisphere (LLD) and 21 participants shown to have atypical right hemisphere dominance (RLD). All participants were healthy and left-handed, and most (80%) were female. Gray matter (GM) volume asymmetry was measured using an automated surface-based technique in both ROIs and exploratory analyses. In the ROI analysis, a significant difference between LLD and RLD was found in the insula. No differences were found in planum temporale (PT), pars opercularis (POp), pars triangularis (PTr), or Heschl's gyrus (HG). The PT, POp, insula, and HG were all significantly left lateralized in both LLD and RLD participants. Both the positive and negative ROI findings replicate a previous study using manually labeled ROIs in a different cohort [Keller, S. S., Roberts, N., Garcia-Finana, M., Mohammadi, S., Ringelstein, E. B., Knecht, S., et al. Can the language-dominant hemisphere be predicted by brain anatomy? Journal of Cognitive Neuroscience, 23, 2013–2029, 2011]. The exploratory analysis was accomplished using a new surface-based registration that aligns cortical folding patterns across both subject and hemisphere. A small but significant cluster was found in the superior temporal gyrus that overlapped with the PT. A cluster was also found in the ventral occipitotemporal cortex corresponding to the visual word recognition area. The surface-based analysis also makes it possible to disentangle the effects of GM volume, thickness, and surface area while removing the effects of curvature. For both the ROI and exploratory analyses, the difference between LLD and RLD volume laterality was most strongly driven by differences in surface area and not cortical thickness. Overall, there were surprisingly few differences in GM volume asymmetry between LLD and RLD indicating that gross morphometric asymmetry is only subtly related to functional language laterality.

Objective: In Alzheimer’s FDG PET research, the choice of reference region for normalization and use of partial volume correction are inconsistent and have not been studied in a large multi-center study. Herein, we identified which normalization region provided the highest degree of discrimination between subjects who were classified as normal aging, mild cognitive impairment, or Alzheimer’s disease. The effects of partial volume correction using either a gray matter mask or cortical thickness and subcortical volume residuals were also examined. Methods: Stepwise logistic regression models were used to identify the optimal normalization region and partial volume correction method to discriminate between disease stages in over 400 subjects from research sites across North America. Normalization region candidates were the brainstem, precentral gyrus, postcentral gyrus, cerebellum, and thalamus. Partial volume correction methods tested were anatomically or statistically based. Results: Pre- and post- central gyri, and the thalamus showed AD-related changes in FDG PET and did not qualify for further testing. Normalizing to the cerebellum while using the gray matter mask for partial volume correction provided the highest indicator of discrimination. Conclusions: Normalization region and partial volume correction are critical to FDG PET analysis and candidate normalization regions should be tested for disease effects in the study sample prior to use. Cerebellar normalization and gray matter mask partial volume correction are recommended for use with the ADNI dataset.

The term space-variant vision was introduced in the late 1980s to refer to sensor architectures based on a smooth variation of resolution across the workspace, like that of the human visual system. The use of such sensor architectures is rapidly becoming an important factor in machine vision in which the constraints of size weight, cost and performance must be jointly optimized. The structure of this paper consists of four parts. A review of the four generic architectures for vision will be presented, providing a context for the term “ active vision”, and a justification for the importance, and the connection between, space-variant architectures and active vision methods. A brief quantitative review of the specific space-variant properties of primate visual cortex topography will be provided, in the cortex of sensor design. The engineering and algorithmic problems that are associated with exploiting space-variant systems will be stated. Examples of several recently constructed miniature space-variant active vision systems will be briefly reviewed, along with a brief discussion of solutions to the basic problem areas in space-variant vision.

