Todd Constable | Yale University (original) (raw)

Papers by Todd Constable

Background. Altered resting state functional connectivity (FC) involving the anterior insula (aIN... more Background. Altered resting state functional connectivity (FC) involving the anterior insula (aINS), a key node in the salience network, has been reported consistently in autism. Method. Here we examined, for the first time, FC between the aINS and the whole brain in a sample of full-term, postmenstrual age (PMA) matched neonates (mean 44.0 weeks, SD=1.5) who due to family history have high likelihood (HL) for developing autism (n=12) and in controls (n=41) without family history of autism (low likelihood, LL). Behaviors associated with autism were evaluated between 12 and 18 months (M=17.3 months, SD=2.5) in a subsample (25/53) of participants using the First Year Inventory (FYI). Results. Compared to LL controls, HL neonates showed hypoconnectivity between left aINS and left amygdala. Lower connectivity between the two nodes was associated with higher FYI risk scores in the social domain (r(25) = -.561, p=.003) and this association remained robust when maternal mental health facto...

Scientific Reports, 2020

Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task... more Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in fMRI connectivity analyses. One approach to limit motion has been to use shorter MRI protocols, though this reduces the reliability of results. Hence, there is a need to implement methods to achieve high-quality, low-motion data while not sacrificing data quantity. Here we show that by using a mock scan protocol prior to a scan, in conjunction with other in-scan steps (weighted blanket and incentive system), it is possible to achieve low-motion fMRI data in pediatric participants (age range: 7–17 years old) undergoing a 60 min MRI session. We also observe that motion is low during the MRI protocol in a separate replication group of participants, including some with autism spectrum disorder. Collectively, the results indicate it is possible to conduct long scan protocols in difficult-to-sc...

M. Negishi, R. T. Constable Diagnostic Radiology, Yale University, School of Medicine, New Haven,... more M. Negishi, R. T. Constable Diagnostic Radiology, Yale University, School of Medicine, New Haven, CT, United States, Biomedical Engineering and Neurosurgery, Yale University, School of Medicine, New Haven, CT, United States Introduction Simultaneous Imaging for Tomographic Electrophysiology (SITE), or simultaneous EEG-fMRI recording, is becoming an important tool for correlating electrophysiological changes with hemodynamic changes in the brain. EEG data recorded during fMRI acquisition is contaminated with large gradient, RF pulse, and cardiac pulse artifacts. Hence, effective artifact removal is essential for SITE. Because RF and gradient artifacts are periodical, they are commonly removed by average waveform subtraction methods. However, since spectra of these artifacts include frequency bands much higher than common EEG sampling rates, average waveform subtraction requires EEG sampling timing correction beforehand. EEG sampling time correction involves recording of exact image a...

The human brain flexibly controls different cognitive behaviors, such as memory and attention, to... more The human brain flexibly controls different cognitive behaviors, such as memory and attention, to satisfy contextual demands. Much progress has been made to reveal task-induced modulations in the whole-brain functional connectome, but we still lack a way to model changes in the brain’s functional organization. Here, we present a novel connectome-to-connectome (C2C) state transformation framework that enables us to model the brain’s functional reorganization in response to specific task goals. Using functional magnetic resonance imaging data from the Human Connectome Project, we demonstrate that the C2C model accurately generates an individual’s task-specific connectomes from their task-free connectome with a high degree of specificity across seven different cognitive states. Moreover, the C2C model amplifies behaviorally relevant individual differences in the task-free connectome, thereby improving behavioral predictions. Finally, the C2C model reveals how the connectome reorganizes...

