An Interview with the 2022 SSCS-Brain Joint society best paper award winner

By Milin Zhang and Mahsa Shoaran


In 2022, Prof. Mahsa Shoaran together with Uisub Shin, Laxmeesha Somappa, Cong Ding, Yashwanth Vyza, Bingzhao Zhu, Alix Trouillet, Stéphanie P. Lacour from EPFL won the SSCS-Brain joint society best paper award. In an interview with the winners of the award, the IEEE Brain Magazine discussed more potential impact of their work.


Q1: why closed-loop neuramodulation is very important in nuerological disorder and injuries.

Closed-loop neuromodulation is critical in neurological disorders and injuries because it allows for personalized and adaptive treatment with higher efficacy than conventional open-loop simulators. It enables continuous monitoring of neural activity and the ability to adjust stimulation parameters in real-time based on the patient’s clinical state. This dynamic modulation provides more precise targeting of neural circuits, better symptom control, reduced side effects, lower energy consumption, and improved treatment outcomes.


Q2: can the existed FDA approved devices be directly used for closed-loop neuromodulation cures in clinical practice? And why?

Currently only a couple of FDA-approved devices are designed for closed-loop stimulation, given the complexity of circuit design and miniaturization for such systems. The NeuroPace’s Responsive Neurostimulator (RNS) device can deliver closed-loop neuromodulation in epilepsy, using a simple thresholding-based seizure detection mechanism. The Medtronic’s Percept device is also capable of closed-loop stimulation in movement disorders.


Q3: what is the key challenges to circuit designers in the realization of a closed-loop neuromodulation?

Some potential circuit design challenges involved in closed-loop neuromodulation include achieving high channel count integration, ensuring high energy efficiency for the machine learning-based classifier and feature extraction module, low-power neural recording and charge-balanced neuromodulation, cancelling stimulation artifacts, and miniaturized implementation.


Q4: the neural signal acquisition electrode array and the modulation electrode array are located in two different cortex regions in your work. Is this a common solution for closed-loop neuramodulation?

The figure in our paper is symbolic and shows different possibilities for placing the sensing and stimulation electrodes. The specific choice of electrode placement depends on the targeted neural circuitry and the intended therapeutic outcome. In some cases, it may be necessary to target the same cortical or deep-brain region to achieve the desired decoding and modulation effects. Our NeuralTree ASIC is compatible with all of these configurations and can support cortical or deep-brain sensing and stimulation.


Q5: there are 16 electrodes in the acquisitioin array for the in vivo test. What is the density of the array? What is the thickness of the electrode? How to implant such an array into the brain? Is a long surgical incision required?

In this work, we implanted two 15-channel 200-μm-diameter soft and ultra-thin μECoG arrays into the cortex of rats for in-vivo epilepsy monitoring. While the routine clinical procedure to implant ECoG electrodes requires a craniotomy to remove the skull and position the ECoG array over the cortex, our collaborators at EPFL have recently developed a flexible and deployable ECoG (Electrocorticography) system that can be inserted through a small opening in the skull and applied over a relatively large area on the surface of the cortex. This technology holds great promise, especially in providing minimally invasive solutions for patients with epilepsy.


Q6: there are 256-channel integrated in the AFE. Why not implanted an array of electrode with a total number of 256? Does it mean for most of the cases, 256 channel acquisition ability is not required?

The integration of 256 channels in the AFE does not necessarily imply that a total of 256 channels are required in all cases. The number of required channels depends on the specific application, target region in the brain, and the desired level of neural information acquisition. In some cases, a higher channel count may be necessary to capture a broader range or higher resolution neural activity. However, for certain applications or specific neural targets, a lower channel count may be sufficient to achieve the desired therapeutic outcome.


Q7: is there any plan for in vivo test on human patient suffered from seizure?

Yes, our ultimate objective is to conduct in vivo tests on human patients suffering from epilepsy or other neurological disorders. To develop a fully implantable neuromodulation system suitable for humans, one should conduct chronic studies in animal models of disease to ensure safety and biocompatibility of the system, as well as its long-term therapeutic efficacy. The work presented here serves as a proof-of-concept for our novel neural interface technology, paving the way to develop systems with improved therapeutic outcomes. We are actively exploring the commercialization paths to facilitate its future availability for patients.


Q8: can this work be used for other neurodiseases in the future?

Indeed, the proposed method and system for closed-loop neuromodulation has the potential to be applied to a wide range of neurodiseases. Our developed system incorporates a versatile multi-symptom feature extraction engine, enabling the prediction of various neurological conditions. These conditions encompass seizures in epilepsy, motor symptoms like tremors in Parkinson’s disease, movement decoding for prosthetic control, as well as the detection of psychiatric symptoms or memory dysfunction. The crucial elements for all these applications are a comprehensive set of biomarkers and a robust classifier for detecting disease states. However, further research and validation are necessary to determine the effectiveness of this approach for each specific application.

Uisub Shin, Cong Ding, and Prof. Mahsa Shoaran

Figure 1: The winners of the 2022 SSCS–Brain Best Paper Award: (left to right) Uisub Shin, Cong Ding, and Prof. Mahsa Shoaran