Thalamic and cortical contributions to physiological brain rhythms in vivo

Thalamic and cortical contributions to physiological brain rhythms in vivo

Thalamische und kortikale Komponenten physiologischer Hirnrhythmen in vivo

Dissertation

zur Erlangung des Doktorgrades der Naturwissenschaften

vorgelegt beim Fachbereich 15 der Johann Wolfgang Goethe-Universität

in Frankfurt am Main

von

Joscha Tapani Schmiedt aus Oxford, Großbritannien

Frankfurt (2016)

(D 30)

Gutachter: Prof. Dr. Manfred Kössl und Dr. Michael Schmid Datum der Disputation: 2.5.2016

Contents

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Zusammenfassung und Ausblick

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Part I

General introduction and discussion

CHAPTER 1

Introduction

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0TDJMMBUJPOT JO EZOBNJDBM TZTUFNT 1.1 Oscillations in dynamical systems

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1.1.1 The harmonic oscillator

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Y(U) = " sin(ѱU + ѵ)

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A B C

φ

¨

φ Pendulum:

interacting energies Single cell:

interacting currents Cell network:

interacting populations

I

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E

E

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200 ms

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Ih

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deactivate I_t

activate I_t inactivate

+

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t r(

r(

) )

Figure 1.1| Oscillationsindynamicalsystemsaretheresultoffeedbackinteractions.

A, An ideal pendulum exposed to gravitationHand displaced byѵfrom the resting equilibrium position will oscillate between a state of maximal potential energy at the highest point and and maximal kinetic energy at the lowest.

B, Example for a cell-intrinsic oscillation. A thalamocortical cell released from hyperpolarization will oscillate between burst firing and hyperpolarization due to an interplay between trans-membrane currents. Reproduced with permission from McCormick and Pape (1990).

C, Network oscillations of (population) firing rate result from interacting populations. In this example an inhibitory population (open circles) and an excitatory population (filled circles) are coupled. By mutual feedback their firing ratesScan oscillate (irrespective whether embedded in same area or segregated), possibly with a delay.

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1.1.2 Anharmonic oscillations

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1.1.3 Coupling of oscillators

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Isolated oscillators Coupled oscillators

f₁ f₂ f_sync f_sync

C

Figure 1.2 | Synchronization of coupled oscillators.

Two oscillators of different inherent frequenciesGŴandGŵ

(left) can synchronize under certain conditions if coupled with coupling strength$, and settle on a common fre- quencyG^sync(right). In general however, the extent of syn- chronization depends on many parameters of the cou- pling and individual oscillators.

1.2 Rhythms of the brain

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QPTJOH QPQVMBUJPOT WJB DIFNJDBM TZOBQTFT 'JH $

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(PVUBHOZ FU BM 1SPCBCMZ EVF UP JUT IFBWJMZ JOUFSDPOOFDUFE TUSVD UVSF XJUI NBOZ EJČFSFOU DFMM UZQFT UIF DPSUFY JT UIF NPTU QSPNJOFOU TJUF UIBU QSPEVDFT OFUXPSL PTDJMMBUJPOT GPS FYBNQMF UIF TMPX PTDJMMBUJPO )[ 4BODIF[7JWFT BOE .D$PSNJDL PS HBNNB PTDJMMBUJPOT )[ #V[TÈLJ BOE 8BOH *O UIF GVMMZ DPOOFDUFE JOUBDU CSBJO

3IZUINT PG UIF CSBJO 'SFR )[ &OHBHFE CSBJO BSFBT

TMPX $PSUFY UIBMBNVT IJQQPDBNQVT

EFMUB $PSUFY UIBMBNVT

UIFUB )JQQPDBNQVT DPSUFY

TQJOEMFT ćBMBNVT $PSUFY

BMQIB 7JTVBM DPSUFY -(/

CFUB .PUPS QBSJFUBM BOE WJTVBM DPSUFY CBTBM HBOHMJB HBNNB )[ 7JTVBM DPSUFY IJQQPDBNQVT

Table 1.1|Incomplete list of common names for frequency bands of brain rhythms. See Steriade (1993) and Buzsáki (2006) for an overview.

