An Optogenetic Platform for Freely Moving Animal Applications

Dimitris Firfilionis, JunWen Luo and Patrick Degenaar

uSystems group, Newcastle University, Newcastle upon Tyne, U.K.

1 OBJECTIVES

In this work, the main objective was to develop a

closed-loop optogenetic platform capable of

performing electrical recording and optical

stimulation in a closed loop manner. The system is

based on an ARM Cortex M4 Microcontroller Unit

(MCU). The MCU is responsible for controlling the

system and, processing and storing the recorded

data. Placing an MCU as a processing unit

significantly increases the flexibility of the system,

as it allows several algorithms and software

architectures to be implemented; this makes the

system suitable for most optogenetic based

applications. As presented by Ramezani et al., a

custom Application Specific Integrated Circuit

(ASIC) is responsible for recording the neural

activity and delivering the optical stimulus. The

recorded and stimulation data are stored on a micro-

SD card. The system is powered by a 155 mAh

Lithium-Polymer (LiPo) battery. Figure 1 illustrates

a conceptual model of the system.

2 METHODS

The system comprises of two main blocks: 1) the

head-stage unit and 2) the embedded control unit.

The head-stage unit contains a neural interface ASIC

responsible for recording neural activity and

delivering optical stimulus. The ASIC is used in

order for the capabilities of the system to be

demonstrated. It requires a 5 V and a 3.3 V supply,

which are provided by the embedded control unit.

The data communication between the two units is

established through a Serial Peripheral Interface

(SPI) link. This makes the system capable of

interfacing with any custom or commercial ASIC,

provided that an SPI link exists on the ASIC to be

used. The head-stage unit contains a microcontroller

unit, a micro-SD card header and a Power

Management Unit (PMU). The system is powered

by a 3.7 V LiPo battery. Figure 2 represents the

proposed system in the form of a block diagram.

2.1 Neural Interface ASIC

A detailed description of the neural interface ASIC

is given by Ramezani et al. It consists of three main

blocks: a) digital controller for external communica-

tion, interpreting and executing commands; b)

neural recording system for amplifying, filtering,

and digitising biopotentials; and c) optical

stimulation system for generating, sequencing and

driving μLEDs providing the systems with

optogenetic neural stimulation capabilities.

For covering the power necessities of the system,

two power domains have been used: 3.3V (using

native devices) and 5V (using thick oxide devices).

The 3.3V supply is used in order for all the

electronics, apart from the optical stimulation output

stage, to be powered. The 5V supply is required to

power the blue μLEDs, due to their threshold

voltage being significantly higher compared to

conventional ones.

Figure 1: Conceptual model of the proposed system.

2.1.1 Digital Control

The digital controller is responsible for providing the

following functions: 1) SPI communication interface

with external processing and control units; 2) a Finite

State Machine (FSM) with defined instructions,

which allow the control of the μLED driving circuits,

Firﬁlionis, D., Luo, J. and Degenaar, P.

An Optogenetic Platform for Freely Moving Animal Applications.

In Extended Abstracts (NEUROTECHNIX 2018), pages 3-5

Figure 2: Block diagram representation of the proposed system. On the left the Embedded Control Unit, containing an MCU,

a PMU, a μSD card and a battery. On the right the Head-stage Unit, containing the neural interface ASIC and an optrode. A

5V and 3.3 V supply are provided to the Head-stage Unit, and biderectional data communication is achieved via an SPI link.

as well as the configuration and control of the

acquisition data from the recording circuits.

2.1.2 Neural Recording

The LFP recording sub-system is comprised of four

recording channels, a shared Analog-to-Digital

Converter (ADC) and corresponding control logic.

Each recording channel consists of a low noise Front-

End Amplifier (FEA) to couple to an electrode and

provide low-noise amplification. It also consists of a

amplification stage, allowing further

amplification for low noise requirements. As

mentioned previously, the ADC is shared between

multiple recording channels, which raises the

requirement of a buffer with sufficient drive strength,

in order for the settling error and crosstalk between

multiplexing to be reduced.

Figure 3: Physical representation of the proposed system.

The system comprises of the head-stage and control units.

A CREE Light Emitting Diode (LED) has been used for

demonstrating the optical stimulation capabilities of the

system. The LED was turned on through one of the

addressable optical drivers in the ASIC.

