Nonlinear Signal-Specific ADC for Efficient Neural Recording in Brain-Machine Interfaces

A Vector Quantization-Based Spike Compression Approach Dedicated to Multichannel Neural Recording Microsystems

Implantable high-density multichannel neural recording microsystems provide simultaneous recording of brain activities. Wireless transmission of the entire recorded data causes high bandwidth usage, which is not tolerable for implantable applications. As a result, a hardware-friendly compression module is required to reduce the amount of data before it is transmitted. This paper presents a novel compression approach that utilizes a spike extractor and a vector quantization (VQ)-based spike compressor. In this approach, extracted spikes are vector quantized using an unsupervised learning process providing a high spike compression ratio (CR) of 10-80. A combination of extracting and compressing neural spikes results in a significant data reduction as well as preserving the spike waveshapes. The compression performance of the proposed approach was evaluated under variant conditions. We also developed new architectures such that the hardware blocks of our approach can be implemented more efficiently. The compression module was implemented in a 180-nm standard CMOS process achieving a SNDR of 14.49[Formula: see text]dB and a classification accuracy (CA) of 99.62% at a CR of 20, while consuming 4[Formula: see text][Formula: see text]W power and 0.16[Formula: see text]mm² chip area per channel.

Light Modulation of Brain and Development of Relevant Equipment

Light modulation plays an important role in understanding the pathology of brain disorders and improving brain function. Optogenetic techniques can activate or silence targeted neurons with high temporal and spatial accuracy and provide precise control, and have recently become a method for quick manipulation of genetically identified types of neurons. Photobiomodulation (PBM) is light therapy that utilizes non-ionizing light sources, including lasers, light emitting diodes, or broadband light. It provides a safe means of modulating brain activity without any irreversible damage and has established optimal treatment parameters in clinical practice. This manuscript reviews 1) how optogenetic approaches have been used to dissect neural circuits in animal models of Alzheimer's disease, Parkinson's disease, and depression, and 2) how low level transcranial lasers and LED stimulation in humans improves brain activity patterns in these diseases. State-of-the-art brain machine interfaces that can record neural activity and stimulate neurons with light have good prospects in the future.

Spatial Redundancy Reduction in Multi-Channel Implantable Neural Recording Microsystems

This paper introduces a lossless approach for data reduction in multi-channel neural recording microsystems. The proposed approach benefits from eliminating the redundancy that exists in the signals recorded from the same space in the brain, e.g., local field potentials in intra-cortical recording from neighboring recording sites. In this approach, a single baseline component is extracted from the original neural signals, which is treated as the component all the channels share in common. What remains is a set of channel-specific difference components, which are much smaller in word length compared to the sample size of the original neural signals. To make the proposed approach more efficient in data reduction, length of the difference component words is adaptively determined according to their instantaneous amplitudes. This approach is low in both computational and hardware complexity, which introduces it as an attractive suggestion for high-density neural recording brain implants. Applied on multi-channel neural signals intra-cortically recorded using 16 multi-electrode array, the data is reduced by around 48%. Designed in TSMC 130-nm standard CMOS technology, hardware implementation of this technique for 16 parallel channels occupies a silicon area of 0.06 mm², and dissipates 6.4 μW of power per channel when operates at V_DD=1.2V and 400 kHz.Clinical Relevance- This paper presents a lossless data reduction technique, dedicated to brain-implantable neural recording devices. Such devices are developed for clinical applications such as the treatment of epilepsy, neuro-prostheses, and brain-machine interfacing for therapeutic purposes.