This study examined the cortical representation of vibrotactile detection in humans using event-related fMRI paired with psychophysics. Suprathreshold vibrotactile stimulation activated several areas, including primary (SI) and second somatosensory cortices (SII/PV). For threshold-level stimuli, poststimulus activity in contralateral and ipsilateral SII/PV was the best correlate of detection success. In these areas, evoked signals on hit trials were significantly greater than on missed trials in all participants, and the relative activity level across stimulation amplitudes matched perceptual performance. Activity in the anterior insula and superior temporal gyrus also correlated with hits and misses, suggesting that a “ventral stream” of somatosensory representations may play a crucial role in detection. In contrast, poststimulus activity in Area SI was not well correlated with perception and showed an overall negative response profile for threshold-level stimulation. A different correlate of detection success was, however, observed in SI. Activity in this representation immediately before stimulus onset predicted performance, a finding that was unique to SI. These findings emphasize the potential role of SII/PV in detection, the importance of state dynamics in SI for perception, and the possibility that changes in the temporal and spatial pattern of SI activity may be essential to the optimal representation of threshold-level stimuli for detection.

Structural analysis of MRI data on the cortical surface usually focuses on cortical thickness. Cortical surface area, when considered, has been measured only over gross regions or approached indirectly via comparisons with a standard brain. Here we demonstrate that direct measurement and comparison of the surface area of the cerebral cortex at a fine scale is possible using mass conservative interpolation methods. We present a framework for analyses of the cortical surface area, as well as for any other measurement distributed across the cortex that is areal by nature. The method consists of the construction of a mesh representation of the cortex, registration to a common coordinate system and, crucially, interpolation using a pycnophylactic method. Statistical analysis of surface area is done with power-transformed data to address lognormality, and inference is done with permutation methods. We introduce the concept of facewise analysis, discuss its interpretation and potential applications.

In functional magnetic resonance imaging (fMRI), the blood oxygenation level dependent (BOLD) signal is often interpreted as a measure of neural activity. However, because the BOLD signal reflects the complex interplay of neural, vascular, and metabolic processes, such an interpretation is not always valid. There is growing evidence that changes in the baseline neurovascular state can result in significant modulations of the BOLD signal that are independent of changes in neural activity. This paper introduces some of the normalization and calibration methods that have been proposed for making the BOLD signal a more accurate reflection of underlying brain activity for human fMRI studies.

Near-infrared spectroscopy (NIRS) signals have been shown to correlate with resting-state BOLD-fMRI data across the whole brain volume, particularly at frequencies below 0.1 Hz. While the physiological origins of this correlation remain unclear, its existence may have a practical application in minimizing the background physiological noise present in BOLD-fMRI recordings. We performed simultaneous, resting-state fMRI and 28-channel NIRS in seven adult subjects in order to assess the utility of NIRS signals in the regression of physiological noise from fMRI data. We calculated the variance of the residual error in a general linear model of the baseline fMRI signal, and the reduction of this variance achieved by including NIRS signals in the model. In addition, we introduced a sequence of simulated hemodynamic response functions (HRFs) into the resting-state fMRI data of each subject in order to quantify the effectiveness of NIRS signals in optimizing the recovery of that HRF. For comparison, these calculations were also performed using a pulse and respiration RETROICOR model. Our results show that the use of 10 or more NIRS channels can reduce variance in the residual error by as much as 36% on average across the whole cortex. However the same number of low-pass filtered white noise regressors is shown to produce a reduction of 19%. The RETROICOR model obtained a variance reduction of 6.4%. Our HRF simulation showed that the mean-squared error (MSE) between the recovered and true HRFs is reduced by 21% on average when 10 NIRS channels are applied and by introducing an optimized time lag between the NIRS and fMRI time series, a single NIRS channel can provide an average MSE reduction of 14%. The RETROICOR model did not provide a significant change in MSE. By each of the metrics calculated, NIRS recording is shown to be of significant benefit to the regression of low-frequency physiological noise from fMRI data.