Journal of Neuroscience Research, 2021

The endocannabinoid system is an important regulator of emotional responses such as fear, and a n... more The endocannabinoid system is an important regulator of emotional responses such as fear, and a number of studies have implicated endocannabinoid signaling in anxiety. The fatty acid amide hydrolase (FAAH) C385A polymorphism, which is associated with enhanced endocannabinoid signaling in the brain, has been identified across species as a potential protective factor from anxiety. In particular, adults with the variant FAAH 385A allele have greater fronto-amygdala connectivity and lower anxiety symptoms. Whether broader network-level differences in connectivity exist, and when during development this neural phenotype emerges, remains unknown and represents an important next step in understanding how the FAAH C385A polymorphism impacts neurodevelopment and risk for anxiety disorders. Here, we leveraged data from 3,109 participants in the nationwide Adolescent Brain Cognitive Development Study℠ (10.04 ± 0.62 years old; 44.23% female, 55.77% male) and a cross-validated, data-driven approach to examine associations between

ABSTRACTAutism Spectrum Disorder (ASD) is associated with multiple complex abnormalities in funct... more ABSTRACTAutism Spectrum Disorder (ASD) is associated with multiple complex abnormalities in functional brain connectivity measured with functional magnetic resonance imaging (fMRI). Despite much research in this area, to date, neuroimaging-based models are not able to characterize individuals with ASD with sufficient sensitivity and specificity; this is likely due to the heterogeneity and complexity of this disorder. Here we apply a data-driven subject-level approach, connectome-based predictive modeling, to resting-state fMRI data from a set of individuals from the Autism Brain Imaging Data Exchange. Using leave-one-subject-out and split-half analyses, we define two functional connectivity networks that predict continuous scores on the Social Responsiveness Scale (SRS) and Autism Diagnostic Observation Schedule (ADOS) and confirm that these networks generalize to novel subjects. Notably, these networks were found to share minimal anatomical overlap. Further, our results generalize ...

Nature Neuroscience, Oct 12, 2015

While fMRI studies typically collapse data from many subjects, brain functional organization vari... more While fMRI studies typically collapse data from many subjects, brain functional organization varies between individuals. Here, we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a "fingerprint" that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but notably, the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence; the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects based on functional connectivity fMRI. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Computational psychiatry, Jan 11, 2022

We conducted a feasibility analysis to determine the quality of data that could be collected ambi... more We conducted a feasibility analysis to determine the quality of data that could be collected ambiently during routine clinical conversations. We used inexpensive, consumer-grade hardware to record unstructured dialogue and open-source software tools to quantify and model face, voice (acoustic and language) and movement features. We used an external validation set to perform proof-of-concept predictive analyses and show that clinically relevant measures can be produced without a restrictive protocol. 2 Barron et al.

Brain and behavior, Feb 12, 2014

Biological Psychiatry, May 1, 2020

Background: Co-morbid chronic musculoskeletal pain and posttraumatic stress (CMSP/PTS) is a commo... more Background: Co-morbid chronic musculoskeletal pain and posttraumatic stress (CMSP/PTS) is a common outcome of trauma exposure and is associated with greater disability than either outcome alone. Identification of CMSP/PTS vulnerable individuals would aid in preventative treatment decisions. In the current study, we performed analyses to identify significant predictors and build a prediction tool for CMSP/PTS based on clinical and biological data. Methods: African American men/women presenting to the emergency department (ED) within 24 hours of motor vehicle collision were enrolled. Sociodemographic and psychological/ cognitive characteristics, and blood (PAXgeneRNA) for microRNA-seq were collected in the ED. Six-month surveys identified individuals with CMSP (4, 0-10 Numeric Rating Scale)/PTS (33, Impact of Events Scale-Revised). The prediction tool was built using regularized logistic regression with feature selection, where significant predictors were identified via 1,000x repetitions of Monte Carlo cross-validation. Results: 30% (n¼222/741) of the full cohort reported CMSP/PTS and 27% (n¼198/741) reported neither outcome. Clinical and demographic variables were identified using a subset of individuals without miRNA data (n¼332); selected variables showed good reliability in predicting CMSP/PTS (AUC¼0.76+/-0.008). miRNA data alone (n¼88) yielded weak reliability (AUC¼0.64+/-0.009). Combining clinical, demographic, and miRNA variables (n¼88) improved prediction versus either subset alone (AUC¼0.79+/-0.008). Top predictors included initial pain severity, fear of pain getting worse, feeling frustrated or angry, socioeconomic status and microRNAs miR-199a, miR-339, let-7d, miR-192, and miR-29. Conclusions: These analyses suggest that supplementing clinical prediction with microRNA moderately improves accuracy of identifying vulnerable individuals. Future studies should aim to replicate these findings in additional trauma cohorts.

