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Ledochowitsch, P.

Publications and source records attributed to Ledochowitsch, P..

11 recordsLinked to original sources

Map of spiking activity underlying change detection in the mouse visual system

Visual behavior requires coordinated activity across hierarchically organized brain circuits. Understanding this complexity demands datasets that are both large-scale (sampling many areas) and dense (recording many neurons in each area). Here we present a database of spiking activity across the mouse visual system--including thalamus, cortex, and midbrain--while mice perform an image change detection task. Using Neuropixels probes, we record from >75,000 high-quality units in 54 mice, mapping area-, cortical layer-, and cell type-specific coding of sensory and motor information. Modulation by task-engagement increased across the thalamocortical hierarchy but was strongest in the midbrain. Novel images modulated cortical (but not thalamic) responses through delayed recurrent activity. Population decoding and optogenetics identified a critical decision window for change detection and revealed that mice use an adaptation-based rather than image-comparison strategy. This comprehensive resource provides a valuable substrate for understanding sensorimotor computations in neural networks.

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Deciphering neuronal variability across states reveals dynamic sensory encoding

Influenced by factors such as brain states and behavior, neurons exhibit substantial response variability even to identical stimuli. Because these factors are non-stationary, they dynamically impact the fidelity of sensory processing. However, it remains unclear how their relative impact on neuronal variability evolves over time. To address this question, we designed an encoding model with latent states to partition visual cortical variability across three crucial categories of sources: internal brain dynamics, behavior, and external visual stimulus. Applying a hidden Markov model to the rhythmic patterns of cortical local field potentials, we consistently identified three distinct oscillation states. Each state revealed a unique variability profile and a consistent descending trend of stimulus modulation across the visual hierarchy. Regression models within each state revealed a dynamic composition of factors contributing to the observed spiking variability, with the primary influencing factor switching within seconds. In the state dominated by high-frequency oscillations, sensory inputs and behavior exerted the most influence on population dynamics. Conversely, internal brain activity explained most of the variance in the state dominated by low-frequency oscillations. This heterogeneity across states underscores the importance of partitioning variability over time, particularly when considering the dynamic influence of non-stationary factors on sensory processing.

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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.

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Saccade-responsive visual cortical neurons do not exhibit distinct visual response properties

Rapid saccadic eye movements are used by animals to sample different parts of the visual scene. Previous work has investigated neural correlates of these saccades in visual cortical areas such as V1, however how saccade-responsive neurons are distributed across visual areas, cell types, and cortical layers has remained unknown. Through analyzing 818 one-hour experimental sessions from the Allen Brain Observatory, we present a large-scale analysis of saccadic behaviors in head-fixed mice and their neural correlates. We find that saccade-responsive neurons are present across visual cortex, but their distribution varies considerably by transgenically-defined cell type, cortical area, and cortical layer. We also find that saccade-responsive neurons do not exhibit distinct visual response properties from the broader neural population, suggesting the saccadic responses of these neurons are likely not predominantly visually-driven. These results provide insight into the roles played by different cell types within a broader, distributed network of sensory and motor interactions. HighlightsO_LISaccadic eye movement behaviors in head-fixed mice tend to occur in bursts, preferentially along the horizontal axis, and do not strongly depend on visual stimulus. C_LIO_LIDistributions of saccade-responsive neurons vary considerably by transgenically-defined cell type, visual area, and cortical layer. They are most prevalent in dorsal visual areas AL/PM/AM, inhibitory neurons, and deeper cortical layers. C_LIO_LIThe majority of saccade-responsive neurons are selective for saccades in a particular direction, with an overwhelming preference for temporal over nasal saccades. C_LIO_LISaccade-responsive neurons do not exhibit distinct visual response properties, suggesting saccade neural responses are not likely to be predominantly visually-driven. C_LI

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Columnar localization and laminar origin of cortical surface electrical potentials

Electrocorticography (ECoG) methodologically bridges basic neuroscience and understanding of human brains in health and disease. However, the localization of ECoG signals across the surface of the brain and the spatial distribution of their generating neuronal sources are poorly understood. To address this gap, we recorded from rat auditory cortex using customized ECoG, and simulated cortical surface electrical potentials with a full-scale, biophysically detailed cortical column model. Experimentally, ECoG-derived auditory representations were tonotopically organized and signals were anisotropically localized to [≤]{+/-}200 m, i.e., a single cortical column. Biophysical simulations reproduce experimental findings, and indicate that neurons in cortical layers V and VI contribute [~]85% of evoked high-gamma signal recorded at the surface. Cell number and synchronicity were the primary biophysical properties determining laminar contributions to evoked ECoG signals, while distance was only a minimal factor. Thus, evoked ECoG signals primarily originate from neurons in the infragranular layers of a single cortical column. In BriefBaratham et al., investigated the localization and origins of sensory evoked ECoG responses. They experimentally found that ECoG responses were anisotropically localized [≤]{+/-}200 m, i.e., a single cortical column. Biophysically detailed simulations revealed that neurons in layers V &VI were the primary sources of evoked ECoG responses, in contrast to common thinking. HighlightsEvoked ECoG signals are localized on the surface to a cortical column. Neurons in cortical layers V and VI constitute the vast majority of the signal recorded at the surface. Different laminar contributions to ECoG signal are driven by cell density and synchronicity.

