About

Shana Cooper is an Associate Professor in the Department of Theatre at Northwestern University School of Communication. Her most recent project is the world premiere of Kate Hamill's The Odyssey at A.R.T. in Cambridge. Her directing credits include classics and new work across the country, including New York, the Oregon Shakespeare Festival, Chicago Shakespeare Theater, The Old Globe, American Conservatory Theater, Yale Repertory Theatre, Woolly Mammoth, Hudson Valley Shakespeare Festival, Court Theatre in Chicago, Studio Theater, Seattle Repertory Theatre, California Shakespeare Theater, and Playmakers Repertory Company. Ms. Cooper is an assistant professor in Northwestern University's Directing M.F.A. program, where she serves as a faculty lead for The Rehearsal Dinner. She is also a faculty member at Woolly Mammoth Theatre in Washington D.C., and has served as Associate Artistic Director of Cal Shakes and Co-Founder of New Theater House. She received her MFA from Yale School of Drama and has been recognized with awards including a 2014 Leadership U Grant funded by The Andrew W. Mellon Foundation, a 2010 Princess Grace Award, a Julian Milton Kaufman Memorial Prize from Yale School of Drama, and a Drama League Directing Fellowship. Her upcoming projects include directing Winter's Tale at American Players Theater.

Research topics

• Oncology
• Psychiatry
• Audiology
• Internal medicine
• Biology
• Psychology
• Medicine

Selected publications

• The human olfactory amygdala: Anatomical connections between the olfactory bulb and amygdala subregions

  Imaging Neuroscience · 2025-01-01 · 3 citations

  articleOpen access

  The human olfactory bulb is thought to send direct monosynaptic projections to the amygdala, though anatomical evidence for this is scant. Here, we applied a specialized diffusion-weighted magnetic resonance imaging protocol optimized for olfactory brain areas to systematically quantify connections between the olfactory bulb and the amygdala in 25 healthy human participants. We found that the olfactory bulb exhibits a higher density of streamline connections to the medial nucleus, the anterior cortical nucleus, the central nucleus, and the periamygdala complex compared to the basomedial nucleus, the basolateral nucleus, the lateral nucleus, and the posterior cortical nucleus. We used k-means clustering algorithms to confirm these results by performing a data-driven grouping of amygdala subregions into those that connect to the olfactory bulb and those that do not. We further found that olfactory amygdala subregions and non-olfactory amygdala subregions exhibit different structural connectivity patterns with the rest of the brain. Our findings provide confirmatory evidence that a set of amygdala subnuclei-medial nucleus, anterior cortical nucleus, central nucleus, and periamygdala complex-communicate with the olfactory bulb and contribute to primary olfactory processing in humans.

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• Anatomical connectivity-based parcellation of the human orbitofrontal cortex.

  Behavioral Neuroscience · 2025-07-10 · 2 citations

  articleOpen access1st authorCorresponding

  The orbitofrontal cortex (OFC) is critical for learning and decision making, but its organization in terms of anatomical connections to other brain areas is not well understood in humans. Here we used diffusion magnetic resonance imaging and probabilistic tractography to characterize the cortical and subcortical white matter connections of the human OFC. We found widespread connectivity of the OFC with frontal and temporal cortices, anterior cingulate, insula, olfactory cortex, as well as the striatum, hippocampus, amygdala, and thalamic nuclei. We then used k-means clustering to parcellate the OFC into different subregions based on these connections, revealing a medial-lateral division with two clusters, and a separation into medial, lateral-anterior, and lateral-posterior subdivisions with three clusters. Higher order parcellations revealed more complex subdivisions mirroring cytoarchitectural boundaries of the primate OFC. Analysis of the white matter connectivity of the medial and lateral OFC clusters revealed differences in their connectivity patterns with frontal cortices, insula, olfactory cortex, anterior cingulate cortex, as well as the striatum and several thalamic nuclei. In addition, lateral-anterior and lateral-posterior OFC clusters showed different connectivity strengths with several frontal cortices, anterior cingulate cortex, insula, and the caudate. These findings suggest parallels between the anatomical organization of the human and macaque OFC and may help to elucidate how the OFC contributes to adaptive behavior. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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• Evaluation of the NIH Toolbox Odor Identification Test across normal cognition, amnestic mild cognitive impairment, and dementia due to Alzheimer's disease

