Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation

Sendi, Mohammad S.E.; Waters, Allison; Tiruvadi, Vineet; Riva‐Posse, Patricio; Crowell, Andrea; Isbaine, Faiçal; Gale, John T.; Choi, Ki Sueng; Gross, Robert E.; Mayberg, Helen S.; Mahmoudi, Babak

doi:10.1038/s41398-021-01669-0

Cited by 37 publications

(36 citation statements)

References 31 publications

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“…Additionally, the identification of oscillatory correlates during active stimulation may capture depression-salient brain dynamics present only during active stimulation drive, complementing recent results from our group [28, 47]. The observation of changes within the β range is consistent with other DBS indications [48] as well as with resting-state results from our own lab [47, 18]. The asymmetry observed aligns with asymmetries found in depression, though these typically involve frontal α , and with asymmetries evoked by SCCwm actions on brain networks [49].…”

Section: Discussionsupporting

confidence: 75%

“…Explicit mismatch compression corrections enabled the use of hourly recordings sampled evenly across weeks, more regularly capturing symptoms probed by the HDRS17 [22, 24]. Additionally, the identification of oscillatory correlates during active stimulation may capture depression-salient brain dynamics present only during active stimulation drive, complementing recent results from our group [28, 47]. The observation of changes within the β range is consistent with other DBS indications [48] as well as with resting-state results from our own lab [47, 18].…”

Section: Discussionmentioning

confidence: 76%

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Decoding depression during subcallosal cingulate deep brain stimulation

Tiruvadi

Veerakumar²,

Smart

et al. 2022

Preprint

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Deep brain stimulation of subcallosal cingulate white matter (SCCwm-DBS) alleviates symptoms of treatment resistant depression (TRD) over months of therapy. Readouts of depression symptom severity derived from neural recordings are needed for more systematic study and improvement of the therapy. In this study, we measured local field potentials (LFP) multiple times a day alongside seven months of therapy using the Activa PC+S™ in six patients treated with SCCwm-DBS. We found significant changes in oscillatory power between early and late therapy after accounting for stimulation-related distortions, particularly within the β band. We then used a decoder strategy to identify oscillatory activity that tracked with depression measurements over seven months, with asymmetric δ and β oscillations contributing to a statistically significant prediction of 10% of the measured depression signal. Simulating its use in clinical decision-making, we demonstrated that the DR-SCC yield clinically meaningful information that can augment other measures of depression state. Ultimately, this DR-SCC provides a data-driven first-step towards objectively tracking chronic recovery after antidepressant DBS implantation and developing adaptive DBS strategies in the presence of active stimulation.

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Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 76%

Decoding depression during subcallosal cingulate deep brain stimulation

Tiruvadi

Veerakumar²,

Smart

et al. 2022

Preprint

Self Cite

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“…Lastly, we applied TRAKR to an 8-channel neural time-series dataset recorded from the SCC of human patients (Figure 4). The overall goal of the recording protocol in the OR was to find neural signatures (or biomarkers) of behavioral effects observed in response to intraoperative brain stimulation ([34]; see subsubsection 2.5.2 for more details). For a particular individual, 8-channel recordings were obtained after stimulation on each contact (Figure 4A).…”

Section: Resultsmentioning

confidence: 99%

“…We also applied TRAKR to another neural dataset, 8-channel data recorded from the subcallosal cingulate (SCC) region of human patients with treatment-resistant depression who are undergoing deep brain stimulation in the operating room (OR) ([34, 36]). We found that TRAKR-derived reservoir activations can be used to better distinguish the effect of stimulation on neural patterns, achieving greater separation in latent space compared to raw traces.…”

Section: Introductionmentioning

confidence: 99%

Reservoir-based Tracking (TRAKR) For One-shot Classification Of Neural Time-series Patterns

