Microcircuit Recording and Imaging Ed Boyden Synthetic Neurobiology - - PowerPoint PPT Presentation

Microcircuit Recording and Imaging

Ed Boyden

Synthetic Neurobiology Laboratory Massachusetts Institute of Technology Invited lecture at Stanford in CS379C on April 10, 2013

Today’s outline

PRINCIPLES, USES, UNKNOWNS Electrodes Electrode arrays Dyes Indicators Microscopes Endoscopes

Electrodes

• A wire can do the trick

– Want an impedance of 100-5000 kiloohms

• Polyimide, teflon, or

parylene coated tungsten, steel, or platinum-iridium

• Precise impedance,

material, tip angle, shank length, taper, etc. can all impact your recording

– Ad hoc adjustment of these parameters

Tetrodes

Motorized microdrives

• An individual motor on each microdrive

(Yamamoto and Wilson, 2008)

Early electrode array: theme: simple, reliable engineering tricks (Campbell et al., 1991)

• Thermomigration of Al

through n-type silicon

– Takes a few minutes; heat

• pens up migration slots

– PNP junctions isolate probes from each other – Modern probes are physically separated by glass (silicon dioxide) layers

• Take a dicing saw and cut

in between each of these p+ trails

– Diamond, 250-micron-wide blade, 30krpm – Cut one way, then the other – Can use wire EDM to do this (Ian Hunter’s lab at MIT)

Making the tips

• Vigorously stirred 3-

minute etch with 5% HF and 95% HNO3

– Followed by a shallow 3- minute etch (simply, do not stir)

Coating the tips

• These two steps remove 75% of the volume of

each needle, thus displacing <2% of nerve tissue upon insertion

• Deposit gold on the tips

– Stick array through thin foil, then sputter gold on the exposed surface – Platinum also used

Inserting it into the brain

• Pneumatic inserter (Rousche and Normann,

1992)

• Scale bar = 1 mm

Modern such array

• Silicon oxide layers for even

better insulation

• Next steps: integrating

electronics in

• Lesson: neurons are pretty

macroscopic as far as MEMS goes

That hasn’t stopped some people from going further

• Create silicon nanowires, then align them using

microfluidics methods (Patolsky et al., 2006)

– By creating p- and n-doped versions, directly make FET amplifiers on the neuron

How do you get nanowires to line up on pads? Do it the other way around

• Langmuir-Blodgett

aligning: compress a monolayer of nanowires floating on a trough

• Then etch away silicon

wires outside each domain

• f interest
• Since silicon, can then

add other devices

Yield and drift

• Hard arrays - most studies indicate that the neurons

recorded drift

– Yield: 25-60% of electrodes on a given implantation will have useful recordings

• Often get multiple neurons per trode, but must separate

in software

– No way to move these electrodes dynamically yet – Drift over several weeks

• Wire arrays

– “a few cells” could be recorded over 3 years in a monkey (sporadic result; not replicated)

• Insert stiff electrodes that relax (exciting area!!)
• Tetrodes – can drift somewhat over many weeks

– Can be high yield – many neurons per tetrode can be separated thanks to combinations; can adjust depth of each to optimize positions – Flexible – move somewhat with brain?

Modern ideas

• Make the electrode flexible, to match the

impedance of tissue

– Carbon fiber, polyimide

• Make the electrode small, comparable to the size
• f neurons

– “Microthread”

• Coat the electrode with anti-biofouling

compounds

– PEGMA

Spike sorting

• Many electrodes will get more than one neuron

– Can only analyze spikes separated in time

• A few attempts to overcome this problem, but none universally

accepted – Clustering in spike-property space allows you to separate the spikes

• Tetrodes give you many spike properties, and measured from

multiple positions – Of course, spikes that always occur close in time will be ignored/ deleted since they will never be separable, so synchrony or other properties will be eliminated by clustering analysis – Tons of heuristics, free software, MATLAB scripts, etc.

Make the electrode fit the purpose

• Example: lots of interest in

recording large sets of neurons in a peripheral nerve

• Cuff electrodes – get a

few (3-10) recording sites

– Crude for recording; crude for stimulation too – Most nerves are mixed – both motor and sensory

• Sieve electrodes

– Cut nerve, let it regenerate – Lots of problems

One partial solution: change the neural code

• Reroute arm nerves to muscles in chest to

broadcast coherent signals

Patch clamping

• Glass electrode, place near cell, suck membrane close,

and then ‘break in’ using suction

– Get access to the inside – Negative

• Wash out cell’s contents
• Short recording times (minutes) à cell death
• Low yield
• Irreversible (can’t tune back and forth)
• Works best for surfaces structures

– Positives

• Great isolation
• Fine resolution à subthreshold activity
• Voltage control
• Dialyze in filling dyes, indicators, blocking drugs, or other

chemicals

• Suck out mRNA/other intracellular information

Patch clamping in freely moving rats

• Must anchor after achieving whole cell recording

(Lee et al., 2006)

A robot that can automatically patch clamp neurons in living brain

Commercialized by Neuromatic Devices, Inc. (ESB has no financial affiliation) 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.