  Alzheimer s & Dementia · 2023 · 5 citations

  1st authorCorresponding
  • Medicine
  • Internal medicine
  • Audiology

  INTRODUCTION: Olfactory decline is associated with cognitive decline in aging, amnestic mild cognitive impairment (aMCI), and amnestic dementia associated with Alzheimer's disease neuropathology (ADd). The National Institutes of Health Toolbox Odor Identification Test (NIHTB-OIT) may distinguish between these clinical categories. METHODS: We compared NIHTB-OIT scores across normal cognition (NC), aMCI, and ADd participants (N = 389, ≥65 years) and between participants positive versus negative for AD biomarkers and the APOE ε4 allele. RESULTS: NIHTB-OIT scores decreased with age (p < 0.001) and were lower for aMCI (p < 0.001) and ADd (p < 0.001) compared to NC participants, correcting for age and sex. The NIHTB-OIT detects aMCI (ADd) versus NC participants with 49.4% (56.5%) sensitivity and 88.8% (89.5%) specificity. NIHTB-OIT scores were lower for participants with positive AD biomarkers (p < 0.005), but did not differ based on the APOE ε4 allele (p > 0.05). DISCUSSION: The NIHTB-OIT distinguishes clinically aMCI and ADd participants from NC participants. HIGHLIGHTS: National Institutes of Health Toolbox Odor Identification Test (NIHTB-OIT) discriminated normal controls from mild cognitive impairment. NIHTB-OIT discriminated normal controls from Alzheimer's disease dementia. Rate of olfactory decline with age was similar across all diagnostic categories. NIHTB-OIT scores were lower in participants with positive Alzheimer's biomarker tests. NIHTB-OIT scores did not differ based on APOE genotype.

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• The role of memory in addiction: a commentary on Bornstein and Pickard memory sampling theory

  Neuropsychopharmacology · 2020-01-31 · 4 citations

  letterOpen access1st authorCorresponding
  PublisherOA PDFDOI

• Characterizing functional pathways of the human olfactory system

  eLife · 2019-07-24 · 211 citations

  articleOpen access

  The central processing pathways of the human olfactory system are not fully understood. The olfactory bulb projects directly to a number of cortical brain structures, but the distinct networks formed by projections from each of these structures to the rest of the brain have not been well-defined. Here, we used functional magnetic resonance imaging and k-means clustering to parcellate human primary olfactory cortex into clusters based on whole-brain functional connectivity patterns. Resulting clusters accurately corresponded to anterior olfactory nucleus, olfactory tubercle, and frontal and temporal piriform cortices, suggesting dissociable whole-brain networks formed by the subregions of primary olfactory cortex. This result was replicated in an independent data set. We then characterized the unique functional connectivity profiles of each subregion, producing a map of the large-scale processing pathways of the human olfactory system. These results provide insight into the functional and anatomical organization of the human olfactory system.

  PublisherDOI

• Author response: Characterizing functional pathways of the human olfactory system

