Functional network properties derived from wide-field calcium imaging differ with wakefulness and across cell type.

To improve 'bench-to-bedside' translation, it is integral that knowledge flows bidirectionally-from animal models to humans, and vice versa. This requires common analytical frameworks, as well as open software and data sharing practices. We share a new pipeline (and test dataset) for the preprocessing of wide-field optical fluorescence imaging data-an emerging mode applicable in animal models-as well as results from a functional connectivity and graph theory analysis inspired by recent work in the human neuroimaging field. The approach is demonstrated using a dataset comprised of two test-cases: (1) data from animals imaged during awake and anesthetized conditions with excitatory neurons labeled, and (2) data from awake animals with different genetically encoded fluorescent labels that target either excitatory neurons or inhibitory interneuron subtypes. Both seed-based connectivity and graph theory measures (global efficiency, transitivity, modularity, and characteristic path-length) are shown to be useful in quantifying differences between wakefulness states and cell populations. Wakefulness state and cell type show widespread effects on canonical network connectivity with variable frequency band dependence. Differences between excitatory neurons and inhibitory interneurons are observed, with somatostatin expressing inhibitory interneurons emerging as notably dissimilar from parvalbumin and vasoactive polypeptide expressing cells. In sum, we demonstrate that our pipeline can be used to examine brain state and cell-type differences in mesoscale imaging data, aiding translational neuroscience efforts. In line with open science practices, we freely release the pipeline and data to encourage other efforts in the community.

Substance use patterns in 9-10 year olds: Baseline findings from the adolescent brain cognitive development (ABCD) study.

BACKGROUND: The Adolescent Brain Cognitive Development ™ Study (ABCD Study®) is an open-science, multi-site, prospective, longitudinal study following over 11,800 9- and 10-year-old youth into early adulthood. The ABCD Study aims to prospectively examine the impact of substance use (SU) on neurocognitive and health outcomes. Although SU initiation typically occurs during teen years, relatively little is known about patterns of SU in children younger than 12. METHODS: This study aims to report the detailed ABCD Study® SU patterns at baseline (n = 11,875) in order to inform the greater scientific community about cohort's early SU. Along with a detailed description of SU, we ran mixed effects regression models to examine the association between early caffeine and alcohol sipping with demographic factors, externalizing symptoms and parental history of alcohol and substance use disorders (AUD/SUD). PRIMARY RESULTS: At baseline, the majority of youth had used caffeine (67.6 %) and 22.5 % reported sipping alcohol (22.5 %). There was little to no reported use of other drug categories (0.2 % full alcohol drink, 0.7 % used nicotine, <0.1 % used any other drug of abuse). Analyses revealed that total caffeine use and early alcohol sipping were associated with demographic variables (p's<.05), externalizing symptoms (caffeine p = 0002; sipping p = .0003), and parental history of AUD (sipping p = .03). CONCLUSIONS: ABCD Study participants aged 9-10 years old reported caffeine use and alcohol sipping experimentation, but very rare other SU. Variables linked with early childhood alcohol sipping and caffeine use should be examined as contributing factors in future longitudinal analyses examining escalating trajectories of SU in the ABCD Study cohort.

Baseline brain function in the preadolescents of the ABCD Study.

The Adolescent Brain Cognitive Development (ABCD) Study® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development.

Characterizing Attention with Predictive Network Models.

Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction.

Food image-induced brain activation is not diminished by insulin infusion.

