Update README.md

README.md

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 ### 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 **(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)**.  
+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)**.  
 The BETA database is composed of **64-channel Electroencephalogram (EEG)** data from **70 subjects** performing a **40-target cued-spelling task**.  
 
 - The design and acquisition of BETA aim to meet the demands of **real-world BCI applications**.  
@@ -47,8 +43,6 @@ print(dataset)
 
 We appreciate it if you cite the following work:
 
-**BibTeX:**
-
 ```bibtex
 @article{liu2020beta,
   title={BETA: A large benchmark database toward SSVEP-BCI application},