Andrew R. Mayer

YNICL Journal 2025 Journal Article

A one year longitudinal study of cortical myelination changes following pediatric mild traumatic brain injury

• Jessica R. McQuaid
• Tracey V. Wick
• Josef Ling
• Andrew B. Dodd
• Divyasree Sasi Kumar
• Upasana Nathaniel
• Samuel D. Miller
• Vadim Zotev

The impact of pediatric mild traumatic brain injury (pmTBI) on cortical (i. e. , grey matter) myelination is not yet understood, especially for interactions with neurodevelopment. The current study examined the impact of pmTBI on cortical myelination relative to healthy controls (HC) by estimating myelin content using the T1w/T2w ratio method. Data were obtained from pmTBI (N = 217) participants at approximately 7 days (Visit 1 [V1]), 4 months (Visit 2 [V2]), and 1 year (Visit 3 [V3]) post-injury, with equivalent sampling points for age and sex-matched HC (N = 180). Clinical results suggested only partial recovery from post-concussive symptoms from V1 to V3, with similar incomplete recovery of sleep, functional outcomes, behavior, and long-term memory. Myelin content increased with chronological age and as a function of individual aging across study visits in a hemisphere specific fashion (left > right), most visibly within the posterior parietal lobe. Myelin content was also greater for females relative to males. There was evidence of both a reduction in myelination within the posterior parietal cortex for the pmTBI group at 4 months post-injury, as well as evidence of increased myelination within the left prefrontal cortex at one-year post-injury. However, neither of these findings survived various sensitivity analyses, suggesting that there were minimal effects of pmTBI on cortical myelin content in general. In summary, although rapid changes in myelin content existed as a function of neurodevelopment, there was little evidence to suggest that pmTBI permanently altered cortical myelin development trajectories.

YNIMG Journal 2024 Journal Article

Dynamic Functional Connectivity in Pediatric Mild Traumatic Brain Injury

• Harm J. van der Horn
• Josef M. Ling
• Tracey V. Wick
• Andrew B. Dodd
• Cidney R. Robertson-Benta
• Jessica R. McQuaid
• Vadim Zotev
• Andrei A. Vakhtin

Resting-state fMRI can be used to identify recurrent oscillatory patterns of functional connectivity within the human brain, also known as dynamic brain states. Alterations in dynamic brain states are highly likely to occur following pediatric mild traumatic brain injury (pmTBI) due to the active developmental changes. The current study used resting-state fMRI to investigate dynamic brain states in 200 patients with pmTBI (ages 8-18 years, median = 14 years) at the subacute (∼1-week post-injury) and early chronic (∼ 4 months post-injury) stages, and in 179 age- and sex-matched healthy controls (HC). A k-means clustering analysis was applied to the dominant time-varying phase coherence patterns to obtain dynamic brain states. In addition, correlations between brain signals were computed as measures of static functional connectivity. Dynamic connectivity analyses showed that patients with pmTBI spend less time in a frontotemporal default mode/limbic brain state, with no evidence of change as a function of recovery post-injury. Consistent with models showing traumatic strain convergence in deep grey matter and midline regions, static interhemispheric connectivity was affected between the left and right precuneus and thalamus, and between the right supplementary motor area and contralateral cerebellum. Changes in static or dynamic connectivity were not related to symptom burden or injury severity measures, such as loss of consciousness and post-traumatic amnesia. In aggregate, our study shows that brain dynamics are altered up to 4 months after pmTBI, in brain areas that are known to be vulnerable to TBI. Future longitudinal studies are warranted to examine the significance of our findings in terms of long-term neurodevelopment.

YNICL Journal 2024 Journal Article

ENIGMA’s simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury

• Karen Caeyenberghs
• Phoebe Imms
• Andrei Irimia
• Martin M. Monti
• Carrie Esopenko
• Nicola L. de Souza
• Juan F. Dominguez D
• Mary R. Newsome

Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.

