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Bill Kristan Section of Neurobiology Division of Biological Sciences UC San Diego La Jolla, CA The dynamics of decision-making by leech neurons Neurobiology of Decision-Making CSH 24 May 2005
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We make all kinds of choices: Choosing whether Choosing when Choosing how Choosing which (respond or ignore) Choosing what(feed on it, fight it, love it) (direct/indirect, strongly/subtly) (now, later) (regular/diet, large/medium, left/right)
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We make all kinds of choices: Choosing whether Choosing when Choosing how Choosing which (respond or ignore) Choosing what(feed on it, fight it, love it) (direct/indirect, strongly/subtly) (now, later) (regular/diet, large/medium, left/right)
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Leeches crawl in shallow water (3 mm)
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Leeches swim in deep water (33 mm)
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Anatomy of the leech CNS
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Leech preparations
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Leech locomotory behaviors Swimming 1 sec Dorsal Ventral 10 sec CCC CCC EEE G10 G13 Elongation (E) Contraction (C) Crawling
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Cell 204 DE motor neuron 5 sec 10 mV Weeks & Kristan, 1978 Swim initiation by a command neuron, cell 204
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Invertebrate model of choice: inhibition of command neurons Command neurons Command neurons
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Problem #1: some “command neurons” are activated in incompatible behaviors. Shaw & Kristan, 1997
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Semi-intact preparation Intracellular Extracellular Stimulate cell R3b1: Esch,Mesce & Kristan, 2002 Problem #2: Some “command neurons” are bifunctional Shallow water Deep water
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using a combinatorial code by multiplexed neurons Decisions appear to be made interactively
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Leech nervous system can swim or crawl to the same stimulus Use isolated nerve cord Head brain Tail brain G15 same stimulation elicits different responses: S Stimulate (S) one nerve electrically R, record (R) from another Stimulus Swimming Crawling Imaging Briggman, Abarbanel & Kristan, 2005
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Optical activity in motor neurons during swimming Data of Adam Taylor
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Membrane potential trajectories of 144 neurons dF/F (%) Swim Time (msec) Cell number Crawl Time (msec) Cell number Briggman, Abarbanel & Kristan, 2005
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Discrimination by single neurons Non-discriminating (ND) Early Discriminating (ED) Late Discriminating (LD)Transiently Discriminating (TD) Swim Trials Crawl Trials p > 0.000001 p < 0.000001 Nerve DT Single cell DT Single cells with early DTs Briggman, Abarbanel & Kristan, 2005
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PC1 PC2 PC3 Cell Number Principal component analysis, across neurons
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Discrimination of single cells vs. neuronal populations { Cells contributing to Linear DiscriminantSingle cells with early DTs LDA DTs Earliest cell DTs Nerve DTs Single cell DTs {
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Polarizing cell 208 biases behavioral choice Hyperpolarized Trials (-1.5 nA) Depolarized Trials (+1.5 nA) Intracellular Stimulation DP Nerve Stimulus Briggman, Abarbanel & Kristan, 2005
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Leeches make behavioral choices sequentially R3b1 swimming “Locomote” crawling 204 swimming “Swim!” 28 swimming “Bend up (down)” Cell Active during Command 208 swimming “Do something!” shortening
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x y z Swim CPG Crawl CPG Rest state Stimulation Decision making and dynamically:
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Many leech neurons take part in both swimming and crawling. Only a few differ early -- using a combinatorial code. -- among multiplexed neurons Decision-making may depend on dynamic interactions (good candidates for being decision-makers). About half of them have different activity in the two behaviors. CONCLUSIONS
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COLLABORATORS: DavidKleinfeld RogerTsien Tito Gonzalez Peter Brodfuehrer HenryAbarbanel KRISTAN LAB: Brian Shaw TimCacciatore Adam Taylor TeresaEsch KarenMesce Kevin Briggman Cast of characters (PanVera)(AuroraBiosciences) Dyesprovided by Vertex Pharmaceuticals Gary Cottrell
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Linear Discriminant Analysis (LDA) Cell A Cell B Cell C LD Direction a b c
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PC1 PC2 Principal component analysis, by participating neurons: PC1 PC2 A B PC1 PC2 PC3 Cell Number Briggman, Abarbanel & Kristan, 2005
