Driving Slow-Oscillations (1 Hz) in rats with optical readout via two-photon microscopy. Alternative download link: https://dl.dropboxusercontent.com/u/6757026/slideShare/neuromodFUS_v2016.pdf

1. Focused Ultrasound Neuromodulation
Driving Slow-Oscillations (1 Hz) in rats
Petteri Teikari, PhD
Nov 2015

2. Corticothalamic circuit
Lee et al. (2012)
Generation of slow oscillations (Crunelli et al., 2015)
Entrainment of channelrhodopsin2-expressing TC neurons in rats
[David et al. (2013)]. With different stimulation frequencies.
Rhythm flattened with 2 Hz stimulation

3. tACS in humans and slow oscillations
Kirov et al. (2009)
“tSOS (at 0.75 Hz) in humans increased EEG power in the slow oscillation frequency band (0.4 1.2 Hz); however, clearly–
restricted to the electrode sites closest to the location of the stimulating electrodes, i.e., at the frontal leads F7, Fz, and F8.
Also, the effect seemed to decrease already at the 5th stimulation period. Stimulation produced a most pronounced increase
in power in the theta frequency band (4 8 Hz; stimulation).–
Notably, these effects were equally distributed across electrode sites. Beta activity (15 25 Hz) was also increased. For–
frontal slow oscillation activity, theta and beta frequencies, power was specifically increased during the 1-min stimulation-free
intervals after the five stimulation intervals, but not at 30 or 60 min after the stimulation period. All other frequency bands
(i.e., delta, slow and fast alpha) were not consistently influenced.”
Example setup from Groppa et al, (2010)

4. tACS in vivo rats entrain slow oscillations
Ozen et al, (2010)
INT ENSITY and STAT E-dependent responses
Lack of entrainment in exploring rats
Entrainment in sleeping rats (with
endogenous slow oscillations)
“The goal of our experiments was to entrain cortical neurons by exogenously applied electric fields and to
determine the underlying mechanisms. .. Under anesthesia, the spontaneous slow oscillation, in the frequency
range of 1 1.5 Hz, exerted a powerful effect on both the membrane potential and the discharge probability of–
most neurons [100% entrainment of n = 81 neocortical units in prefrontal cortex and somatosensory cortex;
n = 5 animals; Steriade et al. (1993); Isomura et al. (2006)].
Against this strong network effect, weak TES stimulation (0.4 V) did not have a profound effect on the
neuronal population (only 6% of units were entrained, n = 16 units). At higher intensities (0.8 1.2 V), a larger–
fraction of the neurons (15% and 69%; n = 13 and n = 26 units; respectively) was significantly (p 0.01)<
phase-locked to the forced TES field and the strength of their entrainment increased as stimulation intensity
increased.

5. tACS & Network Resonance
Time to phase lock after the onset of tACS
(modeling). A, Change in power of networks
stimulated at 3 Hz with 9 pA starting at different
onset phases. The line color indicates the onset
phase of the stimulation waveform at stimulation
onset for that trial (increasing onset phase with
warmer colors). All onset phases eventually
entrained the network.
The presence of network bistability with alternating periods of entrainment and lack of
entrainment for stimulation frequencies that do not match intrinsic (harmonic) frequencies.
Fragmentation of power away from intrinsic frequencies resulted in macroscopic, bistable
dynamics with periods of entrainment interleaved with periods of seemingly little stimulation
effect.
tACS in anesthetized ferrets enhanced
cortical oscillations at the stimulation
frequency. Averaged spectrogram for
all stimulation frequencies.
Ali et al. (2013)
See journal club by Helfrich and Schneider (2013)

6. Optogenetic in vivo simulation
Kuki et al. (2013)
Entrainment of the LFP oscillation to repeated 1 Hz optical
stimulation (gray spines) as indicated by the time-domain and
frequency-domain activity.
The frequency power spectrum of the LFP recordings in the
cortex, stimulated at different stimulus frequencies. Optical
stimulation caused a local peak in the spectrum at the
frequency corresponding to the stimulus frequency (colored
arrow heads). Note the exclusive amplification of the power at
1 Hz by the 1 Hz stimulation.
W-TChR2V4 rats that expressed the ChR2-Venus
conjugate under regulation of the thy1.2-promotor