  2019-06-19

  peer-reviewOpen access

  Article Figures and data Abstract Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract The central processing pathways of the human olfactory system are not fully understood. The olfactory bulb projects directly to a number of cortical brain structures, but the distinct networks formed by projections from each of these structures to the rest of the brain have not been well-defined. Here, we used functional magnetic resonance imaging and k-means clustering to parcellate human primary olfactory cortex into clusters based on whole-brain functional connectivity patterns. Resulting clusters accurately corresponded to anterior olfactory nucleus, olfactory tubercle, and frontal and temporal piriform cortices, suggesting dissociable whole-brain networks formed by the subregions of primary olfactory cortex. This result was replicated in an independent data set. We then characterized the unique functional connectivity profiles of each subregion, producing a map of the large-scale processing pathways of the human olfactory system. These results provide insight into the functional and anatomical organization of the human olfactory system. https://doi.org/10.7554/eLife.47177.001 Introduction The human sense of smell serves a variety of important functions in everyday life (Bushdid et al., 2014; Devanand et al., 2015; McGann, 2017). It is used to monitor the safety of inhaled air (Pence et al., 2014) and edibility of food (Yeomans, 2006). It also strongly impacts our social and emotional lives (Durand et al., 2013; Endevelt-Shapira et al., 2018; Frumin et al., 2015; Gelstein et al., 2011; Krusemark et al., 2013; Walla, 2008; Walla et al., 2003). Thus, the brain must extract different types of information from odor stimuli, including information about the identities of objects and foods, environmental hazards, and social and emotional cues. These functions are likely carried out by distinct cortical networks within the olfactory system, yet the organization of these functional networks is not fully understood. This incomplete understanding is due partly to ambiguity about the anatomical and functional properties of the cortical targets of human olfactory bulb projections. Collectively, these areas are commonly referred to as primary olfactory cortex (Carmichael et al., 1994; Feher and Feher, 2017; Gottfried, 2010; Mai and Paxinos, 2012; Price, 2009) (although see Wilson, 2009; Haberly, 2001; Chapuis and Wilson, 2011 and others for discussions of the accuracy of this definition of the pirmary olfactory cortex). In humans, this includes the anterior olfactory nucleus, the olfactory tubercle, the frontal and temporal piriform cortices, and subregions of both the amygdala and entorhinal cortex (Allison, 1954; Eslinger et al., 1982; Gonçalves Pereira et al., 2005; Insausti et al., 2002; Milardi et al., 2017). The fact that the olfactory bulb simultaneously projects directly to a number of structures suggests parallel functional pathways in the olfactory system (Haberly, 2001; Kauer, 1991), but the distinct roles of these primary olfactory areas and their functional pathways are not fully understood (Bensafi et al., 2007; Gottfried et al., 2006; Gottfried et al., 2004; Gottfried et al., 2002; Howard et al., 2009; Li et al., 2008; Li et al., 2006; Sobel et al., 2000; Sobel et al., 1999; Zelano et al., 2005). Additionally, the olfactory system is organized differently than other sensory systems, which contain pre-cortical thalamic relays, further suggesting a deeper understanding of the organization of olfactory networks in the human brain is warranted. The vast majority of research on primary olfactory cortex has focused on piriform cortex, which is the largest recipient of bulbar projections. Most of this research has been conducted in rodents, where piriform cortex is divided into anatomically and functionally distinct anterior and posterior subdivisions (Calu et al., 2007; Grau-Perales et al., 2019; Haberly and Price, 1978; Stettler and Axel, 2009; Yang et al., 2017). In humans, the anatomy and functionality of piriform cortex is less understood. Although it can be divided into frontal- and temporal-lobe subregions (Mai et al., 2015; Vaughan and Jackson, 2014; Young et al., 2018; Allison, 1954), whether these correspond to rodent anterior and posterior subdivisions is unclear. While neuroimaging studies have pointed to functional heterogeneity within human piriform cortex (Bensafi, 2012; Fournel et al., 2016; Gottfried et al., 2002; Howard et al., 2009; Howard and Gottfried, 2014; Li et al., 2008; Porter et al., 2005; Seubert et al., 2013; Zelano et al., 2011; Zelano et al., 2005), its anatomical and functional distinctions are still not clearly defined. While numerous rodent and human studies have focused on piriform cortex, far fewer have examined other primary olfactory structures, such as the anterior olfactory nucleus and the olfactory tubercle. These structures have been anatomically well-defined in rodents (Aqrabawi and Kim, 2018a; Haberly and Price, 1978; Shipley and Adamek, 1984), primates (Carmichael et al., 1994), and humans (Allison, 1954; Eslinger et al., 1982; Mai et al., 2015), but their roles in olfactory processing are not fully understood in any of these species (Gadziola et al., 2015; Wesson and Wilson, 2011). Recent rodent data suggest that the anterior olfactory nucleus may be involved in odor memory (Aqrabawi and Kim, 2018b; Oettl et al., 2016) and localization (Kikuta et al., 2010), and the olfactory tubercle may play an important role in multisensory integration and attention (Wesson