Reading the mind of a worm 0.1 Global dynamics embed the motor - PowerPoint PPT Presentation

Reading the mind of a worm 0.1 Global dynamics embed the motor command sequence of C. elegans 0.05 PC3 0 −0.05 0.1 0 PC2 −0.1 0.2 0 −0.2 PC1 Saul Kato (IMP Vienna) Stanford, 2016-04-04

collaborators Yifan Xu, Rockefeller Cori Bargmann, Rockefeller Christine Cho, Rockefeller Larry Abbott, Columbia Harris Kaplan, IMP Tina Schrödel, IMP Manuel Zimmer, IMP funding EMBO Simons Collaboration on the Global Brain European Research Council NIH

Today 1. Introduction 2. Single cell dynamics 3. Network dynamics 4. What’s next

my motivating hypothesis Some aspects of higher cognition, such as flexible reasoning, may have originated in the production of variable but controlled behavioral sequences in simpler animals.

what would a “complete” story of how a nervous system generates behavior look like?

a complete story of neurons-to-behavior should, at the minimum: organism behavior must be explain single trials competent on a single trial basis explain behavior as behavior is an continuous, as a time series online output of a nervous system cannot rely on a be self-contained homunculus or components outside of the model

a one neuron animal Chemotaxis in E. coli Analysed by 3D Tracking Berg & Brown, Nature 1972 G 0 = k m (1 − I ) A − k p IG + k r k b A A 0 = − k m A (1 − I ) − + k p GI A + K mm

a one neuron animal G 0 = k m (1 − I ) A − k p IG + k r k b A A 0 = − k m A (1 − I ) − + k p GI A + K mm p ( CW → CCW ) = f 1 ( G ) p ( CCW → CW ) = f 2 ( G ) Robustness and adaptation in simple biochemical networks Barkai & Leibler, Nature 1997 Larry Abbott

C. elegans 302 neurons ~6000 synapses ~900 gap junctions Virtual Worm Project no classical action potentials. Na + channels lost during nematode evolution • cell lineage fully mapped (Sulston et al., 1983) • connectome fully mapped (White et al., 1986) • genome sequenced ( C. elegans Consortium, 1998)

worm ethology

describing high-level behavior REVERSE RUN VENTRAL SLOWING TURN DORSAL FORWARD TURN RUN state transition diagram

the worm connectome sensory neurons sensory neurons 2 2 interneurons interneurons ASJL PHAR AIMR ASJR motor neurons motor neurons 1.5 ASIR AINL ALMR PHAL PVM AIML HSNL ASIL PHCR AINR AWAR ASGL AWAL AVFL ADLR AWBL IL2R ADLL ASEL IL2L AWBR ALML 1 PVQL PLNR FLPR ADFL PVDR VC05 AVM IL2VL LUAR CEPDR SDQL IL2VR CEPVR ASGR PDEL ASER ASHR PLMR IL2DL AWCR PVPR PLNL ASHL IL2DR AWCL ADFR AVHR RIH BDUL BDUR ADEL AVHL PHBR PVDL VC04 BAGL PVNL FLPL PVQR CEPDL PHBL CEPVL URBR ADER PQR URXL PDER ASKL PLML PHCL processing depth ASKR AVG RIFR ALNL LUAL SDQR AFDR RIR RIFL HSNR AFDL OLLL 0.5 ADAL processing depth BAGR PVWR AUAL URXR AUAR ALNR URYVR URBL URYVL PVT AIYL RMGR RIS PVNR RMGL AIAL ALA PVR URAVR ADAR AIAR AVFR URADR AIZL AVJR PVPL OLLR AIZR AQR URAVL IL1VR PVWL IL1R RICL PVCR DVA URADL IL1L AIYR URYDR OLQVL SAAVL IL1VL RICR AIBL OLQVR URYDL AVDR 0 RIVR RMFL SMBVR VA12 0 AVDL RIAR DVC RIAL PDA OLQDR SAAVR IL1DL RIVL AVJL VD11 AIBR PVCL DVB RIGL RIGR VB01 VC02 OLQDL SAADR SMBVL AVKR IL1DR SMBDR AVKL AVL RMFR RMHR RMHL RIBL SAADL VB08 RMEL AVER AVEL VB11 VC03 RIBR AVBL AVAL AVAR RIPL SMBDL RIPR DB01 SIADR RIMR SIBDR RMER AVBR VB10 RIML SIADL RMEV 0.5 VB09 SIBVL SIAVR RMED RMDL RID VA07 VB02 SIBDL VB07 SIAVL RMDDR SIBVR VB06 DB07 VA02 SMDVL DB02 VC01 RMDDL SABD AS11 DA09 VB03 DB03 PDB VA09 VA08 DB04 VB05 VB04 RMDR VA01 VA04 AS01 AS02 VD10 VD13 VA03 SMDVR RMDVR VA11 AS09 SMDDL AS06 DA01 SABVR DA03 DA04 VA06 RMDVL DB05 DB06 AS03 SMDDR 1 AS05 DA05 DA02 DA08 AS04 VA05 SABVL VD01 VD09 DA06 AS07 AS10 VD12 VA10 DA07 AS08 DD05 DD06 1.5 VD07 VD08 VD02 DD01 VD05 DD04 DD02 VD04 DD03 VD03 VD06 -2 2 0.025 0.02 0.015 0.01 0.005 0 0.005 0.01 0.015 0.02 normalized Laplacian eigenvector 2 Chen 2011

