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Raunak Sinha

Raunak Sinha

· ProfessorVerified

University of Wisconsin-Madison · Physiology and Biophysics

Active 2007–2026

h-index18
Citations1.7k
Papers6236 last 5y
Funding$2.7M1 active
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About

Raunak Sinha, PhD, is an Associate Professor in the Department of Neuroscience at the University of Wisconsin–Madison. His research focuses on understanding neural mechanisms, as indicated by his role within the Sinha Lab. Further details about his specific research interests, background, or key contributions are not provided in the page text.

Research topics

  • Neuroscience
  • Biology
  • Cell biology
  • Biochemistry
  • Genetics
  • Anatomy

Selected publications

  • Autonomous Multi-Agent System for Cloud Architecture Design and Infrastructure Deployment

    Iconic Research and Engineering Journals · 2026-03-19

    articleOpen access1st authorCorresponding

    Cloud infrastructure design and deployment traditionally require significant expertise in cloud services, networking, security, and Infrastructure-as-Code (IaC). Translating high-level business requirements into production-ready infrastructure can take days of manual effort and often involve multiple domain experts. This research presents Cloud Infrastructure Crew, an autonomous multi-agent system built using the CrewAI framework that automates cloud architecture design, IaC generation, and deployment validation. The system utilizes three specialized Large Language Model (LLM) powered agents that collaborate sequentially to convert business requirements into infrastructure artifacts such as architecture diagrams, Terraform configuration files, and deployment reports. A human-in-the-loop approval mechanism ensures architectural accuracy before infrastructure generation,also added at agents steps. Experimental evaluation shows that the proposed system significantly reduces infrastructure planning time from several days to minutes while maintaining transparency, auditability, and extensibility. The architecture is designed to be cloud-agnostic and supports integration with multiple LLM providers.

  • Afferent input differentially regulates establishment and maintenance of synapses in the mammalian retina

    Scientific Reports · 2025-11-20

    articleOpen access

    How afferent input shapes synaptic connections is fundamental to our understanding of cues that govern assembly of sensory circuits. In the retina, photoreceptors provide afferent visual information to second-order bipolar cells (BCs) that in turn transfer signals to output neurons. BCs have distinct inhibitory synapses at dendrites and axons but the role of afferent input for regulating the composition and function of these synapses remains unknown. We used a photoreceptor degeneration murine transgenic with labeled BCs and combined immunohistochemical assessment of synaptic proteins across timepoints with single-cell electrophysiology and transcriptomics to address how photoreceptor input regulates BC synapses. We find that inhibitory synapses across BCs have distinct dependencies on afferent input, with axonal synapses reacting first to deafferentation even though the dendritic synapses are at the site of deafferentation. Synapses were altered in a BC-type specific manner and deafferentation differentially impacted expression of synaptic proteins vs. RNA transcripts for synaptic genes revealing disrupted synaptic trafficking pathways. Loss of afferent input also prompted production of nonfunctional receptor proteins and led to withdrawal of BC output synapses. Our findings thus reveal susceptible and resilient retinal synapse types upon deafferentation and uncover how afferent input differentially regulates synapses across second-order neurons.

  • Divergent mechanisms of neural adaptation and instability in the mammalian retina

    Current Biology · 2025-06-27 · 2 citations

    article
  • Layer-specific anatomical and physiological features of the retina’s neurovascular unit

    Current Biology · 2024-12-16 · 22 citations

    articleOpen access

    stores. When rod photoreceptors die in a mouse model of retinitis pigmentosa (rd10), Müller sheaths dissociate from the deep vascular plexus (DVP) but are largely unchanged within the IVP or SVP. Thus, Müller glia interact with retinal vessels in a laminar, compartmentalized manner: glial sheaths are virtually complete in the SVP but fenestrated in the IVP, permitting direct neurovascular contacts. In the DVP, the glial sheath is only modestly fenestrated and is vulnerable to photoreceptor degeneration.

  • Reviewer #3 (Public Review): Predictably manipulating photoreceptor light responses to reveal their role in downstream visual responses

    2024-07-04

    peer-reviewOpen access

    Computation in neural circuits relies on judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this hampers our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.

  • Predictably manipulating photoreceptor light responses to reveal their role in downstream visual responses

    eLife · 2024-11-05 · 2 citations

    articleOpen access

    Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents – including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.

  • Reviewer #2 (Public Review): Light-adaptation clamp: a tool to predictably manipulate photoreceptor light responses

    2024-02-02

    peer-reviewOpen access

    Computation in neural circuits relies on judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this hampers our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including the compensation for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of the role of photoreceptor adaptation in downstream visual signals or in perception.

  • Light-adaptation clamp: a tool to predictably manipulate photoreceptor light responses

    eLife · 2024-02-02 · 3 citations

    preprintOpen access

    Abstract Computation in neural circuits relies on judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this hampers our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including the compensation for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of the role of photoreceptor adaptation in downstream visual signals or in perception.

  • Regional tuning of photoreceptor adaptation in the primate retina

    Nature Communications · 2024-10-12 · 5 citations

    articleOpen accessSenior author

    Adaptation in cone photoreceptors allows our visual system to effectively operate over an enormous range of light intensities. However, little is known about the properties of cone adaptation in the specialized region of the primate central retina called the fovea, which is densely packed with cones and mediates high-acuity central vision. Here we show that macaque foveal cones exhibit weaker and slower luminance adaptation compared to cones in the peripheral retina. We find that this difference in adaptive properties between foveal and peripheral cones is due to differences in the magnitude of a hyperpolarization-activated current, Ih. This Ih current regulates the strength and time course of luminance adaptation in peripheral cones where it is more prominent than in foveal cones. A weaker and slower adaptation in foveal cones helps maintain a higher sensitivity for a longer duration which may be well-suited for maximizing the collection of high-acuity information at the fovea during gaze fixation between rapid eye movements. Light adaptation in the primate fovea is poorly understood. Here, Saha et al. show that cone photoreceptors in the fovea exhibit weaker and slower light adaptation than cones in the peripheral retina due to differences in ion-channel properties.

  • Predictably manipulating photoreceptor light responses to reveal their role in downstream visual responses

    eLife · 2024-02-02 · 3 citations

    articleOpen access

    Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.

Recent grants

Frequent coauthors

  • Mrinalini Hoon

    Northwestern University

    45 shared
  • Fred Rieke

    University of Washington

    41 shared
  • Jacob Baudin

    University of Washington

    28 shared
  • Juan M. Angueyra

    University of Washington

    18 shared
  • Aindrila Saha

    University of Wisconsin–Madison

    16 shared
  • Rachel Wong

    University of Washington

    13 shared
  • Briana Ebbinghaus

    University of Wisconsin–Madison

    13 shared
  • William N. Grimes

    National Institutes of Health

    12 shared

Labs

Education

  • Ph.D., Neuroscience

    University of California, San Francisco

    2007
  • M.S., Neuroscience

    University of California, San Francisco

    2002
  • B.S., Neuroscience

    University of California, San Diego

    2000
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