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1Neuro-Transistors– JASS 2005
How everything started…
Direct link between brain and computer.
1985:
Peter Fromherz, Max Planck Institute of Biochemistry
How to design a neuron-silicon junction?
2Neuro-Transistors– JASS 2005
Content
1. Neuronal signalingi. Neuron architectureii. Membrane potentialiii. Action potential
2. Neuro-Transistorsi. Point-Contact Modelii. Transistor recordingiii. Capacitive stimulationiv. Two neurons and a chip
3Neuro-Transistors– JASS 2005
Architecture of a neuron
Basic functional units:Input component
Trigger component
Long-range conducting component
Output component
Dendrites
Cell body (soma)
Axon
Presynaptic terminals
4Neuro-Transistors– JASS 2005
Neurons communicate by electrical signaling.
Action potential:
Brief, invariant and large electrical pulse
All-or-none signal
Frequency-coded
Signaling
5Neuro-Transistors– JASS 2005
The cell membrane
Double layer of hydrophobic lipid molecules
Membrane proteins:
1. voltage-gated ion channels
2. ligand-gated (chemically- controlled) ion channels
3. energy consuming ion pumps
Control transport of ions throughthe cell membrane.
6Neuro-Transistors– JASS 2005
Separation of charges across membrane
Membrane potential: outinM VVV
Reduction in charge separation: Depolarization
Increase in charge separation: Hyperpolarization
Potential determined by:Ionic conductances of the cell membrane
Distribution of ions across the membrane(mainly potassium and sodium )K Na
Membrane Potential
7Neuro-Transistors– JASS 2005
Charge separationacross the membrane.
Potential difference acrossthe membrane driving -ions back into the cell.
-ions concentrated inside the cell.
K
Chemical force drivingthem outside downconcentration gradient.
chemF elF
K
Membrane Potential
8Neuro-Transistors– JASS 2005
Equilibrium potential:
i
oBK K
K
ez
TkV ln Nernst Equation
Giant squid axon: mVmV
VK 75400
20ln
1
25
Passive process, consumes no energy.
Energy is needed to set up initial concentration gradients.
Ion pumps: Proteins in cell membrane. Ion transport through hydrolysis of ATP to ADP.
Equilibrium:
Chemical force = Electrical force
Membrane Potential
9Neuro-Transistors– JASS 2005
Equilibrium with several ion species:
Ion flux = (electrical force + chemical force) x membrane conductance
Influence of each ion species by concentration gradient and permeability of membrane
Membrane potential described by Goldman-Hodgkin-Katz equation:
oCliNaiK
iCloNaoKBm ClPNaPKP
ClPNaPKP
e
TkV ln GHK Equation
usually around -60mV. mV
10Neuro-Transistors– JASS 2005
Generation of an action potential
Membrane potential and ionic conductancescomputed from the Hodgkin-Huxley model.
11Neuro-Transistors– JASS 2005
Recording electrical signals from neurons:
Small glass micropipettes (d < 1µm) filled with concentrated salt solutionare inserted into the cell.
Connection via an amplifier to an oscilloscope.
12Neuro-Transistors– JASS 2005
Voltage-clamp technique:
Difficult to examine ion conductances and because of their strong voltage dependence.
Holding (clamping) the potential in the cell at a certain value.
Opening of voltage-gated ion channels does not affect membrane potential.
Kg Nag
13Neuro-Transistors– JASS 2005
Patch-Clamp Technique
Allows measurement of currentsthrough single ion channels.
Seal between electrode and membrane.
Reduction of electronic noise.
Suction
14Neuro-Transistors– JASS 2005
Signal Propagation along the Axon
Axon can be described as one-dimensional cable.
Cell membrane: insulating coat Intracellular fluid: conductive core
Conduction velocity depends on:
Diameter of axon (Giant squid axon d=1mm)
Insulation of axonal membrane
15Neuro-Transistors– JASS 2005
Myelination
Myelin: electrically insulating layer around axons.
Nodes of Ranvier
Conduction velocity:
Unmyelinated: v = 5 to 10
Myelinated: up to v = 150
smsm
16Neuro-Transistors– JASS 2005
Synapses
Chemical signal transmission across the synaptic cleft.
