Reviewer Spotlight: Rupesh K. Chillale

The quality of eNeuro depends on the effort that is generously contributed by our reviewers, who lend their expertise and time helping to ensure we publish great science. This Reviewer Recognition series introduces the research of selected reviewers, as well as their strategies for approaching peer review of a paper. Dr. Rupesh K. Chillale is currently an Assistant Research Scientist in the Neural System Laboratory at University of Maryland, College Park. Chillale’s research focuses on understanding how the brain encodes structured auditory sequences, integrates sensory-motor feedback, and adapts to complex auditory stimuli such as speech and music.

"Studying how musicians process sound in real-time combines my interests in sensory processing, motor control, and dynamic systems—making it an exciting area to explore."

Rupesh K Chillale, PhD

Tell us about your work. 

I am a systems neuroscientist interested in understanding how the brain integrates sensory information, makes decisions, and translates them into goal-directed actions.

My research focuses on how the brain encodes structured auditory sequences, integrates sensory-motor feedback, and adapts to complex auditory stimuli such as speech and music. I use a multidisciplinary approach that combines EEG, electrophysiology, behavioral experiments, and computational modeling to study these processes in both human and animal models (ferrets). My work is particularly interested in how the brain encodes speech and music, how it predicts and adapts to auditory input, and how sensory and motor systems interact in tasks such as violin playing and speech processing. This research has implications for developing brain-computer interfaces (BCIs), understanding communication disorders, and advancing cognitive neuroscience.

My past work has demonstrated that the auditory system dynamically encodes categories of sounds, with neural responses adapting based on the behavior (passive listening vs task engagement). We have investigated the emergence and maintenance of categorical information in primary auditory cortex of ferrets. Employing neuronal population analysis, we disentangled the sensory vs categorical encoding and showed the categorical responses during the stimulus presentation exhibited a significant correlation with those from stimulus off delay epoch, suggesting an early involvement of A1 in auditory categorization. My group has also studied the neural basis of sensory-motor coordination during music performance, showing how EEG captures distinct motor and auditory signatures during violin playing and mimed execution without sound. More recently, we have been exploring the neural correlates of temporal sequence learning in naturalistic settings, examining how the brain generalizes learned auditory patterns across different contexts. In efforts to bridge fundamental neuroscience with applications, we are investigating how neural signatures of auditory-motor learning could inform rehabilitation strategies and brain-computer interface development.

What research questions are you currently working on?

I am currently investigating how individual phonemes combine to form words, focusing on the neural mechanisms underlying speech comprehension. This research explores how the brain processes temporal sequences in speech, how it integrates phonemic information over time, and how predictive coding influences auditory perception. Understanding these processes has implications for speech recognition, language learning, and disorders affecting comprehension. In parallel, I am studying how sensory and motor processes interact during violin playing, analyzing how the brain coordinates fine motor execution with auditory feedback. This work aims to disentangle sensory-driven and motor-driven neural signals using EEG and motion tracking, providing insights into how musicians adapt their motor actions based on auditory input. Both projects contribute to a broader understanding of how the brain encodes structured sequences, whether in language or music, and how experience shapes these representations.

Any exciting recent findings in your work you want to share?

Yes! In our lab, previously we have established that imagined music exhibits phase-reversed temporal response functions (TRFs) compared to listened music, suggesting that the brain actively suppresses expected sensory input when imagining sound. Similar to this, we also found speaking, listening and miming behaviors may be related to each other which aligns with predictive coding models, where the brain generates an internal expectation that cancels expected sensory feedback.

Additionally, our work on mimed violin playing showed that motor representations in EEG persist even when auditory feedback is absent, highlighting the strong link between motor execution and sensory expectation.

How did you become interested in this line of research?

I have always been fascinated by how the brain makes sense of complex patterns. My early research in nonlinear dynamics and chaotic neural systems gave me a computational perspective on brain activity. Over time, I became more interested in how neural populations encode sensory information, which led me to computational neuroscience and auditory perception research.

Studying how musicians process sound in real-time combines my interests in sensory processing, motor control, and dynamic systems—making it an exciting area to explore.

What do you do when not in the lab?

Outside of research, I enjoy hiking, photography, and playing the violin (which certainly helps in my music-related neuroscience work!). I am also passionate about science communication and mentoring students in computational neuroscience.

What advice would you share with new reviewers?

I recommend reading the paper holistically first to understand its key contributions before diving into detailed critiques. Focus on clarity, methodology, and scientific rigor, ensuring the study properly builds on existing literature and employs appropriate analysis. Always provide constructive feedback, highlighting both strengths and areas for improvement to help authors refine their work. Finally, consider the broader impact of the study and whether its conclusions are well-supported by the data.

How do you approach a review?

When reviewing an article, I first assess its novelty, significance, and contribution to the field, ensuring it builds upon previous research and advances existing knowledge. I then critically evaluate the methodology, checking whether the chosen approaches appropriately address the research questions and identifying any potential limitations. Next, I examine the results, ensuring they have sufficient statistical power and are clearly presented to support the study’s conclusions. Finally, I analyze the discussion section, assessing whether the findings are properly interpreted in the context of existing literature and whether the conclusions are justified. Throughout the process, I strive to provide constructive and balanced feedback that enhances the clarity, rigor, and impact of the research.

I have also learned to provide clear, constructive feedback, ensuring my critiques help strengthen the manuscript while maintaining scientific rigor. Sometimes complex study designs make the interpretation of results hard, and leaving technical details can further make this process even harder.

What is your experience as a reviewer with eNeuro's consultation review process?

I appreciate eNeuro's consultation review model, as it fosters a collaborative discussion among reviewers, leading to more balanced and thorough feedback. This approach helps authors improve their manuscripts while ensuring a fair and transparent peer-review process.

You are also a graduate of SfN’s Reviewer Mentor Program. What did you learn during that mentored review that you find the most valuable in your work as a reviewer now? Would you recommend the program?

The SfN Reviewer Mentor Program was incredibly valuable in refining my approach to peer review. Through the program I learned how to evaluate scientific rigor and impact more effectively, the importance of constructive feedback and framing critiques productively and strategies for identifying methodological flaws and suggesting realistic improvements.

I highly recommend the program to early career researchers who want to develop strong reviewing skills. It provides structured training and real-world experience, which is crucial for becoming a fair and effective reviewer.

Rupesh K. Chillale, PhD
Assistant Research Scientist, Neural System Laboratory
University of Maryland College Park
Learn more about Rupesh Chillale
X/Twitter: @roopbrain_dynam

 

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