YNIMG Journal 2024 Journal Article

Validation of real-time fMRI neurofeedback procedure for cognitive training using counterbalanced active-sham study design

• Vadim Zotev
• Jessica R. McQuaid
• Cidney R. Robertson-Benta
• Anne K. Hittson
• Tracey V. Wick
• Josef M. Ling
• Harm J. van der Horn
• Andrew R. Mayer

Investigation of neural mechanisms of real-time functional MRI neurofeedback (rtfMRI-nf) training requires an efficient study control approach. A common rtfMRI-nf study design involves an experimental group, receiving active rtfMRI-nf, and a control group, provided with sham rtfMRI-nf. We report the first study in which rtfMRI-nf procedure is controlled through counterbalancing training runs with active and sham rtfMRI-nf for each participant. Healthy volunteers (n = 18) used rtfMRI-nf to upregulate fMRI activity of an individually defined target region in the left dorsolateral prefrontal cortex (DLPFC) while performing tasks that involved mental generation of a random numerical sequence and serial summation of numbers in the sequence. Sham rtfMRI-nf was provided based on fMRI activity of a different brain region, not involved in these tasks. The experimental procedure included two training runs with the active rtfMRI-nf and two runs with the sham rtfMRI-nf, in a randomized order. The participants achieved significantly higher fMRI activation of the left DLPFC target region during the active rtfMRI-nf conditions compared to the sham rtfMRI-nf conditions. fMRI functional connectivity of the left DLPFC target region with the nodes of the central executive network was significantly enhanced during the active rtfMRI-nf conditions relative to the sham conditions. fMRI connectivity of the target region with the nodes of the default mode network was similarly enhanced. fMRI connectivity changes between the active and sham conditions exhibited meaningful associations with individual performance measures on the Working Memory Multimodal Attention Task, the Approach-Avoidance Task, and the Trail Making Test. Our results demonstrate that the counterbalanced active-sham study design can be efficiently used to investigate mechanisms of active rtfMRI-nf in direct comparison to those of sham rtfMRI-nf. Further studies with larger group sizes are needed to confirm the reported findings and evaluate clinical utility of this study control approach.

YNICL Journal 2020 Journal Article

Amygdala response to emotional faces in adolescents with persistent post-concussion symptoms

• Luisa Bohorquez-Montoya
• Lezlie Y. España
• Amy M. Nader
• Robyn E. Furger
• Andrew R. Mayer
• Timothy B. Meier

Approximately 30% of adolescents with concussion develop persistent post-concussion symptoms (PPCS) that include emotional symptoms. Elevated amygdalae reactivity to emotional faces has been reported in a variety of psychopathologies characterized by emotional symptoms overlapping with those in PPCS. We tested the hypothesis that amygdalae reactivity to emotional faces in adolescents with PPCS+ is elevated compared to concussed adolescents without PPCS and healthy controls. Concussed adolescents (ages 14-18) with (PPCS+; n = 23) and without PPCS (PPCS-; n = 13) participated in visits at least 4 weeks post-injury. Adolescents without prior concussion served as controls (HC; n = 15). All participants completed a detailed clinical battery and a common emotional face processing task that involved matching of emotional faces or shapes. Compared to HC and PPCS-, adolescents with PPCS+ had elevated depression symptoms, anhedonia, general psychological symptoms, and anxiety symptoms. Contrary to our hypothesis, PPCS+ had lower amygdalae activity to the emotional faces versus shapes condition relative to HC and a trend for lower activity relative to PPCS-. There was a non-significant inverse association between anhedonia amygdalae activity in adolescents with PPCS. Results suggest that adolescents with PPCS have altered amygdalae activity during the processing of emotional face stimuli.

YNICL Journal 2020 Journal Article

Brain activation and subjective anxiety during an anticipatory anxiety task is related to clinical outcome during prazosin treatment for alcohol use disorder

• Claire E. Wilcox
• Bryon Adinoff
• Joshua Clifford
• Josef Ling
• Katie Witkiewitz
• Andrew R. Mayer
• Kylar M. Boggs
• Matthew Eck