Near-Infrared Spectroscopy (NIRS) allows the recovery of cortical oxy- and deoxyhemoglobin changes associated with evoked brain activity. NIRS is a back-reflection measurement making it very sensitive to the superficial layers of the head, i.e. the skin and the skull, where systemic interference occurs. As a result, the NIRS signal is strongly contaminated with systemic interference of superficial origin. A recent approach to overcome this problem has been the use of additional short source-detector separation optodes as regressors. Since these additional measurements are mainly sensitive to superficial layers in adult humans, they can be used to remove the systemic interference present in longer separation measurements, improving the recovery of the cortical hemodynamic response function (HRF). One question that remains to answer is whether or not a short separation measurement is required in close proximity to each long separation NIRS channel. Here, we show that the systemic interference occurring in the superficial layers of the human head is inhomogeneous across the surface of the scalp. As a result, the improvement obtained by using a short separation optode decreases as the relative distance between the short and the long measurement is increased. NIRS data was acquired on 6 human subjects both at rest and during a motor task consisting of finger tapping. The effect of distance between the short and the long channel was first quantified by recovering a synthetic hemodynamic response added over the resting-state data. The effect was also observed in the functional data collected during the finger tapping task. Together, these results suggest that the short separation measurement must be located as close as 1.5 cm from the standard NIRS channel in order to provide an improvement which is of practical use. In this case, the improvement in Contrast-to-Noise Ratio (CNR) compared to a standard General Linear Model (GLM) procedure without using any small separation optode reached 50% for HbO and 100% for HbR. Using small separations located farther than 2 cm away resulted in mild or negligible improvements only.

An increasing number of studies use functional MRI (fMRI) and blood oxygen level-dependent (BOLD) signal to investigate the neurofunctional basis of acute alcohol effects on the brain. However, the BOLD signal reflects neural activity only indirectly as it depends on regional hemodynamic changes and is therefore sensitive to vasoactive substances, such as alcohol. We used MRI-based pulsed arterial spin labeling (ASL) method to quantify effects of acute intoxication on resting cerebral perfusion. Gender effects have not been previously examined and yet they are of particular interest given the differences in hormonal dynamics, alcohol metabolism, and hemodynamic regulation. Nineteen young, healthy individuals (nine women) with no personal or familial alcohol- or drug-related problems served as their own controls by participating in both alcohol (0.6g/kg ethanol for men, 0.55g/kg for women) and placebo scanning sessions in a counterbalanced manner. Regionally specific effects of the moderate alcohol dose on gray matter perfusion were examined with voxel-wise and region-of-interest analyses suggesting an interaction between gender and alcohol beverage. Acute intoxication increased perfusion in bilateral frontal regions in men but not in women. Under placebo, stronger cortical perfusion was observed in women compared with men primarily in the left hemisphere in frontal, parietal, and temporal areas. These results emphasize gender differences and regional specificity of alcohol's effects of cerebral perfusion possibly because of interactive influences on hormonal, metabolic, and hemodynamic autoregulatory systems. Alcohol-induced perfusion increase correlated positively with impulsivity/antisocial tendencies, consistent with dopaminergic mediation of reward, and its effects on cortical perfusion. Additional ASL studies are needed to investigate dose- and time-dependent effects of alcohol intoxication and gender on the hemodynamic factors that conjointly influence BOLD signal to disambiguate the vascular/metabolic mechanisms from the neurally based changes.

This article describes how corollary discharges from outflow eye movement commands can be transformed by two stages of opponent neural processing into a head-centered representation of 3-D target position. This representation implicitly defines a cyclopean coordinate system whose variables approximate the binocular vergence and spherical horizontal and vertical angles with respect to the observer's head. Various psychophysical data concerning binocular distance perception and reaching behavior are clarified by this representation. The representation provides a foundation for learning head-centered and body-centered invariant representations of both foveated and non-foveated 3-D target positions. It also enables a solution to be developed of the classical motor equivalence problem, whereby many different joint configurations of a redundant manipulator can all be used to realize a desired trajectory in 3-D space.

