Biology subjects

Ruda, K.

Publications and source records attributed to Ruda, K..

3 recordsLinked to original sources

bioRxiv2025

Brainstem sensing of multiple body signals during food consumption

Studies of body-to-brain communication often examine one stimulus or organ at a time, yet the brain must integrate many body signals during behavior. For example, food consumption generates diverse oral and post-oral chemical and mechanical signals transduced by well-characterized peripheral neuronal pathways. Far less is known about how these and other bodily signals are integrated and organized in the brainstem lateral parabrachial nucleus (LPBN), a key interoceptive sensory hub. We established methods to image the activity of 1000s of neurons throughout a large region of mouse LPBN. Food consumption drove a seconds-long wave of activity across LPBN, with dynamics mirroring the movement of food through the upper gastrointestinal tract observed using X-ray fluoroscopy. By imaging the same neurons across days, we found that spatially clustered subsets of neurons encoded oral signals, stomach filling, visceral malaise, arousal, and/or body movement. Moreover, only certain subsets were modulated by cortical input. Together, these experiments reveal a functional specialization in the LPBN that integrates contextual information from the body to guide behavior.

neuroscience↗

bioRxiv2022

The functional organization of retinal ganglion cell receptive fields across light levels

Two major functions performed by the retina are to establish the parallel processing of visual information and to adapt visual encoding to the trillion-fold range of light intensities encountered in the environment. Previous work has highlighted many specialized cell types and circuits that instantiate parallel processing and light adaptation. However, fully understanding either process requires identifying how light adaptation and parallel processing interact. One possibility is that light adaptation causes uniform or proportional scaling to the receptive fields (RFs) of different retinal ganglion cell (RGC) types, the output neurons of the retina. Alternatively, light adaptation could cause a reorganization of RF structures across RGC types. To resolve these possibilities, we examined how the spatiotemporal RF structure of six simultaneously measured RGC types in the rat retina change from rod- to cone-mediated light levels. While light adaptation altered the RF properties of all six RGC types, we found that the relative structure across different RGC types was largely preserved across light levels. Surprisingly, most RGC types retained their center-surround RF structure even at low light levels, an observation that is at odds with prior efficient coding predictions. However, we show these predictions are incomplete and when RFs interact over a finite viewing area, efficient coding predicts the retention of surrounds under low signal-to-noise conditions.

neuroscience↗

bioRxiv2019

Ignoring correlated activity causes a failure of retinal population codes under moonlight conditions

The retina encodes visual stimuli across light intensities spanning 10-12 orders of magnitude from starlight to sunlight. To accommodate this enormous range, adaptation alters retinal output, changing both the signal and noise among populations of retinal ganglion cells (RGCs). Here we determine how these light level-dependent changes in signal and noise impact decoding of retinal output. In particular, we consider the importance of accounting for noise correlations among RGCs to optimally read out retinal activity. We find that at moonlight conditions, correlated noise is greater and assuming independent noise severely diminished decoding performance. In fact, assuming independence among a local population of RGCs produced worse decoding than using a single RGC, demonstrating a failure of population codes when correlated noise is substantial and ignored. We generalize these results with a simple model to determine the signal and noise conditions under which this failure of population processing can occur. This work elucidates the circumstances in which accounting for noise correlations is necessary to take advantage of population-level codes and shows that sensory adaptation can strongly impact decoding requirements on downstream brain areas.

neuroscience↗