Biology subjects

Svoboda, K.

Publications and source records attributed to Svoboda, K..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Brain-wide measurement of protein turnover with high spatial and temporal resolution

Synaptic plasticity underlies learning and memory by altering neuronal connections in response to experiences1. However, the loci of learning-induced synaptic plasticity, and the degree to which plasticity is localized or distributed, remain largely unknown2. We developed a method (DELTA) for mapping brain-wide changes in synaptic protein turnover with single-synapse resolution, based on Janelia Fluor dyes and HaloTag knock-in mice. During associative learning, the turnover of the ionotropic glutamate receptor GluA2, an indicator of synaptic plasticity, was enhanced in several brain regions, most markedly in the hippocampal area CA1. More broadly distributed increases in turnover of synaptic proteins were observed in response to environmental enrichment. In CA1, GluA2 stability was regulated in an input specific manner, with more turnover in layers containing input from CA3 compared to entorhinal cortex. DELTA will facilitate exploration of the molecular and circuit basis of learning and memory and other forms of adaptive and maladaptive plasticity at scales ranging from single synapses to the entire brain.

neuroscience↗

bioRxiv2022

Brain mechanism of foraging: reward-dependentsynaptic plasticity or neural integration of values?

During foraging behavior, action values are persistently encoded in neural activity and updated depending on the history of choice outcomes. What is the neural mechanism for action value maintenance and updating? Here we explore two contrasting network models: synaptic learning of action value versus neural integration. We show that both models can reproduce extant experimental data, but they yield distinct predictions about the underlying biological neural circuits. In particular, the neural integrator model but not the synaptic model requires that reward signals are mediated by neural pools selective for action alternatives and their projections are aligned with linear attractor axes in the valuation system. We demonstrate experimentally observable neural dynamical signatures and feasible perturbations to differentiate the two contrasting scenarios, suggesting that the synaptic model is a more robust candidate mechanism. Overall, this work provides a modeling framework to guide future experimental research on probabilistic foraging.

neuroscience↗

bioRxiv2022

Sub-threshold neuronal activity and the dynamical regime of cerebral cortex

Cortical neurons exhibit temporally irregular spiking patterns and heterogeneous firing rates. These features arise in model circuits operating in a fluctuation-driven regime, in which fluctuations in membrane potentials emerge from the network dynamics. However, it is still unclear whether the cortex operates in this regime. We evaluated the fluctuation-driven hypothesis by analyzing spiking and sub-threshold membrane potentials of neurons in the sensory and frontal cortex recorded during a decision-making task. Standard fluctuation-driven models account for spiking statistics but fail to capture the heterogeneity in sub-threshold activity. We address this issue by effectively incorporating dendritic conductances into the standard models. Our model suggests that the frontal cortex operates in a fluctuation-driven regime. In contrast, excitatory neurons in layer 4 of the barrel cortex are not fluctuation-driven; they spike in response to occasional synchronous inputs. Our work reveals fundamental differences between cortical areas, suggesting that they operate in different dynamical regimes.

neuroscience↗

bioRxiv2022

Distributing task-related neural activity across a cortical networkthrough task-independent connections

Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a limited subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. We found that task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.

neuroscience↗

bioRxiv2022

PROPOSE: Predictive and robust probe selection for spatial transcriptomics

A prominent trend in single-cell transcriptomics is providing spatial context alongside a characterization of each cells molecular state. This typically requires targeting an a priori selection of genes, often covering less than 1% of the genome, and a key question is how to optimally determine the small gene panel. Reference data from these methods covering the whole genome is unavailable, and using single-cell RNA sequencing (scRNA-seq) datasets as a surrogate can result in suboptimal gene panels due to the fundamentally different data distributions across technologies. We address these challenges by introducing a flexible deep learning framework, PERSIST, to identify informative gene targets for spatial transcriptomics studies by leveraging existing scRNA-seq data. Using datasets spanning different brain regions, species, and scRNA-seq technologies, we show that PERSIST reliably identifies gene panels that provide more accurate prediction of the genome-wide expression profile, thereby capturing more information with fewer genes. Furthermore, PERSIST can be adapted to meet specific biological goals, such as classifying cell types or discerning neuronal electrical properties. Finally, via a simulation study based on a recent in situ hybridization-based dataset, we demonstrate that PERSISTs binarization of gene expression levels enables models trained on scRNA-seq data to generalize with input data obtained using spatial transcriptomics, despite the complex domain shift between these technologies.