BACKGROUND/OBJECTIVES: The obesity epidemic appears to be driven in large part by our modern environment inundated by food cues, which may influence our desire to eat. Although insulin decreases food intake in both animals and humans, the effect of insulin on motivation for food in the presence of food cues is not known. Therefore, the aim of this study was to evaluate the effect of an intravenous insulin infusion on the brain response to visual food cues, hunger and food craving in non-obese human subjects. SUBJECTS/METHODS: Thirty-four right-handed healthy non-obese subjects (19F/15M, age: 29±8 years.; BMI: 23.1±2.1 kg m-2) were divided in two groups matched by age and BMI; the insulin group (18 subjects) underwent a hyperinsulinemic-euglycemic-clamp, and the control group (16 subjects) received an intravenous saline infusion, while viewing high and low-calorie food and non-food pictures during a functional MRI scan. Motivation for food was determined via analog scales for hunger, wanting and liking ratings. RESULTS: Food images induced brain responses in the hypothalamus, striatum, amygdala, insula, ventromedial prefrontal cortex (PFC), dorsolateral PFC and occipital lobe (whole brain correction, P<0.05). Wanting (P<0.001) and liking (P<0.001) ratings were significantly higher for the food than the non-food images, but not different between insulin and saline infusion groups. Hunger ratings increased throughout the MRI scan and correlated with preference for high-calorie food pictures (r=0.70; P<0.001). However, neither brain activity nor food cravings were affected by hyperinsulinemia or hormonal status (leptin and ghrelin levels) (P=NS). CONCLUSIONS: Our data demonstrate that visual food cues induce a strong response in motivation/reward and cognitive-executive control brain regions in non-obese subjects, but that these responses are not diminished by hyperinsulinemia per se. These findings suggest that our modern food cue saturated environment may be sufficient to overpower homeostatic hormonal signals, and thus contribute to the current obesity epidemic.

Application of BOLD Magnetic Resonance Imaging for Evaluating Regional Volumetric Foot Tissue Oxygenation: A Feasibility Study in Healthy Volunteers.

OBJECTIVE/BACKGROUND: To evaluate the feasibility and repeatability of applying blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) in the feet to quantify regional dynamic changes in tissue oxygenation during proximal cuff occlusion and reactive hyperemia. METHODS: Ten healthy male subjects underwent BOLD and T1-weighted imaging of the feet on two separate occasions, using a 3-T scanner. Dynamic changes in BOLD signal intensity were assessed before and during proximal cuff occlusion of the thigh and during reactive hyperemia, and BOLD time course data were evaluated for the time-to-half ischemic minimum, minimum ischemic value, peak hyperemic value, time-to-peak hyperemia, time-to-half peak hyperemia, and end value. T1-weighted images were used for segmentation of volumes of interest (VOI) in anatomical regions of the foot (heel, toes, dorsal foot, medial and lateral plantar foot). Repeatability of vascular responses was assessed for each foot VOI using semiautomated image registration and quantification of serial BOLD images. RESULTS: The heel VOI demonstrated a significantly higher peak hyperemic response, expressed as percent change from baseline BOLD signal intensity, compared with all other VOIs of the foot (heel, 7.4 ± 1.2%; toes, 5.6 ± 0.8%; dorsal foot, 5.7 ± 1.6%; medial plantar, 5.6 ± 1.7%; lateral plantar, 5.6 ± 1.5% [p < .05]). Additionally, the lateral plantar VOI had a significantly lower terminal signal intensity value (i.e., end value) when compared with all foot VOIs (p < .05). BOLD MRI was repeatable between visits in all foot VOIs, with no significant differences between study visits for any of the evaluated functional indices. CONCLUSION: BOLD MRI offers a repeatable technique for volumetric assessment of regional foot tissue oxygenation. Future application of BOLD imaging in the feet of patients with peripheral vascular disease may permit serial evaluation of regional tissue oxygenation and allow for improved assessment of therapeutic interventions targeting specific sites of the foot.

Groupwise whole-brain parcellation from resting-state fMRI data for network node identification.

In this paper, we present a groupwise graph-theory-based parcellation approach to define nodes for network analysis. The application of network-theory-based analysis to extend the utility of functional MRI has recently received increased attention. Such analyses require first and foremost a reasonable definition of a set of nodes as input to the network analysis. To date many applications have used existing atlases based on cytoarchitecture, task-based fMRI activations, or anatomic delineations. A potential pitfall in using such atlases is that the mean timecourse of a node may not represent any of the constituent timecourses if different functional areas are included within a single node. The proposed approach involves a groupwise optimization that ensures functional homogeneity within each subunit and that these definitions are consistent at the group level. Parcellation reproducibility of each subunit is computed across multiple groups of healthy volunteers and is demonstrated to be high. Issues related to the selection of appropriate number of nodes in the brain are considered. Within typical parameters of fMRI resolution, parcellation results are shown for a total of 100, 200, and 300 subunits. Such parcellations may ultimately serve as a functional atlas for fMRI and as such three atlases at the 100-, 200- and 300-parcellation levels derived from 79 healthy normal volunteers are made freely available online along with tools to interface this atlas with SPM, BioImage Suite and other analysis packages.