and Wilson, 2010; Zelano et al., 2005), although a complete understanding of the functions of these areas is lacking. Previous studies have used task-related and resting functional magnetic resonance imaging (fMRI) to examine olfactory networks, using primary olfactory and orbitofrontal cortices as seed regions (Banks et al., 2016; Cecchetto et al., 2019; Fjaeldstad et al., 2017; Karunanayaka et al., 2017; Karunanayaka et al., 2014; Kiparizoska and Ikuta, 2017; Kollndorfer et al., 2015; Krusemark and Li, 2012; Nigri et al., 2013; Sreenivasan et al., 2017; Sunwoo et al., 2015). These studies have contributed important broad knowledge of parallel olfactory networks (Karunanayaka et al., 2014), how they compare to trigeminal networks (Karunanayaka et al., 2017), and how they change with age (Wang et al., 2005) and disease (Caffo et al., 2010; Fjaeldstad et al., 2017; Killgore et al., 2013; Sunwoo et al., 2015; Wang et al., 2010; Wang et al., 2015). However, the functional connectivity profiles of the primary olfactory subregions have not been considered separately. This is important because these subregions, which receive direct and parallel input from the bulb, likely form the anatomical substrates of ethological, parallel olfactory networks. Therefore, a quantitative characterization of the distinct functional pathways of human primary olfactory subregions would be an important step toward understanding the large-scale networks that underlie the basic, parallel, purposes of olfactory processing. The discovery of unique whole-brain connectivity profiles for the different primary olfactory subregions could also provide insight into the nature of the distinct functions of these areas in olfactory perception. This information, in turn, could have clinical implications for diseases that impact particular primary olfactory subregions. Thus, the goals of this study were two-fold: first, to test the hypothesis that primary olfactory subregions form distinct large-scale olfactory processing networks; and second, if so, to characterize these networks across the whole brain. For the first, we used well-established, unsupervised k-means clustering techniques (Eickhoff et al., 2018; Kahnt et al., 2012; Kahnt and Tobler, 2017; Wang et al., 2017), to parcellate primary olfactory cortex into distinct clusters based solely on whole-brain connectivity patterns. We reasoned that if whole-brain functional connectivity patterns alone could be used to accurately parcellate primary olfactory cortex into its established, anatomically-defined subregions, this would suggest that these subregions do in fact form distinct functional pathways. We also reasoned that if these parcellation results were robust, the results should replicate in an independent data set. For the second, we characterized the distinct functional connectivity patterns of each primary olfactory subregion in order to produce a whole-brain map of the networks formed by each area. Our results provide insight into the functional and anatomical organization of the human olfactory system and provide a basis for future investigation into the functions of the distinct cortical targets of the olfactory bulb. Results We used resting-state fMRI connectivity to examine the functional pathways of human primary olfactory cortex in two main steps. First, we used k-means clustering techniques to parcellate primary olfactory cortex into distinct clusters. These clusters were based on the group-level, whole-brain functional connectivity of all voxels within primary olfactory cortex, separately for each hemisphere. Second, using the results of the parcellation analysis, we characterized the distinct, large-scale networks of the human olfactory system. To do this, we first determined that there were no hemispheric differences in the connectivity profiles of primary olfactory subregions, suggesting we should combine corresponding clusters across the left and right hemispheres. We then quantified the whole-brain functional networks that were unique to each subdivision, and those that were common to all subdivisions. Finally, as a discussion point, we considered the functional properties of connected brain areas for each primary olfactory subdivision and attempted to form a speculative hypothetical model of human olfactory functional networks. Parcellation of human primary olfactory cortex To test the hypothesis that primary olfactory subregions form distinct, large-scale olfactory networks, we tested whether their anatomical boundaries could be accurately delineated based on whole-brain functional connectivity maps. To do this, we conducted a functional-connectivity-based parcellation of human primary olfactory cortex. Twenty-five subjects (average ± standard error age: 25.5 ± 1.2 years; 14 female) underwent a 10 min resting-state fMRI scan. We first outlined the entirety of primary olfactory cortex into a combined region-of-interest (ROI) on which to perform the k-means clustering analysis. This ROI was drawn for the left and right hemispheres separately, according to a human brain atlas which contains detailed demarcation of most primary olfactory areas (Mai et al., 2015; Ongür et al., 2003) (Figure 1A). The ROI included only those subregions with detailed boundaries in the atlas, and consisted of a combination of the anterior olfactory nucleus, olfactory tubercle, and frontal and temporal piriform cortices (Figure 1B), defined based on Mai et al. (2015). Note that additional primary olfactory areas, including amygdala and entorhinal cortex (Allison, 1954; Carmichael et al., 1994; Eslinger et al., 1982; Gonçalves