Biological Psychiatry, May 1, 2020

Background: Measuring brain morphology with non-invasive structural magnetic resonance imaging is... more Background: Measuring brain morphology with non-invasive structural magnetic resonance imaging is common practice and can be used to investigate neuroplasticity. Brain morphology changes have been reported over the course of weeks, days, and hours in both animals and humans. If such short-term changes occur even faster, rapid morphological changes while being scanned could have important implications. Methods: In a randomized within-subject study on 47 healthy individuals, two high-resolution T1-weighted anatomical images were acquired (á 263 s) per individual. The images were acquired during passive viewing of pictures or a fixation cross. Two common pipelines for analyzing brain images were used: voxel-based morphometry on gray matter (GM) volume and surface-based cortical thickness. Results: We found that the measures of both GM volume and cortical thickness showed increases in the visual cortex while viewing pictures relative to a fixation cross (whole-brain voxelwise Z>3.73, pFWE<.038). The increase was distributed across the two hemispheres and significant at a corrected level. Conclusions: Brain morphology enlargements were detected in less than 263 s. Neuroplasticity is a far more dynamic process than previously shown, suggesting that individuals' current mental state affects indices of brain morphology. This needs to be taken into account in future morphology studies and in everyday clinical practice.

Biological Psychiatry, Jul 1, 2002

Background: Converging evidence indicates a functional disruption in the neural systems for readi... more Background: Converging evidence indicates a functional disruption in the neural systems for reading in adults with dyslexia. We examined brain activation patterns in dyslexic and nonimpaired children during pseudoword and real-word reading tasks that required phonologic analysis (i.e., tapped the problems experienced by dyslexic children in sounding out words). Methods: We used functional magnetic resonance imaging (fMRI) to study 144 right-handed children, 70 dyslexic readers, and 74 nonimpaired readers as they read pseudowords and real words. Results: Children with dyslexia demonstrated a disruption in neural systems for reading involving posterior brain regions, including parietotemporal sites and sites in the occipitotemporal area. Reading skill was positively correlated with the magnitude of activation in the left occipitotemporal region. Activation in the left and right inferior frontal gyri was greater in older compared with younger dyslexic children. Conclusions: These findings provide neurobiological evidence of an underlying disruption in the neural systems for reading in children with dyslexia and indicate that it is evident at a young age. The locus of the disruption places childhood dyslexia within the same neurobiological framework as dyslexia, and acquired alexia, occurring in adults.

Motion navigation using nonlinear gradient fields is demonstrated experimentally. The method make... more Motion navigation using nonlinear gradient fields is demonstrated experimentally. The method makes use of the simultaneous multi-dimensional encoding capabilities of nonlinear gradient fields. A two-dimensional navigator image is obtained from a single-echo encoded using a nonlinear gradient field and multiple receiver coils. Without exceeding the maximum field generated by the linear gradient fields of a 3T scanner inside a 20cm isotropic field-of-view, the navigator can be acquired in under one millisecond, including its rewinder. The method can track both translational and rotational in-plane rigid body motion, as demonstrated in phantom experiments. Simulations show the method is applicable in oblique angles. Purpose With several MRI applications lasting several minutes, MRI is prone to patient motion. In-slice motion can be corrected in post-processing when motion is tracked. Orbital 1-3 , pencil-beam 4-6 , spherical 7 and volumetric 8 motion navigators use additional gradient waveforms every TR or separate interleaved TRs whereas marker-based methods, MRI-based 9 or optical 10-12 , use markers placed on the body of interest for motion tracking. Marker-based techniques may suffer from false positives due to facial expressions, while motion navigators affect the sequence timing substantially due to the additional waveforms/TRs. Arguably the most commonly used technique is the PROPELLER, which acquires data in an overlapping manner and estimates motion from the overlapping data. Nevertheless, the overlapping acquisition increases the scan time by ~57%, compared to a non-overlapping approach 13,14. Other techniques keep sequence timing unaltered 15,16 but cannot track rotational motion. Last year, we introduced a motion navigator that uses nonlinear gradient fields to encode translational and rotational motion 17. The technique uses the simultaneous multi-dimensional encoding capabilities of NLGFs to encode motion using a single echo and with a time-penalty of less than a millisecond. In this abstract, we demonstrate the technique experimentally for rotational and translational motion.