Integrative analysis of cell types of the brain: molecule to morphology to physiology

+ + gene expression

Suhasa Kodandaramaiah, Ian Wickersham, Craig Forest, Hongkui Zeng and Allen Institute for Brain Science

Ragan et al., Nature Methods 2012

Nanowires inside cells?

(Duan et al., 2012)

Optical principles

• Already covered

absorption

– ‘Intrinsic imaging’ – chromophores like blood that change absorption functionally

• Reflection

– Indirect measure of absorption – good for in vivo

• Fluorescence

– Increase the parameters for more flexibility – excitation vs emission

• Lots of others: coherent

anti-stoke raman scattering, second harmonic generation, fluorescence lifetime imaging, optical coherence tomography,…

Dyes: Calcium

• Calcium is 50 nM inside a

neuron, and 2 mM outside a neuron

• Thus, a natural tag for

neural activity

• Fura-2 (1985)

– Four carboxylate groups – a motif that binds Ca+2

• Kd ~ 236 nM

– Excitation fluorescence shifts when Ca+2 binds A = Ca+2 saturated, B = Ca+2 free

• Big changes!

Calcium dye usage in vivo

• Pressure-eject Oregon Green BAPTA-1 (Stosiek

et al., 2003)

Problems that must already be all too

• bvious
• Big signals

– 20-50% changes in fluorescence – can see by eye

• Calcium is slow

– Slow to enter, slow to leave – Saturates dyes rapidly, because of vast dynamic range of calcium combined with slow kinetics – Even with linear filters, signal processing, or deconvolution, can’t resolve individual spikes at rates much greater than 1 Hz

• Simulate spike ßà Ca

+2 in order to invert better (Vogelstein et al., 2008)

Voltage dyes

• Translocate across the

membrane, or sit in membrane and change conformation when voltage changes

– Fluorescence: RH1691 – Absorption: RH155 – Fluorescence: Di-4- ANEPPS

• Smaller changes than Ca

+2

– < 1%

Two-photon voltage imaging?

• Need a fast scope (Vucinic

and Sejnowski, 2007)

• Hard to resolve cells –

need a good dye (Kuhn et al, 2008)

Genetically-encoded sensors

• Find a sensor of x, and then attach it to a fluorophore in some way
• FRET methods

– Donor and acceptor molecules must be in close proximity (typically 10-100 Å, which is 1-10 nm. For comparison the diameter of a DNA double helix is 2.3 nm, an F-actin filament ~6 nm, an intermediate filament ~10 nm, and a microtubule 25 nm – Absorption spectrum of the acceptor must overlap fluorescence emission spectrum of the donor. – Donor and acceptor transition dipole orientations must be approximately parallel (for optimal energy transfer). – Can be slow

• Protein-unfolding/perturbing methods

– Attach GFP (or other molecule) to a sensor – Circularly permute GFP and attach a sensor inside GFP – Can be slow

• Few of these have been crafted from scratch

– E.g., a stark shift genetic sensor - never been done yet

Genetically-encoded sensors

• Cameleon – one of the earliest proposed sensors

(Miyawaki et al., 1997)

– blue or cyan variant of GFP (FRET donor), calmodulin (CaM), a glycylglycine linker, the CaM-binding domain of myosin light chain kinase (M13), and a green or yellow version of GFP (FRET acceptor) – Used to be lots of background binding (neurons express a lot of stuff), slow, small changes; gotten better

Genetically-encoded sensors

• Circularly permuted GFP

sensors (Nagai et al., 2001)

– GFP is a barrel – can start and stop the strands at any point

Genetically-encoded sensors

• Mostly low signal-to-noise ratio

– Different papers for this week

• Lots of screening to improve,

but still ceilings

• Many work in invertebrates, but

not mammalian cells, or not in mammalian neurons

– E.g., neurons have a lot of calmodulin – disrupts function

• f early Cameleons

GCamp2: combination of circ permut and CaM/M13

GCaMP5

• (Akerboom et al., 2012)

Genetically-encoded sensors

• Many others

– Voltage sensors: several new ones coming out – Synaptophluorin – pH sensitive GFP to measure acidity of organelles (e.g., synaptic vesicles) – Clomeleon – fluorescence voltage sensor – Several fluorescent glutamate sensor – Aequorin – bioluminescent calcium sensor (emits a flash of blue light when it binds calcium)

Voltage sensing opsins

Kleinlogel et al. (2011) Nature Methods 8(12):1083-1088.

Kralj et al. (2012) Nature Methods 9:90-95.

Basic fluorescence microscope designs

• Lots of other modalities for imaging – DIC, phase

contrast, interferometry, at least 50 others

Two-photon microscopy

• Infrared photons go deeper into brain

– Can image down 500-800 microns vs. 80-100 microns for a confocal

• Excitation falls off with the square of intensity, since two

photons needed to excite one fluorophore

– Less background excitation – Less photobleaching of other photons

Instrumentation

• Just a scanning microscope

Endoscopes

• GRIN lens – dope a fiber with

Ag to increase refractive index

• Can make endoscopes

300-1000 microns wide with a lens on the end, to transmit an image

– Not an optical fiber, but a lens; the ‘fiber’ is a ‘relay lens’ – must be a multiple of the focal length of the relay – Optical fibers themselves cannot transmit images: rays at different angles will have different pathlengths, causing

• blur. The gradient-index curves

light instead, assembling them into an image.

