Focused Ultrasound NeuromodulationDriving Slow-Oscillations (1 Hz) in rats

Petteri Teikari, PhDNov 2015

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

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)

tACS in vivo rats entrain slow oscillationsOzen et al, (2010)

INT ENSIT Y 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 T ES 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 T ES field and the strength of their entrainment increased as stimulation intensity increased.

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.

T he 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)

Optogenetic in vivo simulationKuki 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.

T he 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

Optogenetic in vitro s(t)imulationSchmidt 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.”

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 Readoutfor FUS stimulation

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 windowwith a 12 mm coverslip

http://www.mind.ilstu.edu/dev/parkinsons_lab/rat_brain/Paxinos_Watson/Paxinos_Watson_published_rat%20_brain.php

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 rathttp://www.cosmobio.co.jp/connections/p_ku_e_view.asp?PrimaryKeyValue=20643&selPrice=1

Rat Anatomy #3

Seki et al. (2013) http://dx.doi.org/10.3389/fnana.2013.00045

Rat Anatomy #4

Rat EEGXu et al. (2013)

Protocol for Rat Sleep EEG http://www.ndineuroscience.com/userfiles/Rat_Sleep_EEG_Methods.pdf

DYESSR-101 astrocytes

OGB-1 calciumdi-4-ANEPPS membrane potential

Qdot800 vessel diameter

Schematic of FUS stimulation

CALCIUM OGB-1

Neuron CA2+

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 vasodilationfollowing 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 IC1on Red ch

Bleed of IC2on 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

CALCIUM OGB-1

Neuron CA2+

ASTROCYTE SR-101

Astrocytic CA2+

LUMEN Cascade Blue

Vessel diameter Membrane potential

Membrane potential with VSD using rTMS to stimulate cat visual cortex

Astrocytes trigger rapid vasodilationfollowing photolysis of caged Ca+.

Low-intensity afferent neural activity caused vasodilation in the absence of astrocyte Ca2+ transients.

Dye Options #2

BRAIN DRIVINGSTATE-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.

FUS & 2-PM Triggering

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 PfurtschellerBioSig Toolbox

e.g. ECG Regression correctionwith human EEG

TTL High TTL High TTL High

1 Hz Amplitude envelope

+EXTRA SLIDESEmpty in purpose

THALAMUS in FUS studies of rats #1Yoo et al. (2011)

Bystritsky and Korb (2015):

Kim et al. (2014)

THALAMUS in FUS studies of rats #2

Bystritsky and Korb (2015):

Kim et al. (2013)

Min et al. (2011)

Yang et al. (2012)

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)

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. –

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)

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?

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.” -

AD Model & Slow OscillationsMenkes-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)

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

Predictive coding & State dependencyArnal and Giraud, 2012

Braboszcz and Delorme (2011)