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" NPSF PS MFTT HFOFSBM GFBUVSF PG CSBJO SIZUINT JT UIBU MPX GSFRVFODZ SIZUINT TVDI BT UIF EFMUB SIZUINT BSF BTTPDJBUFE XJUI CFIBWJPSBM TUBUFT PG NJOJNBM BSPVTBM TVDI BT TMFFQ PS ESPXTJOFTT )JHI GSFRVFODZ SIZUINT PO UIF PUIFS IBOE BSF TUSPOHFTU JO IJHIMZ BMFSU BOJNBMT 4UFSJBEF )PXFWFS TVDI BO BTTPDJBUJPO JT MFTT DMFBS GPS TPNF JOUFSNFEJBUF SIZUINT FH UIF BMQIB BOE CFUB SIZUINT

1.2.1 Measuring brain rhythms

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&&( 8IFSFBT DPSUJDBM SFHJPOT DBO TPNFUJNFT CF TBNQMFE XJUI OPO PS NJOJNBMMZ JOWBTJWF UFDIOJRVFT TVCDPSUJDBM TUSVDUVSFT IBWF UP CF SFBDIFE XJUI QFOFUSBUJOH FMFDUSPEFT *O BMM DBTFT UIF SFGFSFODF FMFDUSPEF IBT UP CF QMBDFE XJUI DBSF TVDI UIBU UIF TBNQMFE WPMUBHF SFĘFDUT UIF FMFDUSJD ĕFME PG JOUFSFTU

3IZUINT PG UIF CSBJO DBO UIFO CF PCTFSWFE JO UIF SFDPSEFE TJHOBMT CF JU JO B SIZUINJD TFRVFODF PG BDUJPO QPUFOUJBMT GPS QBDFNBLFSMJLF OFV SPOT PS JO DPOUJOVPVT ĕFME QPUFOUJBMT ćF LFZ NFUIPE JO UIF RVBOUJĕ DBUJPO PG UIFTF SIZUINT JT UIF 'PVSJFS USBOTGPSN F XIJDI EFDPNQPTFT B TJHOBM Y ( U ) VTJOH TJOVTPJEBM GVODUJPOT PG GSFRVFODZ G = ѱ /( ŵɢ )

F

( ѱ ) = Ŵ

√ ŵɢ

!

∞

Y ( U ) F

EU

= Ŵ

√ ŵɢ

!

∞

Y ( U ) "

cos( −ѱU )) + J sin( −ѱU ) # EU

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ƭEJČFSFOUJBCMF DPOUJOVPVT JOUFHSBCMF JO-^ŵTQBDF

3IZUINT PG UIF CSBJO

BCPVU UIF TUSFOHUI BOE DPNPEVMBUJPOT PG SIZUINT JO UIF OFVSPOBM BD UJWJUZ TFF 5PSSFODF BOE $PNQP .JUSB BOE #PLJM GPS JOUSP EVDUJPO BOE SFWJFX 'PS FBDI GSFRVFODZ BOE UJNF QPJOU JG BQQMJFE XJUI B NPWJOH XJOEPX VQ UP UIF /ZRVJTU GSFRVFODZ UIF ''5 ZJFMET B DPN QMFY DPFďDJFOU F XJUI

" = |F|

ѵ = arctan Re( F ) Im( F )

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A

B

Time domain Frequency domain

2 4 6 8 10

0 0.5 1

2 4 6 8 10

0 0.5 1

Power (a.u.)

Frequency (Hz) Frequency (Hz)

Power (a.u.)

Sinusoidal simulationReal data

Time

Figure 1.3 | Examplesoffrequencyspectra.

A, 5 s of two summed sinusoids with frequen- ciesGŴ = 1.3 Hz andGŵ = 8.4 Hz. The peri- odicity is apparent in time domain (left) and as two sharp peaks in the power spectrum (right) at the respective frequencies.

B, 5 s of real intracranial EEG data from so- matosensory cortex of an anesthetized rat.

Note the non-sinusoidal shape of the oscilla- tion, i.e., sharpness of the downward transi- tions compared to the slow upward rises, which result in a blurred peak in the power spectrum (right) and nonzero energy at all frequencies.

1.2.2 Slow and delta rhythms in thalamus and cortex

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1.2.3 Beta rhythms in visual cortex

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1.2.4 Functional relevance of brain rhythms

'PS TPNF QIZTJPMPHJDBM TZTUFNT UIF GVODUJPO PG SIZUINJD CFIBWJPS JT NPSF PS MFTT BQQBSFOU TZTUFNT UIBU BDU BT WPMVNF QVNQT TVDI BT UIF IFBSU PS UIF MVOH DBO POMZ PQFSBUF JO BO PTDJMMBUPSZ NBOOFS EVF UP FO FSHZ BOE TQBDF DPOTUSBJOUT "MUIPVHI UIFZ BSF WJSUVBMMZ VCJRVJUPVT UIF SIZUINT PG UIF CSBJO IBWF CFFO QSPWFO EJďDVMU UP CF BTTJHOFE UP QBSUJDV MBS GVODUJPOT $PSSFMBUJPOBM FWJEFODF MFE UP UIF GPSNVMBUJPO PG EJČFSFOU IZQPUIFTFT GPS EJČFSFOU SIZUINT GPS FYBNQMF UIF TVQQSFTTJPO PG TFO

