Closed-loop : reading and stimulating#
This tutorial details how to use the Intan to read the number of spikes in a way that may be used to perform closed-loop experiments.
The concept is that if you need to trigger stimulations based on some response of the organoids, you may use these functionalities to do so.
Note
If you need the activity over periods longer than minutes, you may wish to use the database instead. See the Database tutorial.
The counting will obtain the count for 200ms after the trigger is sent. The count is stored in a buffer for all 128 electrodes.
Using the Intan to read the number of spikes#
The IntanSofware
class provides the following methods to be used for closed-loop:
set_count
: set which triggers start the counting processThe input should be a list of trigger IDs (from 0 to 15).
For example, to set trigger 8 and 15 to start the counting process, use
set_count([8, 15])
.
Next, you must send the trigger in question to start the counting process.
Finally,
read_count
lets you retrieve the buffer storing the number of spikes.The buffer is a 128-length array containing the number of spikes for each electrode.
Make sure to select the channels relevant to your experiment.
Caution
read_count
intrinsically does nothing to count the spikes.
It only retrieves the buffer storing the number of spikes.
You must first send the triggers that have been set to listen (using set_count
) to populate the read_count
buffer.
Additional considerations#
If you set a trigger to read on which there is a StimParam defined, the StimParam will be triggered as well.
If you only wish to read, make sure to use a trigger without a StimParam.
When using both at the same time, the artifact from the stimulation is occluded by default, by removing the first 10ms of the recording.
Example code#
The following code showcases a minimal experiment where we use the described functionalities to compare the number of spikes 200ms after a trigger is sent, with or without a stimulation.
from neuroplatform import Experiment, StimParam, IntanSofware, Trigger
from datetime import datetime, UTC
import time
import numpy as np
token = "E9JTQDS62Y" # Experiment token
exp = Experiment(token)
print(f"Electrodes: {exp.electrodes}") # Electrodes that can be used with the token
stim_param1 = StimParam()
stim_param1.index = exp.electrodes[0] # the first electrode
stim_param1.trigger_key = 0 # the first trigger
stim_param1.phase_amplitude1 = 2.0
stim_param1.phase_amplitude2 = 2.0
stim_param1.display_attributes()
intan = IntanSofware()
trigger_gen = Trigger()
intan.set_count(
[0, 1]
) # Set the Intan to record the number of spike whenever sending trigger 0 or 1
stim_params = [stim_param1]
try:
if exp.start(): # Signal the start of an experiment to all users
# Send stim parameters to the Intan
intan.send_stimparam(stim_params)
start_exp = datetime.now(UTC)
# Create the array of triggers, and set the desired triggers to 1
trigger0 = np.zeros(16, dtype=np.uint8)
trigger0[0] = 1
trigger1 = np.zeros(16, dtype=np.uint8)
trigger1[1] = 1
for i in range(10):
# Stimulation on electrode 0
trigger_gen.send(trigger0) # THIS TRIGGERS BOTH THE STIM AND THE READ
# Wait 200ms to read for a close loop
time.sleep(0.2)
count_spikes = intan.read_count() # np.array(128)
# Get the number of spike of electrode 22 for the read
total_spikes_stim = count_spikes[22]
###
# Send trigger 1 - no stimulation
trigger_gen.send(trigger1) # THIS TRIGGERS ONLY THE READ
# Wait 200ms to read for a close loop
time.sleep(0.2)
count_spikes = intan.read_count() # np.array(128)
# count the number of spike of electrode 22
total_spikes_read_only = count_spikes[22]
print(f"Spikes with stimulation: {total_spikes_stim}")
print(f"Spikes without stimulation: {total_spikes_read_only}")
time.sleep(1)
stop_exp = datetime.now(UTC)
# Disable all parameters
for stim in stim_params:
stim.enable = False
intan.send_stimparam(stim_params)
finally:
# Close the connection to the trigger generator
trigger_gen.close()
# Close the connection to the Intan
intan.close()
# Signal the end of an experiment to all users
exp.stop()