Biological Intelligence
description
Transcript of Biological Intelligence
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Biological Intelligence
Biological IntelligenceBiological Intelligence
Artificial IntelligenceBiological SensorsCognitive NeuroscienceCognitive ScienceNeuronal Pattern Analysis
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PhysiologicalSaline
MALDI MatrixSolution
Matrix
Sample Plate
Cell
1000 2000 3000 4000 5000m/z
Relative Intensity
ELHAP
AP9-27βγ
δ
εpε
ELH1-14pβ−γ pELH
AP8-27
α1-9
1-8
1-7
ELH15-36
ELH30-36
ELH1-29
AP7-27
Sample Plate
Matrix
Embedded Sample Molecules
Laser Pulses
EnergizedMatrix/SampleCrystals
DesorptionIonization Analysis by
Mass Spectrometer
Single Cell and Subcellular MALDI Mass Spectrometry for the Direct Assay of the Neuropeptides
Neuropeptides and hormones can be directly detected from biological samples ranging in size from femtoliter peptidergic vesicles to large invertebrate neurons. When combined with genetic information, the complete processing of prohormones into biologically active peptides can be measured in a single cell. Current work involves developing mass spectrometric imaging (to determine the precise locations of the peptides) and the ability to measure peptide release from single cells and brain slices.
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Placenta vs. Brain – 3800 Placenta Array cy3 cy5
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Center for Biomedical Computing
• Narendra Ahuja • Bill Greenough • William O'Brien• Mark Band • Steve Boppart • Sariel Har-Peled• Art Kramer
• Harris Lewin • Zhi-Pei Liang • Lei Liu• Greg Miller • Jean Ponce • Jim Zachary
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Bruce C. Wheeler, Member of the Neuronal Pattern Analysis and Biosensor Research Groups, Faculty in the Electrical and Computer Engineering Department
Micro Patterned Neuronal Networks in CultureRecent Progress
Robustness:Neurons Stay in Patterns
for One Month
Designability:Neurons Can Be Guided Over
Electrodes on a Microelectrode Array
Patterned fiber track superimposed on electrodes
Single fibers superimposed on electrodes
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0 10 20 30 40 50 60 70 80 90 100-1000
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Bruce C. Wheeler, Member of the Neuronal Pattern Analysis and Biosensor Research Groups, Faculty in the Electrical and Computer Engineering Department
Micro Patterned Neuronal Networks in Culture
Recent Progress
Input/Output:Multiple Channel
Electrical Recordings Can be Obtained Routinely
Function: Are Neurons in Patterns More Active?
A. Patterned Networks Have Greater ActivityWithout Patterns: 1% ± 3% active electrodesWith Patterns: 16% 12% active electrodes
% A
cti
ve
Ele
ctr
od
es
10
20
30
40
0
Local Cell Density (per mm2)100 200 500400300
B. Activity Increases with Cell Density
PatternedNeuron Cultures
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Detection of weak signals in noisy spike trains
number of spikes in a 10 ms window with mean subtracted
A) Signal due to small prey
B) Signal superimposed on noisy spike train
C) Signal superimposed on regular afferent spike train
Model of electric fish with electroreceptors distributed over its body. (A) Thechange in afferent firing activity due to a small prey. (B) the signal due to theprey superimposed on fluctuations due to spontaneous activity, in the case of a standard (binomial) model for afferent firing activity with the same firing rate asthe afferent and (C) the signal superimposed on the actual afferent baseline activity. In contrast to (B), the afferent spike train exhibits long-term regularity (memory). This limits the fluctuations in baseline firing rate, making weak signals easier to detect.
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Production of transgenic mice using cre-loxP technology
• Create cell-type specific knockout mice
• Two lines of mice required:
– cre mice which express cre in desired cells
– loxP mice with loxP sites flanking the gene of interest
cre mice loxP mice
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Creation of NR1 loxP mice
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Characterization of NR1 loxP mice
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Dendritic Development in Barrel Cortex
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Dendritic Development in Barrel Cortex
Chang and Greenough, 1988
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Dendritic Development in Barrel Cortex
CTL KO
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v
ey rt
h
i
g
Optical Coherence Tomography
Non-Invasive Imaging of Developing Biology
Fiber-Optic OCT Instrument
Real-Time Endoscopic Imaging
High-Resolution OCT of Cell Mitosis & Migration
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Non-invasive optical imaging
• New group of procedures for measuring the optical parameters of the cortex– Scattering and absorption of near-infrared (NIR)
photons traveling through tissue
• These parameters can be inferred by measuring:– The degree of light attenuation (intensity)– The degree of photon (phase) delay
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Optical Methods
Assessment of exposed tissue Assessment of deep tissue (UV and visible light) (Near infrared light)
ContrastAgents
IntrinsicContrast
LightScatter
Brain cellswellingduring
functionalactivity?
FASTNIRS-Signals
EROS
Fluores-cence
?
Absorp-tion
[Cytochrome-C-Oxidase]
[Oxy-Hb]
[Deoxy-Hb]NIRS
DopplerShift
BloodFlow
IntrinsicContrast
ContrastAgents
Absorp-tion
[Cytochrome-C-Oxidase]
[Oxy-Hb]
[Deoxy-Hb]
‘IntrinsicBrain signals’?