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1.2.5 Understanding rhythmogenesis by neuronal inactivation in vivo

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Figure 1.4 | Method of experimental inter- vention. In the studies presented here, the role of an area for a rhythm present in a con- nected downstream area was tested by re- moval of input to the downstream area. This was achieved by reversible pharmacological in- activation or permanent lesioning of the area under investigation.

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ćFSFGPSF JO UIJT UIFTJT * UFTUFE UIF SPMF PG B CSBJO BSFB TPNBUPTFO TPSZ UIBMBNVT BOE QSJNBSZ WJTVBM DPSUFY GPS UIF HFOFSBUJPO PG B SIZUIN TMPX SIZUIN BOE CFUB SIZUIN JO B DPOOFDUFE EPXOTUSFBN BSFB TP NBUPTFOTPSZ DPSUFY BOE WJTVBM FYUSBTUSJBUF DPSUFY CZ JOBDUJWBUJPO JO WJWP

Ʈ&Y WJWPQSFQBSBUJPOT TVDI BT CSBJO TMJDFT PG DPVSTF BMTP QSPWJEF FYDFMMFOU DPOUSPM PG WJSUVBMMZ BMM FY QFSJNFOUBM QBSBNFUFST BOE DBO QSPWJEF DPNQMFNFOUBSZ BOE JNQPSUBOU JOTJHIUT BCPVU UIF NJDSPTDPQJD HFOFSBUJPO PG CSBJO SIZUINT 5P TUVEZQIZTJPMPHJDBMCSBJO SIZUINT IPXFWFS UIF GVMMZ JOUBDU TZTUFN TIPVME CF UIF ĕOBM TVCKFDU PG JOWFTUJHBUJPO 4UFSJBEF C

"OBUPNJDBM BOE GVODUJPOBM BTQFDUT PG UIF UIBMBNVT

1.3 Anatomical and functional aspects of the thalamus

1.3.1 Anatomy

ćF UIBMBNVT JT B DPMMFDUJPO PG OVDMFJ JO UIF NJECSBJO UIBU BMM QSPKFDU UP DPSUFY +POFT BOE DBO CF EJTUJOHVJTIFE CBTFE PO UIFJS JOQVU PVUQVU QBUUFSOT ćFSF BSF UISFF LJOET PG OVDMFJ 'JH 4IFSNBO BOE (VJMMFSZ

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JOOFSWBUFT BMM PUIFS UIBMBNJD OVDMFJ BOE SFDFJWFT JOQVU GSPN CPUI UIBMBNJD OVDMFJ BOE DPSUFY

HO FO

CORTEX

THALAMUS

SENSORY PERIPHERY BRAINSTEM

-

- +

+ + +

+ +

+

+ +

NRT

Figure 1.5 | Types of thalamic nuclei.

First order nuclei (FO) relay sensory in- formation from the periphery into cor- tex with strong driving synapses, while the input they receive from cortex is transferred through weaker modulating synapses. Higher order nuclei (HO) on the other hand do not receive sensory input and receive as well as send driving pro- jections from and to cortex. Both types of nuclei are inhibited by the reticular nucleus (NRT), which receives collaterals from both corticothalamic as well as thalamocortical projections.

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1.3.2 Physiology

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4JODF UIJT EJTDPWFSZ EVSJOH UIF T JU DPVME CF FTUBCMJTIFE UIBU B TQFDJĕD JOUFSBDUJPO CFUXFFO B 5UZQF DBMDJVN DVSSFOU *

