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MSTPublications: October 2019

Posted by on Tuesday, October 29, 2019 in New Publications, Science Advocacy .

Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps.
Bermudez C, Rodriguez W, Huo Y, Hainline AE, Li R, Shults R, D’Haese PD, Konrad PE, Dawant BM, Landman BA.
Proc SPIE Int Soc Opt Eng. 2019 Mar;10949. pii: 1094922. doi: 10.1117/12.2509728.

Deep brain stimulation (DBS) has the potential to improve the quality of life of people with a variety of neurological diseases. A key challenge in DBS is in the placement of a stimulation electrode in the anatomical location that maximizes efficacy and minimizes side effects. Pre-operative localization of the optimal stimulation zone can reduce surgical times and morbidity. Current methods of producing efficacy probability maps follow an anatomical guidance on magnetic resonance imaging (MRI) to identify the areas with the highest efficacy in a population. In this work, we propose to revisit this problem as a classification problem, where each voxel in the MRI is a sample informed by the surrounding anatomy. We use a patch-based convolutional neural network to classify a stimulation coordinate as having a positive reduction in symptoms during surgery. We use a cohort of 187 patients with a total of 2,869 stimulation coordinates, upon which 3D patches were extracted and associated with an efficacy score. We compare our results with a registration-based method of surgical planning. We show an improvement in the classification of intraoperative stimulation coordinates as a positive response in reduction of symptoms with AUC of 0.670 compared to a baseline registration-based approach, which achieves an AUC of 0.627 (p < 0.01). Although additional validation is needed, the proposed classification framework and deep learning method appear well-suited for improving pre-surgical planning and personalize treatment strategies.

 

Heterosynaptic GABAB receptor function within feedforward microcircuits gates glutamatergic transmission in the nucleus accumbens core.
Manz KM, Baxley AG, Zurawski Z, Hamm HE, Grueter BA.
J Neurosci. 2019 Oct 2. pii: 1395-19. doi: 10.1523/JNEUROSCI.1395-19.2019. [Epub ahead of print]

Complex circuit interactions within the nucleus accumbens (NAc) facilitate goal-directed behavior. Medium spiny neurons (MSNs) mediate NAc output by projecting to functionally divergent brain regions, a property conferred, in part, by the differential projection patterns of D1- and D2 dopamine receptor-expressing MSNs. Glutamatergic afferents to the NAc direct MSN output by recruiting feedforward inhibitory microcircuits comprised of parvalbumin (PV)-expressing interneurons (INs). Furthermore, the GABAB heteroreceptor (GABABR), a Gi/o-coupled G protein-coupled receptor, is expressed at glutamatergic synapses throughout the mesolimbic network, yet its physiological context and synaptic mechanism within the NAc remains unknown. Here, we explored GABABR function at glutamatergic synapses within PV-IN-embedded microcircuits in the NAc core of male mice. We found that GABABR is expressed presynaptically and recruits a non-canonical signaling mechanism to reduce glutamatergic synaptic efficacy at D1(+) and D1(-) [putative D2] MSN subtypes. Furthermore, PV-INs, a robust source of neuronal GABA in the NAc, heterosynaptically target GABABR to selectively modulate glutamatergic transmission onto D1(+) MSNs. These findings elucidate a new mechanism of feedforward inhibition and refine mechanisms by which GABAB heteroreceptors modulate mesolimbic circuit function. SIGNIFICANCE STATEMENT: Glutamatergic transmission in the nucleus accumbens (NAc) critically contributes to goal-directed behaviors. However, intrinsic microcircuit mechanisms governing the integration of these synapses remain largely unknown. Here, we show that parvalbumin-expressing interneurons within feedforward microcircuits heterosynaptically target GABAB heteroreceptors (GABABR) on glutamate terminals. Activation of presynaptically-expressedGABABR decreases glutamatergic synaptic strength by engaging a non-canonical signaling pathway that interferes with vesicular exocytotic release machinery. These findings offer mechanistic insight into the role of GABAB heteroreceptors within reward circuitry, elucidate a novel arm to feedforward inhibitory networks, and inform the growing use of GABABR-selective pharmacotherapy for various motivational disorders, including addiction, major depressive disorder, and autism (Cousins, Roberts, & Wit, 2002; Jacobson, Vlachou, Slattery, Li, & Cryan, 2018; Kahn et al., 2009; Pisansky et al., 2019; Stoppel et al., 2018).