part of the parts list HEAD (4) BODY TAIL CHEMOSENSORY PHARYNX NEURONS AMPHIDS (LR) OUTER DEIRIDS PHASMIDS (LR) LABIA (6) PQR M1 awal AWA awar ASK adel ADE ader ADE PDE PHA I1 L R L R L R L R L R L R L R INNER LABIA (6) AWB ASJ AQR BAG PHB I2 M2 R R R L R L R L R L L L L R L IL1 R awcl awcr AWC ASG I3 M3 L R L R L R URX L R R L ASE ADL I4 M4 L R L R DL DR DL DR CEP OLQ L R L R VL VR VL VR URY PHC L R L IL2 R ASI ADF I5 M5 L R R R L L OLL L R ALN L R AFD R L I6 L R FLP ASH R L R L MECHANOSENSORY MI AVM pvm PVM R L MC ALM PLM R R L L NSM dva DVA PVD R L aiml AIY aiyr INTERNEURONS L R aual AUA auar riaL RIA riar L R R L ribL RIB ribr R L ricL RIC ricr R L BODY avkl avkr AVK L R L R SAA rifl RIF rifr L R ala ALA R L rigl RIG rigr L R sdql SDQ sdqr RING R L rid RID avfl avfr AVF rih RIH L R aial aiar adal adar dvc DVC AIA ADA L R L R avhl AVH avhr bdul BDU bdur lual LUA luar L R R R pvpl PVP pvpr L L R L urbl URB urbr R rir RIR L avjl AVJ avjr avel AVE aver aibl AIB aibr L R R R L L pvqr PVQ pvql L R pvr PVR D ris RIS SAB aiml AIM aimr R rmgl RMG rmgr L R pvnl pvnr L PVN pvr PVT R L R D D L aiml AIN aimr R L avg AVG ripl ripr pvwl PVW pvwr RIP L R L R aval avar avbl AVB avbr AVA L R L R avl AVL aizl AIZ aizr pvcl PVC pvcr avdl avdr L R AVD avm AVM L R L R rivl RIV rivr R L MOTONEURONS pdb PDB riml RIM rimr L R L R rmfl RMF rmfr SIA SMB R L L R dvb DVB L R L R pda PDA rmhl RMH rmhr L R hsnl HSN hsnr L R L R L R L R SIB SMD URA RME L R L R L R L R L R L R va01 va12 da01 da09 1 2 3 4 5 6 VA 7 8 9 10 11 12 1 2 3 4 5 6 DA 7 8 9 RMD L R vb01 vb11 1 2 3 4 5 6 VB 7 8 9 10 11 11 db01 1 2 3 4 5 6 DB 7 db07 R L vc01 vc06 1 2 3 4 5 VC 6 dd01 1 2 3 4 5 DD 6 dd06 vd01 1 2 3 4 5 6 VD 7 8 9 10 11 12 13 11 vd13 as01 1 2 3 4 5 6 AS 7 8 9 10 11 11 as11