Action potential
Neurotransmitter release
Neural plasticity:Regulation of synaptic strength.
Learning and memory
17Neuro-Transistors– JASS 2005
Today: Trying to understand fundamental principles of neuron-silicon junctions.
Physical rationalization of junction to optimize neuron-silicon interfacing
Hybrid systems with neuronal networksand microelectronic devices.
………..?
Today Science-Fiction
Where to go?
18Neuro-Transistors– JASS 2005
Principles of coupling
(a) Electrical field across the membrane polarizes the silicon dioxide on the chip.
(b) Electrical field across the silicon dioxide polarizes the membrane affecting voltage- gated ion-channels.Unfortunately:
(c) Neuronal activity leads to ionic and displacement currents through the membrane.
Proteins from cell membrane keepmembrane at certain distance fromthe chip.
(d) Voltage transient applied to silicon causes displacement current through oxide.
Transductive Extracellular Potential (TEP)
Transductive Extracellular Potential (TEP)
Current spreads along the cleft.
19Neuro-Transistors– JASS 2005
MC
JM
JJ A
Gg
JM
MM A
Cc
SCJM
SS A
Cc JG
JM
iJMi
JM A
Gg
Capacitance of the chip: ,
Ionic conductances:iJMG
Conductance of the cleft: ,
Capacitance of the Membrane:
Point-Contact Model
,
,
Transductive extracellular potential mediates coupling of neuron and silicon.
TEP is determined by current balance in junction.
Point-Contact Model
20Neuro-Transistors– JASS 2005
i
iJM
iJM
ionicM VVVgI 0
dt
dV
dt
dVcI JMM
capM
dt
dV
dt
dVcI JSS
capS
i
iJM
iJM
JMM
JSSEJJ VVVg
dt
dV
dt
dVc
dt
dV
dt
dVcVVg 0
Kirchhoff‘s law: ionicM
capM
capS
ohmiccleft IIII
EJJohmiccleft VVgI
Point-Contact Model
21Neuro-Transistors– JASS 2005
Current balance in the cell:
i
iJM
iJM
JMMJM VVVg
dt
dV
dt
dVcA 0
i
iEM
iFM
EMMFM VVVg
dt
dV
dt
dVcA 0
:Area of the free membrane.
:Area of the attached membrane.JMA
FMA
Point-Contact Model
22Neuro-Transistors– JASS 2005
Remarks:ionic conductances depend on voltage difference across the membrane (Hodgkin-Huxley-Model).point-contact model assumes that all currents flow through one point in the membrane. Parameters , , represent average values.point-contact model is a simplification of an area-contact modelwhere depends on the position in the junction.
iJMg
Jg
Mc Sc
yxVJ , yx,
Point-Contact Model
Efficient recording and stimulation:
small distance high specific resistancelarge radius
high ionic conductanceshigh capacitance of the chip
JdJ
Jasmall
Jg
23Neuro-Transistors– JASS 2005
ESV
DSV
Stimulation voltage
Source-drain-voltage
Electrolyte-source-voltage
Source-drain current is controlled by gate-source voltage
Resulting current is changed to a voltage, amplified and watched on an osciloscope.
Calibration measurement without cell to determine voltage-current characteristic GSD VI
DI SJGS VVV
Transistor recording
24Neuro-Transistors– JASS 2005
Leech neuron on FET contacted with patch-pipette in whole cell configuration.
Ac-voltage is amplified. Response recorded with transistor.
M
J
V
V
tVJ
Plot of transfer spectrum :
tVM
Two different types of spectra observed:
A-type: - small amplitude at low frequencies.- increase of phase around 10Hz.- increase of amplitude above 1000Hz.
B-type: - high amplitude at low frequencies.- just minor change in phase.- further increase of amplitude above 1000Hz.
