Update README.md

README.md

@@ -20,8 +20,8 @@ tags:
 
 ### Summary
 
-The **brain–computer interface (BCI)** provides an alternative means of communication and has sparked growing interest in the past two decades.  
-Specifically, for **Steady-State Visual Evoked Potential (SSVEP)**-based BCI, significant improvements have been made in frequency recognition methods and data sharing.  
+The **Brain–Computer Interface (BCI)** provides an alternative means of communication and has sparked growing interest in the past two decades.  
+Specifically, for **Steady-State Visual Evoked Potential (SSVEP)**-based BCI **(SSVEP-BCI)**, significant improvements have been made in frequency recognition methods and data sharing.  
 However, the number of public databases in this field is still limited.  
 
 To address this gap, we present **BEnchmark database Towards BCI Application (BETA)**.  
@@ -29,8 +29,8 @@ The BETA database is composed of **64-channel Electroencephalogram (EEG)** data
 
 - The design and acquisition of BETA aim to meet the demands of **real-world BCI applications**.  
 - BETA can be used as a **test-bed** for algorithm development and benchmarking.  
+
 ---
- 
 
 ## Usage
 
@@ -39,11 +39,16 @@ from datasets import load_dataset
 
 dataset = load_dataset("your-username/beta")
 print(dataset)
+```
+
+---
 
 ### Citation
 
 We appreciate it if you cite the following work:
 
+**BibTeX:**
+
 ```bibtex
 @article{liu2020beta,
   title={BETA: A large benchmark database toward SSVEP-BCI application},
@@ -53,4 +58,5 @@ We appreciate it if you cite the following work:
   pages={627},
   year={2020},
   publisher={Frontiers Media SA}
-}
+}
+```