Fig. 1 Incoming external (e.g. thalamic) EPSCs sum to a

~Gaussian conductance at input PY neurons (1,2) . We bypass

the first step by introducing a randomly varying, non-specific

cation conductance is induced into ChR2-expressing PY cells

using amplitude modulated blue light (3). Then the network

response can be measured with an MEA.

PY

PY

PY

PY

PY

PY

References/acknowledgements

Conclusions

Introduction Experimental methods

Amplitude modulated photostimulation for probing neuronal network dynamicsJ.P. Newman1,*, T. Tchumatchenko2,*, M.-F. Fong1,4, S.M. Potter1

1 Laboratory for Neuroengineering, Dept. of Biomedical Engineering, Georgia Institute of Technology, Atlanta , GA, 303322 Center for Theoretical Neuroscience, Columbia University, *equal contributions

4Department of Physiology, Emory University School of Medicine, Atlanta, GA, 30322

Light → photocurrent in uncoupled neurons

Light → population activity in the temporally irregular, low-rate regime

References: [1] Dayan, P. and Abbott, L.F. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems.Cambridge: MIT Press; 2001; [2] Tchumatchenko T, Malyshev A., Wolf F, Volgushev M (2011) Ultrafast Population Encoding byCortical Neurons. J. Neurosci, 31:12171 12179. [3] S.M Potter and T.DeMarse (2001) A new approach to neural cell culture for long-term studies. J. Neurosci. Methods 110. [4] Nikolic K, et al. (2009) Photocycles of channelrhodopsin-2. Photochemistry. andPhotobiology 85: 400411. [5] J. Mattis, et. al. (2011) Principles for applying optogenetic tools derived from direct comparativeanalysis of microbial opsins. Nat. Methods 9:2.Acknowledgements: This work was supported by NSF COPN grant 1238097 and NIH grant 1R01NS079757 from NINDS, NSF GRFPFellowship 08-593 to J.P.N., NSF GRFP Fellowship 09-603 to M.F., NSF IGERT Fellowship DGE-0333411 to J.P.N and M.F. , andComputational Sciences Fellowship from the Volkswagen Foundation to T.T. The viral vectors used in this study were provided byKarl Deisseroth via the UNC at Chapel Hill Gene Therapy Center. We thank J.T. Shoemaker for performing tissue harvests. Finally, wegratefully acknowledge all those who have contributed to NeuroRighter's hardware forums and supplied bug reports to theNeuroRighter code repository.

Sensory stimuli arrive in the cortex as fluctuating currents topopulations of cortical neurons. How cortical networks encodeincoming synaptic currents ultimately determines an animal’scognitive and behavioral response. A number of theoretical studieshave addressed this transduction process using model corticalnetworks [1]. However, while dynamical rate responses have beenstudied experimentally in single neurons [2], few experimentalsystems offer the access/manipulability required to examinenetwork responses. Optogenetic techniques in dissociated corticalnetworks (DCNs) that are grown on microelectrode arrays (MEAs)offer the opportunity to test key aspects of network responsedynamics [3]. In this study, we use amplitude modulatedphotostimulation to impose specific, irregular spiking patterns onDCNs. By using continuous time inputs to control aspects of thenetwork response, we create viable biological analog to simulatedrandom cortical networks.

Neurons expressing ChR2(H134R) support non-specific cationcurrents in response to blue light [4]. We use ChR2 to introduceamplitude modulated, temporally random currents into CaMKllα-expressing (pyramidal) cells embedded within a randomlyconnected cortical network grown on an MEA. This provides:• Simultaneous manipulation of many neurons• Non-invasive, long-term recording• Easy manipulation of connectivity using drugs

Subthreshold control of neurons using light

Temporally irregular, low-rate network firing is achieved using an Ornstein-Uhlenbeck (OU) stimulation process.

data

model

Fitted values:

quantum efficiency · photon fluxRate of channel closureRate of channel recovery

• Fraction of channels in the open state (O), in the desensitized state (D) and closed state (C=1-O-D) is governed by the following 3-state model: New findings:

• A continuum of ChR2 (H134R) channels exhibit a resonance located at ~10Hz.

