Visualize Connection Statistics of CBGTC model¶
- class analyseur.cbgtc.visual.connections.Conn(rootfolder=None, region_connections='ctx->bg')[source]¶
Bases:
objectUse Cases¶
1. Pre-requisites¶
1.1. Import Modules¶
from analyseur.cbgtc.visual.connectiions import Conn
1.2. Assign path to data location¶
root_folder = "/path/to/data_folder/"
The root_folder is the CBGT data directory whose structure is shown below
. ├── BG/ │ ├── connection_list/ │ │ ├── scale=4_nbchannels=4/ │ │ │ └── model_9/ │ │ └── active_cortex_inputs_scale=4_nbchannels=4/ │ │ └── model_9/ │ └── ... ├── CORTEX/ │ ├── connection_list/ │ │ ├── Thalamus_inputs_nbpops=4/ │ │ └── nbpops=4/ │ └── ... ├── THALAMUS/ │ ├── connection_list/ │ │ ├── nbpops=4/ │ │ ├── BG_inputs_nbpops=4/ │ │ └── active_cortex_inputs_nbpops=4/ │ └── ... ├── ... :
where
terminal folders in connection_list/ contains files connection_lists_i.dat and connection_lists_j.dat
1.3. Instantiate class object¶
Following the choice of desired connected regions
“CTX->CTX”
“CTX->BG”
“CTX->THAL”
“BG->THAL”
“THAL->CTX”
“BG->BG”
“THAL->THAL”
Note that tests abbreviations are not case-sensitive. Instantiate for “ctx->bg”
conn = Conn(rootfolder=root_folder, region_connections="ctx->bg") # or simply conn = Conn(root_folder, "ctx->bg")
2. Cases¶
For visualizing connection related stuffs invoke conn.<method_name> from the available options:
Method name
Obligatory argument
no argument is mandatory
no argument is mandatory
no argument is mandatory
string: “<nucleus>-><nucleus>”
string: “<nucleus>-><nucleus>”
string: “<nucleus>-><nucleus>”
no argument is mandatory
no argument is mandatory
no argument is mandatory
string: “<nucleus>-><nucleus>”
no argument is mandatory
no argument is mandatory
- connections_bar_chart(show=True)[source]¶
Show summary of connections at population level
Source Region → Target Region Connectivity Populations Number of Connections src target -------------------------------- R1a → R2a ██████████████████████████ R1b → R2a ████ R1a → R2b ████ R1b → R2c █ R1b → R2b ▏
- global_stats()[source]¶
Returns connection statistics for each population connection pair:
total connections
number of cortex neurons
number of basal ganglia neurons
convergence
divergence
- overall_connections_bar_chart(show=True)[source]¶
Compare connection patterns across all populations
Source Region → Target Region Connectivity Total Connections R1a→R2a █████████████████████████████████████████ R1a→R2b ██ R1b→R2a ██ R1b→R2c ▏ R1b→R2b ▏ Unique Neurons Cortex: R1a→R2a ████████ R1a→R2b ███████ R1b→R2a ███████ BasalGanglia: R1a→R2a ██████████████████████████ R1b→R2a ████████ Avg Convergence (BG neurons) R1a→R2a █████████████████ R1a→R2b █████████████ R1b→R2c █████ Avg Divergence (Cortex neurons) R1a→R2a █████████████████████████████████████ R1a→R2b ██ R1b→R2a ██
- plot_all_channel_projections(n_channels=None)[source]¶
Show channel-projection map for all population pairs using
plot_channel_projection()
- plot_all_connectivity_matrices(show=True)[source]¶
Shows all the projection patterns.
Source → Target connectivity Target │ │ ████ │ ████ │ ████ │ ████ └──────────────── Source
- plot_all_density(bins=100, show=True)[source]¶
Shows connection density patterns for all source region nucleus to target region nucleus.
Projection Density: Source Region → Target Target neurons ↑ │ [::::***:::#:] │ [:::**:*::] │ [::*:#::*] │ [::**:#::] │ └────────────────────────────────→ Source neurons
- plot_channel_projection(pair_name, n_channels=None, show=True)[source]¶
Show channel-projection map for desired population pair as diagonal channel blocks.
Target channels 0 1 2 3 Sx 0 ██ Sx 1 ██ Sx 2 ██ Sx 3 ██Patterns References:
Focused connectivity
█ █ █ █Diffuse connectivity
████ ████ ████
Surround inhibition
█ ███ █
Channel crosstalk
█ █ █ █
- plot_connectivity_matrix(pair_name, show=True)[source]¶
Plot connection matrix for a <source nucleus>-><target nucleus> (e.g PTN->MSN)
Target neuron index ↑ │ 42000 ┤ ███████████████ │ │ ███████████████ │ 32000 ┤ ███████████████ │ │ ███████████████ │ 21000 ┤ ███████████████ │ │ ███████████████ │ 10000 ┤██████████████ │ │██████████████ │ 0 └──────────────────────────────────────────→ Source neuron index 0 2000 4000 6000 8000
- plot_degree_distribution(pair_name, show=True)[source]¶
Plot convergence and divergence patterns for a <Source nucleus>-><Target nucleus> (e.g PTN->MSN)
Source divergence 1 ███████████████████████████████████ 2 ███████████████████ 3 █████████ 4 ███ 5 █ 6 ▏ 7 ▏ Target convergence 1 █████████████████████████████████████████████████ 2 ▏ 3 ▏ 4 ▏
- plot_density(pair_name, bins=100, show=True)[source]¶
Plot density heatmap for a <Source nucleus>-><Target nucleus> (e.g PTN->MSN)
Basal Ganglia neurons ↑ 16000 | :##::*:*:#* 14000 | **:#*::*:#: 12000 | :*#*::*:#*: 10000 | :*#::*:#*#: 8000 | *:#*#::*#: 6000 | :##::*:*#* 4000 | *:#*::*:#: 2000 | :*#::*:#* ----------------------------------------------------→ Cortex neurons 0 2000 4000 6000 8000
- plot_global_connectivity(n_channels=None, band_height=2000, density_contours=False)[source]¶
Shows global connectivity scatter plot with channel boundaries.
Target neurons ↑ |----|----|----|----| | ██ | | | | |----|----|----|----| | | ██ | | | |----|----|----|----| | | | ██ | | → Source neurons