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193 Publications
Showing 41-50 of 193 resultsNeural circuits within the frontal cortex support the flexible selection of goal-directed behaviors by integrating input from brain regions associated with sensory, emotional, episodic, and semantic memory functions. From a connectomics perspective, determining how these disparate afferent inputs target their synapses to specific cell types in the frontal cortex may prove crucial in understanding circuit-level information processing. Here, we used monosynaptic retrograde rabies mapping to examine the distribution of afferent neurons targeting four distinct classes of local inhibitory interneurons and four distinct classes of excitatory projection neurons in mouse infralimbic cortex. Interneurons expressing parvalbumin, somatostatin, or vasoactive intestinal peptide received a large proportion of inputs from hippocampal regions, while interneurons expressing neuron-derived neurotrophic factor received a large proportion of inputs from thalamic regions. A more moderate hippocampal-thalamic dichotomy was found among the inputs targeting excitatory neurons that project to the basolateral amygdala, lateral entorhinal cortex, nucleus reuniens of the thalamus, and the periaqueductal gray. Together, these results show a prominent bias among hippocampal and thalamic afferent systems in their targeting to genetically or anatomically defined sets of frontal cortical neurons. Moreover, they suggest the presence of two distinct local microcircuits that control how different inputs govern frontal cortical information processing.
The basolateral amygdala (BLA) plays essential roles in behaviors motivated by stimuli with either positive or negative valence, but how it processes motivationally opposing information and participates in establishing valence-specific behaviors remains unclear. Here, by targeting Fezf2-expressing neurons in the BLA, we identify and characterize two functionally distinct classes in behaving mice, the negative-valence neurons and positive-valence neurons, which innately represent aversive and rewarding stimuli, respectively, and through learning acquire predictive responses that are essential for punishment avoidance or reward seeking. Notably, these two classes of neurons receive inputs from separate sets of sensory and limbic areas, and convey punishment and reward information through projections to the nucleus accumbens and olfactory tubercle, respectively, to drive negative and positive reinforcement. Thus, valence-specific BLA neurons are wired with distinctive input-output structures, forming a circuit framework that supports the roles of the BLA in encoding, learning and executing valence-specific motivated behaviors.
In order to successfully obtain a faculty position, postdoctoral fellows or ‘postdocs’, must submit an application which requires considerable time and effort to produce. These job applications are often reviewed by mentors and colleagues, but rarely are postdocs offered the opportunity to solicit feedback multiple times from reviewers with the same breadth of expertise often found on an academic search committee. To address this gap, this manuscript describes an international peer reviewing program for small groups of postdocs with a broad range of expertise to reciprocally and iteratively provide feedback to each other on their application materials. Over 145 postdocs have participated, often multiple times, over three years. A survey of participants in this program revealed that nearly all participants would recommend participation in such a program to other faculty applicants. Furthermore, this program was more likely to attract participants who struggled to find mentoring and support elsewhere, either because they changed fields or because of their identity as a woman or member of an underrepresented population in STEM. Participation in programs like this one could provide early career academics like postdocs with a diverse and supportive community of peer mentors during the difficult search for a faculty position. Such psychosocial support and encouragement has been shown to prevent attrition of individuals from these populations and programs like this one target the largest ‘leak’ in the pipeline, that of postdoc to faculty. Implementation of similar peer reviewing programs by universities or professional scientific societies could provide a valuable mechanism of support and increased chances of success for early-career academics in their search for independence.Competing Interest StatementThe authors have declared no competing interest.
To successfully perform goal-directed navigation, animals must know where they are and what they are doing—e.g., looking for water, bringing food back to the nest, or escaping from a predator. Hippocampal neurons code for these critical variables conjunctively, but little is known about how this where/what code is formed or flexibly routed to other brain regions. To address these questions, we performed intracellular whole-cell recordings in mouse CA1 during a cued, two-choice virtual navigation task. We demonstrate that plateau potentials in CA1 pyramidal neurons rapidly strengthen synaptic inputs carrying conjunctive information about position and choice. Plasticity-induced response fields were modulated by cues only in animals previously trained to collect rewards based on these cues. Thus, we reveal that gradual learning is required for the formation of a conjunctive population code, upstream of CA1, while plateau-potential-induced synaptic plasticity in CA1 enables flexible routing of the code to downstream brain regions.
The small size and translucency of larval zebrafish () have made it a unique experimental system to investigate whole-brain neural circuit structure and function. Still, the connectivity patterns between most neuronal types remain mostly unknown. This gap in knowledge underscores the critical need for effective neural circuit mapping tools, especially ones that can integrate structural and functional analyses. To address this, we previously developed a vesicular stomatitis virus (VSV) based approach called Tracer with Restricted Anterograde Spread (TRAS). TRAS utilizes lentivirus to complement replication-incompetent VSV (VSVΔG) to allow restricted (monosynaptic) anterograde labeling from projection neurons to their target cells in the brain. Here, we report the second generation of TRAS (TRAS-M51R), which utilizes a mutant variant of VSVΔG [VSV(M51R)ΔG] with reduced cytotoxicity. Within the primary visual pathway, we found that TRAS-M51R significantly improved long-term viability of transsynaptic labeling (compared to TRAS) while maintaining anterograde spread activity. By using Cre-expressing VSV(M51R)ΔG, TRAS-M51R could selectively label excitatory ( positive) and inhibitory ( positive) retinorecipient neurons. We further show that these labeled excitatory and inhibitory retinorecipient neurons retained neuronal excitability upon visual stimulation at 5-8 days post fertilization (2-5 days post-infection). Together, these findings show that TRAS-M51R is suitable for neural circuit studies that integrate structural connectivity, cell-type identity, and neurophysiology.