Pereira et al., 2005; Zatorre et al., 1992), were not included in our ROI because the exact location of olfactory afferents into these areas is poorly understood (Gonçalves Pereira et al., 2005). This is an important topic for future investigation of human olfactory networks. Figure 1 Download asset Open asset Region of interest. (A) Panels show examples from the human brain atlas used to define the region of interest used in the parcellation analysis. Relevant areas include the anterior olfactory nucleus (AON), olfactory tubercle (TUB), and frontal (PirF) and temporal (PirT) piriform cortex (Mai et al., 2015). (B) The region of interest shown overlaid on the FSL's MNI152_T1_1mm_brain. The coronal and axial slices correspond to the vertical and horizontal lines on the sagittal slice respectively. R, right hemisphere. https://doi.org/10.7554/eLife.47177.002 Figure 1—source data 1 Relates to Figure 1. Atlas and region-of-interest of the human primary olfactory cortex. https://doi.org/10.7554/eLife.47177.003 Download elife-47177-fig1-data1-v1.zip We then estimated the whole-brain functional connectivity profile of each voxel within the ROI by computing the Pearson correlation coefficient between the resting-state fMRI time-series of a given voxel and that of every other voxel in the rest of the brain. This resulted in subject-wise connectivity matrices. We then performed a leave-one-out analysis (Kahnt et al., 2012) to estimate the stability of the connectivity profiles of individual primary olfactory cortex voxels across participants, as a prerequisite for averaging the connectivity matrices across subjects (Figure 2A). To examine the similarity between the individual functional connectivity matrices, we computed a histogram of correlation values between individual matrices and the group matrix. The histogram of correlation values showed that the similarity of connectivity patterns was above zero in all voxels in primary olfactory cortex (mean correlation coefficient: 0.19, standard error: 0.0041), justifying averaging across subjects. Note that because they are computed across rest-of-the-brain voxels, R values larger than 0.0088 are statistically significant at p<0.05 (Bonferroni corrected for the number of voxels in primary olfactory cortex). To parcellate within-ROI voxels into subdivisions based on their whole-brain functional connectivity profiles, we applied unsupervised k-means clustering methods to the average connectivity matrix. We used a priori k = 4 based on the fact that our ROI was comprised of four anatomically distinct brain regions. For both the left and right hemispheres, this analysis successfully parcellated the primary olfactory cortex ROI into four distinct brain regions that corresponded anatomically to the anterior olfactory nucleus, olfactory tubercle, and frontal and temporal piriform cortices (Figure 2B). Figure 2 with 2 supplements see all Download asset Open asset Parcellation of human left and right primary olfactory cortex. (A) Inter-subject stability of functional connectivity patterns. The correlation of the functional connectivity patterns between each subject and all other subjects was calculated for each voxel using a leave-one-out method. The coronal slices, corresponding to the vertical lines on the sagittal slice, show the average stability map. The bar plot shows the histogram of the correlation values. (B) k-means (k = 4) clustering results shown on the FSL's MNI152_T1_1mm_brain. The right column shows one axial and one coronal slice of the Atlas (Mai et al., 2015). (C) Parcellation accuracy of each subregion. Left column: proportion of voxels from each parcellation subdivision located within each anatomical subregion. Right column: z score of the proportion maps. * indicates p<0.001 (false discovery rate corrected). R, right hemisphere; AON, anterior olfactory tubercle; TUB, olfactory tubercle; PirF, frontal piriform cortex; PirT, temporal piriform cortex. https://doi.org/10.7554/eLife.47177.004 Figure 2—source data 1 Relates to Figure 2, panel (A). Correlation between individual and group-level (leave-one-out) connectivity profiles. https://doi.org/10.7554/eLife.47177.008 Download elife-47177-fig2-data1-v1.zip Figure 2—source data 2 Relates to Figure 2, panel (B) and (C). Manual segmentation and parcellation of the human primary olfactory cortex. https://doi.org/10.7554/eLife.47177.009 Download elife-47177-fig2-data2-v1.zip To confirm the correspondence between our parcellation results and the anatomical delineation of primary olfactory subregions in the Atlas of the Human Brain (Mai et al., 2015), we computed the proportion of voxels from each parcellation cluster located within each of the atlas-derived subdivisions, drawn prior to performing the parcellation analysis (Figure 2B). The statistical significance of this proportion was tested using a permutation test. Specifically, for each permutation, we shuffled the labels of the anatomical subdivision and re-calculated the proportion. This procedure was repeated 10,000 times, resulting in a distribution of permuted proportions for each parcellation cluster. A z score of the actual proportion values was computed by subtracting the average and then dividing by the standard deviation, which was obtained by normal distribution fitting of the permuted data (Matlab's normfit). We found that for each parcellated subdivision, there was one anatomical ROI that contained significantly more voxels than the other anatomical ROIs (Figure 2C, minimal z score = 7.18). Thus, we found that the location of voxels within each parcellated subdivision corresponded