Circuit Elements of the Nervous System Ed Boyden Synthetic - PowerPoint PPT Presentation

Circuit Elements of the Nervous System Ed Boyden Synthetic Neurobiology Laboratory Massachusetts Institute of Technology Invited lecture at Stanford in CS379C on April 8, 2013

Today’s outline PARTS • Cells as engineerable circuit elements • Molecules in the context of cells • Brain regions in the context of cells THEMES • Implications for neuroengineering • What properties of cells make them observable? • What properties of cells make them amenable to being controlled?

Why Neurotechnology? PERSISTENT, ENORMOUS, • Economic Costs of UNMET NEEDS Neuro-disorders: Orange font = top 7 $1.3 trillion/yr in the U.S (greater than 200 million alone people worldwide) • People: 2 billion people Alzheimer's Insomnia worldwide, >100 million Addiction Migraine Americans suffer from a ALS Multiple Anxiety sclerosis brain or nervous system Blindness Obesity illness Chronic Pain Paralysis Depression Parkinson's Epilepsy Schizophrenia Source: Neurotechnology Industry Organization, Oct 2008 Headache Sleep disorders http://www.neurotechindustry.org/ Hearing loss Spinal Cord Huntington’s Injury Stroke

The Numbers Cost (US alone, 2008) People (global, 2008) • Addiction: 790m • Addiction: $366b • Anxiety: 400m • Alzheimer's: $146b • Obesity: 300m • Obesity: $123b • Chronic pain: 290m • Chronic pain: $95b • Migraine: 240m • Depression: $83b • Depression: 240m • Attention deficits: $77b • Sleep: 238m • Sleep: $75b • Hearing loss: 140m • Stroke: $57b • Attention deficits: 120m • TBI: $56b • Alzheimer's: 90m • Vision loss: $52b • Stroke: 60m • Epilepsy: 50m • Hearing loss: $50b • Anxiety: $47b Source: Neurotechnology Industry Organization, Oct 2008 http://www.neurotechindustry.org/

What is the right abstraction layer for engineering the brain? Lewis et al. Denk and Horstmann 2005 2004 Brain regions 1700s-present 1 µ m ‘Precise’ microcircuitry? 1990s-present Ramon y Cajal 1899 ‘Population’ microcircuitry in tissue/slices 1890-present

Goals for a good technology • Make the most meaningful measurements, and interpret them accurately • Make the most precise perturbations of specific substrates, and test the necessity and sufficiency of those substrates • Understand the mechanisms behind symptoms in the most precise way possible • Control a neural circuit in the most powerful way, with the fewest side effects

Today’s outline PARTS • Cells as engineerable circuit elements • Molecules in the context of cells • Brain regions in the context of cells THEMES • Implications for neuroengineering • What properties of cells make them observable? • What properties of cells make them amenable to being controlled?

Cells as engineerable circuit elements • Cell types are defined by geometry, genome state/gene expression, physiology, connectivity, and protein state • Self-contained computational units – Maintain stable resting potential; contain genome; survive autonomously – Go smaller: vastly more incomplete picture; go larger: heterogeneity • Molecules only make sense in the context of the specific cell type they’re in • Brain regions only make sense in the context of the cell types found therein

The Neuron

Molecular components of the neuron • Postsynapse and dendrites – Receptors for neurotransmitters (excitatory - glutamate, inhibitory - GABA, modulatory – DA, ACh, 5-HT, NE; slow vs. fast forms of each) – Integrate signals passively on the membrane, as well as with active conductances (potassium, calcium, sodium) – Prominent plastic elements (kinases, receptors, mRNA) • Cell bodies – Nonlinearity towards a spike • Axons – Sodium and potassium channels: conduction of spike • Presynapse – Calcium channels admit calcium; then, release of neurotransmitter (excitatory, inhibitory, modulatory; short-range vs. long-range) – Prominent plastic elements (release machinery, kinases, cytoskeleton) • Throughout the neuron – Pumps and exchangers to maintain resting potential (Na+ out, K+ in, Cl- out) – Receptors for neurotransmitters – Ion channels – Gap junctions

Cell classes: shapes, location • Unlike many other fields of biology, in neuroscience, “Anatomy is function” • Shapes (Markram et al., 2004)

Molecular markers that correlate with shape/location • Shapes correlate with markers, but not perfectly (Markram et al., 2004)

Cell types: spiking • Physiology (Markram et al., 2004)

Shape, molecules, physiology • Not perfect correspondence (Markram et al., 2004)

Whole cell patch clamp: enables simultaneous measurement of electrophysiology, morphology, and gene expression in single cells in living brain Kodandaramaiah et al. (2012) Nature Methods 9:585–587.