A neural network model is described for how an invariant head-centered representation of 3-D target position can be autonomously learned by the brain in real time. Once learned, such a target representation may be used to control both eye and limb movements. The target representation is derived from the positions of both eyes in the head, and the locations which the target activates on the retinas of both eyes. A Vector Associative Map (VAM) learns the many-to-one transformation from multiple combinations of eye-and-retinal position to invariant 3-D target position. Eye position is derived from outflow movement signals to the eye muscles. Two successive stages of opponent processing convert these corollary discharges into a head-centered representation that closely approximates the azimuth, elevation, and vergence of the eyes' gaze position with respect to a cyclopean origin located between the eyes. VAM learning combines this cyclopean representation of present gaze position with binocular retinal information about target position into an invariant representation of 3-D target position with respect to the head. VAM learning can use a teaching vector that is externally derived from the positions of the eyes when they foveate the target. A VAM can also autonomously discover and learn the invariant representation, without an explicit teacher, by generating internal error signals from environmental fluctuations in which these invariant properties are implicit. VAM error signals are computed by Difference Vectors (DVs) that are zeroed by the VAM learning process. VAMs may be organized into VAM Cascades for learning and performing both sensory-to-spatial maps and spatial-to-motor maps. These multiple uses clarify why DV-type properties are computed by cells in the parietal, frontal, and motor cortices of many mammals. VAMs are modulated by gating signals that express different aspects of the will-to-act. These signals transform a single invariant representation into movements of different speed (GO signal) and size (GRO signal), and thereby enable VAM controllers to match a planned action sequence to variable environmental conditions.

Cortical subpial demyelination is frequent in multiple sclerosis (MS) and is closely associated with disease progression and poor neurological outcome. Although cortical lesions have been difficult to detect using conventional MRI, preliminary data using T2*-weighted imaging at ultra-high field 7T MRI showed improved sensitivity for detecting and categorizing different histological types of cortical MS lesions. In this study we combined high-resolution 7T MRI with a surface-based analysis technique to quantify and map subpial T2*-weighted signal changes in seventeen patients with MS. We applied a robust method to register 7T data with the reconstructed cortical surface of each individual and used a general linear model to assess in vivo an increase in subpial T2*-weighted signal in patients versus age-matched controls, and to investigate the spatial distribution of cortical subpial changes across the cortical ribbon. We also assessed the relationship between subpial T2* signal changes at 7T, Expanded Disability Status Scale (EDSS) score and white matter lesion load (WMLL). Patients with MS showed significant T2*-weighted signal increase in the frontal lobes (parsopercularis, precentral gyrus, middle and superior frontal gyrus, orbitofrontal cortex), anterior cingulate, temporal (superior, middle and inferior temporal gyri), and parietal cortices (superior and inferior parietal cortex, precuneus), but also in occipital regions of the left hemisphere. We found significant correlations between subpial T2*-weighted signal and EDSS score in the precentral gyrus (R=0.56, P=0.02) and between T2*-weighted signal and WMLL in the lateral orbitofrontal, superior parietal, cuneus, precentral and superior frontal regions. Our data support the presence of disseminated subpial increases in T2* signal in subjects with MS, which may reflect the diffuse subpial pathology described in neuropathology.

Investigators perform multi-site functional magnetic resonance imaging studies to increase statistical power, to enhance generalizability, and to improve the likelihood of sampling relevant subgroups. Yet undesired site variation in imaging methods could off-set these potential advantages. We used variance components analysis to investigate sources of variation in the blood oxygen level-dependent (BOLD) signal across four 3-T magnets in voxelwise and region-of-interest (ROI) analyses. Eighteen participants traveled to four magnet sites to complete eight runs of a working memory task involving emotional or neutral distraction. Person variance was more than 10 times larger than site variance for five of six ROIs studied. Person-by-site interactions, however, contributed sizable unwanted variance to the total. Averaging over runs increased between-site reliability, with many voxels showing good to excellent between-site reliability when eight runs were averaged and regions of interest showing fair to good reliability. Between-site reliability depended on the specific functional contrast analyzed in addition to the number of runs averaged. Although median effect size was correlated with between-site reliability, dissociations were observed for many voxels. Brain regions where the pooled effect size was large but between-site reliability was poor were associated with reduced individual differences. Brain regions where the pooled effect size was small but between-site reliability was excellent were associated with a balance of participants who displayed consistently positive or consistently negative BOLD responses. Although between-site reliability of BOLD data can be good to excellent, acquiring highly reliable data requires robust activation paradigms, ongoing quality assurance, and careful experimental control.