BOE UIF IZQFS QPMBSJ[BUJPOBDUJWBUFE DVSSFOU *

BMMPXT UIBMBNJD OFVSPOT UP TXJUDI CF

"OBUPNJDBM BOE GVODUJPOBM BTQFDUT PG UIF UIBMBNVT

UXFFO UIFTF NPEFT $SVOFMMJ FU BM .D$PSNJDL BOE 1BQF

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FUD ZJFMEJOH B SIZUINJD TFRVFODF PG TQJLF CVSTUT 'JH

ćJT NFNCSBOF QPUFOUJBMEFQFOEFOU TXJUDIJOH PG NPEVT PQFSBOEJ JT UIPVHIU UP BMMPX UIBMBNPDPSUJDBM OFVSPOT UP BDU BT HBUF GPS JOGPSNB UJPO USBOTNJTTJPO CZ TXJUDIJOH CFUXFFO EJČFSFOU GVODUJPOBM EZOBNJDBM SFHJNFT 8IFSFBT UIF EFQPMBSJ[FE NPEF BMMPXT UIF IJHI ĕEFMJUZ SFMBZ PG TFOTPSZ JOGPSNBUJPO BU IZQFSQPMBSJ[FE MFWFMT BO JOQVU XJMM MFBE UP B TUFSFPUZQFE SIZUINJD QBUUFSO UIBU DPOUBJOT MJUUMF JOGPSNBUJPO BCPVU UIF JOQVU 4UFSJBEF ćJT JEFB JT DPSSPCPSBUFE CZ UIF GBDU UIBU OFVSPOT JO UIF UIBMBNJD SFMBZ OVDMFJ EP OPU CVSTU JO BUUFOUJWF BOJNBMT CVU POMZ EVSJOH TMFFQ XIFO UIF DPSUFY JT EJTDPOOFDUFE GSPN UIF PVUTJEF XPSME

-65 mV

-58 mV

2 s 20 mV Tonic mode Oscillatory mode Oscillatory mode

Figure 1.6| Membranepotential-dependentswitchingofmodeinthalamocorticalneurons. A hyperpolarized thalamocortical neuron will operate in an oscillatory mode and switch to cortical-like tonic mode when brought to a slightly depolarized membrane potential. Reproduced with permission from McCormick and Pape (1990).

1.4 The primate visual system

ćF JNBHFGPSNJOH WJTVBM TZTUFN QSPDFTTFT TFOTPSZ JOGPSNBUJPO BCPVU UIF XPSME UIBU FOUFST UIF PSHBOJTN WJB QIPUPO BCTPSQUJPO JO UIF QIP UPSFDFQUPST PG UIF SFUJOB 8VSU[ BOE ,BOEFM "ęFS JOUSBSFUJOBM QSPDFTTJOH TFF 8ÊTTMF GPS B SFWJFX SFUJOBM HBOHMJPO DFMMT 3($T USBOTNJU UIF MJHIU JOGPSNBUJPO UP UIF MBUFSBM HFOJDVMBUF OVDMFVT -(/ JO UIF UIBMBNVT XIFSF JU JT SFMBZFE JOUP WJTVBM DPSUFY TUSPOHFTU JOUP QSJ NBSZ WJTVBM DPSUFY 7 *O BEEJUJPO UIF 3($T QSPKFDU UP UIF TVQFSJPS DPMMJDVMVT 4$ JO UIF UFDUVN XIJDI DPOUSPMT TBDDBEJD FZF NPWFNFOUT

Figure 1.7 | Schematicoftheprimatevisualsys- tem. Visual information from the retina of the eye is primarily relayed through the lateral geniculate nu- cleus (LGN) into primary visual cortex (V1). From there it spreads through and is processed in the heavily interconnected visual cortex (intracortical connections are omitted for clarity). A second vi- sual pathway goes into superior colliculus, which projects to pulvinar (PUL) and the LGN. Pulvinar is reciprocally connected with virtually all visual cor- tical areas. Branching of its projections to cortex is common. Next to the strong connection with V1, LGN projects weakly to extrastriate visual cortex (gray arrows).

PUL V4

MT V3 V2

V1 Cortex

Thalamus

Tectum LGN

Retina SC

1.4.1 Lateral geniculate nucleus

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ćF QSJNBUF WJTVBM TZTUFN

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M M

K

KK K K PP

PP Striate cortex

V1

LGN L1

L2/3 L4 L5 L6

Thalamus Superior Colliculus

Extrastriate cortex V2, V3, V4, MT, ...

FF FF

FB

Figure 1.8 | Schematic of connectivity betweenthalamicandcorticallayersof thevisualsystem. LGN consists of four parvocellular (P) and two magnocellular layers (M) that project strongest to gran- ular layer 4 of V1. From there visual in- formation is processed within a microcol- umn and output is sent to subcortical struc- tures from layer 5, back to LGN from layer 6 and to extrastriate cortical areas from layer 2/3 in a feedforward manner (FF). Feed- back (FB) from extrastriate cortex is re- ceived mainly from infragranular layers into supra- and infragranular layers. The konio- cellular layers (K) of LGN in between the M and P layers project to supragranular lay- ers of both striate and extrastriate cortex (omitted for clarity).