7. Optogenetic in vitro s(t)imulation
Schmidt et al. (2014)
Frequency preference of the optogenetic oscillation
slice for the tACS stimulation frequency, at two
stimulation amplitudes.
“We hypothesized that endogenous cortical oscillations constrain neuromodulation by
tACS. ... Using an optogenetic approach, we tested the hypothesis that intrinsically
oscillating neocortical networks exhibit network resonance (Hutcheon et al., 2000) by
preferentially responding to frequency-matched sine-wave EF (tACS) stimulation. ...
Weak electric fields enhanced endogenous oscillations but failed to induce a frequency
shift of the ongoing oscillation for stimulation frequencies that were not matched to the
endogenous oscillation. This constraint on the effect of electric field stimulation imposed
by endogenous network dynamics was limited to the case of weak electric fields
targeting in vivo-like network dynamics.
Together, these results suggest that the key mechanism of tACS may be enhancing,
but not overriding, intrinsic network dynamics.”

8. PersistenceBaseline
PRF = 1 kHz, pulse duration = 0.36 ms, number of pulses = 500
Position of the electrodes in the rat brain
(A=+4 mm, L=2.5 mm for the prefrontal
cortex; A=−4 mm, L=4 mm for the
sensorimotor cortex). Sebban et al.
(1999)
2-PM:
Rat prefrontal cortex
FUS Target:
Rat thalamus
Selected sub-regions of the thalamus. In (G) thalamus. th, thalamus,
whole region; sub, submedius thalamic nucleus; Po, posterior thalamic
nucleus; VPM, ventral posterolateral thalamic nucleus; VPL, ventral
posteromedial thalamic nucleus; Rt, reticular thalamic nucleus; PF,
parafasicular thalamic nucleus. Hjornevik et al. (2007)
No of blocks?
Optical Readout
for FUS stimulation

9. Position of the electrodes in the rat
brain (A=+4 mm, L=2.5 mm for the
prefrontal cortex; A=−4 mm, L=4
mm for the sensorimotor cortex).
Sebban et al. (1999)
2-PM Imaging:
Rat prefrontal cortex
Selected sub-regions of the thalamus. In (G) thalamus. th,
thalamus, whole region; sub, submedius thalamic nucleus;
Po, posterior thalamic nucleus; VPM, ventral posterolateral
thalamic nucleus; VPL, ventral posteromedial thalamic
nucleus; Rt, reticular thalamic nucleus; PF, parafasicular
thalamic nucleus. Hjornevik et al. (2007)
FUS Target:
Rat thalamus
0.5 mm opening
(or at least less than 1 mm, e.g. Garaschuk et al. 2006)
- Remember well for water-immersed objective!
“Standard” transducer window
with a 12 mm coverslip
http://www.mind.ilstu.edu/dev/parkinsons_lab/rat_brain/Paxinos_Watson/Paxinos_Watson_published_rat%20_brain.php

11. Rat Anatomy #2
Paxinos G, Watson C. 2007. The
Rat Brain in Stereotaxic
Coordinates, Sixth Edition: Hard
Cover Edition 6 edition.
Amsterdam ; Boston: Academic
Press.
A Color atlas of sectional anatomy of the rat
http://www.cosmobio.co.jp/connections/p_ku_e_view.asp?PrimaryKeyValue=20643&selPrice=1

12. Rat Anatomy #3
Seki et al. (2013)
http://dx.doi.org/10.3389/fnana.2013.00045

13. Rat Anatomy #4

14. Rat EEG
Xu et al. (2013)
Protocol for Rat Sleep EEG
http://www.ndineuroscience.com/userfiles/Rat_Sleep_EEG_Methods.pdf

