Browsing by Author "Bartoli, Eleonora"

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    A biophysically constrained brain connectivity model based on stimulation-evoked potentials.
    (Elsevier, 2024) Schmid, William; Danstrom, Isabel A.; Crespo Echevarria, Maria; Adkinson, Joshua; Mattar, Layth; Banks, Garrett P.; Sheth, Sameer A.; Watrous, Andrew J.; Heilbronner, Sarah R.; Bijanki, Kelly R.; Alabastri, Alessandro; Bartoli, Eleonora
    Background Single-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. New method Using intracranial electrophysiology data recorded from a single patient undergoing stereo-electroencephalography (sEEG) evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D electrical conductivity to infer neural pathways from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. Results The proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlated with additional PEP features and displayed stable, weak correlations with tractography measures. Comparison with existing method Existing methods for estimating neural signal pathways are imaging-based and thus rely on anatomical inferences. Conclusions These results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.
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    Beta activity in human anterior cingulate cortex mediates reward biases
    (Springer Nature, 2024) Xiao, Jiayang; Adkinson, Joshua A.; Myers, John; Allawala, Anusha B.; Mathura, Raissa K.; Pirtle, Victoria; Najera, Ricardo; Provenza, Nicole R.; Bartoli, Eleonora; Watrous, Andrew J.; Oswalt, Denise; Gadot, Ron; Anand, Adrish; Shofty, Ben; Mathew, Sanjay J.; Goodman, Wayne K.; Pouratian, Nader; Pitkow, Xaq; Bijanki, Kelly R.; Hayden, Benjamin; Sheth, Sameer A.
    The rewards that we get from our choices and actions can have a major influence on our future behavior. Understanding how reward biasing of behavior is implemented in the brain is important for many reasons, including the fact that diminution in reward biasing is a hallmark of clinical depression. We hypothesized that reward biasing is mediated by the anterior cingulate cortex (ACC), a cortical hub region associated with the integration of reward and executive control and with the etiology of depression. To test this hypothesis, we recorded neural activity during a biased judgment task in patients undergoing intracranial monitoring for either epilepsy or major depressive disorder. We found that beta (12–30 Hz) oscillations in the ACC predicted both associated reward and the size of the choice bias, and also tracked reward receipt, thereby predicting bias on future trials. We found reduced magnitude of bias in depressed patients, in whom the beta-specific effects were correspondingly reduced. Our findings suggest that ACC beta oscillations may orchestrate the learning of reward information to guide adaptive choice, and, more broadly, suggest a potential biomarker for anhedonia and point to future development of interventions to enhance reward impact for therapeutic benefit.
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    Towards objective, temporally resolved neurobehavioral predictors of emotional state
    (Elsevier, 2024) Kabotyanski, Katherine E.; Yi, Han G.; Hingorani, Rahul; Robinson, Brian S.; Cowley, Hannah P.; Fifer, Matthew S.; Wester, Brock A.; Lamichhane, Bishal; Sabharwal, Ashutosh; Allawala, Anusha B.; Rajesh, Sameer V.; Diab, Nabeel; Mathura, Raissa K.; Pirtle, Victoria; Adkinson, Joshua; Watrous, Andrew J.; Bartoli, Eleonora; Xiao, Jiayang; Banks, Garrett P.; Mathew, Sanjay J.; Goodman, Wayne K.; Pitkow, Xaq; Pouratian, Nader; Hayden, Benjamin Y.; Provenza, Nicole R.; Sheth, Sameer A.