###### Abstract  
Selective attention can be a useful tactic for speech-in-noise (SiN) interpretation as it strengthens cortical responses to attended sensory inputs while suppressing others. This cortical process is referred to as attentional modulation. Our earlier study showed that a neurofeedback training paradigm was effective for improving the attentional modulation of cortical auditory evoked responses. However, it was unclear how such neurofeedback training improved attentional modulation. This paper attempts to unveil what neural mechanisms underlie strengthened auditory selective attention during the neurofeedback training paradigm. Our EEG time-frequency analysis found that, when spatial auditory attention was focused, a fronto-parietal brain network was activated. Additionally, the neurofeedback training increased beta oscillation, which may imply top-down processing was used to anticipate the sound to be attended selectively with prior information. When the subjects were attending to the sound from the right, they exhibited more alpha oscillation in the right parietal cortex during the final session compared to the first, indicating improved spatial inhibitory processing to suppress sounds from the left. After the four-week training period, the temporal cortex exhibited improved attentional modulation of beta oscillation. This suggests strengthened neural activity to predict the target. Moreover, there was an improvement in the strength of attentional modulation on cortical evoked responses to sounds. The Placebo Group, who experienced similar attention training with the exception that feedback was based simply on behavioral accuracy, did not experience these training effects. These findings demonstrate how neurofeedback training effectively improves the neural mechanisms underlying auditory selective attention. selective attention; auditory modulation; neural oscillation 202313849  
successful SiN understanding. This finding showed that the amplitude ratio of auditory cortical responses to the target speech and noise during a SiN task correlated with behavioral SiN performance [5; 6; 7; 8]. Recent studies [9; 10] demonstrated that training on maintaining attention to low-intensity signals extracted from background noise improved SiN performance and was transferable to untrained stimuli. In these studies, both auditory segregation and selective attention were involved in the training effects. To explicitly reinforce attentional modulation of cortical auditory evoked responses, our previous study created a neurofeedback training paradigm [11]. Two voice streams--spoken by a high-pitched and a low-pitched speaker--were played from different directions (left and right) with no physical overlap in time (i.e., no energetic masking) to maximize stream segregation. Subjects were tasked with focusing on one voice stream at a time. Throughout this auditory selective attention training, 64-channel electroencephalography (EEG) decoded auditory selective attention from single-trial EEG signals [12; 13; 14]. Only the Experimental Group participants received visual feedback based on the EEG-based attention decoder. The Control Group went through a comparable selective attention training program without receiving neurofeedback to rule out a placebo effect. The accuracy of attention decoding from single-trial EEG signals reflects the strength of attentional modulation on cortical auditory evoked responses [13]. Therefore, giving users the outcome of EEG-based attention decoding in the form of neurofeedback [15] may strengthen their attentional modulation of cortical response. However, it is still elusive which neural mechanisms enable strengthened auditory selective attention and which crucial auditory cues drive the training effect in the neurofeedback training paradigm, where the competing streams varied in location, speaker identity, and tempo to maximize stream segregation.