Honors & Awards
PRARP Convergence Science Research Award, Department of Defense (2021-2024)
Graduate Research Fellowship Program, National Science Foundation (2008-2011)
PhD, Harvard University, Neuroscience (2013)
BA, Columbia University, Biochemistry (2005)
Deep Brain Stimulation for the Treatment of Traumatic Brain Injury
This study involves the treatment of cognitive impairment secondary to moderate to severe brain injury using central thalamic deep brain stimulation. Although all patients will receive stimulation continuously through a surgically implanted pacemaker-like device, half of the patients will have the device deactivated during a blinded assessment phase. The device will be reactivated following this assessment and patients will have the option to continue stimulation in an open-label continuation.
Stanford is currently not accepting patients for this trial. For more information, please contact Jaimie M Henderson, MD, 650-723-5574.
Thalamic nuclei atrophy at high and heterogenous rates during cognitively unimpaired human aging.
The thalamus is a central integration structure in the brain, receiving and distributing information among the cerebral cortex, subcortical structures, and the peripheral nervous system. Prior studies clearly show that the thalamus atrophies in cognitively unimpaired aging. However, the thalamus is comprised of multiple nuclei involved in a wide range of functions, and the age-related atrophy of individual thalamic nuclei remains unknown. Using a recently developed automated method of identifying thalamic nuclei (3T or 7T MRI with white-matter-nulled MPRAGE contrast and THOMAS segmentation) and a cross-sectional design, we evaluated the age-related atrophy rate for 10 thalamic nuclei (AV, CM, VA, VLA, VLP, VPL, pulvinar, LGN, MGN, MD) and an epithalamic nucleus (habenula). We also used T1-weighted images with the FreeSurfer SAMSEG segmentation method to identify and measure age-related atrophy for 11 extra-thalamic structures (cerebral cortex, cerebral white matter, cerebellar cortex, cerebellar white matter, amygdala, hippocampus, caudate, putamen, nucleus accumbens, pallidum, and lateral ventricle). In 198 cognitively unimpaired participants with ages spanning 20-88 years, we found that the whole thalamus atrophied at a rate of 0.45% per year, and that thalamic nuclei had widely varying age-related atrophy rates, ranging from 0.06% to 1.18% per year. A functional grouping analysis revealed that the thalamic nuclei involved in cognitive (AV, MD; 0.53% atrophy per year), visual (LGN, pulvinar; 0.62% atrophy per year), and auditory/vestibular (MGN; 0.64% atrophy per year) functions atrophied at significantly higher rates than those involved in motor (VA, VLA, VLP, and CM; 0.37% atrophy per year) and somatosensory (VPL; 0.32% atrophy per year) functions. A proximity-to-CSF analysis showed that the group of thalamic nuclei situated immediately adjacent to CSF atrophied at a significantly greater atrophy rate (0.59% atrophy per year) than that of the group of nuclei located farther from CSF (0.36% atrophy per year), supporting a growing hypothesis that CSF-mediated factors contribute to neurodegeneration. We did not find any significant hemispheric differences in these rates of change for thalamic nuclei. Only the CM thalamic nucleus showed a sex-specific difference in atrophy rates, atrophying at a greater rate in male versus female participants. Roughly half of the thalamic nuclei showed greater atrophy than all extra-thalamic structures examined (0% to 0.54% per year). These results show the value of white-matter-nulled MPRAGE imaging and THOMAS segmentation for measuring distinct thalamic nuclei and for characterizing the high and heterogeneous atrophy rates of the thalamus and its nuclei across the adult lifespan. Collectively, these methods and results advance our understanding of the role of thalamic substructures in neurocognitive and disease-related changes that occur with aging.
View details for DOI 10.1016/j.neuroimage.2022.119584
View details for PubMedID 36007822
Nonhuman primate meso-circuitry data: a translational tool to understand brain networks across species
Brain Structure & Function
2021; 226 (1): 1-11
View details for DOI 10.1007/s00429-020-02133-3
Corticostriatal Projections of Macaque Area 44
Cerebral Cortex Communications
2020; 1 (1): 1-11
View details for DOI 10.1093/texcom/tgaa079
Improved Vim targeting for focused ultrasound ablation treatment of essential tremor: A probabilistic and patient‐specific approach
Human Brain Mapping
2020; 41 (17): 4769-4788
View details for DOI 10.1002/hbm.25157
Fast, fully automated segmentation of thalamic nuclei from structural MRI.
