Onur Tanglay

Mr. Onur Tanglay

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2021 in World Neurosurgery
Verified
Journal Article
Closed access
RBRobert G. Briggs
Robert G. Briggs
YLYueh-Hsin Lin
Yueh-Hsin Lin
NDNicholas Dadario
Nicholas Dadario
SKSihyong J. Kim
Sihyong J. Kim
IYIsabella M. Young
Isabella M. Young
Michael Edward SughrueMichael Edward Sughrue
Michael Edward Sughrue

1 April 2021 in World Neurosurgery
Verified
Journal Article
Closed access
YLYueh-Hsin Lin
Yueh-Hsin Lin
VDVukshitha Dhanaraj
Vukshitha Dhanaraj
AMAlana E. Mackenzie
Alana E. Mackenzie
IYIsabella Young
Isabella Young
OTOnur Tanglay
Onur Tanglay
Michael Edward SughrueMichael Edward Sughrue
Michael Edward Sughrue

1 October 2020 in Hearing Research
Verified
Journal Article
Closed access
JKJoseph J. Kuiper
Joseph J. Kuiper
YLYueh-Hsin Lin
Yueh-Hsin Lin
IYIsabella Young
Isabella Young
MBMichael Y. Bai
Michael Y. Bai
RBRobert Briggs
Robert Briggs
Michael Edward SughrueMichael Edward Sughrue
Michael Edward Sughrue

18 February 2021 in Brain and Behavior
Verified
Journal Article
Open access
PDF file
CMCamille K. Milton
Camille K. Milton
VDVukshitha Dhanaraj
Vukshitha Dhanaraj
IYIsabella Young
Isabella Young
HTHugh M. Taylor
Hugh M. Taylor
PNPeter J. Nicholas
Peter J. Nicholas
Michael Edward SughrueMichael Edward Sughrue
Michael Edward Sughrue
Introduction: The semantic network is an important mediator of language, enabling both speech production and the comprehension of multimodal stimuli. A major challenge in the field of neurosurgery is preventing semantic deficits. Multiple cortical areas have been linked to semantic processing, though knowledge of network connectivity has lacked anatomic specificity. Using attentional task‐based fMRI studies, we built a neuroanatomical model of this network.Methods: One hundred and fifty‐five task‐based fMRI studies related to categorization of visual words and objects, and auditory words and stories were used to generate an activation likelihood estimation (ALE). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the semantic network based on the cortical parcellation scheme previously published under the Human Connectome Project. Deterministic fiber tractography was performed on 25 randomly chosen subjects from the Human Connectome Project, to determine the connectivity of the cortical parcellations comprising the network.Results: The ALE analysis demonstrated fourteen left hemisphere cortical regions to be a part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. These regions showed consistent interconnections between parcellations. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model.Conclusions: We describe a preliminary cortical model for the underlying structural connectivity of the semantic network. Future studies will further characterize the neurotractographic details of the semantic network in the context of medical application.

18 December 2020 in Brain and Behavior
Verified
Journal Article
Open access
PDF file
ZSZainab Sandhu
Zainab Sandhu
OTOnur Tanglay
Onur Tanglay
IYIsabella Young
Isabella Young
RBRobert G. Briggs
Robert G. Briggs
MBMichael Y. Bai
Michael Y. Bai
Michael Edward SughrueMichael Edward Sughrue
Michael Edward Sughrue
Background: The default mode network (DMN) is an important mediator of passive states of mind. Multiple cortical areas, such as the anterior cingulate cortex, posterior cingulate cortex, and lateral parietal lobe, have been linked in this processing, though knowledge of network connectivity had limited tractographic specificity.Methods: Using resting‐state fMRI studies related to the DMN, we generated an activation likelihood estimation (ALE). We built a tractographical model of this network based on the cortical parcellation scheme previously published under the Human Connectome Project. DSI‐based fiber tractography was performed to determine the structural connections between cortical parcellations comprising the network.Results: Seventeen cortical regions were found to be part of the DMN: 10r, 31a, 31pd, 31pv, a24, d23ab, IP1, p32, POS1, POS2, RSC, PFm, PGi, PGs, s32, TPOJ3, and v23ab. These regions showed consistent interconnections between adjacent parcellations, and the cingulum was found to connect the anterior and posterior cingulate clusters within the network.Conclusions: We present a preliminary anatomic model of the default mode network. Further studies may refine this model with the ultimate goal of clinical application.

22 June 2022 in Brain and Behavior
Verified
Journal Article
Open access
RBRobert G. Briggs
Robert G. Briggs
IYIsabella M. Young
Isabella M. Young
NDNicholas Dadario
Nicholas Dadario
RFR. Dineth Fonseka
R. Dineth Fonseka
JHJorge Hormovas
Jorge Hormovas
Michael Edward SughrueMichael Edward Sughrue
Michael Edward Sughrue
Background: The salience network (SN) is a transitory mediator between active and passive states of mind. Multiple cortical areas, including the opercular, insular, and cingulate cortices have been linked in this processing, though knowledge of network connectivity has been devoid of structural specificity.Objective: The current study sought to create an anatomically specific connectivity model of the neural substrates involved in the salience network.Methods: A literature search of PubMed and BrainMap Sleuth was conducted for resting‐state and task‐based fMRI studies relevant to the salience network according to PRISMA guidelines. Publicly available meta‐analytic software was utilized to extract relevant fMRI data for the creation of an activation likelihood estimation (ALE) map and relevant parcellations from the human connectome project overlapping with the ALE data were identified for inclusion in our SN model. DSI‐based fiber tractography was then performed on publicaly available data from healthy subjects to determine the structural connections between cortical parcellations comprising the network.Results: Nine cortical regions were found to comprise the salience network: areas AVI (anterior ventral insula), MI (middle insula), FOP4 (frontal operculum 4), FOP5 (frontal operculum 5), a24pr (anterior 24 prime), a32pr (anterior 32 prime), p32pr (posterior 32 prime), and SCEF (supplementary and cingulate eye field), and 46. The frontal aslant tract was found to connect the opercular‐insular cluster to the middle cingulate clusters of the network, while mostly short U‐fibers connected adjacent nodes of the network.Conclusion: Here we provide an anatomically specific connectivity model of the neural substrates involved in the salience network. These results may serve as an empiric basis for clinical translation in this region and for future study which seeks to expand our understanding of how specific neural substrates are involved in salience processing and guide subsequent human behavior.