Research

Figure. The dorsal auditory stream plays an essential role in accurate musical phase perception, shown using downregulatory TMS. Ross, Iversen, & Balasubramaniam, 2018, J. Cogn. Neurosci.

Figure. Mu (µ) synchronization occurs during passive music listening, localizes to premotor and motor cortices (bilaterally and on the midline), and reflects overt motor inhibition. Figure adapted from Ross et al., 2022, J. Neurophysiol.

Figure. Auditory rhythms desynchronize mu. Figure from Ross et al., 2025

Cognition and Aging

Develop Brain Stimulation Interventions

In modern psychiatry dysfunctional brain networks are considered the neural substrates of mental disorders. These networks can be precisely targeted with Transcranial Magnetic Brain Stimulation (TMS), a non-invasive, FDA-approved treatment with minimal side effects. I develop and test new and augmented TMS protocols for the treatment of mood disorders. In one meta-analysis and one review paper, my collaborators and I assess the state of the field of using repetitive TMS (rTMS) protocols to modulate brain activity.

One application of TMS is to probe the brain to identify dysfunctional brain networks. In this work, I use Electroencephalography (EEG) during TMS (TMS-EEG) to identify dysfunctional network activity in the case of Alzheimer’s disease and other dementias and delirium. Delirium is a state of confusion that occurs in ~1/3 of surgical patients over the age of 65. In this work we conceptualize delirium as the result of exposure to a stressor (in this case surgery) for patients with pre-existing deficits in brain health. These deficits can be in network connectivity and/or atypical mechanisms of plasticity. The identification of pre-operative predictors of post-operative delirium can help stratify individual patient risk and identify novel therapeutic targets for interventions to prevent delirium or mitigate its impact in predisposed individuals. My work demonstrates the feasibility of gathering EEG and TMS in individuals scheduled for elective surgery to identify neurophysiologic signatures of vulnerability to post-operative delirium. I present preliminary experimental evidence that EEG and TMS-EEG of cerebral oscillatory activity and cortical plasticity, which are non-invasive and scalable neurophysiological measures, identify surgery patients who are at risk for post-operative delirium.

Figure. Non-invasive and scalable neurophysiologic measures can identify individuals at risk of post-operative delirium. Figure from Ross et al., 2022, JAGS.

TMS Methods

Develop Novel Methods for Brain Stimulation

My collaborators and I track transient cortical excitability using single pulse TMS following and during rTMS. In this work, I show local and non-local EEG changes, including in oscillatory phase dynamics using Dynamical Systems Theory, and in resting state EEG after theta burst protocols. I am also studying cognitive interference tasks for capturing rTMS-induced prefrontal network modulation.

For the development of causal TMS-EEG metrics, including for biomarkers of psychiatric disease, it is essential to maximize signal-to-noise by increasing the non-peripherally activated brain signals and minimize all other brain and non-brain signals unrelated to TMS causation. In a recent review paper, I explore the importance of reliability and validity metrics in the development of TMS-EEG biomarkers and provide specific recommendations. For stimulation of the prefrontal cortex, I show that the TMS-EEG signal may have the best signal-to-noise for targets that are more posterior and medial than targets that are more anterior and lateral, and that a personalized approach to targeting can boost the signal by >50%. I develop methods for examining sensory parts of the TMS-EEG response including Vertex Potentials (VP) and Auditory Evoked Potentials (AEP) that are largely from the sound of TMS. I developed and tested an Independent Components Analysis-based technique for isolating the VP and show that the TMS-EEG remaining after removal of VP is unique to stimulation site and to individual subjects and can provide insight into TMS-evoked potentials as well as other-modulated oscillatory dynamics. Importantly, however, an ICA-based removal technique may not always be optimal (due to multisensory or non-model contributions to the VP). To address this issue, I also developed ATTENUATE for collecting TMS-EEG with a suppressed VP. This protocol uses concepts from sensory neuroscience to minimize the sensory potential, including additional multisensory masking as well as using a predictable TMS pulse timing. ATTENUATE reduces the size of the VP and sensory perception of TMS significantly more than the most commonly used masking protocols.

Figure. TMS-evoked potentials (TEPs) before and after ICA-based removal of sensory vertex potential in TMS-EEG. Figure adapted from Ross et al., 2022, Sci. Rep.