2.1.3 Optical Stimulation

The system proposed in [6] allows up to six optical

stimulation sites. Control of the light intensity can be

achieved via a voltage DAC which is then converted

to a current via a transconductance amplifier.

Intensity can be controlled via both pulse width

modulation and intensity control.

2.2 Microcontroller Unit (MCU)

The MCU used in the system is part of the Kinetis

K22F family. It was selected due to its low power

consumption and Digital Signal Processing (DSP)

capabilities. The DSP block enhances the

computational performance of the system allowing it

to accommodate algorithms of various complexities.

It is also responsible for acquiring the digitised data

from the ASIC, performing some computation

according to the selected algorithm and controlling

the optical stimulation system within the ASIC. The

control of the ASIC is achieved through a custom

Finite State Machine (FSM) based software structure

implemented on the microcontroller.

Figure 4: Output voltage of the optical stimulation circuit

(1 second on – 1 second off period).

NEUROTECHNIX 2018 - 6th International Congress on Neurotechnology, Electronics and Informatics

2.3 Data Logging

The recorded data, along with information about the

stimulation commands and the algorithm, are stored

in a 1 GB micro SD card. The data is stored to the SD

card though an SPI link. The size of the SD card was

selected to specifically accommodate enough

memory space for a 24 hour continuous recording.

However, depending on the application and power

needs, any alternative memory size could be used.

2.4 Power Management Unit (PMU)

The PMU provides the whole system with 3.3 V and

5 V supply voltages. This is achieved by first

regulating the 3.7 V - provided by a 155 mAh LiPo

battery – down to 3.3 V. The 3.3V are then boosted

up to 5 V, offering enough voltage for the optical

stimulation system. A commercial boost converter IC

was used in order for the 5 V source to be generated.

3 RESULTS

The funcionality of the system was evaluated through

a series of bench top experiments. Both the

stimulation and recording capabilities of the system

were assessed.

3.1 Optical Stimulation

For testing the stimulation circuitry, a CREE LED

was introduced to the output of one of the LED optical

stimulation sites. Two main pulsing sequences were

applied with variations on the intensity level and duty

cycle of the pulse. The first one was a fixed intensity

and fixed duty cycle (1 s ON, 1 s OFF). As shown in

figure 3, the LED could be successully turned on. The

same stimulation pattern was tested for different duty

cycles. Figure 4 represents the voltage at the output

of the optical stimulation circuit.

Figure 5: Measured response of LED across output range of

DAC value showing the range of illumination power.

The ability of the optical driver to define different

light intensities by controling the output of voltage

DAC was also tested. For an increasing DAC value,

the current at the output of the stimulation circuit and

the intensity of the LED were increasing accordingly.

Optical measurements we performed by placing the

LED inside and integrating sphere. The measured

results are shown in Figure 5. An optical stimulus of

up to 0.8 mW can be illuminated.

3.2 Electrical Recording

In order for the recording of the system to be tested,

pre-recorded LFP data were introduced inside some

saline solution with the use of a signal generator. The

signal signal was captured from the solution using an

electrode from a Neuronexus probe. Part of the results

(20 seconds) is shown in figure 6.

Figure 6: Pre-recorded seizure data were introduce in the

saline with the use of a signal generator. The signal was

recorded by the Neural ASIC and stored in the SD card. The

figure illustrates part of (20 seconds) the 3-hour continuous

recording. The system was powered off a LiPo battery.

4 DISCUSSION

As presented in the results section, the system

successfully managed to produce stimulation patterns

of various on/off periods and LED light intensities.

The system also managed to record seizure-like data

and store the recorded data on the μSD card. For the

whole duration the system was powered off a 3.7 V

LiPo battery.

REFERENCES

Reza Ramezani, Yan Liu, Fahimeh Dekhoda, Ahmed

Soltan, Dorian Haci, Hubin Zhao, Dimitrios Firfilionis,

Timothy G. Constantinou, Patrick Degenaar, 2018,

“On-probe Neural Interface ASIC for Combined

Electrical Recording and Optogenetic Stimulation”,

IEEE Transactions on Biomedical Circuits and

Systems.

An Optogenetic Platform for Freely Moving Animal Applications