Lily Srujana Chamakura

Finding suitable therapies for treatment-refractory neuropsychiatric disorders constitutes a major goal for translational neuroscience. Deep brain stimulation shows promise for treatment resistant depression, but treatment efficacy varies substantially across patients. Objective, electrophysiologically driven strategies to optimize deep brain stimulation for treatment resistant depression could greatly improve clinical efficacy by minimizing the trial-and-error approach needed to personalize stimulation settings. This may not only reduce the delay between the start of the treatment and symptom improvement, but also enable acute, real-time verification of circuit engagement, advancing our understanding of the mechanism mediating antidepressant effects. Here, we investigate whether cerebro-cerebral evoked potentials elicited through different deep brain stimulation configurations could be used to guide stimulation personalization for treatment resistant depression. Cerebro-cerebral evoked potentials offer a fast, objective way to identify regions engaged by stimulation, revealing the effective connectivity pattern of the stimulated location. Data were collected from eight patients with treatment resistant depression who received dual bilateral deep brain stimulation devices targeting the subcallosal cingulate and ventral capsule/ventral striatum. During an initial in-hospital monitoring period, single-pulse electrical stimulation was delivered through the deep brain stimulation devices and cerebro-cerebral evoked potentials were recorded through temporary stereo-electroencephalography probes across fronto-temporal regions. Patients underwent several outpatient stimulation programming sessions over the course of 9 months to identify the stimulation configurations leading to the greatest improvement in depressive symptoms. We retrospectively analysed cerebro-cerebral evoked potentials obtained in response to stimulation of different stimulation configurations to identify features distinguishing the clinically effective configurations. The deep brain stimulation configurations leading to the greatest improvement in depressive symptoms were associated with significantly larger evoked potentials in the orbitofrontal cortex and showed an increased number of evoked potentials across dorsal and ventral prefrontal regions. Waveform similarity analysis revealed a gradient in therapeutic effects, such that multiple alternative stimulation configurations led to similar symptom improvement. The vast deep brain stimulation parameter space might contain a configuration subspace defined by comparable therapeutic effects. In addition, evoked potentials obtained from single-pulse and from bursts of high-frequency stimulation displayed similar spatial patterns, suggesting that either method might be able to identify the configuration best engaging the circuit mediating the clinical response. Together, these findings provide proof-of-principle evidence that stimulation-evoked prefrontal responses reflect network engagement associated with antidepressant effects. Cerebro-cerebral evoked potentials may offer an objective and acute strategy to guide contact selection in deep brain stimulation for treatment resistant depression.

The ability to override prepotent actions is critical to control impulses and adjust behavior depending on goals and contextual needs. In this study, we investigate the inhibitory control abilities of a patient diagnosed with Klüver-Bucy Syndrome following a left temporal resection. The patient presented with disruptive hypersexuality symptoms akin to compulsions, leading to the inability to control and suppress inappropriate actions. The patient was recruited for the current research study while undergoing intracranial monitoring for epilepsy, to investigate the cognitive and neural processes underlying the patient’s inhibitory control symptoms. We formulated the hypothesis that an inhibitory control deficit emerges in response to provocative triggers, and we designed a personalized paradigm pairing arousing images with a classic inhibitory control task. We not only confirmed disrupted performance following exposure to triggering, provocative material, but we also leveraged the simultaneously recorded neural data to identify a biomarker reflecting inhibitory control failures. Next, we repeated the experimental paradigm during and after personalized neuromodulation via direct high-frequency stimulation of the right inferior frontal cortex. The patient displayed a marked improvement in his behavior during neuromodulation, mirrored by changes in neural activity, spanning spectral features, event-related potentials and functional connectivity. Altogether, our study revealed that the patient’s symptoms were not due to a global inhibition deficit, but to a specific control issue triggered by exposure to provocative material. Overall, our work showcases a feasible, effective approach towards data-driven personalized neuromodulation, which could be leveraged to mitigate specific inhibitory control deficits and potentially other symptoms of executive dysfunction. Abstract Figure: Graphical abstract. This case study investigates context-dependent inhibitory control abilities in a patient with Kluver-Bucy syndrome during intracranial monitoring for epilepsy .

Recent studies of functional connectivity networks (FCNs) suggest that the reconfiguration of brain network across time, both at rest and during task, is linked with cognition in human adults. In this study, we tested this prediction, i.e. cognitive ability is associated with a flexible brain network in preschool children of 3-4 years - a critical age, representing a ‘blossoming period’ for brain development. We recorded magnetoen-cephalogram (MEG) data from 88 preschoolers, and assessed their cognitive ability by a battery of cognitive tests. We estimated FCNs obtained from the source reconstructed MEG recordings, and characterized the temporal variability at each node using a novel path-based measure of temporal variability; the latter captures reconfiguration of the node’s interactions to the rest of the network across time. Using connectome predictive modeling, we demonstrated that the temporal variability of fronto-temporal nodes in the dynamic FCN can reliably predict out-of-scanner performance of short-term memory and attention distractability in novel participants. Further, we observed that the network-level temporal variability increased with age, while individual nodes exhibited an inverse relationship between temporal variability and node centrality. These results demonstrate that functional brain networks, and especially their reconfiguration ability, are important to cognition at an early but a critical stage of human brain development.