'imagenet scans/README.md' ändern

imagenet scans/README.md

@@ -3,21 +3,21 @@
 
 We provide the imagenet scans in the .zip format. Unzipping them will create two folders **data** and **meta**.
 
-- **data:** includes the variables that were recorded during the experiment. The experimental variables are saved as a collection of numpy arrays. Each numpy array contains the value of that variable at a specific image presentation (i.e. trial). Note that the name of the files does not contain any information about the order or time at which the trials took place in experimental time. They are randomly ordered.
+- **data:** Includes the variables that were recorded during the experiment. The experimental variables are saved as a collection of numpy arrays. Each numpy array contains the value of that variable for a specific image presentation (i.e. trial). Note that the name of the files does not contain any information about the order or time at which the trials took place in experimental time. They are randomly ordered.
   - **images:** This directory contains NumPy arrays where each single `X.npy` contains the image that was shown to the mouse in trial `X`.
-  - **responses:** This directory contains NumPy arrays where each single `X.npy` contains the deconvolved calcium traces (i.e. responses) recorded from the mouse in trial `X` in response to the particular presented image.
-  - **behavior:** Behavioral variables include pupil dilation, the derivative of the pupil size, and running speed. The directory contain NumPy arrays (of size `1 x 3`) where each single `X.npy` contains the behavioral variables (in the same order that was mentioned earlier) for trial `X`.
-  - **pupil_center:** the eye position of the mouse, estimated as the center of the pupil. The directory contain NumPy arrays (of size `1 x 2`) for horizontal and vertical eye positions.
-- **meta:** includes meta data of the experiment
+  - **responses:** This directory contains NumPy arrays where each single `X.npy` contains the deconvolved calcium traces (i.e. responses) recorded from mouse V1 in trial `X` in response to the particular presented image.
+  - **behavior:** Behavioral variables include pupil dilation, the derivative of the pupil size, and locomotion speed. The directory contains NumPy arrays (of size `1 x 3`) where each single `X.npy` contains the behavioral variables (in the same order that was mentioned earlier) for trial `X`.
+  - **pupil_center:** The eye position of the mouse, estimated as the center of the pupil. The directory contains NumPy arrays (of size `1 x 2`) for horizontal and vertical eye positions.
+- **meta:** Includes meta data of the experiment
     - **neurons:** This directory contains neuron-specific information. Below are a list of important variables in this directory
-        - `area.npy`: contains the area of each neuron
-        - `cell_motor_coordinates.npy`: contains the position (x, y, z) of each neuron in the cortex, given in microns.
-        - `layer.npy`: contains the cortex layer to which neuron belongs to
-        - `unit_ids.npy`: contains a unique id for each neuron
+        - `area.npy`: Contains the area of each neuron.
+        - `cell_motor_coordinates.npy`: Contains the position (x, y, z) of each neuron in the recording field, given in microns.
+        - `layer.npy`: Contains the cortical layer the neuron was recorded in.
+        - `unit_ids.npy`: Contains a unique id for each neuron.
     - **statistics:** This directory contains statistics (i.e. mean, median, etc.) of the experimental variables (i.e. behavior, images, pupil_center, and responses).
    
     - **trials:** This directory contains trial-specific meta data. 
-        They contain single 1-d NumPy arrays for each trial variable. 
+        This includes single 1-d NumPy arrays for each trial variable. 
         
         How to relate these meta data to the neuronal data (images, responses, ...)?
         
@@ -33,6 +33,6 @@ We provide the imagenet scans in the .zip format. Unzipping them will create two
         ```
 
         Below are a list of important variables in this directory.
-        - `colorframeprojector_image_id.npy`: contains unique image id. If the image is presented multiple times (which is the case in the test set) this image ID will be present multiple times.
-        - `tiers.npy`: contains labels that are used to split the data into *train*, *validation*, and *test* set
-        - `trial_idx.npy`: contains the index for each trial. It corresponds to the actual order of image presentations to the mouse.
+        - `colorframeprojector_image_id.npy`: Contains unique image id. If the image is presented multiple times (which is the case in the test set) this image ID will be present multiple times.
+        - `tiers.npy`: Contains labels that are used to split the data into *train*, *validation*, and *test* set.
+        - `trial_idx.npy`: Contains the index for each trial. It corresponds to the actual order of image presentations to the mouse.