Nature Neuroscience, Apr 24, 2023

Magnetic Resonance Imaging, Apr 1, 2017

Purpose-While O-Space imaging is well known to accelerate image acquisition beyond traditional Ca... more Purpose-While O-Space imaging is well known to accelerate image acquisition beyond traditional Cartesian sampling, its advantages compared to undersampled radial imaging, the linear trajectory most akin to O-Space imaging, have not been detailed. In addition, previous studies have focused on ultrafast imaging with very high acceleration factors and relatively low resolution. The purpose of this work is to directly compare O-Space and radial imaging in their potential to deliver highly undersampled images of high resolution and minimal artifacts, as needed for diagnostic applications. We report that the greatest advantages to O-Space imaging are observed with extended data acquisition readouts. Theory and Methods-A sampling strategy that uses high resolution readouts is presented and applied to compare the potential of radial and O-Space sequences to generate high resolution images at high undersampling factors. Simulations and phantom studies were performed to investigate whether use of extended readout windows in O-Space imaging would increase k-space sampling and improve image quality, compared to radial imaging. Results-Experimental O-Space images acquired with high resolution readouts show fewer artifacts and greater sharpness than radial imaging with equivalent scan parameters. Radial images taken with longer readouts show stronger undersampling artifacts, which can cause small or subtle image features to disappear. These features are preserved in a comparable O-Space image. Conclusions-High resolution O-Space imaging yields highly undersampled images of high resolution and minimal artifacts. The additional nonlinear gradient field improves image quality beyond conventional radial imaging.

Nature Communications

The full neural circuits of conscious perception remain unknown. Using a visual perception task, ... more The full neural circuits of conscious perception remain unknown. Using a visual perception task, we directly recorded a subcortical thalamic awareness potential (TAP). We also developed a unique paradigm to classify perceived versus not perceived stimuli using eye measurements to remove confounding signals related to reporting on conscious experiences. Using fMRI, we discovered three major brain networks driving conscious visual perception independent of report: first, increases in signal detection regions in visual, fusiform cortex, and frontal eye fields; and in arousal/salience networks involving midbrain, thalamus, nucleus accumbens, anterior cingulate, and anterior insula; second, increases in frontoparietal attention and executive control networks and in the cerebellum; finally, decreases in the default mode network. These results were largely maintained after excluding eye movement-based fMRI changes. Our findings provide evidence that the neurophysiology of consciousness is ...

Understanding consciousness is one of the most important and challenging questions in modern scie... more Understanding consciousness is one of the most important and challenging questions in modern science. Existing theories have pursued single unifying mechanisms but do not succeed in explaining consciousness. Importantly, the neural circuits that distinguish messages that arrive from the outside world and attain consciousness have remained unknown. Here we identify signals throughout the entire brain at high spatiotemporal resolution specifically related to consciousness. To accomplish this, we combined a large sample size of electrical and neuroimaging data with a novel experimental approach to remove confounding signal unrelated to consciousness1-3. We discovered three major brain networks driving conscious visual perception. First, we found increases in signal detection regions in visual, fusiform cortex, and frontal eye fields; and in arousal/salience networks involving midbrain, thalamus, nucleus accumbens, anterior cingulate, and anterior insula. Second, we found increases in f...