Fluores-cence
[NADH]
[oxy-Flaveo-proteins]
LightScatter
Brain CellSwellingduring
functionalactivity?
‘IntrinsicBrain signals’?
DopplerShift
BloodFlow
BloodVolume
Blood CellVelocity
LDF
Absorp-tion
Blood Flow(e.g.Indicator
Dilutionwith
Cardiogreen)
Fluores-cence
Ion-Conc(Ca, K, Mg)
VoltageSensitive
Dyes
Micro-circulation
Fluores-cence
Principallyfeasible,
dependingon tracer
development?
Absorp-tion
BloodFlow
(Indicator dilution
with Cardio-green
oxygen)NIRS
Modified from A. Villringer
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Optical effects
“Slow” effects– develop over several seconds after stimulation– correspond to effects observed with fMRI and PET– are presumably due to hemodynamic changes
• “Fast” effects (EROS)– develop within the first 500 ms after stimulation– are most visible on the photon delay parameter– are presumably due to neuronal changes
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Hb oxygenation in visual cortex
5 15 25 35 45 550 10 20 30 40 50 60
-0.6
-0.4
-0.2
0.0
0.2
-0.2
0.0
0.2
0.4
0.6
Modified from A. Villringer
[oxy-Hb]
[deoxy-Hb]
Time / s
Co
nce
ntr
atio
n c
han
ges
/ m
icro
M
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Comparison of PET and NIRS
Modified from A. Villringer
[oxy-Hb]vs.
CBF
[deoxy-Hb]vs.
CBF
[total-Hb]vs.
CBF
C
BF
(P
ET
)
C
BF
(P
ET
)
C
BF
(P
ET
)
12
-14
12
-14
12
-14
oxy-Hb (NIRS) total-Hb (NIRS) deoxy-Hb (NIRS)-20 30 -15 15-30 15
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Hb
HbO2
WaterA
bso
rpti
on C
oeff
icie
nt
(cm
-1)
Wavelength (nm)600 700 800 900 1000
0.0
0.1
0.2
0.3
0.4
0.5
NIR Absorption Spectra
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In-vitro scattering effects
Scattering changes duringan action potential
Scattering changes duringtetanic activation of a hippocampal slice
scatteringvoltage
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EROS: Methods
Synthesizer
112 MHz
Phase delay
measuredat 5 kHz
PMT
OpticfiberLEDHead
surface
Cerebral cortex Volume describedby photons reaching fiber
SignalAveraging
Del
ays
(p
s)
1 2 3 Time (s)
Stimulus
Del
ays
(p
s)
200 400 Time (ms)
Average Evoked Response
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Recording helmet
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Neuro-Vascular Relationship
1.001
1.002
1.003
1.004
Relative DC Intensity
0.0 1.0 2.0 Fast Effect x Stimulation Frequency
Slow/Fast Effects Relationship
Baseline
1 Hz
2 Hz
10 Hz
5 Hz
• The hemodynamic (NIRS) effect is proportional to the size of the neuronal (EROS) effect integrated over time
• This supports the use of hemodynamic brain imaging methods to quantify neuronal activity
Gratton, Goodman-Wood, & Fabiani,HBM, in press
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fMRI
RH LH
-0.36 -0.3 -0.24 -0.18 -0.12 -0.06 0 0.06 0.12 0.18 0.24 0.3 0.36
EROS
-0.3 -0.24 -0.18 -0.12 -0.06 0 0.06 0.12 0.18 0.24 0.3
-0.3 -0.24 -0.18 -0.12 -0.06 0 0.06 0.12 0.18 0.24 0.3
100 ms latency
200 mslatency
pre-stimulusbaseline
Upper-left visual stimulation
Gratton et al., NeuroImage, 1997
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Right Visual Field StimulationLeft Hemisphere Response
+
Screen
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Right Visual Field StimulationLeft Hemisphere Response
+
Screen
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Right Visual Field StimulationLeft Hemisphere Response
+
Screen
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Right Visual Field StimulationLeft Hemisphere Response
+
Screen
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Right Visual Field StimulationLeft Hemisphere Response
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Screen
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Right Visual Field StimulationLeft Hemisphere Response
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Right Visual Field StimulationLeft Hemisphere Response
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Right Visual Field StimulationLeft Hemisphere Response
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Screen
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Right Visual Field StimulationLeft Hemisphere Response
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Right Visual Field StimulationLeft Hemisphere Response
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Screen
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Right Visual Field StimulationLeft Hemisphere Response
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Screen
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Right Visual Field StimulationLeft Hemisphere Response
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Right Visual Field StimulationLeft Hemisphere Response
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Screen
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Right Visual Field StimulationLeft Hemisphere Response
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Right Visual Field StimulationLeft Hemisphere Response
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Right Visual Field StimulationLeft Hemisphere Response
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Right Visual Field StimulationLeft Hemisphere Response
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Right Visual Field StimulationLeft Hemisphere Response
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