BACKGROUND: Higher levels of anxiety, negative affect, and impaired emotion regulation are associated with alcohol use disorder (AUD) and contribute to relapse and worse treatment outcomes. Prazosin, while typically used to treat post-traumatic stress disorder (PTSD) and other anxiety disorders, has shown promise for treating AUD. In order to better understand these underlying neural processes in individuals with AUD, our aims in this study were to measure brain activation during an anticipatory anxiety task before treatment to determine whether observed patterns supported previous work. We then aimed to measure the effects of prazosin on patients with AUD and explore whether greater baseline anticipatory anxiety (as measured by subjective and neural measures) predicts better treatment outcomes. METHODS: Thirty-four individuals seeking treatment for AUD participated in a six-week placebo-controlled study of prazosin and underwent an anticipatory anxiety task during fMRI scans at baseline and three weeks. Alcohol use over six weeks was measured. RESULTS: Greater levels of subjective anxiety and deactivation in posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (vmPFC) were observed during high-threat stimuli compared to low-threat stimuli. Compared to placebo, prazosin reduced subjective anxiety to high-threat stimuli but there were no observed significant effects of prazosin on brain activation during the task. However, AUD patients with greater vmPFC deactivation during high threat relative to low threat and patients with low baseline anticipatory anxiety during the task had worse clinical outcomes on prazosin. CONCLUSIONS: Deactivation in PCC and vmPFC to high-threat stimuli replicated previous work and shows promise for further study as a marker for AUD. Although prazosin did not affect brain activation in the regions of interest during the anticipatory anxiety task, subjective levels of anxiety and brain activation in vmPFC predicted treatment outcomes in individuals with AUD undergoing treatment with prazosin, highlighting individuals more likely to benefit from prazosin than others.

YNICL Journal 2019 Journal Article

Group ICA for identifying biomarkers in schizophrenia: ‘Adaptive’ networks via spatially constrained ICA show more sensitivity to group differences than spatio-temporal regression

• Mustafa S. Salman
• Yuhui Du
• Dongdong Lin
• Zening Fu
• Alex Fedorov
• Eswar Damaraju
• Jing Sui
• Jiayu Chen

Brain functional networks identified from fMRI data can provide potential biomarkers for brain disorders. Group independent component analysis (GICA) is popular for extracting brain functional networks from multiple subjects. In GICA, different strategies exist for reconstructing subject-specific networks from the group-level networks. However, it is unknown whether these strategies have different sensitivities to group differences and abilities in distinguishing patients. Among GICA, spatio-temporal regression (STR) and spatially constrained ICA approaches such as group information guided ICA (GIG-ICA) can be used to propagate components (indicating networks) to a new subject that is not included in the original subjects. In this study, based on the same a priori network maps, we reconstructed subject-specific networks using these two methods separately from resting-state fMRI data of 151 schizophrenia patients (SZs) and 163 healthy controls (HCs). We investigated group differences in the estimated functional networks and the functional network connectivity (FNC) obtained by each method. The networks were also used as features in a cross-validated support vector machine (SVM) for classifying SZs and HCs. We selected features using different strategies to provide a comprehensive comparison between the two methods. GIG-ICA generally showed greater sensitivity in statistical analysis and better classification performance (accuracy 76.45 ± 8.9%, sensitivity 0.74 ± 0.11, specificity 0.79 ± 0.11) than STR (accuracy 67.45 ± 8.13%, sensitivity 0.65 ± 0.11, specificity 0.71 ± 0.11). Importantly, results were also consistent when applied to an independent dataset including 82 HCs and 82 SZs. Our work suggests that the functional networks estimated by GIG-ICA are more sensitive to group differences, and GIG-ICA is promising for identifying image-derived biomarkers of brain disease.

YNICL Journal 2018 Journal Article

Association of acute depressive symptoms and functional connectivity of emotional processing regions following sport-related concussion

• William T. McCuddy
• Lezlie Y. España
• Lindsay D. Nelson
• Rasmus M. Birn
• Andrew R. Mayer
• Timothy B. Meier

Acute mood disturbance following sport-related concussion is common and is known to adversely affect post-concussion symptoms and recovery. The physiological underpinnings of depressive symptoms following concussion, however, are relatively understudied. We hypothesized that functional connectivity of the emotional processing network would be altered in concussed athletes and associated with the severity of depressive symptoms following concussion. Forty-three concussed collegiate athletes were assessed at approximately one day (N = 34), one week (N = 34), and one month post-concussion (N = 30). Fifty-one healthy contact-sport athletes served as controls and completed a single visit. The Hamilton Rating Scale for Depression (HAM-D) was used to measure depressive symptoms. Resting state fMRI data was collected on a 3 T scanner (TR = 2 s) and functional connectivity was calculated in a meta-analytically derived network of regions associated with emotional processing. Concussed athletes had elevated depressive symptoms across the first month post-concussion relative to control athletes, but showed partial recovery by one month relative to more acute visits (ps < 0. 05). Concussed athletes had significantly different connectivity in regions associated with emotional processing at one month post-concussion relative to one day post-concussion (p = 0. 002) and relative to controls (p = 0. 003), with higher connectivity between default mode and attention regions being common across analyses. Additionally, depressive symptoms in concussed athletes at one day (p = 0. 003) and one week post-concussion (p = 7 × 10−8) were inversely correlated with connectivity between attention (e. g. , right anterior insula) and default mode regions (e. g. , medial prefrontal cortex). Finally, the relationships with HAM-D scores were not driven by a general increase in somatic complaints captured by the HAM-D, but were strongly associated with mood-specific HAM-D items. These results suggest that connectivity of emotional processing regions is associated with acute mood disturbance following sport-related concussion. Increased connectivity between attention and default mode regions may reflect compensatory mechanisms.