Background. Altered resting state functional connectivity (FC) involving the anterior insula (aIN... more Background. Altered resting state functional connectivity (FC) involving the anterior insula (aINS), a key node in the salience network, has been reported consistently in autism. Method. Here we examined, for the first time, FC between the aINS and the whole brain in a sample of full-term, postmenstrual age (PMA) matched neonates (mean 44.0 weeks, SD=1.5) who due to family history have high likelihood (HL) for developing autism (n=12) and in controls (n=41) without family history of autism (low likelihood, LL). Behaviors associated with autism were evaluated between 12 and 18 months (M=17.3 months, SD=2.5) in a subsample (25/53) of participants using the First Year Inventory (FYI). Results. Compared to LL controls, HL neonates showed hypoconnectivity between left aINS and left amygdala. Lower connectivity between the two nodes was associated with higher FYI risk scores in the social domain (r(25) = -.561, p=.003) and this association remained robust when maternal mental health facto...

Scientific Reports, 2020

Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task... more Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in fMRI connectivity analyses. One approach to limit motion has been to use shorter MRI protocols, though this reduces the reliability of results. Hence, there is a need to implement methods to achieve high-quality, low-motion data while not sacrificing data quantity. Here we show that by using a mock scan protocol prior to a scan, in conjunction with other in-scan steps (weighted blanket and incentive system), it is possible to achieve low-motion fMRI data in pediatric participants (age range: 7–17 years old) undergoing a 60 min MRI session. We also observe that motion is low during the MRI protocol in a separate replication group of participants, including some with autism spectrum disorder. Collectively, the results indicate it is possible to conduct long scan protocols in difficult-to-sc...

M. Negishi, R. T. Constable Diagnostic Radiology, Yale University, School of Medicine, New Haven,... more M. Negishi, R. T. Constable Diagnostic Radiology, Yale University, School of Medicine, New Haven, CT, United States, Biomedical Engineering and Neurosurgery, Yale University, School of Medicine, New Haven, CT, United States Introduction Simultaneous Imaging for Tomographic Electrophysiology (SITE), or simultaneous EEG-fMRI recording, is becoming an important tool for correlating electrophysiological changes with hemodynamic changes in the brain. EEG data recorded during fMRI acquisition is contaminated with large gradient, RF pulse, and cardiac pulse artifacts. Hence, effective artifact removal is essential for SITE. Because RF and gradient artifacts are periodical, they are commonly removed by average waveform subtraction methods. However, since spectra of these artifacts include frequency bands much higher than common EEG sampling rates, average waveform subtraction requires EEG sampling timing correction beforehand. EEG sampling time correction involves recording of exact image a...

The human brain flexibly controls different cognitive behaviors, such as memory and attention, to... more The human brain flexibly controls different cognitive behaviors, such as memory and attention, to satisfy contextual demands. Much progress has been made to reveal task-induced modulations in the whole-brain functional connectome, but we still lack a way to model changes in the brain’s functional organization. Here, we present a novel connectome-to-connectome (C2C) state transformation framework that enables us to model the brain’s functional reorganization in response to specific task goals. Using functional magnetic resonance imaging data from the Human Connectome Project, we demonstrate that the C2C model accurately generates an individual’s task-specific connectomes from their task-free connectome with a high degree of specificity across seven different cognitive states. Moreover, the C2C model amplifies behaviorally relevant individual differences in the task-free connectome, thereby improving behavioral predictions. Finally, the C2C model reveals how the connectome reorganizes...

