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2575 Janelia Publications
Showing 11-20 of 2575 resultsSimultaneous recordings from hundreds or thousands of neurons are becoming routine because of innovations in instrumentation, molecular tools, and data processing software. Such recordings can be analyzed with data science methods, but it is not immediately clear what methods to use or how to adapt them for neuroscience applications. We review, categorize, and illustrate diverse analysis methods for neural population recordings and describe how these methods have been used to make progress on longstanding questions in neuroscience. We review a variety of approaches, ranging from the mathematically simple to the complex, from exploratory to hypothesis-driven, and from recently developed to more established methods. We also illustrate some of the common statistical pitfalls in analyzing large-scale neural data.
To understand neocortical function, we must first define its cell types. Recent studies indicate that neurons in the deepest cortical layer play roles in mediating thalamocortical interactions and modulating brain state and are implicated in neuropsychiatric disease. However, understanding the functions of deep layer 6 (L6b) neurons has been hampered by the lack of agreed upon definitions for these cell types. We compared commonly used methods for defining L6b neurons, including molecular, transcriptional and morphological approaches as well as transgenic mouse lines, and identified a core population of L6b neurons. This population does not innervate sensory thalamus, unlike layer 6 corticothalamic neurons (L6CThNs) in more superficial layer 6. Rather, single L6b neurons project ipsilaterally between cortical areas. Although L6b neurons undergo early developmental changes, we found that their intrinsic electrophysiological properties were stable after the first postnatal week. Our results provide a consensus definition for L6b neurons, enabling comparisons across studies.
In natural environments, animals must efficiently allocate their choices across multiple concurrently available resources when foraging, a complex decision-making process not fully captured by existing models. To understand how rodents learn to navigate this challenge we developed a novel paradigm in which untrained, water-restricted mice were free to sample from six options rewarded at a range of deterministic intervals and positioned around the walls of a large ( 2m) arena. Mice exhibited rapid learning, matching their choices to integrated reward ratios across six options within the first session. A reinforcement learning model with separate states for staying or leaving an option and a dynamic, global learning rate was able to accurately reproduce mouse learning and decision-making. Fiber photometry recordings revealed that dopamine in the nucleus accumbens core (NAcC), but not dorsomedial striatum (DMS), more closely reflected the global learning rate than local error-based updating. Altogether, our results provide insight into the neural substrate of a learning algorithm that allows mice to rapidly exploit multiple options when foraging in large spatial environments.
Chemical synapses are the major sites of communication between neurons in the nervous system and mediate either excitatory or inhibitory signaling. At excitatory synapses, glutamate is the primary neurotransmitter and upon release from presynaptic vesicles, is detected by postsynaptic glutamate receptors, which include ionotropic AMPA and NMDA receptors. Here, we have developed methods to identify glutamatergic synapses in brain tissue slices, label AMPA receptors with small gold nanoparticles (AuNPs), and prepare lamella for cryo-electron tomography studies. The targeted imaging of glutamatergic synapses in the lamella is facilitated by fluorescent pre- and postsynaptic signatures, and the subsequent tomograms allow for the identification of key features of chemical synapses, including synaptic vesicles, the synaptic cleft, and AuNP-labeled AMPA receptors. These methods pave the way for imaging brain regions at high resolution, using unstained, unfixed samples preserved under near-native conditions.
In the fruit fly, Drosophila melanogaster, connectome data and genetic tools provide a unique opportunity to study complex behaviors including navigation, mating, aggression, and grooming in an organism with a tractable nervous system of 140,000 neurons. Here we present the Fly Disco, a flexible system for high quality video collection, optogenetic manipulation, and fine-grained behavioral analysis of freely walking and socializing fruit fly groups. The data collection hardware and software automates the collection of videos synced to programmable optogenetic stimuli. Key pipeline features include behavioral analysis based on trajectories of 21 keypoints and optogenetic-specific summary statistics and data visualization. We created the multifly dataset for pose estimation that includes 9701 examples enriched in complex behaviors. All hardware designs, software, and the multifly dataset are freely available.
