ABSTRACT SUBMISSION GUIDELINES
Deadline for abstract submission is February 21, 2025 11:59 PM (MST)
On the "Submissions" page, you will be prompted to add your abstract into a submission form. Please adhere to the following guidelines before submitting. All submitted abstracts will be reviewed by the Local Organizing Committee/Scientific Program Committee. Based on their scientific quality and relevance to the conference topics, the abstract will either be accepted or rejected.
Selecting the Most Appropriate Session
- Please review the full list of Topics that are accepting abstracts.
- Please select the most relevant session for your abstract (required).
Submitting Sections of the Abstract
- Abstract Title: Enter the title of the abstract into the “Abstract Title” text box.
- Authors: under "Authors" click "Add New" and fill out the required information. Please follow this process for every author on your paper.
- Choose the presenting author.
- Body of the Abstract: Either paste pre-formatted text or type the body of the abstract into the “Abstract text” text box. The body of the abstract is limited to 250 words.
- Abstracts must be in English.
- An abstract example is provided below. The abstracts that will not conform to the template may be rejected.
[EXAMPLE]
Spatial resolution of quantitative electroencephalography during phonemic discrimination tasks: an abbreviated meta-analysis
Jacobs EJ 1, McPherson DL 1,2, Nissen SL 1, Petersen DB 1, Cardon G 1
1 Department of Communication Disorders, Brigham Young University, Provo, Utah, USA
2 Neuroscience Center, Brigham Young University, Provo, Utah, USA
Keywords: spatial resolution, electroencephalography, functional magnetic resonance imaging, phoneme discrimination task
Background: Phonological processing is an essential linguistic skill in language acquisition, processing, and communication is a complex neurological activity. Several studies, some using quantitative electroencephalography (qEEG) and others using functional magnetic resonance imaging (fMRI), have been conducted to investigate these neural substrates of phonological processing. Traditionally, it has been shown that qEEG’s strength is in capturing temporal resolution, and fMRI’s strength is in capturing spatial resolution. However, the spatial resolution of qEEG has greatly improved and some studies have suggested qEEG has reached near levels of specificity comparable to fMRI. The present comprehensive review evaluates the ability of consistency in qEEG studies to identify localization of phonological processing.
Methods: A total of 802 studies were screened, resulting in the identification of 154 articles that would provide information on spatial specificity of qEEG when measuring phonemic discrimination. Articles were selected based on six inclusion criteria developed to ensure that the studies would be similar enough to be comparable and include enough statistical information to be analyzed. Eighteen studies, representing 19 experiments, were identified that met the criteria for the meta-analysis. The study’s event rate was defined as the number of times an anatomical area was coded as a source reference, divided by the number of participants in the study.
Results: Due to the relatively small sample size, a fixed-effect model was used; this limited our observations to the current reviewed studies. Cochran’s Q and a chi-squared test showed there was a high level of heterogeneity and little consistency between studies. Results show that each of these experiments had relatively low event rates, culminating into a summary event rate of 0.240.
Conclusion: The results of this meta-analysis indicated that the qEEG studies included in this study are not as accurate or consistent in source localization as fMRI studies. Because a fixed-effect model was used, the results of this study cannot be generalized to all qEEG studies. However, it does suggest that studies may have been assuming source localization that might be incorrect. Overall, the study made it clear that there is not enough information available to effectively compare qEEG spatial resolution to that of fMRI. However, research like the 2011 study by Brodbeck et al., which found that high-resolution qEEG paired with an individual’s MRI, could identify areas of epileptic activity with greater accuracy than MRI alone [1]. This would suggest that the technology is available to further refine the localization (spatial resolution) of qEEG.
References:
[1] Brodbeck V, Spinelli L, Lascano AM, Wissmeier M, Vargas M I, Vulliemoz S, Pollo C, Schaller K, Michel C M, and Seeck M (2011). Electroencephalographic source imaging: A prospective study of 152 operated epileptic patients. Brain 134(10) 2887–2897 https://doi.org/10.1093/brain/awr243.