YNICL Journal 2018 Journal Article

Dynamic functional network connectivity discriminates mild traumatic brain injury through machine learning

• Victor M. Vergara
• Andrew R. Mayer
• Kent A. Kiehl
• Vince D. Calhoun

Mild traumatic brain injury (mTBI) can result in symptoms that affect a person's cognitive and social abilities. Improvements in diagnostic methodologies are necessary given that current clinical techniques have limited accuracy and are solely based on self-reports. Recently, resting state functional network connectivity (FNC) has shown potential as an important imaging modality for the development of mTBI biomarkers. The present work explores the use of dynamic functional network connectivity (dFNC) for mTBI detection. Forty eight mTBI patients (24 males) and age-gender matched healthy controls were recruited. We identified a set of dFNC states and looked at the possibility of using each state to classify subjects in mTBI patients and healthy controls. A linear support vector machine was used for classification and validated using leave-one-out cross validation. One of the dFNC states achieved a high classification performance of 92% using the area under the curve method. A series of t-test analysis revealed significant dFNC increases between cerebellum and sensorimotor networks. This significant increase was detected in the same dFNC state useful for classification. Results suggest that dFNC can be used to identify optimal dFNC states for classification excluding those that does not contain useful features.

YNIMG Journal 2017 Journal Article

Magnetoencephalographic and functional MRI connectomics in schizophrenia via intra- and inter-network connectivity

• Jon M. Houck
• Mustafa S. Çetin
• Andrew R. Mayer
• Juan R. Bustillo
• Julia Stephen
• Cheryl Aine
• Jose Cañive
• Nora Perrone-Bizzozero

Examination of intrinsic functional connectivity using functional MRI (fMRI) has provided important findings regarding dysconnectivity in schizophrenia. Extending these results using a complementary neuroimaging modality, magnetoencephalography (MEG), we present the first direct comparison of functional connectivity between schizophrenia patients and controls, using these two modalities combined. We developed a novel MEG approach for estimation of networks using MEG that incorporates spatial independent component analysis (ICA) and pairwise correlations between independent component timecourses, to estimate intra- and intern-network connectivity. This analysis enables group-level inference and testing of between-group differences. Resting state MEG and fMRI data were acquired from a large sample of healthy controls (n=45) and schizophrenia patients (n=46). Group spatial ICA was performed on fMRI and MEG data to extract intrinsic fMRI and MEG networks and to compensate for signal leakage in MEG. Similar, but not identical spatial independent components were detected for MEG and fMRI. Analysis of functional network connectivity (FNC; i. e. , pairwise correlations in network (ICA component) timecourses) revealed a differential between-modalities pattern, with greater connectivity among occipital networks in fMRI and among frontal networks in MEG. Most importantly, significant differences between controls and patients were observed in both modalities. MEG FNC results in particular indicated dysfunctional hyperconnectivity within frontal and temporal networks in patients, while in fMRI FNC was always greater for controls than for patients. This is the first study to apply group spatial ICA as an approach to leakage correction, and as such our results may be biased by spatial leakage effects. Results suggest that combining these two neuroimaging modalities reveals additional disease-relevant patterns of connectivity that were not detectable with fMRI or MEG alone.