Musical Timing

Build a Theoretical Understanding of Predictive Neural Dynamics

Sensorimotor prediction is critical for accurate perception of time as well as for effectively timed action. Human brain networks used for the control of body movements are affected by and involved with sound perception. My research explores the role of prediction and motor planning in musical rhythm perception. This work rigorously tests proposed networks for predictive timing perception in humans, and supports that the dorsal auditory stream, connecting premotor to auditory cortices through parietal projections, is critically involved in accurate phase timing when listening to music. This research has led to the development of a new TMS protocol called Sensory Entrained TMS that uses music to optimize TMS effects on the brain.

I also study both predictive and reactive movements involved with maintaining stable standing balance, how anticipatory balance control can be manipulated using sounds, and probe brain networks that have been proposed for both musical rhythm perception and anticipatory balance control.

Sound and Balance

Determine Sensory Impacts on Standing Balance

Although it is well-established that sensory feedback is incorporated into human standing balance control, relatively little is known about the direct impact of sound on balance dynamics and stability. My seminal papers in this area showed that sound is incorporated into balance control mechanisms and that exposure to some types of sounds can improve stability in standing balance in healthy young adults and in aging adults with typical age-related balance instability. In this work, I show that music that is rhythmically predictable can entrain balance mechanisms, resulting in reductions in body sway variability related to standing stability. I also show that white noise, such as that which is currently being used in some types of hearing aids for improving speech signal clarity, can reduce body sway variability in young and aging adults, leading to more stable balance. This noise effect is robust across unimodal and multimodal conditions and to the structure of the noise sound (i.e., white, brown, pink). I also study networks involved with anticipatory balance mechanisms using TMS, and am exploring practical balance aids using sensory-based interventions.

Rehab and Development

Develop Tools for Cognitive and Motor Rehabilitation and Development

Parkinson’s disease has serious impacts on motor and cognitive function and can lead to isolation, reduced independence and quality of life, and balance instability. My work in this area shows evidence for positive and translatable effects on multiple dimensions of Parkinson’s disease symptom profiles with group exercise and dance training and on specific cognitive symptoms with daily computer-based training. Further, tools used to describe time series data are broadly applicable to human movement tracking, motor and cognitive rehabilitation and training, and lifetime developmental trajectories. In one study I extended change point analysis methods, used in Parkinson’s disease rehabilitation and training research, to infant data to analyze the developmental trajectory of rhythmic limb and vocal behavior in a typically developing infant. Networks affected by Parkinson’s disease are also implicated in predictive and continuous control of body movement, and rhythm and timing. The research on rhythmic auditory-motor stimulation has the potential to improve performance and quality of life for many individuals while also contributing to basic research on brain network architecture and dynamics and on neurodegenerative disease.

Figure. Beta band phase-alignment occurs to musical rhythms, localizes to sensorimotor, occipital, parietal and frontal networks, and the networks engaged depends on the stimulus properties. Figure adapted from Comstock et al., 2021, Eur. J. Neurosci.

Figure. Meta-analysis shows that standardization of iTBS is urgent and necessary. Figure from Pabst et al., 2022, Neurosci. Biobehav. Rev.

Figure. The precision medicine approach can be applied to repetitive transcranial magnetic stimulation (rTMS) and a better understanding of the wide and modifiable parameter space of rTMS will greatly improve clinical outcome.

Figure. The ATTENUATE protocol uses concepts from sensory neuroscience to minimize the VP in the TEP during data collection. Figure adapted from Ross et al., 2022, Hum. Brain Mapp.

Figure. Sounds dynamically and continuously influence human standing balance and can be used to improve balance stability. Ross & Balasubramaniam, 2015, Exp. Brain Res.; Ross et al., 2016, J. Exp. Psychol.- Hum. Percept. Perform.; Ross et al., 2016, Neurosci. Lett.

Figure. Computer-based cognitive training can improve internally generated (un-cued) movement initiation in people with Parkinson’s disease (PD). Figure from Nguyen et al., 2020.

Figure. The pairing of dynamical systems theory and complexity science brings novel concepts and methods to the study of infant motor development. Figure adapted from Abney et al., 2014.

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