Prior work has demonstrated that the memory dysfunction of Alzheimer’s disease (AD) is accompanied by marked cortical pathology in medial temporal lobe (MTL) gray matter. In contrast, changes in white matter (WM) of pathways associated with the MTL have rarely been studied. We used diffusion tensor imaging (DTI) to examine regional patterns of WM tissue changes in individuals with AD. Alterations of diffusion properties with AD were found in several regions including parahippocampal WM, and in regions with direct and secondary connections to the MTL. A portion of the changes measured, including effects in the parahippocampal WM, were independent of gray matter degeneration as measured by hippocampal volume. Examination of regional changes in unique diffusion parameters including anisotropy and axial and radial diffusivity demonstrated distinct zones of alterations, potentially stemming from differences in underlying pathology, with a potential myelin specific pathology in the parahippocampal WM. These results demonstrate that deterioration of neocortical connections to the hippocampal formation results in part from the degeneration of critical MTL and associated fiber pathways.

With sufficient image encoding, high-resolution fMRI studies are limited by the biological point-spread of the hemodynamic signal. The extent of this spread is determined by the local vascular distribution and by the spatial specificity of blood flow regulation, as well as by measurement parameters that (i) alter the relative sensitivity of the acquisition to activation-induced hemodynamic changes and (ii) determine the image contrast as a function of vessel size. In particular, large draining vessels on the cortical surface are a major contributor to both the BOLD signal change and to the spatial bias of the BOLD activation away from the site of neuronal activity. In this work, we introduce a laminar surface-based analysis method and study the relationship between spatial localization and activation strength as a function of laminar depth by acquiring 1 mm isotropic, single-shot EPI at 7 T and sampling the BOLD signal exclusively from the superficial, middle, or deep cortical laminae. We show that highly-accelerated EPI can limit image distortions to the point where a boundary-based registration algorithm accurately aligns the EPI data to the surface reconstruction. The spatial spread of the BOLD response tangential to the cortical surface was analyzed as a function of cortical depth using our surface-based analysis. Although sampling near the pial surface provided the highest signal strength, it also introduced the most spatial error. Thus, avoiding surface laminae improved spatial localization by about 40% at a cost of 36% in z-statistic, implying that optimal spatial resolution in functional imaging of the cortex can be achieved using anatomically-informed spatial sampling to avoid large pial vessels.

Neuroimaging studies are facilitated significantly when it is possible to recruit subjects and acquire data at multiple sites. However, the use of different scanners and acquisition protocols is a potential source of variability in multi-site data. In this work we present a multi-site study of the reliability of fMRI activation indices, where 10 healthy volunteers were scanned at 4 different sites while performing a working memory paradigm. Our results indicate that, even with different scanner manufacturers and field strengths, activation variability due to site differences is small compared to variability due to subject differences in this cognitive task, provided we choose an appropriate activation measure.

Prior studies have focused on patterns of brain atrophy with aging and age-associated cognitive decline. It is possible that changes in neural tissue properties could provide an important marker of more subtle changes compared to gross morphometry. However, little is known about how MRI tissue parameters are altered in aging. We created cortical surface models of 148 individuals and mapped regional gray and white matter T1-weighted signal intensities from 3D MPRAGE images to examine patterns of age-associated signal alterations. Gray matter intensity was decreased with aging with strongest effects in medial frontal, anterior cingulate, and inferior temporal regions. White matter signal intensity decreased with aging in superior and medial frontal, cingulum, and medial and lateral temporal regions. The gray/white ratio (GWR) was altered throughout a large portion of the cortical mantle, with strong changes in superior and inferior frontal, lateral parietal, and superior temporal and precuneus regions demonstrating decreased overall contrast. Statistical effects of contrast changes were stronger than those of cortical thinning. These results demonstrate that there are strong regional changes in neural tissue properties with aging and tissue intensity measures may serve as an important biomarker of degeneration.