The thalamus and its nuclei are largely indistinguishable on standard T1 or T2 weighted MRI. While diffusion tensor imaging based methods have been proposed to segment the thalamic nuclei based on the angular orientation of the principal diffusion tensor, these are based on echo planar imaging which is inherently limited in spatial resolution and suffers from distortion. We present a multi-atlas segmentation technique based on white-matter-nulled MP-RAGE imaging that segments the thalamus into 12 nuclei with computation times on the order of 10 min on a desktop PC; we call this method THOMAS (THalamus Optimized Multi Atlas Segmentation). THOMAS was rigorously evaluated on 7T MRI data acquired from healthy volunteers and patients with multiple sclerosis by comparing against manual segmentations delineated by a neuroradiologist, guided by the Morel atlas. Segmentation accuracy was very high, with uniformly high Dice indices: at least 0.85 for large nuclei like the pulvinar and mediodorsal nuclei and at least 0.7 even for small structures such as the habenular, centromedian, and lateral and medial geniculate nuclei. Volume similarity indices ranged from 0.82 for the smaller nuclei to 0.97 for the larger nuclei. Volumetry revealed that the volumes of the right anteroventral, right ventral posterior lateral, and both right and left pulvinar nuclei were significantly lower in MS patients compared to controls, after adjusting for age, sex and intracranial volume. Lastly, we evaluated the potential of this method for targeting the Vim nucleus for deep brain surgery and focused ultrasound thalamotomy by overlaying the Vim nucleus segmented from pre-operative data on post-operative data. The locations of the ablated region and active DBS contact corresponded well with the segmented Vim nucleus. Our fast, direct structural MRI based segmentation method opens the door for MRI guided intra-operative procedures like thalamotomy and asleep DBS electrode placement as well as for accurate quantification of thalamic nuclear volumes to follow progression of neurological disorders.
View details for PubMedID 30894331
Circuits, Networks, and Neuropsychiatric Disease: Transitioning From Anatomy to Imaging.
Since the development of cellular and myelin stains, anatomy has formed the foundation for understanding circuitry in the human brain. However, recent functional and structural studies using magnetic resonance imaging have taken the lead in this endeavor. These innovative and noninvasive approaches have the advantage of studying connectivity patterns under different conditions directly in the human brain. They demonstrate dynamic and structural changes within and across networks linked to normal function and to a wide range of psychiatric illnesses. However, these indirect methods are unable to link networks to the hardwiring that underlies them. In contrast, anatomic invasive experimental studies can. Following a brief review of prefrontal cortical, anterior cingulate, and striatal connections and the different methodologies used, this article discusses how data from anatomic studies can help inform how hardwired connections are linked to the functional and structural networks identified in imaging studies.
View details for DOI 10.1016/j.biopsych.2019.10.024
View details for PubMedID 31870495
Automated integrated system for stained neuron detection: An end-to-end framework with a high negative predictive rate.
Computer methods and programs in biomedicine
2019; 180: 105028
Mapping the architecture of the brain is essential for identifying the neural computations that affect behavior. Traditionally in histology, stained objects in tissue slices are hand-marked under a microscope in a manually intensive, time-consuming process. An integrated hardware and software system is needed to automate image acquisition, image processing, and object detection. Such a system would enable high throughput tissue analysis to rapidly map an entire brain.We demonstrate an automated system to detect neurons using a monkey brain slice immunohistochemically stained for retrogradely labeled neurons. The proposed system obtains a reconstructed image of the sample, and stained neurons are detected in three steps. First, the reconstructed image is pre-processed using adaptive histogram equalization. Second, candidates for stained neurons are segmented from each region via marker-controlled watershed transformation (MCWT) using maximally stable extremal regions (MSERs). Third, the candidates are categorized as neurons or non-neurons using deep transfer learning via pre-trained convolutional neural networks (CNN).The proposed MCWT algorithm was compared qualitatively against MorphLibJ and an IHC analysis tool, while our unified classification algorithm was evaluated quantitatively using ROC analyses. The proposed classification system was first compared with five previously developed layers (AlexNet, VGG-16, VGG-19, GoogleNet, and ResNet). A comparison with conventional multi-stage frameworks followed using six off-the-shelf classifiers [Bayesian network (BN), support vector machines (SVM), decision tree (DT), bagging (BAG), AdaBoost (ADA), and logistic regression (LR)] and two descriptors (LBP and HOG). The system achieved a 0.918 F1-score with an 86.6% negative prediction value. Remarkably, other metrics such as precision, recall, and F-scores surpassed the 90% threshold compared to traditional methods.We demonstrate a fully automated, integrated hardware and software system for rapidly acquiring focused images and identifying neurons from a stained brain slice. This system could be adapted for the identification of stained features of any biological tissue.