Orbitofrontal cortex neurofeedback produces lasting changes in contamination anxiety and resting-state connectivity.

Anxiety is a core human emotion but can become pathologically dysregulated. We used functional magnetic resonance imaging (fMRI) neurofeedback (NF) to noninvasively alter patterns of brain connectivity, as measured by resting-state fMRI, and to reduce contamination anxiety. Activity of a region of the orbitofrontal cortex associated with contamination anxiety was measured in real time and provided to subjects with significant but subclinical anxiety as a NF signal, permitting them to learn to modulate the target brain region. NF altered network connectivity of brain regions involved in anxiety regulation: subjects exhibited reduced resting-state connectivity in limbic circuitry and increased connectivity in the dorsolateral prefrontal cortex. NF has been shown to alter brain connectivity in other contexts, but it has been unclear whether these changes persist; critically, we observed changes in connectivity several days after the completion of NF training, demonstrating that such training can lead to lasting modifications of brain functional architecture. Training also increased subjects' control over contamination anxiety several days after the completion of NF training. Changes in resting-state connectivity in the target orbitofrontal region correlated with these improvements in anxiety. Matched subjects undergoing a sham feedback control task showed neither a reorganization of resting-state functional connectivity nor an improvement in anxiety. These data suggest that NF can enable enhanced control over anxiety by persistently reorganizing relevant brain networks and thus support the potential of NF as a clinically useful therapy.

The intrinsic connectivity distribution: a novel contrast measure reflecting voxel level functional connectivity.

Resting-state fMRI (rs-fMRI) holds promise as a clinical tool to characterize and monitor the phenotype of different neurological and psychiatric disorders. The most common analysis approach requires the definition of one or more regions-of-interest (ROIs). However this need for a priori ROI information makes rs-fMRI inadequate to survey functional connectivity differences associated with a range of neurological disorders where the ROI information may not be available. A second problem encountered in fMRI measures of connectivity is the need for an arbitrary correlation threshold to determine whether or not two areas are connected. This is problematic because in many cases the differences in tissue connectivity between disease groups and/or control subjects are threshold dependent. In this work we propose a novel voxel-based contrast mechanism for rs-fMRI, the intrinsic connectivity distribution (ICD), that neither requires a priori information to define a ROI, nor an arbitrary threshold to define a connection. We show the sensitivity of previous methods to the choice of connection thresholds and evaluate ICD using a survey study comparing young adults born prematurely to healthy term control subjects. Functional connectivity differences were found in hypothesized language processing areas in the left temporal-parietal areas. In addition, significant clinically-relevant differences were found between preterm and term control subjects, highlighting the importance of whole brain surveys independent of a priori information.

Resting functional connectivity between the hemispheres in childhood absence epilepsy.

OBJECTIVE: The fundamental mechanisms by which childhood absence epilepsy (CAE) changes neural networks even between seizures remain poorly understood. During seizures, cortical and subcortical networks exhibit bihemspheric synchronous activity based on prior EEG-fMRI studies. Our aim was to investigate whether this abnormal bisynchrony may extend to the interictal period, using a blood oxygen level-dependent (BOLD) resting functional connectivity approach. METHODS: EEG-fMRI data were recorded from 16 patients with CAE and 16 age- and gender-matched controls. Three analyses were performed. 1) Using 16 pairs of seizure-related regions of interest (ROI), we compared the between-hemisphere interictal resting functional connectivity of patients and controls. 2) For regions showing significantly increased interhemispheric connectivity in CAE, we then calculated connectivity to the entire brain. 3) A paired-voxel approach was performed to calculate resting functional connectivity between hemispheres without the constraint of predefined ROIs. RESULTS: We found significantly increased resting functional connectivity between hemispheres in the lateral orbitofrontal cortex of patients with CAE compared to normal controls. Enhanced between-hemisphere connectivity localized to the lateral orbitofrontal cortex was confirmed by all 3 analysis methods. CONCLUSIONS: Our results demonstrate abnormal increased connectivity between the hemispheres in patients with CAE in seizure-related regions, even when seizures were not occurring. These findings suggest that the lateral orbitofrontal cortex may play an important role in CAE pathophysiology, warranting further investigation. In addition, resting functional connectivity analysis may provide a promising biomarker to improve our understanding of altered brain function in CAE during the interictal period.