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What’s ahead? x p(success of A) p(choice A) = response threshold p(choice A) x (benefit of A - risks) = p(any behavior) x sensory processing x (positive - negative) modulation Input to decision makers: source of modulation site of action effects of feeding classical conditioning: bias to swim or crawl
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KRISTAN LAB: Brian Shaw Tim Cacciatore Adam Taylor TeresaEsch KarenMesce KevinBriggman Cast of characters by Dyes provided (PanVera) (AuroraBiosciences ) Vertex Pharmaceuticals COLLABORATORS: DavidKleinfeld Roger Tsien Tito Gonzalez Peter Brodfuehrer Henry Abarbanel Gary Cottrell
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Discrimination by single neurons Non-discriminating (ND) Early Discriminating (ED) Late Discriminating (LD)Transiently Discriminating (TD) Swim Trials Crawl Trials p > 0.000001 p < 0.000001 Nerve DT Single cell DT (Data of Kevin Briggman)
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Discrimination by single neurons Single cells with early DTs
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Swimming… in 144 neurons Data of Kevin Briggman dF/F (%) Cell number Time (msec)
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Cell Stimulation type: produces: Active during: Command: A swimming swimming “Do something!” shortening Is leech decision-making hierarchical? B swimming or swimming “Get out of here!” crawlingcrawling C swimming swimming“Swim!” D bending swimming “Move this muscle group”
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Cell 204 is inhibited during shortening…. Data of Brian Shaw
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Record optically from 91 neurons simultaneously Swim Shorten (Data of Kevin Briggman)
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ShortenSwim Swim – Shorten Subtract no-swim from swim traces for each neuron (Data of Kevin Briggman)
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Reasonable hypothesis: Decision-making neurons have different activity trajectories in different behaviors.
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Swimming Time Component amplitude PCA1 PCA2 PCA3 Shapes of the first 3 components: Use principal component analysis (PCA) to detect neurons with different activity trajectories in different behaviors. Crawling (Data of Kevin Briggman)
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Response Variability Tail brain G12 G15 Head brain (Data of Kevin Briggman)
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Swim Crawl (Data of Kevin Briggman) A few neurons have different trajectories in swimming and crawling:
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Another reasonable hypothesis: Decision-making neurons have the earliest differences in their trajectories.
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Use PCA analysis to follow the trajectories of neuronal classes over time. C1 C2 C3 With just 3 neurons, we could plot their activity on separate axes: 1 st Frame Stimulus delivered 1 st Swim Burst PC 1 PC 2 PC 3 For assemblies of neurons, we plot their PCA components:
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Do we make choices hierarchically? (sequential, linear) …..or interactively? (feedback, resetting) …..or simultaneously? (nonlinearity, overlapping function) “Choice-makers” will be active in sequence “Choice-makers” activity will bounce back and forth “Choice-makers” will all be active at the same time
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Neuronal circuits for whole-body shortening, swimming Mechanosensory neurons Trigger interneurons Gating interneurons Oscillator interneurons Motor neurons
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Shortening and swimming circuits overlap
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Measuring voltage changes with FRET dyes (FRET = fluorescence resonance energy transfer) (Developed by Tito Gonzalez & Roger Tsien)
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FRET VSD optical signals (Figure provided by Tim Cacciatore)
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Tr2 terminates swimming
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Swimming…. in 90 neurons Data of Kevin Briggman
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FRET-based dyes can detect synaptic potentials
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Tr2 spikes elicit 1-1 EPSPs
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Multiple responses to identical stimulation Head brain Tail brain G15 Use isolated nerve cord same stimulation elicits different responses: Stimulate (S) one nerve electrically S, record (R) from another R Swimming Behavioral state ? ? Behavioral choice ? ? Data of Kevin Briggman Crawling
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Do we make choices hierarchically? ”Let’s go out to dinner” “Some place new” “Italian” “Mario’s!” (implies sequential, linear) …..or interactively? ”I’m not that hungry; let’s do that new Bistro” ”I don’t want to dress up; how about our favorite sushi bar?” “The Lakers are playing tonight; maybe we should order in.” (implies feedback, resetting) …..or simultaneously? {impossible to express verbally} (suggests nonlinearity, overlapping function)
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