YNIMG Journal 2017 Journal Article

Replicability of time-varying connectivity patterns in large resting state fMRI samples

• Anees Abrol
• Eswar Damaraju
• Robyn L. Miller
• Julia M. Stephen
• Eric D. Claus
• Andrew R. Mayer
• Vince D. Calhoun

The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability of the human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic functional network connectivity (dFNC) analysis frameworks using 7 500 functional magnetic resonance imaging (fMRI) datasets. To quantify the extent to which the emergent functional connectivity (FC) patterns are reproducible, we characterize the temporal dynamics by deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through the existence of basic connectivity patterns (FC states) amidst an ensemble of inter-regional connections. Furthermore, application of the methods to conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed that some of the studied state summary measures were indeed statistically significant and also suggested that this class of null model did not explain the fMRI data fully. This extensive testing of reproducibility of similarity statistics also suggests that the estimated FC states are robust against variation in data quality, analysis, grouping, and decomposition methods. We conclude that future investigations probing the functional and neurophysiological relevance of time-varying connectivity assume critical importance.

YNIMG Journal 2017 Journal Article

The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA

• Victor M. Vergara
• Andrew R. Mayer
• Eswar Damaraju
• Kent Hutchison
• Vince D. Calhoun

Resting state functional network connectivity (rsFNC) derived from functional magnetic resonance (fMRI) imaging is emerging as a possible biomarker to identify several brain disorders. Recently it has been pointed out that methods used to preprocess head motion variance might not fully remove all unwanted effects in the data. Proposed processing pipelines locate the treatment of head motion effects either close to the beginning or as one of the final steps. In this work, we assess several preprocessing pipelines applied in group independent component analysis (gICA) methods to study the rsFNC of the brain. The evaluation method utilizes patient/control classification performance based on linear support vector machines and leave-one-out cross validation. In addition, we explored group tests and correlation with severity measures in the patient population. We also tested the effect of removing high frequencies via filtering. Two real data cohorts were used: one consisting of 48 mTBI and one composed of 21 smokers, both with their corresponding matched controls. A simulation procedure was designed to test the classification power of each pipeline. Results show that data preprocessing can change the classification performance. In real data, regressing motion variance before gICA produced clearer group differences and stronger correlation with nicotine dependence.

YNIMG Journal 2014 Journal Article

Thalamus and posterior temporal lobe show greater inter-network connectivity at rest and across sensory paradigms in schizophrenia

• Mustafa S. Çetin
• Fletcher Christensen
• Christopher C. Abbott
• Julia M. Stephen
• Andrew R. Mayer
• José M. Cañive
• Juan R. Bustillo
• Godfrey D. Pearlson

Although a number of recent studies have examined functional connectivity at rest, few have assessed differences between connectivity both during rest and across active task paradigms. Therefore, the question of whether cortical connectivity patterns remain stable or change with task engagement continues to be unaddressed. We collected multi-scan fMRI data on healthy controls (N =53) and schizophrenia patients (N =42) during rest and across paradigms arranged hierarchically by sensory load. We measured functional network connectivity among 45 non-artifactual distinct brain networks. Then, we applied a novel analysis to assess cross paradigm connectivity patterns applied to healthy controls and patients with schizophrenia. To detect these patterns, we fit a group by task full factorial ANOVA model to the group average functional network connectivity values. Our approach identified both stable (static effects) and state-based differences (dynamic effects) in brain connectivity providing a better understanding of how individuals' reactions to simple sensory stimuli are conditioned by the context within which they are presented. Our findings suggest that not all group differences observed during rest are detectable in other cognitive states. In addition, the stable differences of heightened connectivity between multiple brain areas with thalamus across tasks underscore the importance of the thalamus as a gateway to sensory input and provide new insight into schizophrenia.

YNIMG Journal 2006 Journal Article

Reproducibility of activation in Broca's area during covert generation of single words at high field: A single trial FMRI study at 4 T

• Andrew R. Mayer
• Jing Xu
• Juliana Paré-Blagoev
• Stefan Posse

Although functional magnetic resonance imaging (FMRI) has arguably become the most ubiquitously used imaging modality, questions remain about the reproducibility of the observed patterns of activation and the acquisition time required to achieve statistically significant and reproducible maps. In the current study, we investigated the reliability of activation in Broca's area, on both a voxel-wise and region of interest level, in response to the covert generation of a single word at 4 T. We also assessed the effects of different parametric (P < 0. 01; P < 0. 005; P < 0. 001) and spatial thresholds (25%, 50% and 75%) on the reproducibility of activation within our region of interest and other randomly selected areas of the brain. We report that the inter-trial consistency of activation within Broca's area for a single trial design using multi-echo EPI is roughly equivalent to previous studies that averaged across a much larger number of trials. However, reliability estimates varied dramatically (approximately 55%) depending on the different parametric and spatial criteria thresholds that were applied to the data. These results show that increased sensitivity at high field strength can be used to reduce the time needed to localize functional activation patterns, which is beneficial for clinical studies such as pre-surgical mapping. Additional benefits of single trial designs, such as the ability to immediately assess for extraneous cognitive processes, are also discussed.