View details for DOI 10.1016/j.cmpb.2019.105028
View details for PubMedID 31437805
How do cortico-striatal projections impact on downstream pallidal circuitry?
Brain structure & function
The frontal cortico-basal ganglia network plays a central role in action selection, associative learning, and motivation, processes requiring the integration of information from functionally distinct cortical regions. The cortico-striatal projection is a likely substrate of information integration, as terminal fields from different cortical regions converge in the striatum. These intersecting projections form complex zones of unique cortical inputs. Here, our goal was to follow these projection zones downstream in the basal ganglia to the globus pallidus. We combined a sizable database of 3D models of striato-pallidal chartings in macaques with maps of frontal cortical inputs to determine the topography of the striato-pallidal projection and the indirect cortical influence over the pallidum. We found that the striato-pallidal projection is highly topographic, with the location of the striatal injection site strongly predicting the location of the resulting pallidal terminal fields. Furthermore, striato-pallidal projections are specific and largely nonoverlapping. Thus, striatal hubs receiving unique combinations of cortical inputs have distinct projections to the pallidum. However, because of the strong convergence of cortical terminal fields in the striatum, the indirect pallidal representation of any given frontal cortical region remains broad. We illustrate this arrangement by contrasting the pallidal projections from two nearby striatal cases: one a putative hub for cortical attentional bias signals, and the other with a different, more ventral set of cortical inputs. Thus, the striato-pallidal projection faithfully conveys unique combinations of cortical inputs to different locations within the pallidum via the striatum.
View details for DOI 10.1007/s00429-018-1662-9
View details for PubMedID 29654360
Evidence for a Functional Hierarchy of Association Networks.
Journal of cognitive neuroscience
Patient lesion and neuroimaging studies have identified a rostral-to-caudal functional gradient in the lateral frontal cortex (LFC) corresponding to higher-order (complex or abstract) to lower-order (simple or concrete) cognitive control. At the same time, monkey anatomical and human functional connectivity studies show that frontal regions are reciprocally connected with parietal and temporal regions, forming parallel and distributed association networks. Here, we investigated the link between the functional gradient of LFC regions observed during control tasks and the parallel, distributed organization of association networks. Whole-brain fMRI task activity corresponding to four orders of hierarchical control [Badre, D., & D'Esposito, M. Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. Journal of Cognitive Neuroscience, 19, 2082-2099, 2007] was compared with a resting-state functional connectivity MRI estimate of cortical networks [Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 1125-1165, 2011]. Critically, at each order of control, activity in the LFC and parietal cortex overlapped onto a common association network that differed between orders. These results are consistent with a functional organization based on separable association networks that are recruited during hierarchical control. Furthermore, corticostriatal functional connectivity MRI showed that, consistent with their participation in functional networks, rostral-to-caudal LFC and caudal-to-rostral parietal regions had similar, order-specific corticostriatal connectivity that agreed in part with the predictions of a striatal gating model of hierarchical rule use. Our results indicate that hierarchical cognitive control is subserved by parallel and distributed association networks, together forming multiple localized functional gradients in different parts of association cortex. As such, association networks, while connectionally organized in parallel, may be functionally organized in a hierarchy via dynamic interaction with the striatum.
View details for DOI 10.1162/jocn_a_01229
View details for PubMedID 29308987
Gene expression links functional networks across cortex and striatum.
2018; 9 (1): 1428
The human brain is comprised of a complex web of functional networks that link anatomically distinct regions. However, the biological mechanisms supporting network organization remain elusive, particularly across cortical and subcortical territories with vastly divergent cellular and molecular properties. Here, using human and primate brain transcriptional atlases, we demonstrate that spatial patterns of gene expression show strong correspondence with limbic and somato/motor cortico-striatal functional networks. Network-associated expression is consistent across independent human datasets and evolutionarily conserved in non-human primates. Genes preferentially expressed within the limbic network (encompassing nucleus accumbens, orbital/ventromedial prefrontal cortex, and temporal pole) relate to risk for psychiatric illness, chloride channel complexes, and markers of somatostatin neurons. Somato/motor associated genes are enriched for oligodendrocytes and markers of parvalbumin neurons. These analyses indicate that parallel cortico-striatal processing channels possess dissociable genetic signatures that recapitulate distributed functional networks, and nominate molecular mechanisms supporting cortico-striatal circuitry in health and disease.
