NeuroNex+Stanford

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# NeuroData

Joshua T. Vogelstein  & Vikram Chandrashekhar

.foot[[jovo@jhu.edu](mailto:jovo at jhu dot edu)
  |  <http://neurodata.io/talks/neuronex-stanford.html>]

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### <center>What is NeuroData?</center>

### <center>Goal: Build tools that work on .r[your] data</center>

---

### Why is it hard?

- classical statistic theory .r[requires]:
  - p dimensions is smaller than n samples
- your data has .r[p >> n]
- recent statistical theory for p >> n,
  - but with .r[inaccurate assumptions] for your data
  - those methods work poorly on your data
-  we develop methods that:
  - statistically valid
  - computationally efficient
  - for your data

---

### Some Examples

1. Hypothesis Testing
2. Dimensionality Reduction
3. Classification
3. Connectome Coding
4. CLARITY & COLM

For 1-3, we have strong theory that I can discuss ad nauseam

---
### Hypothesis Testing

##### Case A: Test whether X is independent of Y

X is CLARITY brain, and  Y is condition (eg, control vs. addicted)

##### Case B: Test whether population A is the same as population B

Pop A are control CLARITY brains, Pop B are addicted CLARITY brains.
<br>
(this is akin to, and a generalization of, a  t-test)

#### Main Idea

.r[MGC]: Compare "correlations" between all .r[local] pairs of points
--
<br>
ps - like Marr-Albus Sparse Expansion Theory
--
<br>
pps - can be used for "CCA", eg, behavior vs neural activity

---

###  MGC Empirically Dominates

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### Dimensionality Reduction

Given pairs of high-dimensional X and corresponding class labels Y, find the best low-dimensional representation of X

#### Main Idea

.r[LOL]: Use the means and PCA of .r[each class separately]

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###  LOL Empirically Dominates

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### Classification

Given pairs of high-dimensional X and corresponding class labels Y, find the best discriminant boundary

#### Main Idea

.r[RerF]: Find many good .r[sparse] projections of data

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### RerF Empirically Dominates

.pull-left[
- random forests  (RF) were best
- recent extensions improve
- we are even better
]

.pull-right[
<img src="images/error_histogram_benchmarks.png"  style="width: 70%;"/>
]

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### Connectome Coding

Characterizing the relationship between
the *past environment* and the *present neural connectivity*
--
<br>
(could be relevant for Callaway and Justus stuff?)

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### CLARITY / COLM

Build comprehensive ecosystem CLARITY/COLM data, including
- storage  & management
- visualization
- registration to atlas and one another
- cell detection &  counting
- tractography

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### Storage &  Management

infinitely  scalable  in  cloud

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### Visualization

.pull-left[
- Google's NeuroGlancer'
- 3D pan, zoom, &  rotate
- Multi-channel  overlays
- Select individual ROIs
- 30 minutes to load once
]

.pull-right[
<img src="images/ndviz2.jpg"  style="width: 120%;"/>
]

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###  Registration

- only ~1 hr per brain
- fully automatic (no landmarks)
- works on iDisco and  other species too

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### Cell Detection

<br>

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### Cell Detection Analysis

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### Tractography

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# <center>[demo](https://tinyurl.com/yco8h787)</center>

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### Acknowledgements

<div class="container">
  <img src="faces/cep.png"/>
  <div class="centered">Carey Priebe</div>
</div>

<div class="container">
  <img src="faces/randal.jpg"/>
  <div class="centered">Randal Burns</div>
</div>

<div class="container">
  <img src="faces/mim.jpg"/>
  <div class="centered">Michael Miller</div>
</div>

<div class="container">
  <img src="faces/bcaffo.jpg"/>
  <div class="centered">Brian Caffo</div>
</div>

<div class="container">
  <img src="faces/milham.jpg"/>
  <div class="centered">Michael Milham</div>
</div>

<div class="container">
  <img src="faces/dtward.jpg"/>
  <div class="centered">Daniel Tward</div>
</div>

<div class="container">
  <img src="faces/avanti.jpg"/>
  <div class="centered">Avanti Athreya</div>
</div>

<div class="container">
  <img src="faces/vince.jpg"/>
  <div class="centered">Vince Lyzinski</div>
</div>

<div class="container">
  <img src="faces/dpmcsuss.jpg"/>
  <div class="centered">Daniel Sussman</div>
</div>

<div class="container">
  <img src="faces/yichen.jpg"/>
  <div class="centered">Yichen Qin</div>
</div>

<div class="container">
  <img src="faces/youngser.jpg"/>
  <div class="centered">Youngser Park</div>
</div>

<div class="container">
  <img src="faces/cshen.jpg"/>
  <div class="centered">Cencheng Shen</div>
</div>

<div class="container">
  <img src="faces/shangsi.jpg"/>
  <div class="centered">Shangsi Wang</div>
</div>

<div class="container">
  <img src="faces/ebridge.jpg"/>
  <div class="centered">Eric Bridgeford</div>
</div>

<div class="container">
  <img src="faces/vikram.jpg"/>
  <div class="centered">Vikram Chandrashekhar</div>
</div>

<div class="container">
  <img src="faces/tyler.jpg"/>
  <div class="centered">Tyler Tomita</div>
</div>

<div class="container">
  <img src="faces/james.jpg"/>
  <div class="centered">James Brown</div>
</div>

<div class="container">
  <img src="faces/disa.jpg"/>
  <div class="centered">Disa Mhembere</div>
</div>

<div class="container">
  <img src="faces/drishti.jpg"/>
  <div class="centered">Drishti Mannan</div>
</div>

<div class="container">
  <img src="faces/jesse.jpg"/>
  <div class="centered">Jesse Patsolic</div>
</div>

<div class="container">
  <img src="faces/falk_ben.jpg"/>
  <div class="centered">Benjamin Falk</div>
</div>

<div class="container">
  <img src="faces/kwame.jpg"/>
  <div class="centered">Kwame Kutten</div>
</div>

<div class="container">
  <img src="faces/perlman.jpg"/>
  <div class="centered">Eric Perlman</div>
</div>

---

### Questions? Now hiring!

.pull-left[
| task |  link |
| --- | --- |
| testing | [MGC](https://github.com/neurodata/mgc) |
| dim red | [LOL](https://github.com/neurodata/LOL) |
| classify | [RerF](https://github.com/neurodata/R-RerF/)  |
| conn code |  [GraphStats](https://github.com/neurodata/graphstats/)
|  CLARITY | [COBALT](https://github.com/neurodata/COBALT) |
| email | [jovo@jhu.edu](mailto:jovo@jhu.edu) |
| web |  [neurodata.io](http://neurodata.io/) |
| startup | [gigantum.com](http://gigantum.com/) |

]

<br>