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Zador, A. M.

Publications and source records attributed to Zador, A. M..

16 recordsLinked to original sources

Discovery and shaping of decision strategies using adversarial stimuli in rats

Animals typically learn to solve decision tasks in the laboratory through trial and error, rather than through explicit instruction of decision rules. The decision rule used by the animal may be difficult to read out directly from choice or accuracy data, when multiple decision rules are possible given the task design. Here, we demonstrate that in rats performing a visual decision task, probe stimuli can be used to gain information about decision strategy, and in our task revealed variation in the decision strategies used across rats. Further, we find that in a more general version of this task, rats use varying decision strategies that differ from the optimal ideal observer strategy, but respond to manipulations of the stimulus distribution by adjusting their behavioral strategy. Therefore, we show that informative probe stimuli can be used in both training and testing to confirm and shape behavioral strategy in a perceptual decision task.

animal behavior and cognition↗

Eigengene reveals invariant global spatial patterns across mouse and fish brain development

Development from a zygote to an adult organism involves complex interactions among thousands of genes. These genes exhibit highly dynamic expression across space and time. Here we report a striking simplicity amidst this complexity: Despite individual gene expression variability, the eigengene--the principal component of gene expression--exhibits an invariant global spatial pattern throughout the embryonic and post-natal stages of the mouse brain. Furthermore, the mouse pattern is observed also in the larval zebrafish, revealing that eigengene expression is conserved over 400 million years of evolution. We show that the eigengene pattern can be explained by a simple lineage model in which daughter cells gene expression is similar to that of their parent, but cannot be explained by one in which gene expression arises through local cellular signaling. The constrained lineage gives rise naturally to a global eigengene expression hierarchy that could aid in the formation of a spatial hierarchy of long-range signal gradients. We propose that lineage thus induces an address-like organization, which could have been co-opted by evolution for developmental processes that require positional information over a wide range of spatial scales, such as tissue patterning and axon navigation.

neuroscience↗

Selective expansion of motor cortical projections in the evolution of vocal novelty

Deciphering how cortical architecture evolves to drive behavioral innovations is a long-standing challenge in neuroscience and evolutionary biology. Here, we leverage a striking behavioral novelty in the Alstons singing mouse (Scotinomys teguina), compared to the laboratory mouse (Mus musculus), to quantitatively test models of motor cortical evolution. We used bulk tracing, serial two-photon tomography, and high-throughput DNA sequencing of over 76,000 barcoded neurons to discover a specific and substantial expansion ([~]200%) of orofacial motor cortical (OMC) projections to the auditory cortical region (AudR) and the midbrain periaqueductal gray (PAG), both implicated in vocal behaviors. Moreover, analysis of individual OMC neurons projection motifs revealed preferential expansion of exclusive projections to AudR. Our results imply that selective expansion of ancestral motor cortical projections can underlie behavioral divergence over short evolutionary timescales, suggesting potential mechanisms for the evolution of enhanced cortical control over vocalizations--a crucial preadaptation for human language.

neuroscience↗

Early dynamics of excitation and inhibition maintain late frequency tuning in auditory cortex

In the auditory cortex the onset of a tone evokes time-varying excitation and inhibition. However, the role of early inhibition in shaping the temporal properties of tone-evoked responses has not been fully characterized. By using Archaerhodopsin-3 (Arch) to photo-suppress the activity of the parvalbumin-expressing (PV) class of inhibitory interneurons, we manipulated the early component of tone-evoked inhibition. We find that early inhibition directly controls the output gain of the response, reducing the number of spikes proportionately across all frequencies. However, by controlling early activity, transient inhibition prevents late excitation and spiking for non-optimal frequencies. Thus, transient tone-evoked inhibition plays a critical long-lasting role in shaping response properties in the auditory cortex.

neuroscience↗

Massive Multiplexing of Spatially Resolved Single Neuron Projections with Axonal BARseq