Ac-stimulation with transistor recording:
25Neuro-Transistors– JASS 2005
Interpretation using the point-contact-model:
Insert intracellular stimulation and extracellular response tiMM eVtV
tiJJ eVtV
i
iJM
iJM
JMM
JSSEJJ VVVg
dt
dV
dt
dVc
dt
dV
dt
dVcVVg 0
with 0EV 0dt
dVS and iJMg JMg
No ion channels, just leak conductance.
in
MSJMJ
MJM
M
J
ccigg
cig
V
V
JMJ
JM
M
J
gg
g
V
V
0
Low frequency limit:
A-type: Small amplitude at low frequencies low membrane conductanceB-type: Enhanced amplitude at low frequencies larger membrane conductance
Further increase at high frequencies large conductance
JMg
Jg
dt
dVcgVcc
dt
dVggV M
MJMMMSJ
JMJJ
26Neuro-Transistors– JASS 2005
With the values and which are known, data fitting gives us:
236.0 cmmSg JM 2217 cmmSg J
25.38 cmmSg JM 28.40 cmmSg J
25 cmFcM 23.0 cmFcS
A-type:
B-type:
Crucial difference: leak conductance of the attached membrane differs by two orders of magnitude.
A-type = Capacitive junction
B-type = Ohmic junction
Ac-stimulation with transistor recording:
27Neuro-Transistors– JASS 2005
Transistor recording of neuronal activity:
Small signal approximation:
Small extracellular potential
No capacitive current to the chip
MJ dVdV
0
dt
dV
dt
dVc JSS
i
iM
iJM
MMJJ VVg
dt
dVcVg 0
INJMi
iM
iJMM
iFM
MMM jVVgg
dt
dVc 11 0
JM
FMM A
A
iMJ VVV 0 ,
28Neuro-Transistors– JASS 2005
A-, B- and C-type response:
No voltage-gated ion channels in the membrane:
dt
dVcVVgVg MM
i
iM
iJMJJ 0
Negligible leak conductance TEP proportional to first derivative
A-type junction
Dominating ohmic leak conductance TEP reflects intracellular waveform
B-type junction
INJi
iM
iJMM
iFM
M
MM jVVgg
dt
dVc
01
1
Insert
in
Transistor recording of neuronal activity:
dt
dVcVVgVg MMMJMJJ 0
29Neuro-Transistors– JASS 2005
i
INJi
MiJMM
iFM
Mi
iM
iJMJJ jVVggVVgVg 00 1
1
i
INJi
MiFM
iJM
MJJ jVVggVg 01
1
TEP of an action potential relies on inhomogeneity of the membrane.Wide spectrum of waveforms depending on distribution ofvoltage-gated ion channels.Details must be treated by numerical simulation.
tVJ
Transistor recording of neuronal activity:
30Neuro-Transistors– JASS 2005
Transistor records of a leech neuron
Two positions of the neuron:
(a)Cell body right on the transistor.(b) Axon stump on transistor array.
Action potential elicited by currentinjection with a micropipette.
Intracellular potential measured with pipette, extracellular potential with transistor.
31Neuro-Transistors– JASS 2005
Transistor records of a leech neuron
Three types of records:
A: first derivative of waveformcapacitive junction
B: waveform itselfohmic junction
C: numerical simulation: accumulation of and -channels in attached membrane.
Depletion of ion-channels in cell body.High density of ion-channels in axon
K Na
32Neuro-Transistors– JASS 2005
Transistor records of neurons from rat hippocampus
Action potentials are elicited by current injection.Records with signal averaging of transistor signals.
Two positive transients in ,one in rising phase of AP andone in falling phase.
tVJ
Interpretation:
Positive peak in falling phase is related with outward potassium current through attached membrane.
With 00 NaM VV 0 Na
FMNaJM gg
Sodium inward current through free membrane gives riseto capacitive outward current through attached membrane.
00 KM VV 0 K
FMKJM gg
Positive peak in rising phase is related with sodium current.
Observation:
33Neuro-Transistors– JASS 2005
Capacitive stimulation of neuronal activity
Changing voltage applied to stimulation spot
Capacitive current through insulating oxide
Current along the cleft Transductive extracellular potential TEP
Voltage-gated ion channels in the membrane may open
Action potential may arise.
tVtV SS 0
tVM
A-type stimulation:
Voltage step
Exponential response of membrane potential.
J
t
MM eVtV 0
with very short time constant sJ 3for mammalian neurons.
tVS
34Neuro-Transistors– JASS 2005
B-type stimulation: tVtV SS 0Voltage step
Exponential response due to capacitive effects.
stat
t
MrestM VeVVV J 0
Also stationary change of intracellular potential.