 

Additional psychometric properties of the WHODAS-II in individuals with autism spectrum disorder.
Williams ZJ.
Autism Res. 2019 Oct 4. doi: 10.1002/aur.2215. [Epub ahead of print]

A Bifactor Model of the Autism Spectrum Disorder Phenotype.
Williams ZJ.
J Am Acad Child Adolesc Psychiatry. 2019 Oct;58(10):1019-1021. doi: 10.1016/j.jaac.2019.02.021.

Zack Williams (G1) recently published two Lettters to the Editor. In the first letter, he commented on a paper published in Autism Research that was validating a WHO quality of life measure in adults with autism. Using the data published in the paper, he was able to derive a few additional statistics that the authors didn’t report, and these statistics helped guide interpretation of the questionnaire scores. In the second letter published in the Journal of the American Academy of Child and Adolescent Psychiatry, Zack commented on an article that sought to understand the best way to model the symptoms of autism spectrum disorder. The authors claimed that autism could best be seen as three separable dimensions of social impairment, communication impairment, and repetitive behavior. This letter re-analyzed some of the data from that paper, arguing instead that autism can best be understood as a unitary construct rather than three separate ones. You can read the letter here and the authors’ reply here.

 

Joe Luchsinger (G4) published a Career Column on nature.com, sharing his advice on advocating for science investment. Click here to read more!

 

Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury.
Remedios S, Roy S, Blaber J, Bermudez C, Nath V, Patel MB, Butman JA, Landman BA, Pham DL.
Proc SPIE Int Soc Opt Eng. 2019 Mar;10949. pii: 109490A. doi: 10.1117/12.2511997.

Optimizing Mannose “Click” Conjugation to Polymeric Nanoparticles for Targeted siRNA Delivery to Human and Murine Macrophages.
Glass EB, Masjedi S, Dudzinski SO, Wilson AJ, Duvall CL, Yull FE, Giorgio TD.
ACS Omega. 2019 Oct 1;4(16):16756-16767. doi: 10.1021/acsomega.9b01465. eCollection 2019 Oct 15.

Pediatric thoracolumbar spine surgery and return to athletics: a systematic review.
Sellyn GE, Hale AT, Tang AR, Waters A, Shannon CN, Bonfield CM.
J Neurosurg Pediatr. 2019 Sep 27:1-11. doi: 10.3171/2019.7.PEDS19290. [Epub ahead of print] Review.

Single cell transcriptomics reveal polyclonal memory T cell responses in abacavir patch test positive skin.
Redwood AJ, Rwandamuriye F, Chopra A, Leary S, Ram R, McDonnell W, Konvinse K, White K, Pavlos R, Koelle DM, Mallal S, Phillips E.
J Allergy Clin Immunol. 2019 Sep 28. pii: S0091-6749(19)31249-7. doi: 10.1016/j.jaci.2019.09.013. [Epub ahead of print]

Notch1 suppression by microRNA-34a: a new mechanism of calcific aortic valve disease.
Raddatz MA, Vander Roest MJ, Merryman WD.
Cardiovasc Res. 2019 Oct 22. pii: cvz280. doi: 10.1093/cvr/cvz280. [Epub ahead of print] [Invited Editorial]

Perineural Invasion With Thick Sheaths of Basal Cell Carcinoma in a Child After a History of Radiation Exposure.
Rogers MC, Bibee KP, Ogrich LM, Carroll BT.
Dermatol Surg. 2019 Sep 23. doi: 10.1097/DSS.0000000000002156. [Epub ahead of print]

Phosphorylated Hexa-Acyl Disaccharides Augment Host Resistance Against Common Nosocomial Pathogens.
Hernandez A, Luan L, Stothers CL, Patil NK, Fults JB, Fensterheim BA, Guo Y, Wang J, Sherwood ER, Bohannon JK.
Crit Care Med. 2019 Sep 17. doi: 10.1097/CCM.0000000000003967. [Epub ahead of print]