The NSF CAREER award is regarded as the agency’s most prestigious honor for early-career faculty. It is designed for researchers who demonstrate exceptional potential in both research and education and who can serve as academic role models within their institutions and communities. Awardees are selected across a wide range of scientific disciplines, with emphasis placed on the originality of their research, the significance of the questions they address, and their ability to connect discovery with teaching and public engagement. For Chandrasekaran, the award will provide a platform to investigate how neural circuits evaluate incoming information before selecting and executing an action.

At the center of his research is a problem that appears simple in daily life but is extraordinarily complex in the brain. Consider a driver approaching an intersection: visual signals indicate the color of a traffic light, sounds may provide information about nearby vehicles or pedestrians, and memory and expectations establish the broader context. The brain must combine these sources, determine what matters, estimate when an action should occur, and generate an appropriate movement. Chandrasekaran’s work examines how this process unfolds, including how the nervous system decides whether to turn left or right, accelerate, stop, or wait when conditions change.

The research program combines electrophysiology, behavioral analysis, optogenetics, and computational modeling. Electrophysiological techniques allow researchers to record the electrical activity of neurons as animals perceive sensory cues, interpret context, and make decisions. Behavioral experiments reveal how those neural signals relate to choices, reaction times, learning, and movement. Optogenetics provides a way to test causality by using light-sensitive proteins to activate or inhibit precisely defined populations of neurons. Computational methods then help translate complex patterns of activity into models of how the brain represents evidence, weighs competing possibilities, and transforms decisions into coordinated motor commands.

This approach is particularly important because sensory processing and decision-making are not separate stages that operate independently. The significance of a visual or auditory signal depends on the circumstances in which it appears. A sound that signals danger in one environment may be irrelevant in another, while the same visual cue can prompt different behaviors depending on an individual’s goals or prior experience. Chandrasekaran’s research seeks to clarify how neural systems integrate sensory evidence with context, allowing the brain to distinguish between information that requires immediate action and information that can be ignored.

His interest in this question developed through an international and interdisciplinary scientific training path. Chandrasekaran earned a master’s degree in neural and behavioral sciences through the International Max Planck Research School at the University of Tübingen in Germany. He later completed his PhD at Princeton University under the mentorship of Asif Ghazanfar, PhD. During his doctoral work, he investigated multisensory integration, the process by which the brain combines information arriving through different senses, such as sight and hearing, to form a more reliable interpretation of the world.

Multisensory integration is a central feature of perception and behavior. Visual and auditory signals often reach the brain at different speeds and may vary in reliability, yet the nervous system must merge them into a coherent estimate of what is happening. Chandrasekaran’s earlier work examined the neural mechanisms that support this integration, providing a foundation for his current focus on how combined sensory information guides decisions and action. The questions are relevant not only to basic neuroscience but also to conditions in which perception, attention, decision-making, or movement is disrupted.

Following his doctoral training, Chandrasekaran became a postdoctoral fellow with the late Krishna Shenoy, PhD, at Stanford University. There, he developed computational and experimental approaches to studying how the brain makes decisions and controls everyday movements. His work at Boston University builds on that foundation by examining the dynamic relationship between sensory signals, internal context, neural computation, and behavior. Through the NSF-supported program, he will pursue a more detailed account of how the brain selects the right action at the right moment—a process that underlies everything from navigating an intersection to responding to unexpected events. The award also reflects the broader goal of training students to connect rigorous experimentation with quantitative models of brain function.

Subject of Research: How the brain integrates sensory input and contextual information to make decisions and generate appropriately timed actions.

Article Title: Boston University Neuroscientist Receives NSF CAREER Award to Study How the Brain Converts Sensory Information Into Action

References: National Science Foundation CAREER award program; Boston University Chobanian & Avedisian School of Medicine announcement.

Keywords: neuroscience, brain research, sensory integration, multisensory integration, decision-making, motor control, electrophysiology, optogenetics, computational neuroscience, National Science Foundation CAREER Award

At the core of these investigations is the fundamental question of conflict resolution among competing sensory cues. Organisms frequently encounter sensory stimuli that can drive behavior in divergent directions—an evolutionary predicament necessitating sophisticated neural strategies. The larval zebrafish, with its relatively simple and transparent nervous system, provides an ideal framework to dissect such sensory conflicts experimentally. These fish exhibit two robust visually guided behaviors: the optomotor response, where they reflexively swim to follow moving visual patterns, and phototaxis, a movement toward light sources that helps them navigate and find optimal environments.

Previous theories proposed two potential neural strategies for resolving conflicts between cues like motion and light: an additive strategy, where multiple sensory inputs are summed together to inform behavior, or a winner-takes-all approach, where the dominant stimulus suppresses alternative inputs to guide action. While these conceptual models framed debates in sensory integration, the neurobiological underpinnings—how specific brain circuits implement these computations—remained elusive. Slangewal, Bahl, and colleagues confronted this challenge by presenting larval zebrafish with carefully manipulated conflicting stimuli involving motion in one direction and light emanating from another.

