Abstract
Markers from local field potentials, neurochemicals, skin conductance, and hormone concentrations have been proposed as a means of closing the loop in Deep Brain Stimulation (DBS) therapy for treating neuropsychiatric and movement disorders. Developing a closed-loop DBS controller based on peripheral signals would require: (i) the recovery of a biomarker from the source neural stimuli underlying the peripheral signal variations; (ii) the estimation of an unobserved brain or central nervous system related state variable from the biomarker. The state variable is application-specific. It is emotion-related in the case of depression or post-traumatic stress disorder, and movement-related for Parkinson's or essential tremor. We present a method for closing the DBS loop in neuropsychiatric disorders based on the estimation of sympathetic arousal from skin conductance measurements. We deconvolve skin conductance via an optimization formulation utilizing sparse recovery and obtain neural impulses from sympathetic nerve fibers stimulating the sweat glands. We perform this deconvolution via a two-step coordinate descent procedure that recovers the sparse neural stimuli and estimates physiological system parameters simultaneously. We next relate an unobserved sympathetic arousal state to the probability that these neural impulses occur and use Bayesian filtering within an Expectation-Maximization framework for estimation. We evaluate our method on a publicly available data-set examining the effect of different types of stress on peripheral signal changes including body temperature, skin conductance and heart rate. A high degree of arousal is estimated during cognitive tasks, as are much lower levels during relaxation. The results demonstrate the ability to decode psychological arousal from neural activity underlying skin conductance signal variations. The complete pipeline from recovering neural stimuli to decoding an emotion-related brain state using skin conductance presents a promising methodology for the ultimate realization of a closed-loop DBS controller. Closed-loop DBS treatment would additionally help reduce unnecessary power consumption and improve therapeutic gains.
Highlights
Deep Brain Stimulation (DBS) is a type of therapy involving the application of high frequency electrical stimulation, usually at ∼130 Hz, to specific anatomical structures deep within the brain (Oluigbo et al, 2012; Carron et al, 2013)
We describe the state-space formulation for the closedloop DBS (CLDBS) system that relates the probability of neural impulses to a latent sympathetic arousal state
The lower sub-panel in each sub-figure shows the corresponding neural stimuli recovered using our deconvolution approach along with the reconstructed signal. It is the timings of these neural impulses that are used for estimating sympathetic arousal
Summary
Deep Brain Stimulation (DBS) is a type of therapy involving the application of high frequency electrical stimulation, usually at ∼130 Hz, to specific anatomical structures deep within the brain (Oluigbo et al, 2012; Carron et al, 2013). A second hypothesis suggests that stimulation from the implanted electrodes modulates electrical circuit activity within dysfunctional brain regions (Oluigbo et al, 2012; Cleary et al, 2015). DBS has been approved by the Food and Drug Administration (FDA) for the treatment of Parkinson’s disease and essential tremor in the United States. Humanitarian device exemptions have been granted by the FDA for the use of DBS in the treatment of severe obsessive compulsive disorder and dystonia (Grahn et al, 2014). The therapy has been investigated as a treatment option for a host of other medical conditions including major depression (Puigdemont et al, 2012; Merkl et al, 2013), chronic pain (Boccard et al, 2015; Lempka et al, 2017), drug-resistant epilepsy (Vesper et al, 2007; Fisher et al, 2010), anorexia nervosa (Lipsman et al, 2013; Wu et al, 2013), and substance abuse (Zhou et al, 2011; Müller et al, 2013)
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