to a single anatomically-determined ROI. Specifically, the medial-rostral-most parcellated subdivision corresponded to the anterior olfactory nucleus. The adjacent caudal subdivision corresponded to the olfactory tubercle. Within the frontal lobe, the lateral-rostral subdivision corresponded to the frontal piriform cortex, and within the temporal lobe, the caudal-most subdivision corresponded to temporal piriform cortex. Replication of parcellation results To confirm the robustness of our parcellation results, we performed two control analyses aimed at replicating the initial findings. First, we performed the k-means clustering analysis on a different ROI of primary olfactory cortex, drawn independently by one of the co-authors of this paper. Second, we performed the k-means clustering analysis on an independent data set (N = 53), collected for a previous study on a different scanner, with different acquisition parameters and different subjects (Kahnt and Tobler, 2017). In the first control analysis, performed on an independently drawn ROI, we found that k-means clustering still successfully parcellated primary olfactory cortex into four distinct regions, corresponding anatomically to the anterior olfactory nucleus, olfactory tubercle, and frontal and temporal piriform cortices (Figure 2—figure supplement 1A,B). In our second control analysis, performed on an independent data set, we found that, again, primary olfactory cortex successfully parcellated into the same four distinct regions (Figure 2—figure supplement 1C,D). Importantly, all analysis steps performed on this independent data set were identical to those performed in our initial analysis. These results suggest good reliability of our finding that human olfactory cortex can be accurately parcellated based on whole-brain functional connectivity patterns. Parcellation results across hemispheres and k values Thus far, we demonstrated that both the left and right primary olfactory areas can be accurately subdivided based on their functional connectivity profiles. To further examine differences between the left and right hemispheres and at different k values, we conducted additional parcellation analyses using a single primary olfactory ROI containing all subregions from both hemispheres, at a range of k values. We reasoned that if connectivity patterns were similar across hemispheres for each subregion, then parcellation analysis of this combined ROI should group left and right sides of each primary olfactory subregion, as opposed to grouping, for example, the neighboring subregions on the same hemisphere. We computed this analysis using k values ranging from 3 to 6 (Figure 3). We found that for a k value of 3, the parcellation analysis grouped left and right anterior olfactory nucleus and left tubercle as one cluster, left and right frontal piriform cortex and left temporal piriform cortex as a second cluster, and right temporal piriform cortex alone as the third cluster. For a k value of 4, the analysis successfully grouped left and right hemispheres for both piriform subregions, but it grouped left anterior olfactory nucleus with left olfactory tubercle and right anterior olfactory nucleus with right olfactory tubercle, suggesting these two primary olfactory areas have relatively more lateralized connectivity patterns. A k value of 5 grouped the left and right hemispheres of all subregions, with a fifth cluster consisting of only right temporal piriform cortex. Finally, a k value of 6 grouped all subregions across hemispheres except for the anterior olfactory nucleus. These results indicate a clear separation of frontal and temporal piriform cortex for a wide range of cluster solutions and even across hemispheres (Figure 3A). All parcellation results showed good agreement with the anatomical subregions (Figure 3B,C). Of note, the anterior olfactory nucleus and olfactory tubercle are classified as one subregion for a clustering solution of k = 3. The left and right anterior olfactory nucleus were separated into different subregions for k = 4, 6. These findings suggest stronger lateralization of connectivity patterns for the anterior olfactory nucleus compared to other primary olfactory areas. Figure 3 Download asset Open asset Parcellation of primary olfactory cortex combined across left and right hemispheres. (A) k-means clustering results shown on the FSL's MNI152_T1_1mm_brain for k = 3 to 6. Each color represents one cluster. (B) Proportion of voxels of each parcellation subdivision within each anatomical subregion. (C) z score of the proportion maps in panel B. * indicates p<0.001 (false discovery rate corrected). L, left hemisphere; R, right hemisphere; AON, anterior olfactory tubercle; TUB, olfactory tubercle; PirF, frontal piriform cortex; PirT, temporal piriform cortex. https://doi.org/10.7554/eLife.47177.010 Figure 3—source data 1 Relates to Figure 3. Parcellation result (k = 3 to 6) of left and right hemispheres combined ROI. https://doi.org/10.7554/eLife.47177.011 Download elife-47177-fig3-data1-v1.zip Primary olfactory cortical functional connectivity does not statistically differ between hemispheres Our next step was to examine the whole-brain functional connectivity profiles of the different primary olfactory subregions. Prior to performing this analysis, we first determined whether to use hemispherically combined clusters, or hemispherically distinct clusters. We reasoned that if connectivity profiles of left and right primary olfactory areas did not statistically differ, then they should not be analyzed separately. We therefore conducted a lateralization-index