Biology subjects

Bawany, A.

Publications and source records attributed to Bawany, A..

5 recordsLinked to original sources

bioRxiv2026

Increased activity without changes in coupling between somata and apical dendrites during visual mismatches

Leading theories of cortical function posit that sensory processing involves a comparison between top-down predictions and bottom-up sensory data. Tests of these theories have been hampered by experimental challenges related to simultaneously recording top-down and bottom-up signals in response to sensory stimuli that either do or do not match internally-generated predictions. Here, we conduct dual-plane 2-photon calcium imaging near-simultaneously from distal apical dendrites and somata of pyramidal neurons in each of 4 different regions of mouse visual cortex while the mice are presented with visual sequences that can either match or mismatch previously habituated visual stimuli. Specifically, we examine the responses in the distal apical dendrites and cell bodies of pyramidal neurons while mice view either movie clips that reverse unexpectedly or Gabor patch sequences that have orientations that do not match habituated patterns. We find that in response to unexpected reversals in natural movies, both the apical dendrites and somata show increased activity that decreases over repeated exposures, consistent with a prediction error response. However, we do not find any clear evidence for increased activity in response to mismatches in Gabor sequences, beyond possible release from adaptation effects. We additionally use volumetric images to connect dendritic and somatic compartments and examine the coupling between connected dendrites and cell bodies in layer 5 pyramidal neurons. We do not find evidence for changes in coupling in response to mismatch stimuli, either for natural movies or Gabor sequences. Our results are consistent across four regions of visual cortex. We also observe that increased responses to reversals in natural movies are stronger in layer 2/3 than layer 5 pyramidal neurons. Altogether, these data suggest that visual cortex is sensitive to deviations from previously-experienced naturalistic inputs. Our data do not suggest that this mismatch sensitivity extends to artificial stimuli, nor do they support theories of prediction error causing changes in the coupling between apical dendrites and somata.

neuroscience↗

bioRxiv2026

Moving object generates topographic responses in the majority of entorhinal neurons

Vision is crucial in generating a complex array of responses in rodents during spatial exploration and in humans during memory tasks. These tasks involve other variables too, e.g. multisensory cues in rodents and complex memories in humans. Further, there are major differences between the medial and lateral entorhinal cortical (MEC and LEC) functional cell types. To understand the contribution of purely visual information to entorhinal responses, we presented a simple, moving vertical bar of light to head-fixed mice, without any task or reward. Surprisingly, 66% (2391/3601) of the MEC broad spiking neurons were significantly modulated by the bar position on the screen. Visual tuning in MEC had a pronounced dorsoventral topography --the tuning strength dropped from 79% in the dorsal most quartile to 40% in the ventral most quartile. Unlike major differences in spatial and other codes between MEC and LEC during free foraging experiments, LEC cells showed very similar visual tuning (392/606, 65%), including the dorso-ventral gradient in LEC5. Additionally, the majority of putative interneurons, from MEC as well as LEC, showed similar, widespread visual tuning, unlike spatial tasks. Neurons also encoded the object motion direction (naso-temporal vs. temporo-nasal visual motion) with changes in mean rate, tuning strength and/or tuning location. Such directional nature of visual tuning indicates significant history-dependence or sequence encoding. Consistently, replacing the continuous motion by randomly flashing bar of light abolished bar-tuning in two-thirds of continuous bar-tuned cells and substantially altered tuning in the rest. These results reveal the contribution of purely visual inputs in generating anatomically organized responses in the majority of entorhinal neurons. The prevalence and similarity of visual tuning across all layers of MEC as well as LEC exceeds that of other known functional cell types (like grid cells in MEC or egocentric object tuning/time-cells in LEC) during spatial navigation tasks and could be foundational in understanding entorhinal complexity.

neuroscience↗

bioRxiv2026

Psilocybin collapses visual change detection and drives cortical dynamics toward a state of surprise

Psilocybin profoundly alters visual perception, yet the neuronal mechanisms underlying these effects remain unclear. Here we combined large-scale Neuropixels recordings with cell-type specific optogenetics in head-fixed mice performing a visual change-detection task. Psilocybin severely impaired task performance without overt motor deficits. In cortex, the drug modestly suppressed activity of layer 5 neurons while preserving representations of image identity. By contrast, psilocybin imposed a 4-Hz oscillation on visually evoked activity that preferentially affected neurons encoding image change rather than image identity. Under psilocybin, expected image repetitions aberrantly recruited change-encoding ensembles and shifted cortical population dynamics towards trajectories normally evoked by genuine stimulus changes. These effects were strongest in somatostatin-expressing (SST) interneurons in visual cortex. The strength of this modulation depended on image structure and was greatest for images with clear, continuous contours, which preferentially recruited change-encoding ensembles. These findings demonstrate that psilocybin drives internally generated cortical surprise signals, providing a circuit mechanism for altered perception in the acute psychedelic state.

neuroscience↗

bioRxiv2024

Stimulus history, not expectation, drives sensory prediction errors in mammalian cortex

Hierarchical predictive coding (HPC) models have recently flourished in neuroscience1-9. Feedforward and feedback processing are at the heart of HPC models. Previous experimental studies using fMRI, EEG/MEG, and LFP9-11 do not reliably resolve feedback modulation from local computations and feedforward outputs. Here, using open-science8, multi-species, multi-area, high-density12, laminar neurophysiology13, we empirically test whether hierarchical predictive coding is a key component shaping cortical processing of visual stimuli. To isolate visual information processing and eliminate motor/reward confounders9-11, we use a no-report task. Our task leveraged so-called global oddballs (GO) as unpredictable, deviant stimuli that circumvent low-level adaptation. We examined their responses relative to local oddballs (LO) that we habituated into highly predictable priors. Four surprising findings in this dataset challenge many existing hierarchical predictive coding models. First, GO responses were exclusive to higher-order, more cognitive areas rather than early-to-mid visual cortex. Second, inhibitory interneuron-targeted optogenetics in primates and mice and waveform shape analysis in primates revealed no evidence that predictive suppression was implemented via these interneurons. Third, highly predictable LO responses dominated in over 50% of all neurons, including in higher-order cortex, which should have anticipated them, indicating limited evidence for predictive suppression. Lastly, prediction error responses evoked by GOs did not evoke feedforward processing. These results reveal circuit dynamics that govern how prediction shapes visual processing, motivating more neurally constrained predictive processing models.

neuroscience↗

bioRxiv2023

Recurrent pattern completion drives the neocortical representation of sensory inference

When sensory information is incomplete or ambiguous, the brain relies on prior expectations to infer perceptual objects. Despite the centrality of this process to perception, the neural mechanism of sensory inference is not known. Illusory contours (ICs) are key tools to study sensory inference because they contain edges or objects that are implied only by their spatial context. Using cellular resolution, mesoscale two-photon calcium imaging and multi-Neuropixels recordings in the mouse visual cortex, we identified a sparse subset of neurons in the primary visual cortex (V1) and higher visual areas that respond emergently to ICs. We found that these highly selective IC-encoders mediate the neural representation of IC inference. Strikingly, selective activation of these neurons using two-photon holographic optogenetics was sufficient to recreate IC representation in the rest of the V1 network, in the absence of any visual stimulus. This outlines a model in which primary sensory cortex facilitates sensory inference by selectively strengthening input patterns that match prior expectations through local, recurrent circuitry. Our data thus suggest a clear computational purpose for recurrence in the generation of holistic percepts under sensory ambiguity. More generally, selective reinforcement of top-down predictions by pattern-completing recurrent circuits in lower sensory cortices may constitute a key step in sensory inference.

neuroscience↗