Neurons in the cortex are heterogeneous, sending diverse axonal projections to multiple brain regions. Unraveling the logic of these projections requires single-neuron resolution. Although a growing number of techniques have enabled high-throughput reconstruction, these techniques are typically limited to dozens or at most hundreds of neurons per brain, requiring that statistical analyses combine data from different specimens. Here we present axonal BARseq, a high-throughput approach based on reading out nucleic acid barcodes using in situ RNA sequencing, which enables analysis of even densely labeled neurons. As a proof of principle, we have mapped the long-range projections of >8,000 mouse primary auditory cortex neurons from a single brain. We identified major cell types based on projection targets and axonal trajectory. The large sample size enabled us to systematically quantify the projections of intratelencephalic (IT) neurons, and revealed that individual IT neurons project to different layers in an area-dependent fashion. Axonal BARseq is a powerful technique for studying the heterogeneity of single neuronal projections at high throughput within individual brains.

neuroscience↗

Stable sound decoding despite modulated sound representation in the auditory cortex

The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks. Using two-photon calcium imaging to record populations of single neurons in auditory cortex, we found that both stimulus and reward expectation modulated the activity of these neurons. A linear decoder trained on this population activity could decode stimuli as well or better than predicted by the animals performance. Interestingly, the optimal decoder was stable even in the face of variable sensory representations. Neither the context nor the mouses choice could be reliably decoded from the recorded neural activity. Our findings suggest that in spite of modulation of auditory cortical activity by task priors, auditory cortex does not represent sufficient information about these priors to exploit them optimally and that decisions in this task require that rapidly changing sensory information be combined with more slowly varying task information extracted and represented in brain regions other than auditory cortex.

neuroscience↗

Expansion Sequencing of RNA Barcoded Neurons in the Mammalian Brain: Progress and Implications for Molecularly Annotated Connectomics

Mapping and molecularly annotating mammalian neural circuits is challenging due to the inability to uniquely label cells while also resolving subcellular features such as synaptic proteins or fine cellular processes. We argue that an ideal technology for connectomics would have the following characteristics: the capacity for robust distance-independent labeling, synaptic resolution, molecular interrogation, and scalable computational methods. The recent development of high-diversity cellular barcoding with RNA has provided a way to overcome the labeling limitations associated with spectral dyes, however performing all-optical circuit mapping has not been demonstrated because no method exists to image barcodes throughout cells at synaptic-resolution. Here we show ExBarSeq, an integrated method combining in situ sequencing of RNA barcodes, immunostaining, and Expansion Microscopy coupled with an end-to-end software pipeline that automatically extracts barcode identities from large imaging datasets without data processing bottlenecks. As a proof of concept, we applied ExBarSeq to thick tissue sections from mice virally infected with MAPseq viral vectors and demonstrated the extraction of 50 barcoded cells in the visual cortex as well as cell morphologies uncovered via immunostaining. The current work demonstrates high resolution multiplexing of exogenous barcodes and endogenous synaptic proteins and outlines a roadmap for molecularly annotated connectomics at a brain-wide scale.

neuroscience↗

Diversity and task-dependence of task representations in V1 during freely-moving decisions

Neurons in primary visual cortex (area V1) are strongly driven by both sensory stimuli and non-sensory events. However, although the representation of sensory stimuli has been well characterized, much less is known about the representation of non-sensory events. Here, we characterize the specificity and organization of non-sensory representations in rat V1 during a freely-moving visual decision task. We find that single neurons encode diverse combinations of task features simultaneously and across task epochs. Despite heterogeneity at the level of single neuron response patterns, both visual and non-visual task variables could be reliably decoded from small neural populations (5-40 units) throughout a trial. Interestingly, in animals trained to make an auditory decision following passive observation of a visual stimulus, some but not all task features could also be decoded from V1 activity. Our results support the view that even in V1-- the earliest stage of the cortical hierarchy--bottom-up sensory information is combined with top-down non-sensory information in a task-dependent manner.

neuroscience↗

Wiring logic of the early rodent olfactory system revealed by high-throughput sequencing of single neuron projections