• A continuum of ChR2 (H134R) channels reliably transmits input frequencies up to ~100 Hz

Linear response functionin the 3-state-model:

Linear non-linear (LN) cascade model• Linear filter• Static non-linearity • Predict the population spiking activity.

New finding: • Continuous low-intensity stimulation selectively

targeting PY neurons entrains reliable network activity patterns

Ligh

t in

ten

sity

[mW

/mm

2]

Op

enp

rob

abili

tyO

f C

hR

2P

ho

tocu

rren

t[p

A]

Time [s]

These results indicate that continuous optogenetic stimulation withLEDs is an effective tool for providing correlated input currents tothousands of pyramidal cells embedded in cortical networks whilesimultaneously recording spiking activity in hundreds of individualneurons. Because continuous photostimulation allows for complexcurrent waveforms to be injected into large neural populations, thistechnique opens a new level of control for testing theories of corticalresponse properties and small signal representation under differentnetwork parameter regimes.

Tria

l # (

1-5

0)

1 2 3

Fig. 2 Amplitude modulated ChR2-mediated photocurrents in uncoupled PY cells. (top) recorded light

intensity, (middle) result of 3-state model, (bottom) somatic photocurrent.

Fig. 3 Population

spiking response to

OU input signal. The

top trace shows the

amplitude modulated

457 nm input signal,

which was repeated

for 50 trials. Units are

sorted by decreasing

firing rate and the top

twenty units from a

single culture (Xeko)

are shown. Different

neurons show

variation in mean

firing rate and the

temporal precision of

their response to input

signals.

Fig. 4 Firing statistics of three cultures presented with repeated, 30 second OU

stimuli (same statistics, but different 30 second realization for each culture).

(left) Neuronal firing rate distribution. (right) Neuronal ISI distribution.

Fig. 5 Population firing rate (grey) averaged across 50 repeats of a 30 second

OU realization and the resulting LN model prediction (black). Firing rate

averages and estimates were made with a 2.5 msec bin size.

Fig. 7 The open-source NeuroRighter electrophysiology

platform uses inexpensive NI A/D, D/A , and DIO boards for

recording and signal generation. It provides online spike

sorting via a fully automated Gaussian mixture modeling

procedure. It was used for all MEA recordings and to drive the

stimulation system.

Fig. 8 Optical feedback LED driver circuit. (A)

Photodiode measures light scattered from the

Köhler apparatus. A high bandwidth

transimpedance amplifier converts the resulting

photocurrent to a voltage (VPD) which is

compared to a DAC supplied reference voltage

(VREF). These two voltages enter the non-

inverting and inverting pins of an op-amp

whose output drives the gate of a power-FET

which in turn pulls current through the LED.

(B) A 1 millisecond command pulse and

resulting VPD signal (proportional to light

power).

Fig. 6 Recorded linear response function and the model fit. The

recorded linear response was estimated using repeated logarithmic

chirp inputs from 0.1 to 1000 Hz. The fitted parameters are in

agreement with previously reported values [4].

A

B

Fig. 9 Recording and

stimulation system. (A)

NeuroRighter software; (B)

‘Plug-in' library; (C) 4-channel

LED current source; (D) 4:1

LED-fiber coupler; (E) Köhler

illumination train; (F) 60-

channel MEA amplifier

(MEA1060, MCS) and Peltier

temperature control system; (G)

MEA showing culturing

chamber; (H) ChR2-mCherry-

expressing PY cell.

Culturing methods• E18 cortical tissue

• Laminin-coated ITO MEAs (MCS)

• Cultures infected with 109 cfu ml-1 AAV2-CaMKllα::ChR2(H134)-mCherry 1-5 DIV [5].

• Cultures stored in gas-permeable FEP chambers [3].

• Grown in incubator regulated to 35° C, 5% C02, 65% Humidity.

• All experiments conducted within incubtator.