cell biology↗

bioRxiv2021

Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator

The ability to optically image cellular transmembrane voltage at millisecond-timescale resolution can offer unprecedented insight into the function of living brains in behaving animals. The chemigenetic voltage indicator Voltron is bright and photostable, making it a favorable choice for long in vivo imaging of neuronal populations at cellular resolution. Improving the voltage sensitivity of Voltron would allow better detection of spiking and subthreshold voltage signals. We performed site saturation mutagenesis at 40 positions in Voltron and screened for increased {Delta}F/F0 in response to action potentials (APs) in neurons. Using a fully automated patch-clamp system, we discovered a Voltron variant (Voltron.A122D) that increased the sensitivity to a single AP by 65% compared to Voltron. This variant (named Voltron2) also exhibited approximately 3-fold higher sensitivity in response to sub-threshold membrane potential changes. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, with lower baseline fluorescence. Introducing the same A122D substitution to other Ace2 opsin-based voltage sensors similarly increased their sensitivity. We show that Voltron2 enables improved sensitivity voltage imaging in mice, zebrafish and fruit flies. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.

neuroscience↗

bioRxiv2021

Fast and sensitive GCaMP calcium indicators for imaging neural populations

Calcium imaging with protein-based indicators is widely used to follow neural activity in intact nervous systems. The popular GCaMP indicators are based on the calcium-binding protein calmodulin and the RS20 peptide. These sensors report neural activity at timescales much slower than electrical signaling, limited by their biophysical properties and trade-offs between sensitivity and speed. We used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators. The resulting jGCaMP8 sensors, based on calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (rise times, 2 ms) and still feature the highest sensitivity for neural activity reported for any protein-based sensor. jGCaMP8 sensors will allow tracking of larger populations of neurons on timescales relevant to neural computation.

neuroscience↗

bioRxiv2021

The Neurodata Without Borders ecosystem for neurophysiological data science

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWBs impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

neuroscience↗

bioRxiv2021

Expansion-Assisted Iterative-FISH defines lateral hypothalamus spatio-molecular organization

Determining the spatial organization and morphological characteristics of molecularly defined cell types is a major bottleneck for characterizing the architecture underpinning brain function. We developed Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) to survey gene expression in brain tissue, as well as a turnkey computational pipeline to rapidly process large EASI-FISH image datasets. EASI-FISH was optimized for thick brain sections (300 {micro}m) to facilitate reconstruction of spatio-molecular domains that generalize across brains. Using the EASI-FISH pipeline, we investigated the spatial distribution of dozens of molecularly defined cell types in the lateral hypothalamic area (LHA), a brain region with poorly defined anatomical organization. Mapping cell types in the LHA revealed nine novel spatially and molecularly defined subregions. EASI-FISH also facilitates iterative re-analysis of scRNA-Seq datasets to determine marker-genes that further dissociated spatial and morphological heterogeneity. The EASI-FISH pipeline democratizes mapping molecularly defined cell types, enabling discoveries about brain organization. Highlights- EASI-FISH enables robust gene expression profiling in thick brain slices - A turnkey analysis pipeline for facile analysis of large EASI-FISH image datasets - EASI-FISH reveals novel subregions of the lateral hypothalamus - Identification of rare cell types based on morphological and spatial heterogeneity

neuroscience↗

bioRxiv2020

A midbrain - thalamus - cortex circuit reorganizes cortical dynamics to initiate planned movement

Motor behaviors are often planned long before execution, but only released after specific sensory events. Planning and execution are each associated with distinct patterns of motor cortex activity. Key questions are how these dynamic activity patterns are generated and how they relate to behavior. Here we investigate the multi-regional neural circuits that link an auditory go cue and the transition from planning to execution of directional licking. Ascending glutamatergic neurons in the midbrain reticular and pedunculopontine nuclei show short-latency and phasic changes in spike rate that are selective for the go cue. This signal is transmitted via the thalamus to the motor cortex, where it triggers a rapid reorganization of motor cortex state from planning-related activity to a motor command, which in turn drives appropriate movement. Our studies show how brainstem structures can control cortical dynamics via the thalamus for rapid and precise motor behavior.