C-type stimulation: depends on channel sorting. Must be treated with numerical simulation.
tVM
Step stimulation of a leech neuron:
Voltage step with = 4.8, 4.9, 5.0V0SV
Stimulation below threshold cannot elicit an action potential (4.8V).
Capacitive stimulation of neuronal activity
35Neuro-Transistors– JASS 2005
Burst stimulation of snail neuron:
Excitation is achieved only when aburst of voltage pulses is applied.
After each pulse responds with short capacitive transients at rising and falling edge of
tVM
tVS
After the third pulse the intracellular potential rises so that an action potential is elicited.
36Neuro-Transistors– JASS 2005
Circuits with two neurons on a chip
Probing with FET Signal processing Capacitive stimulation tVJ
Neuronal activity tVM Action potential
(i) Transformation of and amplification.
(ii) Identification of an action potential with a threshold device.
(iii) Delay line(iv) Generation of a train of voltage
pulses.(v) Suppression of crosstalk from
stimulator to transistor by refractory unit.
37Neuro-Transistors– JASS 2005
Connection between a spontaneously firing neuron A along the chip to aseparate neuron B.After each action potential in neuron A a burst of voltage pulses is generatedand applied to neuron B.
Neuron B fires in correlation to neuron A.
Circuits with two neurons on a chip
38Neuro-Transistors– JASS 2005
Signaling chip-neuron-neuron-chip
Action potential Synaptic connection Neuronal activity tVM
Probing with FET tVJ
Problem:
Growing neurites exert strong forces on thecell bodies of neurons.
They pull them of their contacts.
Capacitive stimulation
39Neuro-Transistors– JASS 2005
Mechanical fixation of the cell bodies
Picket fences made out of polyimid (plastic) around each contact.
Two neurons from animmobilized network ofsnail neurons.
Stimulation with burst ofseven voltage pulses.
Third action potential in neuron 1leads to a postsynaptic excitationin neuron 2.
Perturbations in transistor signaldue to capacitive coupling with stimulator.
40Neuro-Transistors– JASS 2005
Towards defined neuronal nets
Systematic experiments on network dynamics require:
(i) Noninvasive, long term supervision and stimulation of neurons(ii) Fabrication of neuronal nets with defined topology of synaptic
connections.
Control of neuronal outgrowth:
1.) Chemical guidance:
Motion of neuronal outgrowth isguided by chemical patterns.
Linear patterns of extracellularmatrix proteins are able to guideneuronal outgrowth and let themform synapses.
41Neuro-Transistors– JASS 2005
2.) Topographical guidance
Grown neurites are immobilized bymicroscopic grooves.
Cell bodies are placed in into the pits ofa polymer structure.Neurites grow along the grooves and split at bifurcations.
Problem: Neuritic tree is not uniquelydefined by the guiding pattern.
Alternative: Disordered growth of neuronal nets on closely packed transistor arrays.
Towards defined neuronal nets
42Neuro-Transistors– JASS 2005
Transistor arrays
12 neurons cultured on an array of 128x128 transistors ( ).
Neurons I, II and III are connected by synapses.
Burst of action potentials elicited at Neuron I with a micropipette.
21mm
43Neuro-Transistors– JASS 2005
Alternative materials
Drawbacks of silicon:(i) Electrochemical instability of silicon dioxideLong-term shift of electrical properties of the FETs.
(ii) High noise-level of Si-based devices.Difficult to observe small signals from neurons.
Realization of EOFETs with AlGaN/GaNheterostructure FETs.
Much higher signal-to-noise ratio thanSi-based devices.
These materials are stable under physiological conditions.
44Neuro-Transistors– JASS 2005
m50
Cardiac myocyte cells cultivated on surface of a AlGaN/GaN array
Alternative materials
45Neuro-Transistors– JASS 2005
Summary and Outlook
Basic principles of neuron-silicon junctions are fairly understood.
Properties of the cleftTransistor recordingCapacitive stimulation
Optimization of neuron-silicon contact:Larger capacity of stimulation contactsLower noise of transistorsDeeper understanding of electrical properties of the cell membrane
Neuronal networks:Small defined networks of neurons with learning synapsesLarge networks of neurons on closely packed transistor arrays
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