Welcome to the BRANE Lab!BRANE_Lab_Logo3



The BRANE Lab’s research program focuses on understanding the spatiotemporal dynamics of brain functions that underlie many psychological phenomena involved in auditory processing, visual perception, audiovisual integration, and attention. We use behavioural and electrophysiological (EEG & MEG) measures to study fundamental principles of these systems and how they develop. BRANE lab’s research program uses multiple measures and methodologies to investigate perceptual and cognitive phenomena. We are particularly fascinated by how a brain functions and communicates across multiple dimensions (space, time, and frequency) and how such communication is altered by experience as a brain develops its abundant perceptual and cognitive abilities.


Current Lab Members:

Research Associates & Post-Docs

PhD Students

MSc Students

  • Natalie Train (2018-present): Thesis
  • Sonay Cheema (2019-present): Thesis
  • Heidi Schaefer (2019-present): Thesis
  • Grace Purnomo (2020-present): Thesis
  • Lauren Watson (2020-present): Thesis
  • Candace Yip (2020-present): Research Project

Undergraduate Students

  • Nima Toussi (2018 – present): Research Projects – machine learning applications for EEG/MEG and EEG signatures of orthographic processing. –> (Toussi et al., submitted)
  • Priyanshu Mahey (2020-present): Research Projects – machine learning applications for EEG/MEG in studies of speech and literacy
  • Catie Futhey (2020-present): Research Projects – investigating and validating inverse source modeling methods for functional connectivity analyses


BRANE Lab Alumni:

Research Associates & Post-Docs


MSc Thesis

MSc Research Projects

  • AJ Hildebrand (MSc 2018-2020): Research Project “Task effects on event-related potentials to single letters and pseudoletters” –> (Hildebrand et al., submitted)
  • Jacob Rowe (MSc 2014-2016): Research Project “N-back vs. discrimination task effects on ERPs to letters and pseudoletters”
  • Jeff Rowell (MSc 2014-2016): Research Project “Schlieren study of external airflow during the production of nasal and oral vowels in French” –> (Rowell et al., 2016)


Undergraduate Research Projects

Seho Bann (BSc 2017-2020): Research Project “Localization of M170 responses to letters and words”

Sewon Bann (BSc 2013-2016): Research Project “Event related potentials reveal early phonological and orthographic processing of single letters in letter-detection and letter-rhyme paradigms” –> (Bann & Herdman, 2016)



Latest Publications:

Conference Posters

Posters at Cognitive NeuroScience Conferences 2015, 2017, and 2019

Neuroimaging Methodology (EEG/MEG)

In addition to our work in perceptual and cognitive areas, we also work as methodologists in electrophysiology and neuroimaging. We develop neuroimaging tools to help answer research questions from multiple disciplines (Moiseev et al., 2011; Moiseev & Herdman, 2013; Herdman et al., 2018). We also use functional connectivity analyses to capture the exciting changes in neural dynamics. Such methods used to study these networks are now being applied to neuroimaging data to provide deeper insights into unlocking the neural codes for perception and cognition. We are excited to be working in this area, which is rapidly receiving scientific interest from many researchers around the world.

Visual Experience

One main objective of BRANE lab’s basic scientific research is to investigate the normal brain functions related to visual expertise. We use reading as a model of visual expertise and have shown that brain responses to unfamiliar pseudoletters are delayed in an object processing network with additional findings of greater gamma-band activity and delayed functional communication within this network for pseudoletter as compare to letters (Herdman, J.Clin.NeuroPhys. 2011; Herdman & Takai, Frontiers Human Neuroscience 2013; Bann & Herdman, Frontiers Human Neuroscience, 2016). Collectively, we interpreted these results as indicators that experience with letters modifies the visual network by shifting it to be a faster, more holistic processor for letters than for pseudoletters in a similar manner to that shown to be used for processing faces as compared to inverted faces.

Figure 4 from Herdman & Takai, 2013

Figure 8 from Herdman & Takai, 2013


Central Auditory Processing

A new line of research in the BRANE lab is investigating the use of electrophysiological responses in assessing central auditory processing . One specific aim is to evaluate the accuracy and precision of using cortical auditory evoked potentials (CAEPs) to estimate behavioural gap-detection thresholds (McDonald & Herdman, in revision; Angel & Herdman, in revision). This will help determine if we can use CAEPs as an objective estimate of auditory temporal resolution. These studies are needed to lay the foundation in order to proceed to evaluate the validity of using CAEPs in testing individuals with central auditory processing disorders.
Gap-evoked CAEPs from a participant with normal auditory temporal resolution(behavioural gap-detection threshold = 5 ms). Two experienced raters judged gap-evoked CAEPs (N1-P2 complex) to be present for gap durations of 8, 10, 12, and 16 ms (as highlighted within the red hatched oval). Thus, CAEP gap-detection threshold was determined to be 8 ms for this participant. Gap durations for each waveform are designated on the right vertical axis. Black-thick line represents the average ERP of the two replications of 50-trial averages (gray lines).

Auditory Selective Attention

Our work on children’s selective attention has provided insights into the neural underpinnings of how socioeconomic gradients can alter the developing brain (D’Angiulli, Herdman, Stapells, and Hertzman, Neuropsychology, 2008). Our results demonstrated that children from low-socioeconomic families recruit a more frontally-mediated system to perform auditory selective attention, whereas children from high-socioeconomic families use more of an auditory-dependent network. Follow-up research showed that selective attention appears to mature from higher-to-lower stages of information processing (Herdman, Brain Topography, 2011). This could have potential implications for understanding neural development of children’s selective attention.