neuroscience↗

bioRxiv2020

Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

To study the dynamics of neural processing across timescales, we require the ability to follow the spiking of thousands of individually separable neurons over weeks and months, during unrestrained behavior. To address this need, we introduce the Neuropixels 2.0 probe together with novel analysis algorithms. The new probe has over 5,000 sites and is miniaturized such that two probes plus a headstage, recording 768 sites at once, weigh just over 1 g, suitable for implanting chronically in small mammals. Recordings with high quality signals persisting for at least two months were reliably obtained in two species and six different labs. Improved site density and arrangement combined with new data processing methods enable automatic post-hoc stabilization of data despite brain movements during behavior and across days, allowing recording from the same neurons in the mouse visual cortex for over 2 months. Additionally, an optional configuration allows for recording from multiple sites per available channel, with a penalty to signal-to-noise ratio. These probes and algorithms enable stable recordings from >10,000 sites during free behavior in small animals such as mice.

neuroscience↗

bioRxiv2020

High throughput instrument to screen fluorescent proteins under two-photon excitation

Two-photon microscopy together with fluorescent proteins and fluorescent protein-based biosensors are commonly used tools in neuroscience. To enhance their experimental scope, it is important to optimize fluorescent proteins for two-photon excitation. Directed evolution of fluorescent proteins under one-photon excitation is common, but many one-photon properties do not correlate with two-photon properties. A simple system for expressing fluorescent protein mutants is E. coli colonies on an agar plate. The small focal volume of two-photon excitation makes creating a high throughput screen in this system a challenge for a conventional point-scanning approach. We present an instrument and accompanying software that solves this challenge by selectively scanning each colony based on a colony map captured under one-photon excitation. This instrument, called the GIZMO, can measure the two-photon excited fluorescence of 10,000 E. coli colonies in 7 hours. We show that the GIZMO can be used to evolve a fluorescent protein under two-photon excitation.

neuroscience↗

bioRxiv2020

Accurate localization of linear probe electrodes across multiple brains

Recently developed silicon probes have large numbers of recording electrodes on long linear shanks. Specifically, Neuropixels probes have 960 recording electrodes distributed over 9.6 mm shanks. Because of their length, Neuropixels probe recordings in rodents naturally span multiple brain areas. Typical studies collate recordings across several recording sessions and animals. Neurons recorded in different sessions and animals have to be aligned to each other and to a standardized brain coordinate system. Here we report a workflow for accurate localization of individual electrodes in standardized coordinates and aligned across individual brains. This workflow relies on imaging brains with fluorescent probe tracks and warping 3-dimensional image stacks to standardized brain atlases. Electrophysiological features are then used to anchor particular electrodes along the reconstructed tracks to specific locations in the brain atlas and therefore to specific brain structures. We performed ground-truth experiments, in which motor cortex outputs are labelled with ChR2 and a fluorescence protein. Recording from brain regions targeted by these outputs reveals better than 100 m accuracy for electrode localization.

neuroscience↗

bioRxiv2019

Attractor dynamics gate cortical information flow during decision-making

Decisions about future actions are held in memory until enacted, making them vulnerable to distractors. The neural mechanisms controlling decision robustness to distractors remain unknown. We trained mice to report optogenetic stimulation of somatosensory cortex, with a delay separating sensation and action. Distracting stimuli influenced behavior less when delivered later during delay - demonstrating temporal gating of sensory information flow. Gating occurred even though distractor-evoked activity percolated through the cortex without attenuation. Instead, choice-related dynamics in frontal cortex became progressively robust to distractors as time passed. Reverse-engineering of neural networks trained to reproduce frontal-cortex activity revealed that chosen actions were stabilized via attractor dynamics, which gated out distracting stimuli. Our results reveal a dynamic gating mechanism that operates by controlling the degree of commitment to a chosen course of action. One Sentence SummaryMechanisms controlling state-dependent communication between brain regions allow for robust action-selection.

neuroscience↗

bioRxiv2019

A comparison of neuronal population dynamics measured with calcium imaging and electrophysiology

Calcium imaging with fluorescent protein sensors is widely used to record activity in neuronal populations. The transform between neural activity and calcium-related fluorescence involves nonlinearities and a low-pass filter, but the effects of the transformation on analyses of neural populations are not well understood. We compared neuronal spikes and fluorescence in matched neural populations in behaving mice. We report multiple discrepancies between analyses performed on the two types of data, which were only partially resolved by spike inference algorithms applied to fluorescence. To model the relation between spiking and fluorescence we simultaneously recorded spikes and fluorescence from individual neurons. Using these recordings we developed a model transforming spike trains to synthetic-imaging data. The model recapitulated the differences in analyses. Our analysis highlights challenges in relating electrophysiology and imaging data, and suggests forward modeling as an effective way to understand differences between these data.