The structure of neuronal connectivity often provides insights into the relevant stimulus features, such as spatial location, orientation, sound frequency, etc1-6. The olfactory system, however, appears to lack structured connectivity as suggested by reports of broad and distributed connections both from the olfactory bulb to the piriform cortex7-22 and within the cortex23-25. These studies have inspired computational models of circuit function that rely on random connectivity26-33. It remains, nonetheless, unclear whether the olfactory connectivity contains spatial structure. Here, we use high throughput anatomical methods (MAPseq and BARseq)34-38 to analyze the projections of 5,309 bulb and 30,433 piriform cortex output neurons in the mouse at single-cell resolution. We identify previously unrecognized spatial organization in connectivity along the anterior-posterior axis (A-P) of the piriform cortex. We find that both the bulb projections to the cortex and the cortical outputs are not random, but rather form gradients along the A-P axis. Strikingly, these gradients are matched: bulb neurons targeting a given location within the piriform cortex co-innervate extra-piriform regions that receive strong inputs from neurons within that piriform locus. We also identify signatures of local connectivity in the piriform cortex. Our findings suggest an organizing principle of matched direct and indirect olfactory pathways that innervate extra-piriform targets in a coordinated manner, thus supporting models of information processing that rely on structured connectivity within the olfactory system.

neuroscience↗

Integrating barcoded neuroanatomy with spatial transcriptional profiling reveals cadherin correlates of projections shared across the cortex

Functional circuits consist of neurons with diverse axonal projections and gene expression. Understanding the molecular signature of projections requires high-throughput interrogation of both gene expression and projections to multiple targets in the same cells at cellular resolution, which is difficult to achieve using current technology. Here, we introduce BARseq2, a technique that simultaneously maps projections and detects multiplexed gene expression by in situ sequencing. We determined the expression of cadherins and cell-type markers in 29,933 cells, and the projections of 3,164 cells in both the mouse motor cortex and auditory cortex. Associating gene expression and projections in 1,349 neurons revealed shared cadherin signatures of homologous projections across the two cortical areas. These cadherins were enriched across multiple branches of the transcriptomic taxonomy. By correlating multi-gene expression and projections to many targets in single neurons with high throughput, BARseq2 provides a path to uncovering the molecular logic underlying neuronal circuits.

neuroscience↗

Corticostriatal Plasticity Established by Initial Learning Persists After Behavioral Reversal

The neural mechanisms that allow animals to adapt their previously learned associations in response to changes in the environment remain poorly understood. To probe the synaptic mechanisms that mediate such adaptive behavior, we trained mice on an auditory-motor reversal task, and tracked changes in the strength of corticostriatal synapses associated with the formation of learned associations. Using a ChR2-based electrophysiological assay in acute striatal slices, we measured the strength of these synapses after animals learned to pair auditory stimuli with specific actions. Here we report that the pattern of synaptic strength initially established by learning remains unchanged even when the task contingencies are reversed. Our results suggest that synaptic changes associated with the initial acquisition of this task are not erased or over-written, and that behavioral reversal of learned associations may recruit a separate neural circuit.

neuroscience↗

SYNPLA: A synapse-specific method for identifying learning-induced synaptic plasticity loci

Which neural circuits undergo synaptic changes when an animal learns? Although it is widely accepted that changes in synaptic strength underlie many forms of learning and memory, it remains challenging to connect changes in synaptic strength at specific neural pathways to specific behaviors and memories. Here we introduce SYNPLA (SYNaptic Proximity Ligation Assay), a synapse-specific, high-throughput and potentially brain-wide method capable of detecting circuit-specific learning-induced synaptic plasticity.

neuroscience↗

Single-cell molecular connectomics of intracortically-projecting neurons

The neocortex is organized into distinct areas, whose interconnectivity underlies sensorimotor transformations and integration1-7. These behaviorally critical functions are mediated by intracortically-projecting neurons (ICPN), which are a heterogeneous population of cells sending axonal branches to distinct cortical areas as well as to subcortical targets8-10. Although population-based11-14 and single-cell15-19 intracortical wiring diagrams are being identified, the transcriptional signatures corresponding to single-cell axonal projections of ICPN to multiple sites remain unknown. To address this question, we developed a high-throughput approach, \"ConnectID\", to link connectome and transcriptome in single neurons. ConnectID combines MAPseq projection mapping17,20 (to identify single-neuron multiplex projections) with single-cell RNA sequencing (to identify corresponding gene expression). Using primary somatosensory cortex (S1) ICPN as proof-of-principle neurons, we identify three cardinal targets: (1) the primary motor cortex (M1), (2) the secondary somatosensory cortex (S2) and (3) subcortical targets (Sub). Using ConnectID, we identify transcriptional modules whose combined activities reflect multiplex projections to these cardinal targets. Based on these findings, we propose that the combinatorial activity of connectivity-defined transcriptional modules serves as a generic molecular mechanism to create diverse axonal projection patterns within and across neuronal cell types.