Their experimental design probed how fish weigh and combine three crucial visual parameters: motion coherence, representing the strength and directionality of the motion stimulus; luminance level, describing the brightness intensity of the light cue; and dynamic changes in luminance, or abrupt fluctuations in brightness over time. Through a series of behavioral assays paired with innovative brain-wide imaging approaches, the team unveiled that zebrafish employ an additive algorithm that integrates these multiple visual features in parallel, enabling them to execute rapid, adaptive decisions. This finding shifts the paradigm by demonstrating that sensory integration is not a simple winner-takes-all scenario but a more nuanced process of feature convergence within the nervous system.

Employing state-of-the-art whole-brain calcium imaging techniques, the researchers pinpointed the anterior hindbrain as a pivotal nexus mediating this sensory convergence. This brain region emerged as a central hub where parallel streams of visual information—motion, luminance, and luminance change—converge and are computationally combined. The discovery highlights the anterior hindbrain’s role beyond motor control, positioning it as a sophisticated integrator orchestrating sensory inputs into coherent motor plans. Intriguingly, these parallel pathways operate simultaneously but independently before merging, suggesting a modular organization of sensory processing that enhances flexibility and robustness in decision-making.

To formalize their experimental observations, the team developed a computational model encapsulating the additive network architecture they discovered. By fitting the model to extensive behavioral data, they confirmed that a weighted summation of motion coherence, luminance, and luminance change signals accurately predicts zebrafish responses when confronted with conflicting visual stimuli. This model not only matches observed behaviors but also offers predictive power; it can simulate how silencing specific sensory pathways—such as those processing motion or light—would impair decision-making capabilities, providing a framework for future experimental manipulations.

The implications of this research stretch far beyond understanding fish behavior. It bridges a crucial gap between abstract behavioral algorithms and their concrete neural substrates, a connection vital for advancing computational neuroscience. By elucidating how vertebrate brains integrate complex, multifeature sensory inputs into decisive motor commands, these findings provide a blueprint that may inform artificial systems aiming to emulate biological decision-making. Robotics and AI systems, in particular, could benefit from incorporating additive integration principles to resolve multimodal sensory conflicts encountered in dynamic, unpredictable environments.

Moreover, the study enriches our comprehension of neural circuit organization and function. The identification of distinct parallel pathways that eventually converge in a central brain region challenges existing models positing hierarchical sensory processing streams. Instead, it supports a network architecture where segregated channels carry specialized information, merging through an additive framework that preserves the nuances of each sensory dimension. Such insights are crucial for understanding how neural circuits maintain sensitivity to diverse environmental features while generating unified behavioral outputs.

From a methodological standpoint, this work leverages the transparency and genetic accessibility of larval zebrafish, coupled with cutting-edge imaging and computational modeling, exemplifying the power of integrative approaches in neuroscience. The ability to monitor and manipulate whole-brain activity at single-neuron resolution during behavior provides unprecedented clarity on the neural substrates of complex computations. This approach sets a new standard for future studies aimed at deciphering sensory integration and decision-making across animal taxa.

Professor Armin Bahl emphasizes that their model’s predictive capacity opens avenues for targeted intervention studies. For instance, optogenetic or pharmacological silencing of specific pathways could validate the causal roles of individual sensory streams in decision outcomes. Such experiments would further elucidate how different sensory modalities interact dynamically within neural circuits, enhancing behavioral flexibility and adaptability—a hallmark of biological intelligence.

The study also offers conceptual inroads into human neuroscience and clinical research. Understanding the fundamental neural strategies of sensory integration can illuminate pathologies where these processes malfunction, such as in sensory processing disorders or neurodegenerative diseases affecting decision-making faculties. By revealing conserved principles of additive sensory processing, this research may inspire novel therapeutic approaches or assistive technologies designed to restore or augment impaired neural functions.

In summation, the research led by Slangewal and Bahl unravels a detailed, brain-wide mechanistic account of how vertebrate animals integrate multifaceted sensory information to guide behavior. Their elucidation of additive computations within parallel neural pathways converging in the anterior hindbrain marks a milestone in our understanding of sensory conflict resolution. This work not only advances fundamental neuroscience but also charts promising interdisciplinary pathways linking biology, computation, and technology.

Subject of Research: Neural mechanisms of multisensory integration and decision-making in larval zebrafish.

Article Title: Visuomotor decision-making through multifeature convergence in the larval zebrafish hindbrain.

News Publication Date: 2024.

Web References: http://dx.doi.org/10.1038/s41467-026-69633-4

References: Katja Slangewal, Sophie Aimon, Maxim Q. Capelle, Florian Kämpf, Heike Naumann, Krasimir Slanchev, Herwig Baier, Armin Bahl: Visuomotor decision-making through multifeature convergence in the larval zebrafish hindbrain, Nature Communications, 2024.

Image Credits: Katja Slangewal, University of Konstanz.

Keywords: sensory integration, zebrafish, decision-making, neural circuits, optomotor response, phototaxis, hindbrain, neural computation, additive model, motion coherence, luminance, neuroscience, artificial intelligence.