neuroscience↗

bioRxiv2019

Recurrent interactions in local cortical circuits

The majority of cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing for pattern completion and other computations1. Cortical circuits contain subnetworks, consisting of neurons with similar receptive fields and elevated connectivity relative to the network average2,3. Understanding the computations performed by these subnetworks during behavior has been hampered by the fact that cortical neurons encoding different types of information are spatially intermingled and distributed over large brain volumes 4,5. We used computational modeling, optical recordings and manipulations to probe the function of recurrent coupling in layer (L) 2/3 of the somatosensory cortex during tactile discrimination. A model of L2/3 dynamics revealed that recurrent excitation enhances sensory signals via amplification, but only for subnetwork with elevated connectivity. Networks with high amplification were sensitive to damage: loss of a few subnetwork members degraded stimulus encoding. We tested this prediction experimentally by mapping neuronal selectivity5 and photoablating6,7 neurons with specific selectivity. In L2/3 of the somatosensory cortex, ablating a small proportion (10-20, < 5 % of the total) of neurons representing touch dramatically reduced responses in the spared touch representation, but not other representations. Network models further predicted that degradation following ablation should be greatest among spared neurons with stimulus responses that were most similar to the ablated population. Consistent with this prediction, ablations most strongly impacted neurons with selectivity similar to the ablated population. Our data shows that recurrence among cortical neurons with similar selectivity can drive input-specific amplification during behavior.

neuroscience↗

bioRxiv2019

Spatiotemporal limits of optogenetic manipulations in cortical circuits

Neuronal inactivation is commonly used to assess the involvement of groups of neurons in specific brain functions. Optogenetic tools allow manipulations of genetically and spatially defined neuronal populations with excellent temporal resolution. However, the targeted neurons are coupled with other neural populations over multiple length scales. As a result, the effects of localized optogenetic manipulations are not limited to the targeted neurons, but produces spatially extended excitation and inhibition with rich dynamics. Here we benchmarked several optogenetic silencers in transgenic mice and with viral gene transduction, with the goal to inactivate excitatory neurons in small regions of neocortex. We analyzed the effects of the perturbations in vivo using electrophysiology. Channelrhodopsin activation of GABAergic neurons produced more effective photoinhibition of pyramidal neurons than direct photoinhibition using light-gated ion pumps. We made transgenic mice expressing the light-dependent chloride channel GtACR under the control of Cre-recombinase. Activation of GtACR produced the most potent photoinhibition. For all methods, localized photostimuli produced photoinhibition that extended substantially beyond the spread of light in tissue, although different methods had slightly different resolution limits (radius of inactivation, 0.5 mm to 1 mm). The spatial profile of photoinhibition was likely shaped by strong coupling between cortical neurons. Over some range of photostimulation, circuits produced the \"paradoxical effect\", where excitation of inhibitory neurons reduced activity in these neurons, together with pyramidal neurons, a signature of inhibition-stabilized neural networks. The offset of optogenetic inactivation was followed by rebound excitation in a light dose-dependent manner, which can be mitigated by slowly varying photostimuli, but at the expense of time resolution. Our data offer guidance for the design of in vivo optogenetics experiments and suggest how these experiments can reveal operating principles of neural circuits.

neuroscience↗

bioRxiv2019

Targeted photostimulation uncovers circuit motifs supporting short-term memory

Short-term memory is associated with persistent neural activity without sustained input, arising from the interactions between neurons with short time constants1,2. A variety of neural circuit motifs could account for measured neural activity3-7. A mechanistic understanding of the neural circuits supporting short-term memory requires probing network connectivity between functionally characterized neurons8. We performed targeted photostimulation of small (< 10) groups of neurons, while imaging the response of hundreds of other neurons9,10, in anterior-lateral motor cortex (ALM) of mice performing a delayed response task11. Mice were instructed with brief auditory stimuli to make directional movements (lick left or lick right), but only after a three second delay epoch. ALM contains neurons with delay epoch activity that is selective for left or right choices. Targeted photostimulation of groups of neurons during the delay epoch allowed us to observe the functional organization of population activity and recurrent interactions underlying short-term memory. These experiments revealed strong coupling between neurons sharing similar selectivity. Brief photostimulation of functionally related neurons produced changes in activity in sparse subpopulations of nearby neurons that persisted for several seconds following stimulus offset, far outlasting the duration of the perturbation. Photostimulation produced behavioral biases that were predictable based on the selectivity of the perturbed neuronal population. These results suggest that ALM contains multiple intercalated modules, consisting of recurrently coupled neurons, that can independently maintain persistent activity.

neuroscience↗