neuroscience↗

Spatial organization of projection neurons in the mouse auditory cortex identified by in situ barcode sequencing

Understanding neural circuits requires deciphering interactions among myriad cell types defined by spatial organization, connectivity, gene expression, and other properties. Resolving these cell types requires both single neuron resolution and high throughput, a challenging combination with conventional methods. Here we introduce BARseq, a multiplexed method based on RNA barcoding for mapping projections of thousands of spatially resolved neurons in a single brain, and relating those projections to other properties such as gene or Cre expression. Mapping the projections to 11 areas of 3579 neurons in mouse auditory cortex using BARseq confirmed the laminar organization of the three top classes (IT, PT-like and CT) of projection neurons. In depth analysis uncovered a novel projection type restricted almost exclusively to transcriptionally-defined subtypes of IT neurons. By bridging anatomical and transcriptomic approaches at cellular resolution with high throughput, BARseq can potentially uncover the organizing principles underlying the structure and formation of neural circuits.

neuroscience↗

Efficient in situ barcode sequencing using padlock probe-based BaristaSeq

Cellular DNA/RNA tags (barcodes) allow for multiplexed cell lineage tracing and neuronal projection mapping with cellular resolution. Conventional approaches to reading out cellular barcodes trade off spatial resolution with throughput. Bulk sequencing achieves high throughput but sacrifices spatial resolution, whereas manual cell picking has low throughput. In situ sequencing could potentially achieve both high spatial resolution and high throughput, but current in situ sequencing techniques are inefficient at reading out cellular barcodes. Here we describe BaristaSeq, an optimization of a targeted, padlock probe-based technique for in situ barcode sequencing compatible with Illumina sequencing chemistry. BaristaSeq results in a five-fold increase in amplification efficiency, with a sequencing accuracy of at least 97%. BaristaSeq could be used for barcode-assisted lineage tracing, and to map long-range neuronal projections.\n\nKey PointsO_LIIn situ sequencing by gap-filling padlock probes is limited by the strand displacement of DNA polymerases\nC_LIO_LIIllumina sequencing chemistry offers superior signal-to-noise ratio in situ compared to sequencing by ligation\nC_LIO_LIBaristaSeq as an accurate method for barcode sequencing in situ with improved gap-filling efficiency\nC_LI

molecular biology↗

A single-cell anatomical blueprint for intracortical information transfer from primary visual cortex

The wiring diagram of the neocortex determines how information is processed across dozens of cortical areas. Each area communicates with multiple others via extensive long-range axonal projections 1-6, but the logic of inter-area information transfer is unresolved. Specifically, the extent to which individual neurons send dedicated projections to single cortical targets or distribute their signals across multiple areas remains unclear5,7-20. Distinguishing between these possibilities has been challenging because axonal projections of only a few individual neurons have been reconstructed. Here we map the projection patterns of axonal arbors from 591 individual neurons in mouse primary visual cortex (V1) using two complementary methods: whole-brain fluorescence-based axonal tracing21,22 and high-throughput DNA sequencing of genetically barcoded neurons (MAPseq)23. Although our results confirm the existence of dedicated projections to certain cortical areas, we find these are the exception, and that the majority of V1 neurons broadcast information to multiple cortical targets. Furthermore, broadcasting cells do not project to all targets randomly, but rather comprise subpopulations that either avoid or preferentially innervate specific subsets of cortical areas. Our data argue against a model of dedicated lines of intracortical information transfer via \"one neuron - one target area\" mapping. Instead, long-range communication between a sensory cortical area and its targets may be based on a principle whereby individual neurons copy information to, and potentially coordinate activity across, specific subsets of cortical areas.

neuroscience↗