15. DYES
SR-101 astrocytes
OGB-1 calcium
di-4-ANEPPS membrane potential
Qdot800 vessel diameter
Schematic of FUS stimulation

16. CALCIUM OGB-1
NeuronCA2+
ASTROCYTE SR-101
Astrocytic
CA2+
ARTERY AlexaFluor 633
or FITC/TexasRed
Vessel
diameter
“BLUE” Autofluorescence
e.g. lipofuscin, NADH
“Noise
correction”?
Membrane potential with VSD
using rTMS to stimulate cat
visual cortex
Astrocytes trigger rapid vasodilation
following photolysis of caged Ca+.
Neuron (OGB-1)
and arteriole
response (Alexa
Fluor 633) to
drifting grating in
cat visual cortex.
Low-intensity afferent neural activity caused vasodilation
in the absence of astrocyte Ca2+ transients.
Green ch Red ch
IC1 IC2
Bleed of IC1
on Red ch
Bleed of IC2
on Green ch
ICA blind source separation
correction of spectral cross-talk
(bleed) between FITC and DOX
Lipofuscin emission spectrum
compared to OGB-1.
or
Dye Options #1

17. CALCIUM OGB-1
NeuronCA2+
ASTROCYTE SR-101
AstrocyticCA2+
LUMEN Cascade Blue
Vesseldiameter Membranepotential
Membrane potential with VSD
using rTMS to stimulate cat
visual cortex
Astrocytes trigger rapid vasodilation
following photolysis of caged Ca+.
Low-intensity afferent neural activity caused vasodilation
in the absence of astrocyte Ca2+ transients.
Dye Options #2

18. BRAIN DRIVING
STATE-DEPENDENT
EYES
CLOSED
EYES
OPEN
FREQUENCY-DEPENDENT INTENSITY-DEPENDENT
Optogenetic intrinsic drive (legend),
driven with different frequencies (x axis)
“eyes closed”
With increasing intensity, possible to
change intrinsic frequency as well.

19. FUS & 2-PM Triggering

20. Physiological signals & 2-PM Triggering
Jin et al. (2013)
Pittau et al. (2014) Brain Pulsation Artifact
correction for di-4-ANEPPS
Grandy et al. (2012)
Schlögl and Pfurtscheller
BioSig Toolbox
e.g. ECG Regression correction
with human EEG
TTL High
TTL High TTL High
1 Hz Amplitude envelope

21. +EXTRA SLIDES
Empty in purpose

22. THALAMUS in FUS studies of rats #1
Yoo et al. (2011)
Bystritsky and Korb (2015):
Kim et al. (2014)

23. THALAMUS in FUS studies of rats #2
Bystritsky and Korb (2015):
Kim et al. (2013)
Min et al. (2011)
Yang et al. (2012)

24. FUS | Response Kinetics
“The response latencies of FUS-evoked brain circuit activity in mice (approximately
20 30 ms) tend to be– slightly slower than those achieved using
channelrhodopsin-2 (ChR2), electrical stimulation or TMS. We presume that these
kinetic differences in reaching activation thresholds are most likely to stem from the
different energy modalities and mechanism(s) of action underlying each method.
... For example, they are similar to the kinetics described for pore formation
triggered by lipid-phase transitions, which are thought to underlie excitatory sound
wave propagation in cellular membranes including neuronal ones.”
This idea represents only one of many testable hypotheses describing how US may
mechanically (nonthermally) stimulate neuronal activity. Further studies are required
to explore the many potential mechanisms underlying the ability of US to stimulate
neuronal activity in the intact brain. Even without knowing the exact mechanisms of
action, however, FUS for brain stimulation represents a powerful new tool for
neuroscience.
Tufail et al. (2011)