Journal of Neuroscience Research, 2021

The endocannabinoid system is an important regulator of emotional responses such as fear, and a n... more The endocannabinoid system is an important regulator of emotional responses such as fear, and a number of studies have implicated endocannabinoid signaling in anxiety. The fatty acid amide hydrolase (FAAH) C385A polymorphism, which is associated with enhanced endocannabinoid signaling in the brain, has been identified across species as a potential protective factor from anxiety. In particular, adults with the variant FAAH 385A allele have greater fronto-amygdala connectivity and lower anxiety symptoms. Whether broader network-level differences in connectivity exist, and when during development this neural phenotype emerges, remains unknown and represents an important next step in understanding how the FAAH C385A polymorphism impacts neurodevelopment and risk for anxiety disorders. Here, we leveraged data from 3,109 participants in the nationwide Adolescent Brain Cognitive Development Study℠ (10.04 ± 0.62 years old; 44.23% female, 55.77% male) and a cross-validated, data-driven approach to examine associations between

ABSTRACTAutism Spectrum Disorder (ASD) is associated with multiple complex abnormalities in funct... more ABSTRACTAutism Spectrum Disorder (ASD) is associated with multiple complex abnormalities in functional brain connectivity measured with functional magnetic resonance imaging (fMRI). Despite much research in this area, to date, neuroimaging-based models are not able to characterize individuals with ASD with sufficient sensitivity and specificity; this is likely due to the heterogeneity and complexity of this disorder. Here we apply a data-driven subject-level approach, connectome-based predictive modeling, to resting-state fMRI data from a set of individuals from the Autism Brain Imaging Data Exchange. Using leave-one-subject-out and split-half analyses, we define two functional connectivity networks that predict continuous scores on the Social Responsiveness Scale (SRS) and Autism Diagnostic Observation Schedule (ADOS) and confirm that these networks generalize to novel subjects. Notably, these networks were found to share minimal anatomical overlap. Further, our results generalize ...

Nature Neuroscience, Oct 12, 2015

While fMRI studies typically collapse data from many subjects, brain functional organization vari... more While fMRI studies typically collapse data from many subjects, brain functional organization varies between individuals. Here, we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a "fingerprint" that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but notably, the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence; the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects based on functional connectivity fMRI. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Computational psychiatry, Jan 11, 2022

We conducted a feasibility analysis to determine the quality of data that could be collected ambi... more We conducted a feasibility analysis to determine the quality of data that could be collected ambiently during routine clinical conversations. We used inexpensive, consumer-grade hardware to record unstructured dialogue and open-source software tools to quantify and model face, voice (acoustic and language) and movement features. We used an external validation set to perform proof-of-concept predictive analyses and show that clinically relevant measures can be produced without a restrictive protocol. 2 Barron et al.

Brain and behavior, Feb 12, 2014

Biological Psychiatry, May 1, 2020

Background: Co-morbid chronic musculoskeletal pain and posttraumatic stress (CMSP/PTS) is a commo... more Background: Co-morbid chronic musculoskeletal pain and posttraumatic stress (CMSP/PTS) is a common outcome of trauma exposure and is associated with greater disability than either outcome alone. Identification of CMSP/PTS vulnerable individuals would aid in preventative treatment decisions. In the current study, we performed analyses to identify significant predictors and build a prediction tool for CMSP/PTS based on clinical and biological data. Methods: African American men/women presenting to the emergency department (ED) within 24 hours of motor vehicle collision were enrolled. Sociodemographic and psychological/ cognitive characteristics, and blood (PAXgeneRNA) for microRNA-seq were collected in the ED. Six-month surveys identified individuals with CMSP (4, 0-10 Numeric Rating Scale)/PTS (33, Impact of Events Scale-Revised). The prediction tool was built using regularized logistic regression with feature selection, where significant predictors were identified via 1,000x repetitions of Monte Carlo cross-validation. Results: 30% (n¼222/741) of the full cohort reported CMSP/PTS and 27% (n¼198/741) reported neither outcome. Clinical and demographic variables were identified using a subset of individuals without miRNA data (n¼332); selected variables showed good reliability in predicting CMSP/PTS (AUC¼0.76+/-0.008). miRNA data alone (n¼88) yielded weak reliability (AUC¼0.64+/-0.009). Combining clinical, demographic, and miRNA variables (n¼88) improved prediction versus either subset alone (AUC¼0.79+/-0.008). Top predictors included initial pain severity, fear of pain getting worse, feeling frustrated or angry, socioeconomic status and microRNAs miR-199a, miR-339, let-7d, miR-192, and miR-29. Conclusions: These analyses suggest that supplementing clinical prediction with microRNA moderately improves accuracy of identifying vulnerable individuals. Future studies should aim to replicate these findings in additional trauma cohorts.