Simultaneous EEG, fMRI, and behavior in typical childhood absence seizures.

PURPOSE: Absence seizures cause transient impairment of consciousness. Typical absence seizures occur in children, and are accompanied by 3-4-Hz spike-wave discharges (SWDs) on electroencephalography (EEG). Prior EEG-functional magnetic resonance imaging (fMRI) studies of SWDs have shown a network of cortical and subcortical changes during these electrical events. However, fMRI during typical childhood absence seizures with confirmed impaired consciousness has not been previously investigated. METHODS: We performed EEG-fMRI with simultaneous behavioral testing in 37 children with typical childhood absence epilepsy (CAE). Attentional vigilance was evaluated by a continuous performance task (CPT), and simpler motor performance was evaluated by a repetitive tapping task (RTT). RESULTS: SWD episodes were obtained during fMRI scanning from 9 patients among the 37 studied. fMRI signal increases during SWDs were observed in the thalamus, frontal cortex, primary visual, auditory, somatosensory, and motor cortex, and fMRI decreases were seen in the lateral and medial parietal cortex, cingulate gyrus, and basal ganglia. Omission error rate (missed targets) with SWDs during fMRI was 81% on CPT and 39% on RTT. For those seizure epochs during which CPT performance was impaired, fMRI changes were seen in cortical and subcortical structures typically involved in SWDs, whereas minimal changes were observed for the few epochs during which performance was spared. DISCUSSION: These findings suggest that typical absence seizures involve a network of cortical-subcortical areas necessary for normal attention and primary information processing. Identification of this network may improve understanding of cognitive impairments in CAE, and may help guide development of new therapies for this disorder.

Graph-theory based parcellation of functional subunits in the brain from resting-state fMRI data.

Resting-state fMRI provides a method to examine the functional network of the brain under spontaneous fluctuations. A number of studies have proposed using resting-state BOLD data to parcellate the brain into functional subunits. In this work, we present two state-of-the-art graph-based partitioning approaches, and investigate their application to the problem of brain network segmentation using resting-state fMRI. The two approaches, the normalized cut (Ncut) and the modularity detection algorithm, are also compared to the Gaussian mixture model (GMM) approach. We show that the Ncut approach performs consistently better than the modularity detection approach, and it also outperforms the GMM approach for in vivo fMRI data. Resting-state fMRI data were acquired from 43 healthy subjects, and the Ncut algorithm was used to parcellate several different cortical regions of interest. The group-wise delineation of the functional subunits based on resting-state fMRI was highly consistent with the parcellation results from two task-based fMRI studies (one with 18 subjects and the other with 20 subjects). The findings suggest that whole-brain parcellation of the cortex using resting-state fMRI is feasible, and that the Ncut algorithm provides the appropriate technique for this task.

Error-specific medial cortical and subcortical activity during the stop signal task: a functional magnetic resonance imaging study.

The ability to detect errors and adjust behavior accordingly is essential for maneuvering in an uncertain environment. Errors are particularly prone to occur when multiple, conflicting responses are registered in a situation that requires flexible behavioral outputs. Previous studies have provided evidence indicating the importance of the medial cortical brain regions including the cingulate cortex in processing conflicting information. However, conflicting situations can be successfully resolved, or lead to errors, prompting a behavioral change in the observers. In particular, how does the brain use error signals specifically to adjust behavior on the fly? Here we employ a stop signal task (SST) to elicit errors approximately half of the time in high-conflict trials despite constant behavioral adjustment of the observers. Using functional magnetic resonance imaging, we show greater and, sequentially, less activation in the medial cortical regions when observers made an error, compared with when they successfully resolved high-conflict responses. Errors also evoked greater activity in the cuneus, retrosplenial cortex, insula, and subcortical structures including the thalamus and the region of the epithalamus (the habenula). We further showed that the error-related medial cortical activities are not correlated with post-error behavioral adjustment, as indexed by post-error slowing (PES) in go trial reaction time. These results delineate an error-specific pattern of brain activation during the SST. The results also suggest that the relationship between error-related activity and post-error behavioral adjustment may be more complicated than has been conceptualized by the conflict monitoring hypothesis.