Introduction: Auditory hallucinations or voices are experienced by 75% of people diagnosed with schizophrenia. We presumed that auditory cortex of schizophrenia patients who experience hallucinations is tonically “tuned” to internal auditory channels, at the cost of processing external sounds, both speech and nonspeech. Accordingly, we predicted that patients who hallucinate would show less auditory cortical activation to external acoustic stimuli than patients who did not. Methods: At 9 Functional Imaging Biomedical Informatics Research Network (FBIRN) sites, whole-brain images from 106 patients and 111 healthy comparison subjects were collected while subjects performed an auditory target detection task. Data were processed with the FBIRN processing stream. A region of interest analysis extracted activation values from primary (BA41) and secondary auditory cortex (BA42), auditory association cortex (BA22), and middle temporal gyrus (BA21). Patients were sorted into hallucinators (n = 66) and nonhallucinators (n = 40) based on symptom ratings done during the previous week. Results: Hallucinators had less activation to probe tones in left primary auditory cortex (BA41) than nonhallucinators. This effect was not seen on the right. Discussion: Although “voices” are the anticipated sensory experience, it appears that even primary auditory cortex is “turned on” and “tuned in” to process internal acoustic information at the cost of processing external sounds. Although this study was not designed to probe cortical competition for auditory resources, we were able to take advantage of the data and find significant effects, perhaps because of the power afforded by such a large sample.

In normal humans, relationships between cognitive test performance and cortical structure have received little study, in part, because of the paucity of tools for measuring cortical structure. Computational morphometric methods have recently been developed that enable the measurement of cortical thickness from MRI data, but little data exist on their reliability. We undertook this study to evaluate the reliability of an automated cortical thickness measurement method to detect correlates of interest between thickness and cognitive task performance. Fifteen healthy older participants were scanned four times at 2-week intervals on three different scanner platforms. The four MRI data sets were initially treated independently to investigate the reliability of the spatial localization of findings from exploratory whole-cortex analyses of cortical thickness-cognitive performance correlates. Next, the first data set was used to define cortical ROIs based on the exploratory results that were then applied to the remaining three data sets to determine whether the relationships between cognitive performance and regional cortical thickness were comparable across different scanner platforms and field strengths. Verbal memory performance was associated with medial temporal cortical thickness, while visuomotor speed/set shifting was associated with lateral parietal cortical thickness. These effects were highly reliable - in terms of both spatial localization and magnitude of absolute cortical thickness measurements - across the four scan sessions. Brain-behavior relationships between regional cortical thickness and cognitive task performance can be reliably identified using an automated data analysis system, suggesting that these measures may be useful as imaging biomarkers of disease or performance ability in multicenter studies in which MRI data are pooled.

The ability to spontaneously recall recently learned information is a fundamental mnemonic activity of daily life, but has received little study using functional neuroimaging. We developed a functional MRI (fMRI) paradigm to study regional brain activity during encoding that predicts free recall. In this event-related fMRI study, ten lists of fourteen pictures of common objects were shown to healthy young individuals and regional brain activity during encoding was analyzed based on subsequent free recall performance. Free recall of items was predicted by activity during encoding in hippocampal, fusiform, and inferior prefrontal cortical regions. Within-subject variance in free recall performance for the ten lists was predicted by a linear combination of condition-specific inferior prefrontal, hippocampal, and fusiform activity. Recall performance was better for lists in which pre-frontal activity was greater for all items of the list and hippocampal and fusi-form activity were greater specifically for items that were recalled from the list. Thus, the activity of medial temporal, fusiform, and prefrontal brain regions during the learning of new information is important for the subsequent free recall of this information. These fronto-temporal brain regions act together as a large-scale memory-related network, the components of which make distinct yet interacting contributions during encoding that predict subsequent successful free recall performance.