Afzal

Márton

Rich

et al. 2021

Preprint

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Neuroscience has seen a dramatic increase in the types of recording modalities and complexity of neural time-series data collected from them. The brain is a highly recurrent system producing rich, complex dynamics that result in different behaviors. Correctly distinguishing such nonlinear neural time series in real-time, especially those with non-obvious links to behavior, could be useful for a wide variety of applications. These include detecting anomalous clinical events such as seizures in epilepsy, and identifying optimal control spaces for brain machine interfaces. It remains challenging to correctly distinguish nonlinear time-series patterns because of the high intrinsic dimensionality of such data, making accurate inference of state changes (for intervention or control) difficult. Simple distance metrics, which can be computed quickly do not yield accurate classifications. On the other end of the spectrum of classification methods, ensembles of classifiers or deep supervised tools offer higher accuracy but are slow, data-intensive, and computationally expensive. We introduce a reservoir-based tool, state tracker (TRAKR), which offers the high accuracy of ensembles or deep supervised methods while preserving the computational benefits of simple distance metrics. After one-shot training, TRAKR can accurately, and in real time, detect deviations in test patterns. By forcing the weighted dynamics of the reservoir to fit a desired pattern directly, we avoid many rounds of expensive optimization. Then, keeping the output weights frozen, we use the error signal generated by the reservoir in response to a particular test pattern as a classification boundary. We show that, using this approach, TRAKR accurately detects changes in synthetic time series. We then compare our tool to several others, showing that it achieves highest classification performance on a benchmark dataset, sequential MNIST, even when corrupted by noise. Additionally, we apply TRAKR to electrocorticography (ECoG) data from the macaque orbitofrontal cortex (OFC), a higher-order brain region involved in encoding the value of expected outcomes. We show that TRAKR can classify different behaviorally relevant epochs in the neural time series more accurately and efficiently than conventional approaches. Therefore, TRAKR can be used as a fast and accurate tool to distinguish patterns in complex nonlinear time-series data, such as neural recordings.

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“…Minocycline, which inhibits microglia activation, can prevent behavioral deficits induced by maternal immune activation, maternal sleep deprivation, and neonatal alcohol exposure in rodents [ 67 , 68 , 87 , 104 , 105 , 110 , 111 ]. Deep-brain stimulation is used as a therapeutic in human patients with mood and neuropsychiatric disorders [ 112 , 113 , 114 ]. In animal models, it was found that stimulation of the medial prefrontal cortex in MIA rats prevented behavioral and neuronal deficits [ 69 , 115 ].…”

Section: Developmental Stressors’ Impact On Brain Microgliamentioning

confidence: 99%

Developmental Stressors Induce Innate Immune Memory in Microglia and Contribute to Disease Risk

Carloni

Ramos

Hayes

2021

IJMS

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Many types of stressors have an impact on brain development, function, and disease susceptibility including immune stressors, psychosocial stressors, and exposure to drugs of abuse. We propose that these diverse developmental stressors may utilize a common mechanism that underlies impaired cognitive function and neurodevelopmental disorders such as schizophrenia, autism, and mood disorders that can develop in later life as a result of developmental stressors. While these stressors are directed at critical developmental windows, their impacts are long-lasting. Immune activation is a shared pathophysiology across several different developmental stressors and may thus be a targetable treatment to mitigate the later behavioral deficits. In this review, we explore different types of prenatal and perinatal stressors and their contribution to disease risk and underlying molecular mechanisms. We highlight the impact of developmental stressors on microglia biology because of their early infiltration into the brain, their critical role in brain development and function, and their long-lived status in the brain throughout life. Furthermore, we introduce innate immune memory as a potential underlying mechanism for developmental stressors’ impact on disease. Finally, we highlight the molecular and epigenetic reprogramming that is known to underlie innate immune memory and explain how similar molecular mechanisms may be at work for cells to retain a long-term perturbation after exposure to developmental stressors.

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Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation

Cited by 37 publications

References 31 publications

Decoding depression during subcallosal cingulate deep brain stimulation

Decoding depression during subcallosal cingulate deep brain stimulation

Reservoir-based Tracking (TRAKR) For One-shot Classification Of Neural Time-series Patterns

Developmental Stressors Induce Innate Immune Memory in Microglia and Contribute to Disease Risk

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