Biological Psychiatry, May 1, 2020

Background: Measuring brain morphology with non-invasive structural magnetic resonance imaging is... more Background: Measuring brain morphology with non-invasive structural magnetic resonance imaging is common practice and can be used to investigate neuroplasticity. Brain morphology changes have been reported over the course of weeks, days, and hours in both animals and humans. If such short-term changes occur even faster, rapid morphological changes while being scanned could have important implications. Methods: In a randomized within-subject study on 47 healthy individuals, two high-resolution T1-weighted anatomical images were acquired (á 263 s) per individual. The images were acquired during passive viewing of pictures or a fixation cross. Two common pipelines for analyzing brain images were used: voxel-based morphometry on gray matter (GM) volume and surface-based cortical thickness. Results: We found that the measures of both GM volume and cortical thickness showed increases in the visual cortex while viewing pictures relative to a fixation cross (whole-brain voxelwise Z>3.73, pFWE<.038). The increase was distributed across the two hemispheres and significant at a corrected level. Conclusions: Brain morphology enlargements were detected in less than 263 s. Neuroplasticity is a far more dynamic process than previously shown, suggesting that individuals' current mental state affects indices of brain morphology. This needs to be taken into account in future morphology studies and in everyday clinical practice.

Biological Psychiatry, Jul 1, 2002

Background: Converging evidence indicates a functional disruption in the neural systems for readi... more Background: Converging evidence indicates a functional disruption in the neural systems for reading in adults with dyslexia. We examined brain activation patterns in dyslexic and nonimpaired children during pseudoword and real-word reading tasks that required phonologic analysis (i.e., tapped the problems experienced by dyslexic children in sounding out words). Methods: We used functional magnetic resonance imaging (fMRI) to study 144 right-handed children, 70 dyslexic readers, and 74 nonimpaired readers as they read pseudowords and real words. Results: Children with dyslexia demonstrated a disruption in neural systems for reading involving posterior brain regions, including parietotemporal sites and sites in the occipitotemporal area. Reading skill was positively correlated with the magnitude of activation in the left occipitotemporal region. Activation in the left and right inferior frontal gyri was greater in older compared with younger dyslexic children. Conclusions: These findings provide neurobiological evidence of an underlying disruption in the neural systems for reading in children with dyslexia and indicate that it is evident at a young age. The locus of the disruption places childhood dyslexia within the same neurobiological framework as dyslexia, and acquired alexia, occurring in adults.

Motion navigation using nonlinear gradient fields is demonstrated experimentally. The method make... more Motion navigation using nonlinear gradient fields is demonstrated experimentally. The method makes use of the simultaneous multi-dimensional encoding capabilities of nonlinear gradient fields. A two-dimensional navigator image is obtained from a single-echo encoded using a nonlinear gradient field and multiple receiver coils. Without exceeding the maximum field generated by the linear gradient fields of a 3T scanner inside a 20cm isotropic field-of-view, the navigator can be acquired in under one millisecond, including its rewinder. The method can track both translational and rotational in-plane rigid body motion, as demonstrated in phantom experiments. Simulations show the method is applicable in oblique angles. Purpose With several MRI applications lasting several minutes, MRI is prone to patient motion. In-slice motion can be corrected in post-processing when motion is tracked. Orbital 1-3 , pencil-beam 4-6 , spherical 7 and volumetric 8 motion navigators use additional gradient waveforms every TR or separate interleaved TRs whereas marker-based methods, MRI-based 9 or optical 10-12 , use markers placed on the body of interest for motion tracking. Marker-based techniques may suffer from false positives due to facial expressions, while motion navigators affect the sequence timing substantially due to the additional waveforms/TRs. Arguably the most commonly used technique is the PROPELLER, which acquires data in an overlapping manner and estimates motion from the overlapping data. Nevertheless, the overlapping acquisition increases the scan time by ~57%, compared to a non-overlapping approach 13,14. Other techniques keep sequence timing unaltered 15,16 but cannot track rotational motion. Last year, we introduced a motion navigator that uses nonlinear gradient fields to encode translational and rotational motion 17. The technique uses the simultaneous multi-dimensional encoding capabilities of NLGFs to encode motion using a single echo and with a time-penalty of less than a millisecond. In this abstract, we demonstrate the technique experimentally for rotational and translational motion.