VASO-based calculations of CBV change: accounting for the dynamic CSF volume.

The goal of the vascular space occupancy (VASO) imaging technique is to use selective nulling of the blood signal to infer relative changes in cerebral blood volume (CBV). In accordance with recent work, we show that changes in the local CSF fraction (x(c)) with activation can significantly impact the VASO signal, thereby limiting our ability to infer DeltaCBV from DeltaVASO alone. Here we calculate CBV change using a VASO-based method which ACcounts for the Dynamic Cerebrospinal (ACDC) fluid fraction. By combining data from two separate VASO acquisitions that eliminate either the blood signal (VASO(b)) or the CSF signal (VASO(c)), a nonlinear least-squares optimization may then be used to simultaneously solve for the relative changes in CBV and CSF with activation. The method is applied across the whole brain during a breath-holding task, offering insight into the relationship between changes in CBV and x(c) associated with global vasodilatation. Calculations of mean changes in CBV in different volumes of interest obtained from the proposed method compare much better with previous (gold-standard) PET data than traditional VASO methods that do not account for a nonzero Deltax(c) with activation. This confirms the necessity of incorporating the dynamic CSF volume into VASO-based calculations of DeltaCBV.

Applications and limitations of whole-brain MAGIC VASO functional imaging.

This work extends the multiple acquisitions with global inversion cycling vascular space occupancy (MAGIC VASO) method to human whole-brain functional magnetic resonance imaging (fMRI) at 3.0 Tesla and demonstrates the need to consider the dynamic contribution of cerebrospinal fluid (CSF) to the relative VASO signal change (DeltaVASO/VASO). Simulations were performed to determine the optimal slice number between global inversions, and correction factors were obtained to account for incomplete blood nulling in particular slices. The necessity of an accurate estimate of resting cerebral blood volume (CBV(rest)) is discussed in the context of DeltaCBV/CBV calculations. A three-compartment model is proposed to include both the resting and changing fractional CSF contribution (x(c,rest) and Deltax(c), respectively) to DeltaVASO/VASO. A MAGIC VASO sequence that provides whole-brain coverage is demonstrated using a paradigm comprised of visual, motor, and auditory stimulation. Activated regions are quantitatively compared in the corresponding blood oxygenation level-dependent (BOLD) images. Estimates of the minimum DeltaCBV/CBV resulting from motor and visual stimulation were comparable to previous findings at 17 +/- 8% (N = 8) and 19 +/- 9% (N = 6), respectively. The absence of VASO activation for auditory stimulation and evidence of activation-induced decreases in CSF volume fraction around the insula and superior temporal gyrus support the possibility of a Deltax(c) contribution to the VASO signal. Without specific knowledge of the CSF components (x(c,rest) and Deltax(c)), inference of DeltaCBV/CBV from DeltaVASO/VASO is severely limited.

Spatial resolution, signal-to-noise ratio, and smoothing in multi-subject functional MRI studies.

Functional MRI is aimed at localizing cortical activity to understand the role of specific cortical regions, providing insight into the neurophysiological underpinnings of brain function. Scientists developing fMRI methodology seek to improve detection of subtle activations and to spatially localize these activations more precisely. Except for applications in the clinical environment, such as functional mapping in patients prior to neurosurgical intervention, most basic neuroscience studies involve group level random-effects analyses. Prior to grouping data, the data from each individual are typically smoothed. A wide range of motivations for smoothing have been given including to match the spatial scale of hemodynamic responses, to normalize the error distribution (by the Central Limit Theorem) to improve the validity of inferences based on parametric tests, and, in the context of inter-subject averaging smoothing has been shown necessary to project the data down to a scale where homologies in functional anatomy are expressed across subjects. This work demonstrates that, for single-subject studies, if smoothing is to be employed, the data should be acquired at lower resolutions to maximize SNR. The benefits of a low-resolution acquisition are limited by partial volume effects and by the weak impact of resolution-dependent noise on the overall group level statistics. Given that inter-subject noise dominates across a range of tasks, improvements in within-subject noise, through changes in acquisition strategy or even moving to higher field strength, may do little to improve group statistics. Such improvements however may greatly impact single-subject studies such as those used in neurosurgical planning.