1.4.2 Visual cortex

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ćF QSJNBUF WJTVBM TZTUFN

1.4.3 Pulvinar

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LGN vPUL

dPUL

nRT bsc

PM PL

PI

Visual cortex Fronto-parietal

cortex

Eye

M L

D

V

Figure 1.9 | Anatomical subdivisions of pulvinar. Inferior (PI) and most parts of dorsal lateral pulvinar (PL) are reciprocally connected with visual cortices. Medial pulvinar (PM) and some parts of PL are connected with frontal and parietal cor- tices. nRT, Reticular nucleus. LGN, Lateral geniculate nucleus. dPUL, Dorsal pulvinar, vPUL, Ventral pulvinar.

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CHAPTER 2

Discussion and summary

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2.1 Contribution of thalamus to slow waves

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Figure 2.1 | Decelerationofsleepslow rhythm after thalamic inactivation.

When somatosensory thalamus (VB) and cortex (S1) were connected the slow rhythm was synchronous in both ar- eas (left). Inactivation of the thalamic oscillation did not abolish the cortical rhythm but strongly decreased its fre- quency (right) suggesting that the tha- lamus tunes the frequency of the sleep slow rhythm.

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VB NRT

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V1 V4 Higher visual cortex

L1L2/3 L4

L5L6 β β β

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γ γ

γ

LGN Pulvinar

FF

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δ

M/P

K

Figure 2.2 | Generation of awake beta rhythm in extrastriate cortex. Beta (ќ) rhythms in V4 survived a V1 lesion and were enhanced by post lesion visual stimulation indicating that beta originates from an interaction of local, remote cor- tical (feedback, FB) and/or thalamic os- cillatory generators. LGN was shown to contain alpha/beta-generating networks (see Lőrincz et al., 2009; Bastos et al., 2014, and Chapter 4), which might con- tribute to extrastriate rhythms via the ko- niocellular system. Pulvinar was asso- ciated with alpha/beta activity (Saalmann et al., 2012) but our own study did not find strong alpha/beta generators in pulv- inar. V4 gamma (ѝ) rhythms and spiking were strongly diminished by removal of V1 indicating a reliance on feedforward (FF) projections.

2.3 Summary

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Part II

Contribution of thalamus to slow/delta rhythms

CHAPTER 3

Essential thalamic contribution to slow waves of natural sleep

Status: in press

Name der Zeitschrift: The Journal of Neuroscience Beteiligte Autoren:

- Francois David (FD)

- Joscha T. Schmiedt (Promovierender) - Hannah L. Taylor (HLT)

- Gergely Orban (GO) - Giuseppe Di Giovanni (GDG)

- Victor N. Uebele (VCN) - John J. Renger (JJR) - Régis C. Lambert (RCG) - Nathalie Leresche (NL) - Vincenzo Crunelli (VC)

Was hat der/die Promovierende bzw. was haben die Co-Autoren/Autorinnen beigetragen?

(1) zu Entwicklung und Planung Promovierender 15%

FD 15%, VC 30%, HLT 8%, GO 8%, GDG 8%, RCL 8%, NL 8%

(2) zur Durchführung der einzelnen Untersuchungen und Experimente

Promovierender: Pharmakologische Experimente an anästhesierten und frei schlafenden Tieren (40%) FD: Experimente an anästhesierten und frei schlafenden Tieren, Optogenetische Stimulations- Experimente in anästhetiserten Tieren (40%)

GO: Vorläufige pharmakologische Experimente an anästhesierten Tieren (10%) HLT: Optogenetische Stimulations-Experimente in anästhesierten Tieren (10%) (3) zur Erstellung der Datensammlung und Abbildungen

Promovierender: Aufbau des Ableitsetups in allen Experimenten, Erstellung von Fig. 1-5 (50%) FD: Aufbau des Ableitsetups in allen Experimenten, Erstellung von Fig. 6-9 (50%)

(4) zur Analyse und Interpretation der Daten

Promovierender: Analyse und Interpretation aller Daten, vorwiegend aus Experimenten unter Anästhesie (40%)

FD: Analyse und Interpretation aller Daten, vorwiegend aus Experimenten in frei schlafenen Tieren (40%) VC: Interpretation aller Daten (20%)

(5) zur Verfassung des Manuskripts Promovierender 33%:

FD 33%

VC 33%