25. Anesthesia & Slow oscillations
“We conclude that, although the main features of the slow
oscillation in sleep and anesthesia appear similar, multiple cellular
and network features are differently expressed during natural SWS
compared with ketamine–xylazine anesthesia.“ - Chauvette et al. 2011
Fragments of continuous electrographic recordings during
waking, slow-wave sleep, and ketamine xylazine anesthesia.–
a, Traces of multiunit activity and local field potential in
cortical area 3, EEG from area 5, EOG, and EMG
recorded in one cat during indicated conditions.
Corresponding recordings were obtained with the same
electrodes.
b, Autocorrelograms of the unit recording from the neuron
shown in a. Insets, Fifty spikes and their average (gray line)
of the unit shown in a for the three recorded states. Note a
dramatic increase in rhythmicity of cortical activities under
ketamine xylazine anesthesia.–

26. Anesthesia & Cerebrovascular coupling
“Schummers et al. 2008 also found that isoflurane concentrations (0.6 1.5 %)–
dose-dependently reduced responses of astrocytes, whilst neuronal sensitivity was
significantly less affected. Given accumulating evidence for the central role of
astrocytes in neurovascular coupling, the mechanism underpinning BOLD fMRI,
decreased sensitivity of involved astrocytes as a result of dosage variations could
hence affect phMRI data.”
Haensel et al. (2015)

27. Individual Alpha Frequency (IAF)
tACS driving humans at individual alpha frequency (IAF) done by Zaehle et al. (2010) and
Neuling et al. (2013)
9.5 11.5 Hz–
Klimesch (1999)
Neuling et al. (2013)
Coherence between EEG electrodes P3 and P4
Individual SO frequency?
Thalamus fine-tunes SO by imposing faster rhythm on cortical
oscillator | Interplay of two competing oscillators (
Gutierrez et al. 2013; David et al. 2013)?
Do we really gain much in practice by having a closed-loop
feedback on the dominant slow oscillation frequency?

28. COHERENCE?
Cavelli et al. (2015): Gamma coherence in rats
decrease during REM sleep
Depending on how much electrodes can be fitted
in addition to the prefrontal ones, one could
additionally analyze if the coherence / functional
connectivity is changed due to FUS?
“Data analysis practice”
Already quite coherent to start with?
Chauvette et al. (2011): Slow waves were mostly“
uniform across cortical areas under anesthesia, but
in SWS, they were most pronounced in associative
and visual areas but smaller and less regular in
somatosensory and motor cortices.” -

29. AD Model & Slow Oscillations
Menkes-Caspi et al. (2015): Intracellular and extracellular recordings revealed that transgenic mice had“
lower principal frequency during slow-wave sleep (SWS) and under anesthesia and reduced firing rates. ...
These findings indicate that pathological tau alters the functional connectivity of the cortical network in a
manner that disrupts activity mainly during highly synchronous epochs of synaptic activity, such as SWS
and anesthesia, and to a lesser extent during less synchronized epochs, as quiet wakefulness (QW). The
reduced delta-spindle power ratio found in nonanesthetized 5mo transgenic mice suggests a reduction in
the power of the thalamically gated spindle rhythm. This may imply that pathological tau alters
corticothalamic functional connectivity in addition to the neocortical activity.”
Neurons in 5mo Transgenic Mice Have a Higher Proportion
of False Up Transitions than Controls. Scatterplot revealed
that higher proportion of false Up transitions in transgenic
neurons is maintained when compared with controls at a low
principal frequency (shaded)

30. Cognitive Task?: Mismatch Negativity (MMN)
MMNp. MMNp was defined as the subtraction of
deviant AEP from standard AEP (black). Difference
wave between deviant AEP and many-standards-
control AEP was also shown for comparison (gray).
Shiramatsu et al. (2013)
“In the present study, in order to test whether MMNp in rodents exhibits
comparable properties to human MMN, we attempted to densely map AEP
in the auditory cortex of anesthesized rats using a surface microelectrode
array and to spatio-temporally characterize mismatch responses in an
oddball paradigm.”
Could be done in anesthesized rats, and
would be passive discrimination task

31. Predictive coding & State dependency
Arnal and Giraud, 2012
Braboszcz and Delorme (2011)