analysis to directly statistically compare connectivity patterns across hemispheres. The lateralization index was defined as (Zleft – Zright)/(Zleft + Zright), where Zleft and Zright were the functional connectivity maps for the left and right seed regions, respectively. We found no statistically significant difference between whole-brain connectivity maps for the corresponding left and right primary olfactory subregions (Figure 4—figure supplement 1) (threshold-free cluster enhancement (TFCE) corrected p>0.001). Based on this result, all proceeding analyses were conducted using combined ROIs of corresponding left and right subregions. Distinct whole-brain human olfactory networks The fact that primary olfactory subregions were accurately anatomically parcellated based on their functional connectivity profiles suggests that they form distinct, parallel olfactory networks. To examine these functional networks, we produced whole-brain maps of the non-overlapping brain areas exhibiting functional connectivity with each subregion. To do this, we first applied a statistical threshold to the whole-brain functional connectivity map for each subregion (TFCE corrected p<0.001), and binarized them (assigned a value of 1 or 0). This resulted in four distinct whole-brain maps. We then further masked them according to whether each voxel exhibited statistically significant functional connectivity with a single subregion or with multiple subregions. This produced two maps of functional connectivity: one with the unique connectivity patterns for each subregion, and the other with connectivity patterns shared by multiple subregions. The complete list of areas showing subregion-specific connectivity is contained in Table 1. Table 1 Summary of functional connectivity results. https://doi.org/10.7554/eLife.47177.012 Volume (mm3)LabelOverlapAONTUBPirFPirTFrontal Orbital Cortex25923000144-1048Frontal Medial Cortex9921120---Cingulate Gyrus2760200802304-Insular Cortex384496-224832Subcallosal Cortex3632616---Caudate136120-2024-Paracingulate Gyrus1336-2600--Parahippocampal Gyrus296-464-2584Temporal Pole328---9184Putamen1368--337696Hippocampus1176--1361448Amygdala2120----Accumbens336----Planum Polare-248--480Frontal Pole-27921504-736Temporal Fusiform Cortex-688352-1240Inferior Frontal Gyrus-208---Inferior Temporal Gyrus-1224--248Heschl's Gyrus (includes H1 and H2)-80--208Planum Temporale-104--96Brainstem--592-6056Thalamus--1201384-Pallidum---504-Precentral Gyrus---1616-Postcentral Gyrus---216296Frontal Operculum Cortex---128336Central Opercular Cortex---224376Supramarginal Gyrus---808-Juxtapositional Lobule Cortex---1104-Superior Frontal Gyrus----128Temporal Occipital Fusiform Cortex----344Superior Temporal Gyrus----1464Middle Temporal Gyrus----1368Angular Gyrus----256Parietal Operculum Cortex----640 The volumes of statistically significant voxels in each brain region are shown for overlapping and subregion-specific clusters. The Overlap column does not include subregion-specific regions. - indicates volume less than 80 mm3 (10 voxels). Atlas query was conducted with FSL's HarvardOxford-cort-maxprob-thr50-2mm and HarvardOxford-sub-maxprob-thr50-2mm atlases. AON, anterior olfactory nucleus; TUB, olfactory tubercle; PirF, frontal piriform cortex; PirT, temporal piriform cortex. Table 1—source data 1 Functional connectivity profile of each subregion. https://doi.org/10.7554/eLife.47177.013 Download elife-47177-table1-data1-v1.xlsx Below, we outline the unique connectivity patterns we found for each primary olfactory subregion. Functional connectivity profiles of anterior olfactory nucleus and olfactory tubercle The brain areas that showed connectivity unique to the anterior olfactory nucleus were largest in the orbitofrontal cortex, with smaller clusters in the left inferior temporal gyrus, bilateral anterior temporal gyri, the bilateral anterior insula and the mammillary bodies and retromammillary commissure (Figure 4A,E). Areas of connectivity in the orbitofrontal cortex were extensive, including the entire gyrus rectus and encompassing parts of the medial, anterior and lateral orbital gyri. Notably, there was a cluster of connectivity corresponding to bilateral areas the orbital to its with the orbital is significant because this of orbitofrontal cortex is referred to as human olfactory cortex and 2005). with the left inferior temporal gyrus was a posterior region the were also clusters in the bilateral anterior temporal gyri, and the bilateral anterior in cortex. Finally, there was a cluster the region between the mammillary the retromammillary commissure and the posterior nucleus. Figure 4 with 1 supplement see all Download asset Open asset functional connectivity patterns. Brain regions that are connected to each of the primary olfactory subregions including the (A) anterior olfactory nucleus (B) olfactory tubercle (C) frontal piriform cortex and temporal piriform cortex The results are shown on the FSL's MNI152_T1_1mm_brain. Functional connectivity maps shown on brain for AON, TUB, and All functional connectivity maps were at cluster enhancement corrected L, left hemisphere; posterior nucleus; inferior temporal orbitofrontal cortex; cortex; retromammillary nucleus; frontal anterior cortex; temporal area. Figure data 1 Relates to Figure of the functional connectivity of human primary olfactory cortex subregions. Download The brain areas that exhibited connectivity unique to the olfactory tubercle were largest in the cortex, with smaller clusters in the the left temporal cortex, the nucleus of the and the (Figure between the olfactory tubercle and the