Amygdala responsiveness is modulated by tryptophan hydroxylase-2 gene variation.

The tryptophan hydroxylase-2 gene (TPH2) codes for the enzyme of serotonin (5-HT) synthesis in the brain and variation of TPH2 has been implicated in disorders of emotion regulation. Here, we used functional magnetic resonance imaging (fMRI) to demonstrate that a potentially functional variant of TPH2 modulates amygdala responsiveness to emotional stimuli of both negative and positive valence.

Neural correlates of temporal-order judgments versus those of spatial-location: deactivation of hippocampus may facilitate spatial performance.

The retrieval of temporal-order versus spatial-location information was investigated using fMRI. The primary finding in the hippocampus proper, seen in region of interest analyses, was an increase in BOLD signal intensity for temporal retrieval, and a decrease in signal intensity for spatial retrieval, relative to baseline. The negative BOLD signal change with spatial memory processing, while unexpected, is consistent with the recent fMRI literature indicating decreased BOLD can be associated with neuronal activation, and it is argued that the deactivation observed here may facilitate spatial performance. Spatial-location judgments also yielded a stronger (positive) response in the right midfrontal gyrus, while temporal-order judgments (autobiographic condition only) showed greater activity in the left superior temporal gyrus, suggesting greater working memory demands and greater semantization for each judgment type, respectively. Finally, all conditions activated the left midfrontal gyrus, although autobiographic memories showed additional activity in the medial frontal gyrus.

Functional MRI of language processing: dependence on input modality and temporal lobe epilepsy.

PURPOSE: Functional magnetic resonance imaging (MRI) using two language-comprehension tasks was evaluated to determine its ability to lateralize language processing and identify regions that must be spared in surgery. METHODS: Two parallel cognitive language tasks, one using auditory input and the other visual input, were tested in a group of control subjects and in temporal lobe epilepsy patients who were candidates for surgical intervention. The patient studies provide an opportunity to compare functional MRI language localization with that obtained using Wada testing and electrocorticography. All of the patients in this study underwent all three procedures and a battery of neuropsychological testing. Such studies provide an opportunity not only to validate the fMRI findings but also, by comparing the patient results with those obtained in control subjects, to provide insight into the impact of a pathology such as epilepsy on cortical organization or functional patterns of activation. RESULTS: The results reveal both modality-dependent and modality-independent language-processing patterns for visual versus auditory task presentation. The visual language task activated distinct sites in Broca's area, BA (Brodmann area) 44 that were not activated in the auditory language task. The auditory language task strongly activated contralateral right BA22-21 area (homologous to Wernicke's area on the left). Language lateralization scores were significantly stronger for visual than for auditory task presentation. The conjunction of activation from the two different input modalities (modality-independent areas) likely highlights regions that perform more abstract computations (e.g., syntactic or pragmatic processing) in language processing. Modality-specific areas (e.g., right Wernicke, left fusiform gyrus, Broca BA44, supramarginal gyrus), appear to cope with the computations relevant to making contact with these more abstract dimensions. Patients showed recruitment of contralateral homologous language areas (p < 0.005) that was significantly above that found in a normal control group. Extra- and intraoperative cortical stimulations were concordant with the fMRI data in eight of 10 cases. The fMRI lateralization scores were also consistent with the Wada testing in 8/10 patients. CONCLUSIONS: The fMRI results demonstrate that the epileptic brain may be a progressive model for cortical plasticity.

Repetition time in echo planar functional MRI.

To date, surprisingly little attention has been directed toward determining the optimum TR in a functional imaging experiment. A survey of the literature reveals a wide range of TRs, but little justification for a specific TR. Long-TR functional imaging experiments provide maximum signal-to-noise ratio (SNR) in the raw images; allow for the collection of a large number of slice locations; and decrease the size of the data set acquired, simplifying storage and handling. This work, however, demonstrates that long-TR imaging sacrifices statistical power when the paradigm timing is held fixed. That is, for a fixed-run duration consisting of multiple activation/control blocks, shorter TR acquisitions (on the order of 1000 ms) provide better discrimination between the activated and nonactivated brain tissue regions than do long-TR acquisitions (on the order of 4000 ms). Results are shown for modeling the functional imaging experiment and for three different paradigms performed on normal subjects.