A robot that can automatically patch clamp neurons in living brain Kodandaramaiah et al. (2012) Nature Methods 9:585–587. Commercialized by Neuromatic Devices, Inc. (ESB has no financial affiliation)

The patch algorithm: robotic assessment of sequences of pipette resistances, followed by fast action Kodandaramaiah et al. (2012) Nature Methods 9:585–587.

In vivo robotics: converting an art form to software Kodandaramaiah et al. (2012) Nature Methods 9:585–587.

Derived an algorithm: high-performance recording, with high yields Kodandaramaiah et al. (2012) Nature Methods 9:585–587.

Derived for the cortex, the algorithm works in the hippocampus as well Kodandaramaiah et al. (2012) Nature Methods 9:585–587.

Good access resistances, holding currents, resting potentials, and holding times – independent of depth Kodandaramaiah et al. (2012) Nature Methods 9:585–587.

Integrative analysis of cell types of the brain: molecule to morphology to physiology + Ragan et al., Nature Methods 2012 + gene expression Suhasa Kodandaramaiah, Ian Wickersham, Craig Forest, Hongkui Zeng and Allen Institute for Brain Science

How do the properties of a cell give us a handle on controlling or reading it? • Given a cell, can isolate a promoter – DNA in front of the gene – to target a gene to it – Small promoter – can put in virus – BAC transgenics • Big promoter – knock-ins • Insert your gene into that locus

Labeling something by activity? • Fos-driven feedback loop – Fos = immediate early gene (IEG), turned on by activity (and perhaps plasticity) – Only on for a short time, though. – Solution: turn on a nonlinear switch (Reijmers et al., 2007)

Glial cells • Long thought to be “metabolic supporting” cells, but found to release • Calcium waves can transmitters and spread throughout glial communicate networks, via gap junctions and ATP (Guthrie et • >90% of cells in human al., 1999) brain • Connected by gap junctions, have similar receptors and release machinery to neurons • Don’t fire spikes

Glial cells • Adenosine: • Glial cells release ATP and glutamate (Innocenti et al., – If you block release of ATP, then animals do not develop 2000) sleep debt (normally you sleep more on night 2, if deprived on night 1) – Also, cognitive consequences of sleep loss are ameliorated – Glial release of adenosine to A1A receptors important for effects of DBS? (Bekar et al., • Block release: impairs 2008) synaptic function and • Glutamate release implicated plasticity (Pascual et al., 2005) in neural activity-blood flow coupling (Schummers et al., 2008)

Astrocytes and blood flow • Neuronal activity releases glutamate à astrocyte activation (calcium waves) à release vasoactive substances (prostaglandins) à vasodilation (Zonta et al., 2003)

Astrocytes and blood flow • Neuronal activity releases glutamate à astrocyte activation (calcium waves) à release vasoactive substances (prostaglandins) à vasodilation (Zonta et al., 2003) • Astrocytes are the ‘invisible cell’ in between

Today’s outline PARTS • Cells as engineerable circuit elements • Molecules in the context of cells • Brain regions in the context of cells THEMES • Implications for neuroengineering • What properties of cells make them observable? • What properties of cells make them amenable to being controlled?

Molecules make sense in the context of the specific cell type they’re in: leptin • Leptin released by fat cells, regulates energy homeostasis by action in brain – Potential target for obesity and diabetes • But, leptin receptor expressed in multiple cell classes in the hypothalamus – which is the site? • Delete leptin receptor in one subclass, the steroidogenic factor-1 neurons – neurons are not activated by leptin • Potential brain stimulation target? Clustered in ventromedial hypothalamus …

Channelopathies • Rare, but instructive – Can link molecule to phenotype – Mutations in a single channel can result in many different results

Synapsopathies • A model of obsessive compulsive disorder: molecular deletion of Sapap3, scaffolding protein important for glutamate receptor presence, and synaptic strength (Welch et al., 2007) • Leads to excessive grooming • Striatal intervention reduces phenotype