Neuroanatomical Information System

Neuroanatomical
Information
Systems

daniel.furth@ki.se
meletis lab
karolinska institutet, SWEDEN

Progress in science depends on new techniques, new discoveries and new ideas, probably in that order.

Sidney Brenner

A web-based and open source stereotactic mouse brain atlas.

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.
>800'000 neurons in 21 brains.

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.
>800'000 neurons in 21 brains.
Cell-type specific connectivity tracing in five different Cre-lines (D1, D2, ChAT, Camk2, Gad2).

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.
>800'000 neurons in 21 brains.
Cell-type specific connectivity tracing in five different Cre-lines (D1, D2, ChAT, Camk2, Gad2).
Mapping out connectivity of ~160'000 neurons in the corticostriatal pathway (~0.23% of the entire mouse brain).

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.
>800'000 neurons in 21 brains.
Cell-type specific connectivity tracing in five different Cre-lines (D1, D2, ChAT, Camk2, Gad2).
Mapping out connectivity of ~160'000 neurons in the corticostriatal pathway (~0.23% of the entire mouse brain).
Simultaneous segmentation of cell bodies and fiber tracts.

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.
>800'000 neurons in 21 brains.
Cell-type specific connectivity tracing in five different Cre-lines (D1, D2, ChAT, Camk2, Gad2).
Mapping out connectivity of ~160'000 neurons in the corticostriatal pathway (~0.23% of the entire mouse brain).
Simultaneous segmentation of cell bodies and fiber tracts.
Works with FP, IHC, ISH, widefield, confocal, light-sheet.

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.
>800'000 neurons in 21 brains.
Cell-type specific connectivity tracing in five different Cre-lines (D1, D2, ChAT, Camk2, Gad2).
Mapping out connectivity of ~160'000 neurons in the corticostriatal pathway (~0.23% of the entire mouse brain).
Simultaneous segmentation of cell bodies and fiber tracts.
Works with FP, IHC, ISH, widefield, confocal, light-sheet.
Reconstructing an entire brain in 20 min.

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.
>800'000 neurons in 21 brains.
Cell-type specific connectivity tracing in five different Cre-lines (D1, D2, ChAT, Camk2, Gad2).
Mapping out connectivity of ~160'000 neurons in the corticostriatal pathway (~0.23% of the entire mouse brain).
Simultaneous segmentation of cell bodies and fiber tracts.
Works with FP, IHC, ISH, widefield, confocal, light-sheet.
Reconstructing an entire brain in 20 min.
Compression of large TIFF files (>300 Mb) to ~20 Mb.

A web-based and open source stereotactic mouse brain atlas.
Ability to annotate and query.
>800'000 neurons in 21 brains.
Cell-type specific connectivity tracing in five different Cre-lines (D1, D2, ChAT, Camk2, Gad2).
Mapping out connectivity of ~160'000 neurons in the corticostriatal pathway (~0.23% of the entire mouse brain).
Simultaneous segmentation of cell bodies and fiber tracts.
Works with FP, IHC, ISH.
Reconstructing an entire brain in 20 min.
Compression of large TIFF files (>300 Mb) to ~20 Mb.
Sharing data and images easy over the web.

Geographical Information Systems (GIS)

Geographical Information Systems (GIS)

Raster graphics in neuroscience

Freeman et al. (‎2014) Nature Methods

Raster graphics in neuroscience

8204 citations

Friston et al. (1994) Human Brain Mapping

Raster graphics in neuroscience

y_{xyzt} = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3 + ... + \beta_nx_n

y_{xyzt} = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3 + ... + \beta_nx_n

8204 citations

Friston et al. (1994) Human Brain Mapping

Raster graphics in neuroscience

y_{xyzt} = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3 + ... + \beta_nx_n

y_{xyzt} = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3 + ... + \beta_nx_n

y_{xyzt} = \beta_0 + \beta_{\text{cocaine}}x_{\text{cocaine}}

y_{xyzt} = \beta_0 + \beta_{\text{cocaine}}x_{\text{cocaine}}

+ \beta_{\text{pain}}x_{\text{pain}}

+ \beta_{\text{pain}}x_{\text{pain}}

+ \beta_{\text{attend}}x_{\text{attend}}

+ \beta_{\text{attend}}x_{\text{attend}}

Raster graphics in neuroscience

y_{xyzt} = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3 + ... + \beta_nx_n