Understanding complex biological systems requires visualizing structures and processes deep within living organisms. We developed a compact adaptive optics module and incorporated it into two- and three-photon fluorescence microscopes, to measure and correct tissue-induced aberrations. We resolved synaptic structures in deep cortical and subcortical areas of the mouse brain, and demonstrated high-resolution imaging of neuronal structures and somatosensory-evoked calcium responses in the mouse spinal cord at unprecedented depths in vivo.
Although most experimentally characterized proteins with similar sequences assume the same folds and perform similar functions, an increasing number of exceptions is emerging. One class of exceptions comprises sequence-similar fold switchers, whose secondary structures shift from α-helix <-> β-sheet through a small number of mutations, a sequence insertion, or a deletion. Predictive methods for identifying sequence-similar fold switchers are desirable because some are associated with disease and/or can perform different functions in cells. Here, we use homology-based secondary structure predictions to identify sequence-similar fold switchers from their amino acid sequences alone. To do this, we predicted the secondary structures of sequence-similar fold switchers using three different homology-based secondary structure predictors: PSIPRED, JPred4, and SPIDER3. We found that α-helix <-> β-strand prediction discrepancies from JPred4 discriminated between the different conformations of sequence-similar fold switchers with high statistical significance (P < 1.8*10 ). Thus, we used these discrepancies as a classifier and found that they can often robustly discriminate between sequence-similar fold switchers and sequence-similar proteins that maintain the same folds (Matthews Correlation Coefficient of 0.82). We found that JPred4 is a more robust predictor of sequence-similar fold switchers because of (a) the curated sequence database it uses to produce multiple sequence alignments and (b) its use of sequence profiles based on Hidden Markov Models. Our results indicate that inconsistencies between JPred4 secondary structure predictions can be used to identify some sequence-similar fold switchers from their sequences alone. Thus, the negative information from inconsistent secondary structure predictions can potentially be leveraged to identify sequence-similar fold switchers from the broad base of genomic sequences.
Extant fold-switching proteins remodel their secondary structures and change their functions in response to cellular stimuli, regulating biological processes and affecting human health. In spite of their biological importance, these proteins remain understudied. Few representative examples of fold switchers are available in the Protein Data Bank, and they are difficult to predict. In fact, all 96 experimentally validated examples of extant fold switchers were stumbled upon by chance. Thus, predictive methods are needed to expedite the process of discovering and characterizing more of these shapeshifting proteins. Previous approaches require a solved structure or all-atom simulations, greatly constraining their use. Here, we propose a high-throughput sequence-based method for predicting extant fold switchers that transition from α-helix in one conformation to β-strand in the other. This method leverages two previous observations: (1) α-helix <-> β-strand prediction discrepancies from JPred4 are a robust predictor of fold switching, and (2) the fold-switching regions (FSRs) of some extant fold switchers have different secondary structure propensities when expressed in isolation (isolated FSRs) than when expressed within the context of their parent protein (contextualized FSRs). Combining these two observations, we ran JPred4 on the sequences of isolated and contextualized FSRs from 14 known extant fold switchers and found α-helix <->β-strand prediction discrepancies in every case. To test the overall robustness of this finding, we randomly selected regions of proteins not expected to switch folds (single-fold proteins) and found significantly fewer α-helix <-> β-strand prediction discrepancies (p < 4.2*10−20, Kolmogorov-Smirnov test). Combining these discrepancies with the overall percentage of predicted secondary structure, we developed a classifier that often robustly identifies extant fold switchers (Matthews Correlation Coefficient of 0.70). Although this classifier had a high false negative rate (6/14), its false positive rate was very low (1/211), suggesting that it can be used to predict a subset of extant fold switchers from billions of available genomic sequences.
Understanding complex biological systems requires visualizing structures and processes deep within living organisms. We developed a compact adaptive optics module and incorporated it into two- and three-photon fluorescence microscopes, to measure and correct tissue-induced aberrations. We resolved synaptic structures in deep cortical and subcortical areas of the mouse brain, and demonstrated high-resolution imaging of neuronal structures and somatosensory-evoked calcium responses in the mouse spinal cord at great depths in vivo.
In April 2020, the QUality Assessment and REProducibility for Instruments and Images in Light Microscopy (QUAREP-LiMi) initiative was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models, and tools, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research. This White Paper 1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; 2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of stakeholders including, researchers, imaging scientists, bioimage analysts, bioimage informatics developers, corporate partners, funding agencies, standards organizations, scientific publishers, and observers of such; 3) outlines the current actions of the QUAREP-LiMi initiative, and 4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC. To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.