Bio


I received my undergraduate degree in cognitive and computer science from the University of California, Berkeley in 2019; and an MSc and PhD in Language & Cognition from the University of Connecticut, where I worked in the brainLENS Lab run by Professor Fumiko Hoeft. At UConn, I analyzed both behavioral and large-scale neuroimaging (EEG, MRI/fMRI) datasets for my research. I completed my PhD research in 2024, and currently work as a postdoc at Stanford under Professor Vinod Menon (Stanford Cognitive & Systems Neuroscience Laboratory).

Honors & Awards


  • Ruth L. Kirschstein NRSA Individual Predoctoral Fellowship (F31HD107944), National Institutes of Health (2022 – 2024)
  • National Science Foundation Research Traineeship (NRT-UtB1735225), National Science Foundation (2021 – 2022)
  • National Institutes of Health Training Grant (T32DC017703), National Institutes of Health (2019 – 2021)

Boards, Advisory Committees, Professional Organizations


  • Member, Organization for Human Brain Mapping (2024 - Present)
  • Member, Flux: The Society for Developmental Cognitive Neuroscience (2022 - 2024)

Professional Education


  • PhD, University of Connecticut, Language & Cognition (2024)
  • MSc, University of Connecticut, Language & Cognition (2021)
  • BA, University of California, Berkeley, Cognitive Science, Computer Science (2019)

Stanford Advisors


Current Research and Scholarly Interests


Primary research interests include utilizing neuroimaging techniques to study reading and language ability (particularly developmental dyslexia and language disorders), as well as associated comorbidities, such as ADHD. Methodological specialties include analysis of large-scale neuroimaging data, especially MRI/fMRI and EEG.

All Publications


  • Left-dominance for resting-state temporal low-gamma power in children with impaired word-decoding and without comorbid ADHD. PloS one Lasnick, O. H., Hancock, R., Hoeft, F. 2023; 18 (12): e0292330

    Abstract

    One theory of the origins of reading disorders (i.e., dyslexia) is a language network which cannot effectively 'entrain' to speech, with cascading effects on the development of phonological skills. Low-gamma (low-γ, 30-45 Hz) neural activity, particularly in the left hemisphere, is thought to correspond to tracking at phonemic rates in speech. The main goals of the current study were to investigate temporal low-γ band-power during rest in a sample of children and adolescents with and without reading disorder (RD). Using a Bayesian statistical approach to analyze the power spectral density of EEG data, we examined whether (1) resting-state temporal low-γ power was attenuated in the left temporal region in RD; (2) low-γ power covaried with individual reading performance; (3) low-γ temporal lateralization was atypical in RD. Contrary to our expectations, results did not support the hypothesized effects of RD status and poor decoding ability on left hemisphere low-γ power or lateralization: post-hoc tests revealed that the lack of atypicality in the RD group was not due to the inclusion of those with comorbid attentional deficits. However, post-hoc tests also revealed a specific left-dominance for low-γ rhythms in children with reading deficits only, when participants with comorbid attentional deficits were excluded. We also observed an inverse relationship between decoding and left-lateralization in the controls, such that those with better decoding skills were less likely to show left-lateralization. We discuss these unexpected findings in the context of prior theoretical frameworks on temporal sampling. These results may reflect the importance of real-time language processing to evoke gamma rhythms in the phonemic range during childhood and adolescence.

    View details for DOI 10.1371/journal.pone.0292330

    View details for PubMedID 38157354

    View details for PubMedCentralID PMC10756518

  • Sensory temporal sampling in time: an integrated model of the TSF and neural noise hypothesis as an etiological pathway for dyslexia. Frontiers in human neuroscience Lasnick, O. H., Hoeft, F. 2023; 17: 1294941

    Abstract

    Much progress has been made in research on the causal mechanisms of developmental dyslexia. In recent years, the "temporal sampling" account of dyslexia has evolved considerably, with contributions from neurogenetics and novel imaging methods resulting in a much more complex etiological view of the disorder. The original temporal sampling framework implicates disrupted neural entrainment to speech as a causal factor for atypical phonological representations. Yet, empirical findings have not provided clear evidence of a low-level etiology for this endophenotype. In contrast, the neural noise hypothesis presents a theoretical view of the manifestation of dyslexia from the level of genes to behavior. However, its relative novelty (published in 2017) means that empirical research focused on specific predictions is sparse. The current paper reviews dyslexia research using a dual framework from the temporal sampling and neural noise hypotheses and discusses the complementary nature of these two views of dyslexia. We present an argument for an integrated model of sensory temporal sampling as an etiological pathway for dyslexia. Finally, we conclude with a brief discussion of outstanding questions.

    View details for DOI 10.3389/fnhum.2023.1294941

    View details for PubMedID 38234592

    View details for PubMedCentralID PMC10792016

  • The importance of family history in dyslexia The reading league journal Lasnick, O., Feng, J., Quirion, A., Hart, S., Hoeft, F., et al 2022; 3 (2): 35-42