Nature Neuroscience, Apr 24, 2023

Magnetic Resonance Imaging, Apr 1, 2017

Purpose-While O-Space imaging is well known to accelerate image acquisition beyond traditional Ca... more Purpose-While O-Space imaging is well known to accelerate image acquisition beyond traditional Cartesian sampling, its advantages compared to undersampled radial imaging, the linear trajectory most akin to O-Space imaging, have not been detailed. In addition, previous studies have focused on ultrafast imaging with very high acceleration factors and relatively low resolution. The purpose of this work is to directly compare O-Space and radial imaging in their potential to deliver highly undersampled images of high resolution and minimal artifacts, as needed for diagnostic applications. We report that the greatest advantages to O-Space imaging are observed with extended data acquisition readouts. Theory and Methods-A sampling strategy that uses high resolution readouts is presented and applied to compare the potential of radial and O-Space sequences to generate high resolution images at high undersampling factors. Simulations and phantom studies were performed to investigate whether use of extended readout windows in O-Space imaging would increase k-space sampling and improve image quality, compared to radial imaging. Results-Experimental O-Space images acquired with high resolution readouts show fewer artifacts and greater sharpness than radial imaging with equivalent scan parameters. Radial images taken with longer readouts show stronger undersampling artifacts, which can cause small or subtle image features to disappear. These features are preserved in a comparable O-Space image. Conclusions-High resolution O-Space imaging yields highly undersampled images of high resolution and minimal artifacts. The additional nonlinear gradient field improves image quality beyond conventional radial imaging.

Nature Communications

The full neural circuits of conscious perception remain unknown. Using a visual perception task, ... more The full neural circuits of conscious perception remain unknown. Using a visual perception task, we directly recorded a subcortical thalamic awareness potential (TAP). We also developed a unique paradigm to classify perceived versus not perceived stimuli using eye measurements to remove confounding signals related to reporting on conscious experiences. Using fMRI, we discovered three major brain networks driving conscious visual perception independent of report: first, increases in signal detection regions in visual, fusiform cortex, and frontal eye fields; and in arousal/salience networks involving midbrain, thalamus, nucleus accumbens, anterior cingulate, and anterior insula; second, increases in frontoparietal attention and executive control networks and in the cerebellum; finally, decreases in the default mode network. These results were largely maintained after excluding eye movement-based fMRI changes. Our findings provide evidence that the neurophysiology of consciousness is ...

Understanding consciousness is one of the most important and challenging questions in modern scie... more Understanding consciousness is one of the most important and challenging questions in modern science. Existing theories have pursued single unifying mechanisms but do not succeed in explaining consciousness. Importantly, the neural circuits that distinguish messages that arrive from the outside world and attain consciousness have remained unknown. Here we identify signals throughout the entire brain at high spatiotemporal resolution specifically related to consciousness. To accomplish this, we combined a large sample size of electrical and neuroimaging data with a novel experimental approach to remove confounding signal unrelated to consciousness1-3. We discovered three major brain networks driving conscious visual perception. First, we found increases in signal detection regions in visual, fusiform cortex, and frontal eye fields; and in arousal/salience networks involving midbrain, thalamus, nucleus accumbens, anterior cingulate, and anterior insula. Second, we found increases in f...