Clostridium perfringens is a Gram-positive anaerobic spore-forming bacterial pathogen of humans and animals. C. perfringens also produces type IV pili (T4P) and has two complete sets of T4P-associated genes, one of which has been shown to produce surface pili needed for cell adherence. One hypothesis about the role of the other set of T4P genes is that they could comprise a system analogous to the type II secretion systems (TTSS) found in Gram-negative bacteria, which is used to export folded proteins from the periplasm through the outer membrane to the extracellular environment. Gram-positive bacteria have a similar secretion barrier in the thick peptidoglycan (PG) layer, which blocks secretion of folded proteins >25 kD. To determine if the T4P-associated genes comprise a Gram-positive TTSS, the secretome of mutants lacking type IV pilins were examined and a single protein, a von Willebrand A domain containing protein BsaC (CPE0517) was identified as being dependent on PilA3 for secretion. BsaC is in an operon with a signal peptidase and two putative biofilm matrix proteins with homology to Bacillus subtilis TasA. One of these proteins, BsaA, was shown by another group to produce high mol wt oligomers. We analyzed BsaA monomer interactions with de novo modeling, which projected that the monomers formed isopeptide bonds as part of a donor strand exchange process. Mutations in residues predicted to form the isopeptide bonds led to loss of oligomerization, supporting the predicted bond formation process. Phylogenetic analysis showed the BsaA family of proteins are widespread among bacteria and archaea but only a subset are predicted to form isopeptide bonds.
A cognitive compass enabling spatial navigation requires neural representation of heading direction (HD), yet the neural circuit architecture enabling this representation remains unclear. While various network models have been proposed to explain HD systems, these models rely on simplified circuit architectures that are incompatible with empirical observations from connectomes. Here we construct a novel network model for the fruit fly HD system that satisfies both connectome-derived architectural constraints and the functional requirement of continuous heading representation. We characterize an ensemble of continuous attractor networks where compass neurons providing local mutual excitation are coupled to inhibitory neurons. We discover a new mechanism where continuous heading representation emerges from combining symmetric and anti-symmetric activity patterns. Our analysis reveals three distinct realizations of these networks that all match observed compass neuron activity but differ in their predictions for inhibitory neuron activation patterns. Further, we found that deviations from these realizations can be compensated by cell-type-specific rescaling of synaptic weights, which could be potentially achieved through neuromodulation. This framework can be extended to incorporate the complete fly central complex connectome and could reveal principles of neural circuits representing other continuous quantities, such as spatial location, across insects and vertebrates.
Synaptic transmission mediated by various neurotransmitters influences a wide range of behaviors. However, understanding how neuromodulatory transmitters encode diverse behaviors and affect their functions remains challenging. Here, we introduce GESIAP3.0, an advanced, third-generation image analysis program based on genetically encoded sensors. This tool enables precise quantitative analysis of transmission in both awake, freely moving animals and immobilized subjects. GESIAP3.0 incorporates movement correction algorithms that effectively eliminate image displacement in behaving animals while optimizing synaptic information extraction and simplifying computations on commodity computers. Quantitative analysis of cholinergic, dopaminergic, and serotonergic transmission, corrected for tissue movement, revealed synaptic properties consistent with measurements from ex vivo wide-field and in vivo two-photon imaging under stable conditions. This validates the applicability of GESIAP3.0 for analyzing synaptic properties of neuromodulatory transmission in behaving animals.
Upon inflammation, leukocytes extravasate through endothelial cells. When they extravasate in a paracellular manner, it is generally accepted that neighbouring endothelial cells physically disconnect to open cell-cell junctions, allowing leukocytes to cross. When carefully examining endothelial junctions, we found a partial membrane overlap of endothelial cells beyond VE-cadherin distribution. These overlaps are regulated by actin polymerization and, although marked by, do not require PECAM-1, nor VE-cadherin. Neutrophils prefer wider membrane overlaps as exit sites. Detailed 3D analysis of endothelial membrane dynamics during paracellular neutrophil transmigration in real-time, at high spatiotemporal resolution using resonant confocal and lattice light-sheet imaging, revealed that overlapping endothelial membranes form a tunnel during neutrophil transmigration. These tunnels are formed by the neutrophil lifting the membrane of the upper endothelial cell while indenting and crawling over the membrane of the underlying endothelial cell. Our work shows that endothelial cells do not simply retract upon passage of neutrophils but provide membrane tunnels, allowing neutrophils to extravasate. This discovery defines the 3D multicellular architecture in which the paracellular transmigration of neutrophils occurs.
The brain's ability to rapidly transition between sleep, quiet wakefulness, and states of high vigilance is remarkable. Cerebral norepinephrine (NE) plays a key role in promoting wakefulness, but how does the brain avoid neuronal hyperexcitability upon arousal? Here, we show that NE exposure results in the generation of free fatty acids (FFAs) within the plasma membrane from both astrocytes and neurons. In turn, FFAs dampen excitability by differentially modulating the activity of astrocytic and neuronal Na, K, ATPase. Direct application of FFA to the occipital cortex in awake, behaving mice dampened visual-evoked potential (VEP). Conversely, blocking FFA production via local application of a lipase inhibitor heightened VEP and triggered seizure-like activity. These results suggest that FFA release is a crucial step in NE signaling that safeguards against hyperexcitability. Targeting lipid-signaling pathways may offer a novel therapeutic approach for seizure prevention.