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Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology

Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of neurons in the brain. While these two modalities have distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging or electrophysiology. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging. This work explores which data transformations are most useful for explaining these modality-specific discrepancies. We show that the higher selectivity in imaging can be partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could not reconcile differences in responsiveness without sub-selecting neurons based on event rate or level of signal contamination. This suggests that differences in responsiveness more likely reflect neuronal sampling bias or cluster-merging artifacts during spike sorting of electrophysiological recordings, rather than flaws in event detection from fluorescence time series. This work establishes the dominant impacts of the two modalities respective biases on a set of functional metrics that are fundamental for characterizing sensory-evoked responses.

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A survey of spiking activity reveals a functional hierarchy of mouse corticothalamic visual areas

The mammalian visual system, from retina to neocortex, has been extensively studied at both anatomical and functional levels. Anatomy indicates the cortico-thalamic system is hierarchical, but characterization of cellular-level functional interactions across multiple levels of this hierarchy is lacking, partially due to the challenge of simultaneously recording activity across numerous regions. Here, we describe a large, open dataset (part of the Allen Brain Observatory) that surveys spiking from units in six cortical and two thalamic regions responding to a battery of visual stimuli. Using spike cross-correlation analysis, we find that inter-area functional connectivity mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas. Classical functional measures of hierarchy, including visual response latency, receptive field size, phase-locking to a drifting grating stimulus, and autocorrelation timescale are all correlated with the anatomical hierarchy. Moreover, recordings during a visual task support the behavioral relevance of hierarchical processing. Overall, this dataset and the hierarchy we describe provide a foundation for understanding coding and dynamics in the mouse cortico-thalamic visual system.

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On the correspondence of electrical and optical physiology in in vivo population-scale two-photon calcium imaging.

Multiphoton calcium imaging is commonly used to monitor the spiking of large populations of neurons. Recovering action potentials from fluorescence necessitates calibration experiments, often with simultaneous imaging and cell-attached recording. Here we performed calibration for imaging conditions matching those of the Allen Brain Observatory. We developed a novel crowd-sourced, algorithmic approach to quality control. Our final data set was 50 recordings from 35 neurons in 3 mouse lines. Our calibration indicated that 3 or more spikes were required to produce consistent changes in fluorescence. Moreover, neither a simple linear model nor a more complex biophysical model accurately predicted fluorescence for small numbers of spikes (1-3). We observed increases in fluorescence corresponding to prolonged depolarizations, particularly in Emx1-IRES-Cre mouse line crosses. Our results indicate that deriving spike times from fluorescence measurements may be an intractable problem in some mouse lines.

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Relationship between spiking activity and simultaneously recorded fluorescence signals in transgenic mice expressing GCaMP6

Two-photon calcium imaging is often used with genetically encoded calcium indicators (GECIs) to investigate neural dynamics, but the relationship between fluorescence and action potentials (spikes) remains unclear. Pioneering work linked electrophysiology and calcium imaging in vivo with viral GECI expression, albeit in a small number of cells. Here we characterized the spikefluorescence transfer function in vivo of 91 layer 2/3 pyramidal neurons in primary visual cortex in four transgenic mouse lines expressing GCaMP6s or GCaMP6f. We found that GCaMP6s cells have spike-triggered fluorescence responses of larger amplitude, lower variability and greater single-spike detectability than GCaMP6f. Mean single-spike detection rates at high spatiotemporal resolution measured in our data was >70% for GCaMP6s and ~40-50% for GCaMP6f (at 5% false positive rate). These rates are estimated to decrease to 25-35% for GCaMP6f under generally used population imaging conditions. Our ground-truth dataset thus supports more refined inference of neuronal activity from calcium imaging.

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Two-photon frequency division multiplexing for functional in vivo imaging: a feasibility study.

Recently, we presented a new approach to create high-speed amplitude modulation of femtosecond laser pulses and tag multiple excitation beams with specific modulation frequencies. In this work, we discuss the utility of this method to record calcium signals in brain tissue with two-photon frequency-division multiplexing (2P-FDM) microscopy. While frequency-multiplexed imaging appears slightly inferior in terms of image quality as compared to conventional two-photon laser scanning microscopy due to shot noise-induced cross-talk between frequency channels, applying this technique to record average signals from regions of interest (ROI) such as neuronal cell bodies was found to be promising. We use phase information associated with each pixel or waveform within a selected ROI to phase-align and recombine the signals into one extended amplitude-modulated waveform. This procedure narrows the frequency detection window, effectively decreasing noise contributions from other frequency channels. Using theoretical analysis, numerical simulations, and in vitro imaging we demonstrate a reduction of cross-talk by more than an order of magnitude and predict the usefulness of 2P-FDM for functional studies of brain activity.

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A large-scale, standardized physiological survey reveals higher order coding throughout the mouse visual cortex

To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of neural activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes cortical activity from nearly 60,000 neurons collected from 6 visual areas, 4 layers, and 12 transgenic mouse lines from 221 adult mice, in response to a systematic set of visual stimuli. Using this dataset, we reveal functional differences across these dimensions and show that visual cortical responses are sparse but correlated. Surprisingly, responses to different stimuli are largely independent, e.g. whether a neuron responds to natural scenes provides no information about whether it responds to natural movies or to gratings. We show that these phenomena cannot be explained by standard local filter-based models, but are consistent with multi-layer hierarchical computation, as found in deeper layers of standard convolutional neural networks.

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