Mismatch negativity (MMN) is an intensively studied event-related potential component that reflects pre-attentive auditory processing. Existing spatial MMN (sMMN) studies usually use loud-speakers in different locations or deliver sound with binaural localization cues through earphones to elicit MMN, which either was practically complicated or sounded unnatural to the subjects. In the present study, we generated head related transfer function (HRTF)-based spatial sounds and verified that the HRTF-based sounds retained the left and the right spatial localization cues. We further used them as deviants to elicit sMMN with conventional oddball paradigm. Results showed that sMMN was successfully elicited by the HRTF-based deviants in 18 of 21 healthy subjects in two separate sessions. Furthermore, the left deviants elicited higher sMMN amplitudes in the right hemisphere compared to the left hemisphere, while the right deviants elicited sMMN with similar amplitudes in both hemispheres, which supports a combination of contralateral and right-hemispheric dominance in spatial auditory information processing. In addition, the sMMN in response to the right deviants showed good test-retest reliability, while the sMMN in response to the left deviants had weak test-retest reliability. These findings implicate that HRTF-based sMMN could be a robust paradigm to investigate spatial localization and discrimination abilities.

失配负性 (MMN) 是一种深入研究的事件相关电位成分，它反映了前注意听觉处理。现有的空间 MMN (sMMN) 研究通常使用不同位置的扬声器或通过耳机传递带有双耳定位提示的声音来引发 MMN，这对于受试者来说要么实际上很复杂，要么听起来不自然。在本研究中，我们生成了基于头部相关传递函数 (HRTF) 的空间声音，并验证了基于 HRTF 的声音保留了左右空间定位线索。我们进一步将它们用作偏差，以使用传统的古怪范式来引出 sMMN。结果表明，sMMN 成功地由基于 HRTF 的异常在 21 名健康受试者中的 18 名中在两个单独的会话中引发。此外，与左半球相比，左偏差在右半球引起更高的 sMMN 幅度，而右偏差在两个半球引起的 sMMN 幅度相似，这支持对侧和右半球在空间听觉信息处理中的优势组合。此外，响应右侧偏差的sMMN表现出良好的重测信度，而响应左侧偏差的sMMN的重测信度较弱。这些发现表明，基于 HRTF 的 sMMN 可能是研究空间定位和辨别能力的强大范例。它支持空间听觉信息处理中对侧和右半球优势的组合。此外，响应右侧偏差的sMMN表现出良好的重测信度，而响应左侧偏差的sMMN具有较弱的重测信度。这些发现表明，基于 HRTF 的 sMMN 可能是研究空间定位和辨别能力的强大范例。它支持空间听觉信息处理中对侧和右半球优势的组合。此外，响应右侧偏差的sMMN表现出良好的重测信度，而响应左侧偏差的sMMN的重测信度较弱。这些发现表明，基于 HRTF 的 sMMN 可能是研究空间定位和辨别能力的强大范例。