View details for PubMedID 29651138
View details for PubMedCentralID PMC5897339
- Imaging the striatum in autism spectrum disorder. Autism Imaging and Devices. Taylor and Francis. 2017
Combinatorial Inputs to the Ventral Striatum from the Temporal Cortex, Frontal Cortex, and Amygdala: Implications for Segmenting the Striatum.
2017; 4 (6)
The canonical striatal map, based predominantly on frontal corticostriatal projections, divides the striatum into ventromedial-limbic, central-association, and dorsolateral-motor territories. While this has been a useful heuristic, recent studies indicate that the striatum has a more complex topography when considering converging frontal and nonfrontal inputs from distributed cortical networks. The ventral striatum (VS) in particular is often ascribed a "limbic" role, but it receives diverse information, including motivation and emotion from deep brain structures, cognition from frontal cortex, and polysensory and mnemonic signals from temporal cortex. Using anatomical tract-tracing in 17 male adult monkeys (Macaca nemestrina,Macaca fascicularis,Macaca mulatta), we build upon this striatal map by systematically mapping inputs from frontal cortex, amygdala, temporal pole, and medial temporal cortex. We find that the VS contains heterogeneous subregions that become apparent when considering both the identities and strengths of inputs. We parcellated the VS into a ventromedial sector receiving motivation and emotion-related information from regions including area TG, ventromedial PFC, ACC, and amygdala; and a more functionally diverse dorsolateral sector that receives this information coupled to cognitive and sensorimotor information from dorsolateral PFC, ventrolateral PFC, premotor cortex, area TAr, and area TEr. Each sector was further parcellated into smaller regions that had different proportions of these inputs. Together, the striatum contains complex, selective input combinations, providing substrates for myriad associations. This VS parcellation provides a map that can guide and interpret functional interactions in healthy individuals and those with psychiatric disorders, and may be useful in targeting treatments for specific psychiatric conditions.
View details for DOI 10.1523/ENEURO.0392-17.2017
Convergence of prefrontal and parietal anatomical projections in a connectional hub in the striatum.
Visual attentional bias forms for rewarding and punishing stimuli in the environment. While this attentional bias is adaptive in healthy situations, it is maladaptive in disorders such as drug addiction or PTSD. In both these disorders, the ability to exert control over this attentional bias is associated with drug abstinence rates or reduced PTSD symptoms, indicating the interaction of visual attention, cognitive control, and stimulus association. The inferior parietal lobule (IPL) is central to attention, while the prefrontal cortex (PFC) is critical for reward, cognitive control, and attention. Importantly, regions of the IPL and PFC commonly project to the rostral dorsal caudate (rdCaud) of the striatum. We propose an anatomical network architecture in which IPL projections converge with PFC projections in a connectional hub in the rdCaud, providing an anatomical substrate for the interaction of these projections and their competitive influence on striatal processing. To investigate this, we mapped the dense projections from the caudal IPL and prefrontal (dlPFC, vlPFC, OFC, dACC, and dmPFC) regions that project to the medial rdCaud with anatomical tract-tracing tracer injections in monkeys. These inputs converge in a precise site in the medial rdCaud, rostral to the anterior commissure. Small retrograde tracer injections confirmed these inputs to the medial rdCaud and showed that a proximal ventral striatal location has a very different pattern of cortical inputs. We next used human resting-state functional connectivity MRI (fcMRI) to examine whether a striatal hub exists in the human medial rdCaud. Seed regions in the human medial rdCaud revealed cortical correlation maps similar to the monkey retrograde injection results. A subsequent analysis of these correlated cortical regions showed that their peak correlation within the striatum is in the medial rdCaud, indicating that this is a connectional hub. In contrast, this peak striatal correlation was not found in the ventral striatal location, suggesting that this site is not a connectional hub of cortical regions. Taken together, this work uses the precision of monkey anatomy to identify a connectional hub of IPL and PFC projections in the medial rdCaud. It also translates this anatomical precision to humans, demonstrating that, guided by anatomy, connectional hubs can be identified in humans with fcMRI. These connectional hubs provide more specific treatment targets for drug addiction, PTSD, and other neurological and psychiatric disorders involving the striatum.
