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Groblewski, P.

Publications and source records attributed to Groblewski, P..

10 recordsLinked to original sources
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↗
bioRxiv2023

SHIELD: Skull-shaped hemispheric implants enabling large-scale-electrophysiology datasets in the mouse brain

To understand the neural basis of behavior, it is essential to measure spiking dynamics across many interacting brain regions. While new technologies, such as Neuropixels probes, facilitate multi-regional recordings, significant surgical and procedural hurdles remain for these experiments to achieve their full potential. Here, we describe a novel 3D-printed cranial-replacement implant (SHIELD) enabling electrophysiological recordings from distributed areas of the mouse brain. This skull-shaped implant is designed with customizable insertion holes, allowing dozens of cortical and subcortical structures to be recorded in a single mouse using repeated multi-probe insertions over many days. We demonstrate the procedures high success rate, biocompatibility, lack of adverse effects on behavior, and compatibility with imaging and optogenetics. To showcase the scientific utility of the SHIELD implant, we use multi-probe recordings to reveal novel insights into how alpha rhythms organize spiking activity across visual and sensorimotor networks. Overall, this method enables powerful large-scale electrophysiological measurements for the study of distributed brain computation.

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↗
bioRxiv2023

Differential encoding of temporal context and expectation under representational drift across hierarchically connected areas

The classic view that neural populations in sensory cortices preferentially encode responses to incoming stimuli has been strongly challenged by recent experimental studies. Despite the fact that a large fraction of variance of visual responses in rodents can be attributed to behavioral state and movements, trial-history, and salience, the effects of contextual modulations and expectations on sensory-evoked responses in visual and association areas remain elusive. Here, we present a comprehensive experimental and theoretical study showing that hierarchically connected visual and association areas differentially encode the temporal context and expectation of naturalistic visual stimuli, consistent with the theory of hierarchical predictive coding. We measured neural responses to expected and unexpected sequences of natural scenes in the primary visual cortex (V1), the posterior medial higher order visual area (PM), and retrosplenial cortex (RSP) using 2-photon imaging in behaving mice collected through the Allen Institute Mindscopes OpenScope program. We found that information about image identity in neural population activity depended on the temporal context of transitions preceding each scene, and decreased along the hierarchy. Furthermore, our analyses revealed that the conjunctive encoding of temporal context and image identity was modulated by expectations of sequential events. In V1 and PM, we found enhanced and specific responses to unexpected oddball images, signaling stimulus-specific expectation violation. In contrast, in RSP the population response to oddball presentation recapitulated the missing expected image rather than the oddball image. These differential responses along the hierarchy are consistent with classic theories of hierarchical predictive coding whereby higher areas encode predictions and lower areas encode deviations from expectation. We further found evidence for drift in visual responses on the timescale of minutes. Although activity drift was present in all areas, population responses in V1 and PM, but not in RSP, maintained stable encoding of visual information and representational geometry. Instead we found that RSP drift was independent of stimulus information, suggesting a role in generating an internal model of the environment in the temporal domain. Overall, our results establish temporal context and expectation as substantial encoding dimensions in the visual cortex subject to fast representational drift and suggest that hierarchically connected areas instantiate a predictive coding mechanism.

neuroscience↗
bioRxiv2023

Stimulus novelty uncovers coding diversity in visual cortical circuits

Detecting novel stimuli in the environment is critical for learning and survival, yet the neural basis of novelty processing is not understood. To characterize cell type-specific novelty processing, we surveyed the activity of [~]15,000 excitatory and inhibitory neurons in mice performing a visual task with novel and familiar stimuli. Clustering revealed a dozen functional neuron types defined by experience-dependent encoding. Vasoactive-intestinal-peptide (Vip) expressing inhibitory neurons were diverse, encoding novel stimuli, omissions of familiar stimuli, or behavioral features. Distinct Somatostatin (Sst) expressing inhibitory neurons encoded either familiar or novel stimuli. Subsets of excitatory neurons co-clustered with specific Vip or Sst subpopulations, while Sst and Vip inhibitory clusters were non-overlapping. This study establishes that novelty processing is mediated by diverse functional neuron types in the visual cortex.

