technology is overcoming reductionism in neuroscience
TRANSCRIPT
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Technology is Overcoming Reductionism in NeuroscienceTimothy WigginHHMI Interfaces Scholar Award LectureQB Bootcamp 2020
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What would it mean if Neuralinksucceeds?
Animal models are at the beginning of a high-volume data revolution – what lessons can we learn?
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The usual assumption:Detail and scope are mutually exclusive goals in data collection
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Reductionist NeuroscienceGet a good parts list for the brain, assemble the parts at the end
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Reductionist NeuroscienceDeitcher Y, et al. Cereb Cortex. (2017)An inventory of 60 cells in human cortex
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What’s wrong with Reductionism? L
Human : • 1011 neurons
Mouse : • 108 neurons
Larval Zebrafish : • 105 neurons
arval Drosophila : • 104 neurons
C. Elegans : • 102 neurons
The previous • 60 neurons
study :
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Pablo Picasso, Buste de femme (Dora Maar) (1938)
Reductionist NeuroscienceGet a good parts list for the brain, assemble the parts at the end
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Holistic NeuroscienceGet the overall model right at low resolution, focus in when possible
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Holistic NeuroscienceGordon EM, et al. Neuron (2017)A map of brain use in several individual people during a motor task
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What’s wrong with Holism?
•Human Cerebral Cortex:•1010 cortex neurons• ÷•103 cm3 cortex volume• ו10-2 cm3 max resolution• =•Approx. 100,000 neurons in the smallest resolvable voxel
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Chuck Close, Paul (1994)
Holistic NeuroscienceGet the overall model right at low resolution, focus in when possible
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Evan Penny, (Old) No One – in Particular #6, S 2
Hyper-RealismEvery feature is represented at every scale
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Challenges to Hyper-Realism:1. Resolution2. Storage (solved by money)3. Analysis
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Hyper-Realism in NeuroscienceNeuroGlancer, HHMI
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Talk Outline1. Introduction
2. Ion-beam milling electron microscopy
3. Super-resolution light microscopy
4. How do we navigate a 1:1 scale map?
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Why use electrons in a microscope?
It’s easier to give an electron lots of momentum than it is to build a good microscope for X-Rays
Abbe’s Equation:
𝑑𝑑 =𝜆𝜆
𝑛𝑛 sin 𝑎𝑎
(i.e. 𝑑𝑑 ∝ 𝜆𝜆)
equation:
𝜆𝜆 =ℎ𝑝𝑝
wavelength
Good microscop
e? momentum
Resolution
Planck’s
Constant
De Broglie
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Challenges for electron microscopy:1. How do you collect data in 3D?
2. How can you turn the image data into a network?
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Focused Ion Beam MillingUse Ions to slice tissue instead of a knife
Kubota Y, et al. Front. Neural Circuits (2018)
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Xu CS, et al. eLife (2017)
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Semi-automated annotationTurn a lifetime of manual labor into a person-computer partnership
Buhmann J, et al. bioRxiv 874172
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Breakthrough resultHemi-brain connectome coming later this month
HHMI
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Talk Outline1. Introduction
2. Ion-beam milling electron microscopy
3. Super-resolution light microscopy
4. How do we navigate a 1:1 scale map?
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The challenge:If FIB-SEM is a moonshot, how do you get a sample size of 2?
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Expansion MicroscopyMake little things big
Chen F, et al. Science (2015)
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Expansion MicroscopyMake little things big
Jiang N, et al. Mol Biol Cell (2018)
Before:
After:
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Gao R, et al. Science (2019)
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What can we do with a comprehensive map of the brain?
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The scientific toolkit:• Reasoning and dialog
• Math and human-directed computation
• Artificial Intelligence (In progress)
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T. Graham Brown
Jones JG, et al. J Hist Neurosci. (2011)
1. Observe
2. Reason
3. Report
4. Repeat
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The scientific toolkit:• Reasoning and dialog
• Math and human-directed computation
• Artificial Intelligence (In progress)
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NBLAST, FlyLight
Clustering and dimensionality reductionReduce the scope to human scale
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The scientific toolkit:• Reasoning and dialog
• Math and human-directed computation
• Artificial Intelligence (In progress)
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Neuronal InceptionUse the brain to train a naive artificial neural network
Walker EY, et al. Nature (2019)
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The problem is bigger than biology
An interdisciplinary approach is a necessity, not a luxury