Brain Electrophysiology of Language & Literacy Systems (BELLS Lab)
My research examines issues in the neurocognition of language, with a focus on word comprehension, vocabulary development, and meta-analysis of EEG and MEG patterns in language. My recent studies have combined event-related brain potentials (128- and 256-channel ERPs) with measures of reading and language skill to study individual differences in word representations. I am particularly interested in how these representations develop over time and how they vary with explicit instruction and with repeated (implicit) experience with words in various contexts.
In addition to EEG measures, I have been working with colleagues in computational linguistics to develop measures that capture fine-grained information about meaning representation and allow us to track incremental changes in word knowledge over time. In recent experiments, I have been attempting to relate these new, “incremental” measures of word learning to ERPs. I have been particularly interested in separating the effects of episodic memory from changes in word-specific processes.
Most recently, I have been leading a multi-site, NIH-funded project called NEMO (Neural ElectroMagnetic Ontologies). The goal of NEMO is to enable theoretical and practical integration of results from EEG/ERP and MEG experiments. By “theoretical integration” we mean valid and generalizable definitions of EEG/ERP patterns (e.g., What IS an N400?), and a high-level understanding of their functional significance (e.g., links to cognition). By “practical integration” we mean meta-analysis of results across studies. Without the integration of knowledge at these two levels, individual studies will continue to provide suggestive, but limited —and often inconsistent—contributions to the science of cognition. With NEMO, we have the opportunity to place our science on a more solid footing and to achieve high-level integration of knowledge in this field. To support these efforts, we have recruited co-investigators from the U.S., Canada, and Europe who are internationally known for their EEG and MEG research on language.
Liu, H., Frishkoff, G., Frank, R. M. F., & Dou, D. (2011, in submission). Discovering Mappings between Spatiotemporal Patterns in Event-related Brain Potentials (ERPs) Derived from Heterogeneous Datasets. 2011 SIAM International Conference on Data Mining (SDM’11), Mesa, Arizona USA.
Liu, H., Frishkoff, G., Frank, R. M. F., & Dou, D. (2011, in submission). Ontology-based mining of brainwaves: A unified framework for discovery of mappings across heterogeneous electrophysiological datasets. Journal of Neurocomputing.
Frishkoff, G. (2011, in press). “Top-down and bottom-up approaches to neuro-ontology development”. In J. Turner and A. Laird (Ed.), Principles and methods of neurobiological ontology development for non-ontologists, Erlbaum/Taylor Francis.
Frishkoff, G. (2011, in press). “Representing space and time: Neural ElectroMagnetic Ontologies (NEMO).” In J. Turner and A. Laird (Ed.), Principles and methods of neurobiological ontology development for non-ontologists, Erlbaum/Taylor Francis.
Frishkoff, G. A., Perfetti, C. A., & Collins-Thompson, K. (2011). Predicting robust vocabulary growth from measures of incremental learning. Scientific Studies of Reading, 15(1), 71–91.
Frishkoff, G. A., Perfetti, C. A., & Collins-Thompson, K. (2010). Lexical quality in the brain: ERP evidence for robust word learning from context. Developmental Neuropsychology, 35(4), 376–403.
Liu, H., Frishkoff, G.A., Frank, R., and Dou, D (2010). Ontology-based mining of brainwaves: sequence similarity technique for mapping alternative descriptions of patterns in event-related potentials (ERP) data. Proceedings of the 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’10), 12 pages.
Frishkoff, G.A., Dou, D., Frank, R., LePendu, P., and Liu, H. (2009). Development of Neural Electromagnetic Ontologies (NEMO): Representation and integration of event-related brain potentials. Proceedings of the International Conference on Biomedical Ontologies (ICBO09). July 24-26, 2009. Buffalo, NY.
Frishkoff, G. A., Perfetti, C. A., & Westbury, C. (2009). ERP measures of partial semantic knowledge: Left temporal indices of skill differences and lexical quality. Biological Psychology, 80(1), 130-147.
Frishkoff, G., White, G., & Perfetti, C. (2009). “In Vivo” Testing of Learning and Instructional Principles: The Design and Implementation of School-Based Experimentation. In L. Dinella (Ed.), Conducting Science-Based Psychology Research in Schools (pp. 153-173). Washington, D.C.: American Psychological Association.
Frishkoff, G.A., Collins-Thompson, K., Perfetti, C., & Callan, J. (2008). Measuring incremental changes in word knowledge: Experimental validation and implications for learning and assessment. Behavioral Research Methods, 40 (4), 907–925.
Frishkoff, G.A., Pavlik P., Levin, L., and de Jong, C. (2008). Providing optimal support for robust learning of syntactic constructions in ESL. In Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci08). Washington, D.C.
Perfetti, C. M. and Frishkoff, G.A. (2008). Neural bases of text and discourse processing. In B. Stemmer and H. A. Whitaker (Eds.), Handbook of neuroscience of language (pp. 165-174). Cambridge, MA: Elsevier.
Tucker, D.M., Frishkoff, G. A., and Luu, P. (2008). Microgenesis of language. In B. Stemmer and H. A. Whitaker (Eds.), Handbook of neuroscience of language (pp. 45-56). Cambridge, MA: Elsevier.
White, G. Frishkoff, G., and Bullock, M. (2008). Bridging the gap between psychological science and educational policy and practice. In K. T. C. Fiorello. (Ed.), Cognitive development in K-3 classroom learning: Research applications (227-263). Mahwah, NJ: Lawrence Erlbaum Associates.
Frishkoff, G. A. (2007). Hemispheric differences in strong versus weak semantic priming: Evidence from event-related brain potentials. Brain and Language, 100(1), 23-43.
Frishkoff, G.A., Frank, R., Rong, J., Dou, D., Dien, J., & Halderman, L. (2007). A framework to support automated ERP pattern classification and labeling. Computational Intelligence and Neuroscience, vol. 2007, Article ID 14567, 13 pages.
Frank, R. M., & Frishkoff, G. A. (2007). Automated protocol for evaluation of electromagnetic component separation (APECS): Application of a framework for evaluating statistical methods of blink extraction from multichannel EEG. Clinical Neurophysiology, 118(1), 80-97.
Dien, J. and Frishkoff, G. A. (2005). Principal components analysis of event-related potential datasets. In T. Handy (Ed.), Event-Related Potentials: A Methods Handbook. Cambridge, MA: MIT Press.
Frishkoff, G. A., Tucker, D. M., Davey, C., & Scherg, M. (2004). Frontal and posterior sources of event-related potentials in semantic comprehension. Cognitive Brain Research, 20(3), 329-354.
Dien, J., Frishkoff, G. A., Cerbone, A., & Tucker, D. M. (2003). Parametric analysis of event-related potentials in semantic comprehension: Evidence for parallel brain mechanisms, Cognitive Brain Research, 15(2), 137-15.