y_{xyzt} = \beta_0 + \beta_1x_1 + \beta_2x_2 + \beta_3x_3 + ... + \beta_nx_n

y_{xyzt} = \beta_0 + \beta_{\text{cocaine}}x_{\text{cocaine}}

y_{xyzt} = \beta_0 + \beta_{\text{cocaine}}x_{\text{cocaine}}

+ \beta_{\text{pain}}x_{\text{pain}}

+ \beta_{\text{pain}}x_{\text{pain}}

+ \beta_{\text{attend}}x_{\text{attend}}

+ \beta_{\text{attend}}x_{\text{attend}}

+ \beta_{\text{cocaine}\times\text{attend}}x_{\text{cocaine}}x_{\text{attend}}

+ \beta_{\text{cocaine}\times\text{attend}}x_{\text{cocaine}}x_{\text{attend}}

Raster graphics in neuroscience

food, weight, obese, eating, foods, obesity, reward, energy, hunger, calorie, intake, bmi, mass, body, satiety, normal, cues, responsivity, women, overweight, appetite, individuals, caloric, increases, lean, index, fat, pictures, gain, hungry, images, bed, palatable, craving, receipt, water, overeating, meal, kg, motivation

\text{AP}\times\text{ML}\times\text{DV} \quad 216\text{px} \times 178\text{px} \times 178\text{px}

\text{AP}\times\text{ML}\times\text{DV} \quad 216\text{px} \times 178\text{px} \times 178\text{px}

100\text{ sections} \times 20480\text{px} \times 12288\text{px}

100\text{ sections} \times 20480\text{px} \times 12288\text{px}

neurosynth.org

Vector graphics in neuroscience

?

Vector graphics in neuroscience

Bakker, Tiesinga, Kötter (2015) Neuroinformatics

Why does it matter?

Raster graphics:

Vector graphics:

Neuroanatomical Information Systems (NIS)

Neuroanatomical Information Systems (NIS)

Image processing tools in biology

ITK
- The Insight Segmentation and Registration Toolkit
- Visible Human Project (1986-1995)
- U.S. National Library of Medicine (NLM)
- Joseph Paul Jernigan (1954-1993)
VTK
- Visualization Toolkit
- GE Medical Systems
- Sandia National Laboratories (Dept. Energy)
KitWare
ParaView

ImageJ
- NIH Image (Object Pascal, macintosh only)
- ImageJ (1997)
- Fiji/Imagej (2009)
  Pavel Tomancak

Scale-invariant atlas

Scale-invariant atlas

Scale-invariant atlas

Web based interface

Web based interface

Web based interface

Web based interface

Segmentation

Segmentation

Segmentation

Segmentation

Segmentation

Registration

Segmentation and registration

Segmentation and registration

Connectivity tracing

Connectivity tracing

Connectivity tracing

Connectivity tracing

Connectivity tracing

Connectivity tracing

Decoding motor activity

Decoding motor activity

Decoding motor activity

Decoding motor activity

Barcoding connections

Barcoding connections

What is needed?

A method that:

uniquely labels single postsynaptic neurons
uniquely labels their presynaptic partners
uniquely label axons and trace them

Barcoding connections

What is needed?

A method that:

uniquely labels single postsynaptic neurons
uniquely labels their presynaptic neurons
uniquely label axons and trace them

low MOI barcoded rabies virus
low MOI barcoded rabies virus

impossible with todays technology

Barcoding connections

mesoscale
connectivity

31'295 neurons

single neuronal projections
+target
+strength

MAPseq: barcoded sindbis virus
for projection mapping

Barcoding connections

Barcoding connections

Sindbis virus (Togaviridae)

(+)ssRNA 9.7-11.8 kb

Cytoplasmic replication

Non-structural polyprotein
- processed by host and viral proteases
Structural polyprotein
- expressed through a subgenomic mRNA

Barcoding connections

SAD B19 (Rhabdoviridae)

(-)ssRNA 11-15 kb

Cytoplasmic replication

transcription gradient

Barcoding connections

SAD B19 (Rhabdoviridae)

(-)ssRNA 11-15 kb

Cytoplasmic replication
located to Negri Bodies

G RABV

N RABV

Ménager et al. 2009; Lafon et al. 1985

Barcoding connections

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