View details for DOI 10.1016/j.neuroimage.2016.09.037
View details for PubMedID 27646127
The Human Ortholog of Acid-Sensing Ion Channel Gene ASIC1a Is Associated With Panic Disorder and Amygdala Structure and Function
2014; 76 (11): 902-910
Individuals with panic disorder (PD) exhibit a hypersensitivity to inhaled carbon dioxide, possibly reflecting a lowered threshold for sensing signals of suffocation. Animal studies have shown that carbon dioxide-mediated fear behavior depends on chemosensing of acidosis in the amygdala via the acid-sensing ion channel ASIC1a. We examined whether the human ortholog of the ASIC1a gene, ACCN2, is associated with the presence of PD and with amygdala structure and function.We conducted a case-control analysis (n = 414 PD cases and 846 healthy controls) of ACCN2 single nucleotide polymorphisms and PD. We then tested whether variants showing significant association with PD are also associated with amygdala volume (n = 1048) or task-evoked reactivity to emotional stimuli (n = 103) in healthy individuals.Two single nucleotide polymorphisms at the ACCN2 locus showed evidence of association with PD: rs685012 (odds ratio = 1.32, gene-wise corrected p = .011) and rs10875995 (odds ratio = 1.26, gene-wise corrected p = .046). The association appeared to be stronger when early-onset (age ≤ 20 years) PD cases and when PD cases with prominent respiratory symptoms were compared with controls. The PD risk allele at rs10875995 was associated with increased amygdala volume (p = .035) as well as task-evoked amygdala reactivity to fearful and angry faces (p = .0048).Genetic variation at ACCN2 appears to be associated with PD and with amygdala phenotypes that have been linked to proneness to anxiety. These results support the possibility that modulation of acid-sensing ion channels may have therapeutic potential for PD.
View details for DOI 10.1016/j.biopsych.2013.12.018
View details for Web of Science ID 000344733200013
View details for PubMedID 24529281
The organization of the human striatum estimated by intrinsic functional connectivity
JOURNAL OF NEUROPHYSIOLOGY
2012; 108 (8): 2242-2263
The striatum is connected to the cerebral cortex through multiple anatomical loops that process sensory, limbic, and heteromodal information. Tract-tracing studies in the monkey reveal that these corticostriatal connections form stereotyped patterns in the striatum. Here the organization of the striatum was explored in the human with resting-state functional connectivity MRI (fcMRI). Data from 1,000 subjects were registered with nonlinear deformation of the striatum in combination with surface-based alignment of the cerebral cortex. fcMRI maps derived from seed regions placed in the foot and tongue representations of the motor cortex yielded the expected inverted somatotopy in the putamen. fcMRI maps derived from the supplementary motor area were located medially to the primary motor representation, also consistent with anatomical studies. The topography of the complete striatum was estimated and replicated by assigning each voxel in the striatum to its most strongly correlated cortical network in two independent groups of 500 subjects. The results revealed at least five cortical zones in the striatum linked to sensorimotor, premotor, limbic, and two association networks with a topography globally consistent with monkey anatomical studies. The majority of the human striatum was coupled to cortical association networks. Examining these association networks further revealed details that fractionated the five major networks. The resulting estimates of striatal organization provide a reference for exploring how the striatum contributes to processing motor, limbic, and heteromodal information through multiple large-scale corticostriatal circuits.
View details for DOI 10.1152/jn.00270.2012
View details for Web of Science ID 000310057500014
View details for PubMedID 22832566
Regulation of NMDA receptor trafficking by amyloid-beta
2005; 8 (8): 1051-1058
Amyloid-beta peptide is elevated in the brains of patients with Alzheimer disease and is believed to be causative in the disease process. Amyloid-beta reduces glutamatergic transmission and inhibits synaptic plasticity, although the underlying mechanisms are unknown. We found that application of amyloid-beta promoted endocytosis of NMDA receptors in cortical neurons. In addition, neurons from a genetic mouse model of Alzheimer disease expressed reduced amounts of surface NMDA receptors. Reducing amyloid-beta by treating neurons with a gamma-secretase inhibitor restored surface expression of NMDA receptors. Consistent with these data, amyloid-beta application produced a rapid and persistent depression of NMDA-evoked currents in cortical neurons. Amyloid-beta-dependent endocytosis of NMDA receptors required the alpha-7 nicotinic receptor, protein phosphatase 2B (PP2B) and the tyrosine phosphatase STEP. Dephosphorylation of the NMDA receptor subunit NR2B at Tyr1472 correlated with receptor endocytosis. These data indicate a new mechanism by which amyloid-beta can cause synaptic dysfunction and contribute to Alzheimer disease pathology.
View details for DOI 10.1038/nn1503
View details for Web of Science ID 000230760200017
View details for PubMedID 16025111