The SN65LVDT41 chip is configured to use low-voltage differential signaling to reduce the effects of noise and electromagnetic interference and allow increased cable length. However, the Raspberry Pi communicates using complementary metal-oxide-semiconductor level logic. To translate between the two signal types, the expansion shield uses the SN65LVDT41 chip from Texas Instruments. The SN65LVDT41 chip has four LVDS line drivers and one LVDS line receiver to control data lines required to communicate with the Intan chip over its Serial Peripheral Interface . Connection to electrodes—Electrodes are connected to the Intan RHD 32-channel recording head stage. For experiments reported here, we created a connection to a commercially available 6-well multi-electrode array plate from Axion Bio-systems. However, any other electrode system fitting an Omnetics 32-pin connector is compatible. The design can be adapted to custom and commercial MEAs of different form factors using adapter boards. The Axion electrode plate mates its bottom contacts to spring finger pins on our designed adapter board. The parts are aligned using a custom holder consisting of a plastic interior surrounded by aluminum plates and compressed together by screws on four corners. The aluminum plate casing prevents warping of the plastic and ensures even pressure compressing the plate and connector on both sides. The compressing holder provides consistent mating of spring finger pins to electrode contacts on the plate.The Piphys system runs custom software to perform: communication with the Intan RHD2132 bio-amplifier chip, buffering and file storage of recorded voltage data locally, near real-time data streaming and plotting on the online dashboard, plant pots with drainage and experiment control from the dashboard. In order to stream data, interact with data being recorded, and control the device, we deployed Redis, Amazon IoT, and S3, as described in Methods.

To perform an electrophysiology recording, the user can configure the sampling rate and start the experiment from the dashboard. Once started, the neural cell activity is firstly digitized and sampled by the Intan RHD2132 bio-amplifier chip in 32 channels. Raspberry Pi stores the data on local memory and also streams it to Redis for near real-time visualization on the online dashboard. Since the Raspberry Pi computer has a 10 second streaming buffer, the data visualized on the dashboard is offset by 10 seconds from the data recorded. Therefore the data streaming is “near real-time”. During a recording, raw data is saved in chunks of 5 minutes to local memory and streamed in chunks of 10 seconds to Redis. Once the recording ends, all local data files are uploaded to S3 for permanent storage, and data is further backed up to Amazon Glacier for long-term archiving. Local data files on the Pi auto-erase every 14 days to release memory. To view a dated recording, the user can select and pull the data files from S3 to the dashboard for display . The Raspberry Pi has 4 CPU cores, and allows multicore and multi-threading. According to resource monitoring with “htop”, the Piphys program runs on two cores. The software uses four threads to record and stream to the cloud simultaneously. One thread is used for hardware interfacing with the Intan chip; a second thread is for cloud streaming, the third one is for local saving and another is for experiment control that gets MQTT messages. Communication with hardware—Communication between Raspberry Pi and Intan RHD2132 bio-amplifier chip uses Serial Peripheral Interface . SPI is a fast and synchronous interface that is widely used in embedded systems for short-distance data streaming. It is a full-duplex master-slave-based interface where both master and slave can transmit data at the same time. The protocol for both Raspberry Pi and Intan RHD2132 bio-amplifier chip is a four-wire interface: Clock , Chip select CS , Master-OutSlave-In , and Master-In-Slave-Out . In Piphys, the Raspberry Pi acts as the master device and generates a clock signal and recording commands to configure the Intan RHD2132 bio-amplifier chip through MOSI.

The Intan chip responds as a slave and sends the digitized data back by MISO. The chip allows the configuration of sampling rate and bandwidth of the low-noise amplifiers. The 32 channels on the chip are sampled sequentially with available sampling rate options from 2 kHz to 15 kHz per channel. The SPI clock is divided from the core clock on Raspberry Pi. Performance and error of the SPI clock are discussed in the Supplementary Material. The amplifiers give 46 dB midband gain with lower bandwidth from 0.1 Hz to 500 Hz, and upper bandwidth from 100 Hz to 20 kHz.Online dashboard—Users interact with Piphys devices through a web browser application, referred to as the Graphical User Interface . The GUI allows a user to initiate a recorded experiment and monitor electrical activity on each channel. Programatically, the GUI mimics an IoT device that sends messages to other devices and listens to their corresponding data streams in a high-performance Redis database service. The Piphys device produces a single data stream to Redis, and many users can view the stream from the Redis server. Therefore, many users can monitor and interact with a particular Piphys device without additional overhead placed on that device. Users can be located anywhere on the Internet without concern for where the physical Piphys device is or which network it is on. We routinely perform electrophysiology experiments from Santa Cruz on a Piphys-connected device that is located 90 miles away in San Francisco. When a new user opens the browser GUI, the web application queries the AWS IoT service for online Piphys devices to populate a device dropdown list. When the user selects a device from the dropdown, an MQTT ‘ping’ message is sent to the relevant device every 30 seconds, indicating that a user is actively monitoring data from that device. As long as the Piphys device receives these pings, the Piphys device will continue to send its raw data stream to the central Redis service. When the Piphys device has not received any user messages for at least a minute, it will cease sending its raw data stream. This protocol ensures the proper decoupling of users from devices. The Piphys device is not dependent on a user gracefully shutting down. While the Piphys device feeds raw data to the Redis service, data transformations are applied downstream by other IoT-connected processes. For example, the Piphys Control Panel displays a threshold spike sorted transformation of the raw data.