Today 1. Introduction 2. Single cell dynamics 3. Network dynamics 4. Next steps

AWC

sensory responses circa 2009 GCaMP1.0 WT nlp-1 200% Δ F / F Odor Odor 0 60 120 0 60 120 time (s ) time (s) Chalasani, Kato, et al Nat Neuro 2011

responses to complex input AWC GCaMP3.0 2 0 F/F 1 0 0 30 60 90 120 150 180 210 time (s) Kato et al, Neuron 2014

sensory neurons are highly reliable trials 1 2 20 s Kato et al, Neuron 2014

a simple model predicts sensory responses with high fidelity L N F(x) K(t) input output x u(t) x(t) y(t) normalized magnitude 0 y ( F/F) AWC 0 4 8 12 16 20 24 lag (s) x Kato et al, Neuron 2014

an ODE model of a neuron k f dA dt = k a A+ input F k af dF A input output dt = k f F + k af A k as S k a dS dt = k s S - k A as k s =F + output S S F 0 10 20 30 40 0 10 20 30 40 Lag (s) Lag (s) Kato et al, Neuron 2014

summary part 1 • C elegans sensory neurons can be highly reliable signal transducers. • the analog GCaMP signal can be used for quantitative dynamical studies.

Today 1. Introduction 2. Single cell dynamics 3. Network dynamics 4. Next steps

the c elegans brain

the c elegans brain head ganglia

C. elegans has a stereotypic neuroanatomy Dorsal ganglion Ventral ganglion Anterior ganglion Retrovesicular ganglion Ventral ganglion 10 µm adapted from White, 1986

how to do high quality whole-brain Ca 2+ imaging volumetric microscopy microfluidics spinning disk confocal 10 Z @ 2.9 volumes/s nuclear-localized GCaMP5K N+$ NLS$ M13$ GFP$ CaM$ NLS$ +C$

nuclear localized GCaMP for resolving single cell activity nucleus-localized GCaMP

AVAR AVAL RIMR RIML AVER VA01 SABVL

(OLQVR/URYVR) (OLQDL/URYDL) AIBL AIBR 42 108 38 (OLQDR/URYDR) 9 20 93 40 ALA 31 47 22 50 AVFL 48 76 18 55 52 77 94 62 90 5 85 49 10 14 1 11 (RIFR/AVG/DD01) 51 88 83 35 105 (SMBDR/SMBVR/SMDDR/RMFR) 64 74 7 25 34 86 3 6 0 60 120 180 240 300 360 420 480 540 600 660 720 780 840 900 960 1020 1080 Time (s)

neural dynamics exhibit a widely shared, cyclical signal Δ F/F 0 −0.2 0 1 1.5 AVAR AVAL RIMR RIML AVER VA01 SABVL OLQVL DB01 VB01 DB02 RMER Neuron RMEL RID AVBR RIBL VB02 RMED RMEV AVBL SMDVL SMDVR RIVL RIVR AIBL OLQVR AIBR OLQDL OLQDR RIFR SMBVR PC1 PC2 PC3 0 60 120 180 240 300 360 420 480 540 600 660 720 780 840 900 960 1020 Time (s) PCA TVD 1 TPC# 2 3 0 60 120 180 240 300 360 420 480 540 600 660 720 780 840 900 960 1020 Time (s)

neural dynamics exhibit a widely shared, cyclical low-dimensional signal 80 explained (%) 60 Variance 1 TPC# 40 2 20 3 0 0 60 120 180 240 300 360 420 480 540 600 660 720 780 840 900 960 1020 12345678910 Time (s) PC

neural dynamics exhibit a widely shared, cyclical low-dimensional signal 1 brain cycle 1 TPC# 2 3 0 60 120 180 240 300 360 420 480 540 600 660 Time (s)