neuroscience↗
bioRxiv2021

Learning from unexpected events in the neocortical microcircuit

Scientists have long conjectured that the neocortex learns the structure of the environment in a predictive, hierarchical manner. According to this conjecture, expected, predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of information. It is theorized that the neocortex then changes the representation of incoming stimuli, guided by differences in the responses to expected and unexpected events. In line with this conjecture, different responses to expected and unexpected sensory features have been observed in spiking and somatic calcium events. However, it remains unknown whether these unexpected event signals occur in the distal apical dendrites where many top-down signals are received, and whether these signals govern subsequent changes in the brains stimulus representations. Here, we show that both somata and distal apical dendrites of cortical pyramidal neurons exhibit distinct unexpected event signals that systematically change over days. These findings were obtained by tracking the responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons over multiple days in primary visual cortex of awake, behaving mice using two-photon calcium imaging. Many neurons in both layers 2/3 and 5 showed large differences between their responses to expected and unexpected events. Interestingly, these responses evolved in opposite directions in the somata and distal apical dendrites. These differences between the somata and distal apical dendrites may be important for hierarchical computation, given that these two compartments tend to receive bottom-up and top-down information, respectively.

neuroscience↗
bioRxiv2020

Measuring stimulus-evoked neurophysiological differentiation in distinct populations of neurons in mouse visual cortex

Despite significant progress in understanding neural coding, it remains unclear how the coordinated activity of large populations of neurons relates to what an observer actually perceives. Since neurophysiological differences must underlie differences among percepts, differentiation analysis--quantifying distinct patterns of neurophysiological activity--is an "inside out" approach that addresses this question. We used two-photon calcium imaging in mice to systematically survey stimulus-evoked neurophysiological differentiation in excitatory populations across 3 cortical layers (L2/3, L4, and L5) in each of 5 visual cortical areas (primary, lateral, anterolateral, posteromedial, and anteromedial) in response to naturalistic and phase-scrambled movie stimuli. We find that unscrambled stimuli evoke greater neurophysiological differentiation than scrambled stimuli specifically in L2/3 of the anterolateral and anteromedial areas, and that this effect is modulated by arousal state and locomotion. Contrariwise, decoding performance was far above chance and did not vary substantially across areas and layers. Differentiation also differed within the unscrambled stimulus set, suggesting that differentiation analysis may be used to probe the ethological relevance of individual stimuli.

neuroscience↗
bioRxiv2020

A standardized head-fixation system for performing large-scale, in-vivo physiological recordings in mice

BACKGROUNDThe Allen Institute recently built a set of high-throughput experimental pipelines to collect comprehensive in vivo surveys of physiological activity in the visual cortex of awake, head-fixed mice. Developing these large-scale, industrial-like pipelines posed many scientific, operational, and engineering challenges. NEW METHODOur strategies for creating a cross-platform reference space to which all pipeline datasets were mapped required development of 1) a robust headframe, 2) a reproducible clamping system, and 3) data-collection systems that are built, and maintained, around precise alignment with a reference artifact. RESULTSWhen paired with our pipeline clamping system, our headframe exceeded deflection and reproducibility requirements. By leveraging our headframe and clamping system we were able to create a cross-platform reference space to which multi-modal imaging datasets could be mapped. COMPARISON WITH EXISTING METHODSTogether, the Allen Brain Observatory headframe, surgical tooling, clamping system, and system registration strategy create a unique system for collecting large amounts of standardized in vivo datasets over long periods of time. Moreover, the integrated approach to cross-platform registration allows for multi-modal datasets to be collected within a shared reference space. CONCLUSIONSHere we report the engineering strategies that we implemented when creating the Allen Brain Observatory physiology pipelines. All of the documentation related to headframe, surgical tooling, and clamp design has been made freely available and can be readily manufactured or procured. The engineering strategy, or components of the strategy, described in this report can be tailored and applied by external researchers to improve data standardization and stability.

neuroscience↗
bioRxiv2017

Shared and distinct transcriptomic cell types across neocortical areas

Neocortex contains a multitude of cell types segregated into layers and functionally distinct regions. To investigate the diversity of cell types across the mouse neocortex, we analyzed 12,714 cells from the primary visual cortex (VISp), and 9,035 cells from the anterior lateral motor cortex (ALM) by deep single-cell RNA-sequencing (scRNA-seq), identifying 116 transcriptomic cell types. These two regions represent distant poles of the neocortex and perform distinct functions. We define 50 inhibitory transcriptomic cell types, all of which are shared across both cortical regions. In contrast, 49 of 52 excitatory transcriptomic types were found in either VISp or ALM, with only three present in both. By combining single cell RNA-seq and retrograde labeling, we demonstrate correspondence between excitatory transcriptomic types and their region-specific long-range target specificity. This study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct regions of the mouse cortex.

neuroscience↗