  PublisherDOI

• Working Memory Systems in the Rat

  Current Biology · 2016-01-15 · 35 citations

  articleOpen access
  PublisherOA PDFDOI

• Erratum: Cross-talking noncoding RNAs contribute to cell-specific neurodegeneration in SCA7 (Nature Structural and Molecular Biology (2014) 21 (955-961))

  Nature Structural & Molecular Biology · 2015-01-01 · 8 citations

  erratum
  Publisher

Frequent coauthors

• Thorsten Kahnt

  National Institute on Drug Abuse

  4 shared

• Guangyu Zhou

  Beihang University

  2 shared

• Christina Zelano

  Northwestern University

  2 shared

• Austin Dunn

  Indiana University Bloomington

  1 shared

• Richard Gershon

  Northwestern University

  1 shared

• Amanda R. Doyle

  Indiana University Bloomington

  1 shared

• Jonathon D. Crystal

  Indiana University

  1 shared

• Emily Ho

  Northwestern University

  1 shared

Education

• PhD, Neurology

  Northwestern University - Chicago

  2022

• BA, BS, Department of Psychological and Brain Sciences

  Indiana University Bloomington

  2017

Awards & honors

• 2014 Leadership U Grant, funded by The Andrew W. Mellon Foun…
• 2010 Princess Grace Award
• Julian Milton Kaufman Memorial Prize from Yale School of Dra…
• Drama League Directing Fellowship