• Hard to get working; GRIN lenses still of highly

variable quality

– Supplmementary paper this week discusses endoscopy of brain

Cameras are small and high-resolution

• Can go headborne: (Ghosh et al., 2011)

Light-sheet microscopy

• (Holekamp et al., 2008)

Super-resolution Microscopy

(Hell, 2007)

Super-resolution Microscopy

Willig et al., 2006 – STED of synaptotagmin Rust et al., 2006 – STORM of photoswitchable Cy5 Betzig et al., 2006 – PALM of photoactivatable GFP

Automating Electron Microscopy with Serial Section Backscatter Electron Microscopy

$750,000 for a full setup. (Jurrus et al., 2006) (Denk and Horstmann, 2004)

Other kinds of microscopy?

• Light: lightfield, structured light,…
• Electrons: FIBSEM, TEM, ATLUM,…
• X-rays: CT,…
• Sound: photoacoustic tomography from last

time…

Other ways to label things?

• (Livet et al., 2007)

Beyond imaging

• See the 3-D structure of the genome: Hi-C

(Lieberman-Aiden et al., 2009)

Brainbow + Hi-C:

• Proposed in (Zador et al., 2012)

Recording neural activities into DNA

Zamft, Marblestone, et al. (2012) PLoS ONE 7(8): e43876.

Ca+2 modulates polymerase error rate

Zamft, Marblestone, et al. (2012) PLoS ONE 7(8): e43876.

Detailed sequence analysis

Zamft, Marblestone, et al. (2012) PLoS ONE 7(8): e43876.

Other papers relevant for this week

READINGS Bai Q, Wise KD, Anderson DJ. A high-yield microassembly structure for three-dimensional microelectrode arrays. IEEE Trans Biomed Eng. 2000 Mar;47(3):281-9. http://ieeexplore.ieee.org/iel5/10/17965/00827288.pdf Branner A, Stein RB, Normann RA. Selective stimulation of cat sciatic nerve using an array of varying- length microelectrodes. J Neurophysiol. 2001 Apr;85(4):1585-94. http://jn.physiology.org/cgi/content/full/85/4/1585 Flusberg BA, Jung JC, Cocker ED, Anderson EP, Schnitzer MJ. In vivo brain imaging using a portable 3.9 gram two-photon fluorescence microendoscope. Opt Lett. 2005 Sep 1;30(17):2272-4. http://www.opticsinfobase.org/abstract.cfm?URI=ol-30-17-2272 Dimitar Dimitrov, You He, Hiroki Mutoh, Bradley J. Baker, Lawrence Cohen, Walther Akemann, and Thomas Knöpfel Engineering and Characterization of an Enhanced Fluorescent Protein Voltage Sensor PLoS ONE. 2007; 2(5): e440. doi: 10.1371/journal.pone.0000440. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1857823

SUPPLEMENTARY READINGS Csicsvari J, Henze DA, Jamieson B, Harris KD, Sirota A, Bartho P, Wise KD, Buzsaki G. Massively parallel recording of unit and local field potentials with silicon-based electrodes. J Neurophysiol. 2003 Aug;90(2):1314-23. http://jn.physiology.org/cgi/content/full/90/2/1314 Suner, S. Fellows, M.R. Vargas-Irwin, C. Nakata, G.K. Donoghue, J.P. Reliability of signals from a chronically implanted, silicon-based electrode array in non-human primate primary motor cortex Neural Systems and Rehabilitation Engineering, IEEE Transactions on; Dec. 2005; Volume: 13, Issue: 4; p. 524- 541 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1556610 Andrew B. Schwartz CORTICAL NEURAL PROSTHETICS Annual Review of Neuroscience; Vol. 27: 487-507 http://arjournals.annualreviews.org/doi/full/10.1146/annurev.neuro. 27.070203.144233?cookieSet=1 Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, Branner A, Chen D, Penn RD, Donoghue JP. Neuronal ensemble control of prosthetic devices by a human with tetraplegia.

• Nature. 2006 Jul 13;442(7099):164-71.

http://www.nature.com/nature/journal/v442/n7099/abs/nature04970.html Yu B, Ryu S, Santhanam G, Churchland M, Shenoy K. Improving neural prosthetic system performance by combining plan and peri- movement activity. Conf Proc IEEE Eng Med Biol Soc. 2004;6:4516-9. http://ieeexplore.ieee.org/iel5/9639/30463/01404254.pdf?arnumber=1404254 Reinert KC, Dunbar RL, Gao W, Chen G, Ebner TJ. Flavoprotein autofluorescence imaging of neuronal activation in the cerebellar cortex in vivo. J Neurophysiol. 2004 Jul;92(1):199-211. http://jn.physiology.org/cgi/content/full/92/1/199