This data transformation is an independent process that listens for MQTT requests for the raw data stream and transforms the raw stream into a stream containing the past ten spike events detected per channel. For channels with no detected spikes, a random sample of the channel is saved to the stream every 30 seconds to provide a sampling of the channel’s activity.We tested the Piphys system for long-term recordings of human primary neurons. The goal of this work is to compare the neural signal recorded by the proposed apparatus to commercially available systems. Therefore, as a reference we choose two neural recording devices: Axion Maestro Edge by Axion Biosystems, as one of the leading commercial instruments for neural recording and Intan RHD interface board as one of the leading commercial open source neural recording instruments. These neurons were cultured in an Axion CytoView MEA 6-well plate ‡ . We designed a set of adapters , plastic plants pots which allowed the same culture plate to be used by Piphys and Intan RHD interface board. As mentioned in the Discussion section, the proposed system can interface with any type of neural recording electrodes using the Omnetics connector. After recording, the raw data was ingested to SpyKING CIRCUS software on a personal computer for analysis. SpyKING CIRCUS is a semi-automatic spike sorting software that uses thresholding, clustering, and greedy template match approaches to detect single cell action potentials. Here, we show two types of results, first for single neuron recordings and second for a bursting neural network.After 14 days in culture, primary neurons were recorded with the Piphys system and two commercially available systems: the Intan RHD USB interface board and the Axion Maestro Edge. After recording, all three datasets were filtered with bandpass filtering from 300 Hz to 6000 Hz and spike sorted with a threshold of ± 6 μV. Figure 5 shows a ten-second spike train from Piphys with dots highlighting detected spikes in the raw data. To further demonstrate the applicability of Piphys to primary neuron recording, we compare the shape of the detected action potential and quality metrics such as amplitude distribution, interspike interval distribution, and firing rate to commercially available systems . The data was recorded from the same channel in the same well of neurons by Piphys, Intan, and Axion systems in sequential order on the same day. The data recorded on Piphys corresponds to the data obtained from both commercial systems, with high similarity to Intan and overall consistency with Axion across metrics in Figure 6. The mean spike waveform, shown in the first column of Figure 6, was determined by averaging the voltage in a 3 ms window centered around the point where the voltage crossed the spike threshold. Differences in Axion’s waveform shape are a flatter starting point and a higher upstroke before settling to resting state. The amplitudes for the mean waveform are −24.67 ± 3.92 μV for Piphys, −26.92 ± 4.96 μV for Intan, and −24.50 ± 1.69 μV for Axion. Axion has a smaller deviation than Piphys and Intan, showing lower noise in the recording system. The amplitudes of the detected spikes over time, shown in the middle column of Figure 6 are more sparse for Axion than for Intan and Piphys.

Firing rates in events per second over the recording period shown are 8.05 for Piphys, 8.44 for Intan, and 6.86 for Axion. The interspike interval histograms, shown in the middle column of Figure 6, have similar longer-tail distributions for Piphys and Intan centered at 122.79 ms and 118.15 ms, and a tighter distribution for Axion centered at 145.57 ms. However, the interspike interval means for all three systems are significantly close together.On day 42 of culture, we recorded from the neurons with Piphys and found the primary neurons displayed synchronized network bursts, consistent with previous observations. Figure 7 shows the synchronous activity captured across four channels. After spike sorting, most detected spikes were arranged in short intervals with periods of silence in between. The spikes inside the bursts align among the channels, indicating that synchronized activity was present through the network. Quantitatively, the bursting has a general population rate of 0.13 bursts each second, with each burst lasting around 1 second. Within one burst, the number of spikes is 55 ± 17.58.The variation between Piphys and Axion shown in Figure 6 could be attributed to physical differences in the circuity and possible advanced filtering performed by Axion’s proprietary BioCore v4 chip §. The filtering could account for the smoothness and low variability of the signal , resulting in a smaller number of identified firing events with a tighter distribution. Piphys and Intan systems both use the same amplifier chips , where the optional on-chip filtering was disabled during recording ∥. The raw signal, therefore, has a larger noise margin , which may create more false-positive firing events. The tail of the amplitude distributions in Intan and Piphys is skewed towards lower-amplitude events, closer to the noise floor. The interspike intervals for Intan and Piphys register several events with near-zero intervals, likely suggesting false-positive spikes from noise contamination. Contamination from noise, which is likely symmetrical, could affect the shape of the mean waveform calculated by overlaying and averaging all registered spikes. Overall, these results demonstrate that Piphys can record neural activity in a manner comparable to commercially available hardware and software.Comparison to other platforms—Comparing electrophysiology platforms side by side is challenging because each system fits a specific niche and requirements for a particular workflow. Different platforms are targeted to particular problems and, therefore, have specific challenges and user needs. Piphys is intended to integration with other IoT sensors, and flexible recording equipment that can be used in a fleet for longitudinal study of many in vitro replicates. It should be noted that that the system proposed in this paper has an average signal to noise ratio of 4.35 dB above the baseline noise in recording neuron burst, which is comparable with other similar systems. Table 1 summarizes electrophysiology systems comparable to Piphys.