Morphometric cerebral characteristics were studied in children with prenatal poly-substance exposure (n =14) compared to controls (n = 14) without such exposure. Ten of the substance exposed children were born to mothers who used opiates (heroin) throughout the pregnancy. Groups were compared across 16 brain measures: cortical gray matter, cerebral white matter, hippocampus, amygdala, thalamus, accumbens area, caudate, putamen, pallidum, brainstem, cerebellar cortex, cerebellar white matter, lateral ventricles, inferior lateral ventricles, and the 3rd and 4th ventricles. In addition, continuous measurement of thickness across the entire cortical mantle was performed. Volumetric characteristics were correlated with ability and questionnaire assessments 2 years prior to scan. Compared to controls, the substance-exposed children had smaller intracranial and brain volumes, including smaller cerebral cortex, amygdala, accumbens area, putamen, pallidum, brainstem, cerebellar cortex, cerebellar white matter, and inferior lateral ventricles, and thinner cortex of the right anterior cingulate and lateral orbitofrontal cortex. Pallidum and putamen appeared especially reduced in the subgroup exposed to opiates. Only volumes of the right anterior cingulate, the right lateral orbitofrontal cortex and the accumbens area, showed some association with ability and questionnaire measures. The sample studied is rare, and hence small, so conclusions cannot be drawn with certainty. Morphometric group differences were observed, but associations with previous behavioral assessment were generally weak. Some of the volumetric differences, particularly thinner cortex in part of the right lateral orbitofrontal cortex, may be moderately involved in cognitive and behavioral difficulties more frequently experienced by opiate and poly-substance exposed children.

Many pharmacological stimuli influence multiple neurotransmitter systems in the brain, and the dynamics of the functional brain response can vary regionally. In this study, the temporal response of cerebral blood volume (CBV) was employed to spatially segment cerebral effects due to infusion of a potent mu-opioid receptor agonist. Repeated intravenous injection of 10 μg/kg remifentanil in rats caused reproducible regional positive, negative, and biphasic changes in CBV. Three temporal processes were identified in the cerebral response and analyzed within the framework of the general linear model. Firstly, a slow component identified CBV changes that were almost exclusively negative, and the spatial distribution was similar to the inhibition produced by morphine (200 μg/kg). The largest CBV reductions occurred in caudate, accumbens, ventral hippocampus, cingulate, and piriform cortex. Secondly, a more rapid temporal component corresponded primarily with a regional distribution of positive changes in CBV consistent with GABAergic inhibition of hippocampal interneurons and associated projections. Thirdly, a response with the dynamics of mean arterial blood pressure correlated positively with CBV changes in hypothalamus, consistent with a central mechanism for control of blood pressure. We propose that the dominant source of the temporal variance in signal is dynamic modulation of drug targets by receptor endocytosis, an established effect in vitro. These results suggest that the temporal response of fMRI signal reflects underlying neurobiological processes, so that temporal decomposition strategies may aid interpretation of pharmacological mechanisms by identifying interconnected regions or those associated with common neural targets and processes.

The authors studied presymptomatic individuals with the Huntington disease (HD) mutation to determine whether cortical thinning was present. They found thinning that was regionally selective, semi-independent of striatal volume loss, and correlated with cognitive performance. Early, extensive cortical involvement occurs during the preclinical stages of HD.

Objective: To use fMRI to investigate whether hippocampal and entorhinal activation during learning is altered in the earliest phase of mild cognitive impairment (MCI). Methods: Three groups of older individuals were studied: 10 cognitively intact controls, 9 individuals at the mild end of the spectrum of MCI, and 10 patients with probable Alzheimer disease (AD). Subjects performed a face-name associative encoding task during fMRI scanning, and were tested for recognition of stimuli afterward. Data were analyzed using a functional-anatomic method in which medial temporal lobe (MTL) regions of interest were identified from each individual9s structural MRI, and fMRI activation was quantified within each region. Results: Significantly greater hippocampal activation was present in the MCI group compared to controls; there were no differences between these two groups in hippocampal or entorhinal volumes. In contrast, the AD group showed hippocampal and entorhinal hypoactivation and atrophy in comparison to controls. The subjects with MCI performed similarly to controls on the fMRI recognition memory task; patients with AD exhibited poorer performance. Across all 29 subjects, greater mean entorhinal activation was found in the subgroup of 13 carriers of the APOE e4 allele than in the 16 noncarriers. Conclusions: The authors hypothesize that there is a phase of increased medial temporal lobe activation early in the course of prodromal Alzheimer disease followed by a subsequent decrease as the disease progresses.