YNIMG Journal 2006 Journal Article

The neural networks underlying endogenous auditory covert orienting and reorienting

• Andrew R. Mayer
• Deborah Harrington
• John C. Adair
• Roland Lee

Auditory information communicated through vocalizations, music, or sounds in the environment is commonly used to orient and direct attention to different locations in extrapersonal space. The neural networks subserving attention to auditory space remain poorly understood in comparison to our knowledge about attention in the visual system. The present study investigated whether a parietal–prefrontal right-hemisphere network controls endogenous orienting and reorienting of attention to the location of sounds just as it does for visual–spatial information. Seventeen healthy adults underwent event-related functional magnetic resonance imaging (FMRI) while performing an endogenous auditory orienting task, in which peripheral cues correctly (valid) or incorrectly (invalid) specified the location of a forthcoming sound. The results showed that a right precuneus and bilateral temporal–frontal network mediated the reorienting of auditory attention at both short and long stimulus onset asynchronies (SOAs). In contrast, the more automatic stage of auditory reorienting at the shorter SOA was associated with activation in a bilateral inferior parietal–frontal oculomotor network. These findings suggest that the reorienting of auditory attention is generally supported by a similar inferior parietal–frontal network as visual attention, but in both hemispheres. However, peripheral auditory cues also appear to elicit an automatic orienting response to the spatial location of a sound followed by a period of reduced processing of information that occurs in the same location later in time.

YNIMG Journal 2004 Journal Article

Neural networks underlying endogenous and exogenous visual–spatial orienting

• Andrew R. Mayer
• Jill M. Dorflinger
• Stephen M. Rao
• Michael Seidenberg

The orienting of visual–spatial attention is fundamental to most organisms and is controlled through external (exogenous) or internal (endogenous) processes. Exogenous orienting is considered to be reflexive and automatic, whereas endogenous orienting refers to the purposeful allocation of attentional resources to a predetermined location in space. Although behavioral, electrophysiological and lesion research in both primates and humans suggests that separate neural systems control these different modes of orienting, previous human neuroimaging studies have largely reported common neuronal substrates. Therefore, event-related FMRI (ER-FMRI) was used to independently examine different components of the orienting response including endogenous facilitation, exogenous facilitation and inhibition of return (IOR). In contrast to previous studies, endogenous versus exogenous facilitation resulted in widespread cortical activation including bilateral temporoparietal junction, bilateral superior temporal gyrus, right middle temporal gyrus, right frontal eye field and left intraparietal sulcus. Conversely, IOR compared to endogenous facilitation resulted in only a single focus of activation in the left superior temporal gyrus. These findings suggest that endogenous orienting activates a large cortical network to achieve internally generated shifts of attentional resources versus the automatic orienting that occurs with exogenous cues. However, similar networks may mediate endogenous orienting and IOR. The activation of the temporoparietal junction suggests that it is involved in more effortful processes, such as endogenous orienting, as well as in attentional reorienting and locating targets. Current results are discussed in terms of the functional development of the visual–spatial attentional system.

YNIMG Journal 2000 Journal Article

Neural systems for reorienting visual attention when targets appear in unexpected locations

• Stephen M. Rao
• Catherine M. Arrington
• Andrew R. Mayer
• Thomas H. Carr

YNIMG Journal 2000 Journal Article

The two sides of face perception: Asymmetric cerebral activation associated with featural and configural processing

• Ken A. Paller
• Michael W. Parsons
• Marcia Grabowecky
• Andrew R. Mayer
• Stephen M. Rao

YNIMG Journal 1998 Journal Article

Neural Correlates of the Stroop Interference Effect: An fMRI Study

• Larissa A. Mead
• Stephen M. Rao
• Andrew R. Mayer

YNIMG Journal 1998 Journal Article

Somatotopic Organization of the Medial Wall: A 3T fMRI Study

• Stephen M. Rao
• Yoshimasa Watanabe
• Andrew R. Mayer