MetaDataApp-Wiki/SFB-1280-metadata-fields.md

-_Work in progress, please contact sfb1280data@rub.de in case of questions._
+_Work in progress, please contact_ _sfb1280data@rub.de_ _in case of questions._
 
 In the following, the 16 metadata fields of the SFB 1280 metadata schema are defined, as well as constraints (e.g. allowed values) explained and examples given. General conventions in the SFB for storing metadata can be found [here](https://gitlab.ruhr-uni-bochum.de/sfb1280/metaapp_2/-/wikis/MetaDataApp-Wiki/General-conventions:-SFB-1280-metadata)[ ]()and in the [SFB's research data management policy](https://sfb1280.ruhr-uni-bochum.de/wp-content/uploads/2022/10/SFB1280_ResearchDataManagementPolicy_ADOPTED_20220928.pdf).
 
@@ -12,7 +12,7 @@ In the following, the 16 metadata fields of the SFB 1280 metadata schema are def
 
 ### 2. Experiment Title
 
-**Definition:** Proper description of the experiment.
+**Definition:** Proper and short description of the experiment.
 
 **Constraints:** free text entry
 
@@ -66,7 +66,7 @@ No multiple selection allowed.
 
 **Constraints:** The MetaDataApp enables selection from the following list of fixed terms agreed upon in the SFB:
 
-* behavioral
+* Behavioral
 * ECG|Pulse
 * EDA
 * EEG
@@ -122,7 +122,7 @@ It is possible to select more than one value in the MetaDataAppn by holding “C
 
 **Constraints:** Free text entry
 
-**Example:** Reward prediction errors (RPEs) have been suggested to drive associative learning processes, but their precise temporal dynamics at the single-neuron level remain elusive. Here, we studied the neural correlates of RPEs, focusing on their trial-by-trial dynamics during an operant extinction learning paradigm. Within a single behavioral session, pigeons went through acquisition, extinction and renewal - the context-dependent response recovery after extinction. We recorded single units from the avian prefrontal cortex analogue, the nidopallium caudolaterale (NCL). 
+**Example:** Reward prediction errors (RPEs) have been suggested to drive associative learning processes, but their precise temporal dynamics at the single-neuron level remain elusive. Here, we studied the neural correlates of RPEs, focusing on their trial-by-trial dynamics during an operant extinction learning paradigm. Within a single <span dir="">behavioural</span>session, pigeons went through acquisition, extinction and renewal - the context-dependent response recovery after extinction. We recorded single units from the avian prefrontal cortex analogue, the nidopallium caudolaterale (NCL).
 
 Packheiser, J., Donoso, J. R., Cheng, S., Güntürkün, O., & Pusch, R. (2021). Trial-by-trial dynamics of reward prediction error-associated signals during extinction learning and renewal. _Progress in neurobiology_, _197_, 101901. https://doi.org/10.1016/j.pneurobio.2020.101901
 
@@ -130,7 +130,7 @@ Packheiser, J., Donoso, J. R., Cheng, S., Güntürkün, O., & Pusch, R. (2021).
 
 **Definition:** ID that uniquely identifies each subject within the experiment.
 
-**Constraints:** For human subjects, the 11 digit  [SFB subject code](https://gitlab.ruhr-uni-bochum.de/sfb1280/subject_code_generator) should be used. For animals, aother unique identfier e.g. for pigeons the ring number. 
+**Constraints:** For human subjects, the 11-digit [SFB subject code](https://gitlab.ruhr-uni-bochum.de/sfb1280/subject_code_generator) should be used. For animals, another unique identifier e.g. for pigeons the ring number.
 
 **Example:** sub-BL07AM01IE5