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2496 Janelia Publications

Showing 151-160 of 2496 results
11/20/23 | All-optical reporting of inhibitory receptor driving force in the nervous system.
Joshua S. Selfe , Teresa J. S. Steyn , Eran F. Shorer , Richard J. Burman , Kira M. Düsterwald , Ahmed S. Abdelfattah , Eric R. Schreiter , Sarah E. Newey , Colin J. Akerman , Joseph V. Raimondo
bioRxiv. 2023 Nov 20:. doi: 10.1101/2023.08.30.555464

Ionic driving forces provide the net electromotive force for ion movement across receptors, channels, and transporters, and are a fundamental property of all cells. In the brain for example, fast synaptic inhibition is mediated by chloride permeable GABAA receptors, and single-cell intracellular recordings have been the only method for estimating driving forces across these receptors (DFGABAA). Here we present a new tool for quantifying inhibitory receptor driving force named ORCHID: all-Optical Reporting of CHloride Ion Driving force. We demonstrate ORCHID’s ability to provide accurate, high-throughput measurements of resting and dynamic DFGABAA from genetically targeted cell types over multiple timescales. ORCHID confirms theoretical predictions about the biophysical mechanisms that establish DFGABAA, reveals novel differences in DFGABAA between neurons and astrocytes, and affords the first in vivo measurements of intact DFGABAA. This work extends our understanding of inhibitory synaptic transmission and establishes a precedent for all-optical methods to assess ionic driving forces.

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11/20/23 | Facemap: a framework for modeling neural activity based on orofacial tracking
Atika Syeda , Lin Zhong , Renee Tung , Will Long , Marius Pachitariu , Carsen Stringer
Nature Neuroscience. 2023 Nov 20:. doi: 10.1038/s41593-023-01490-6

Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relate them to neural activity. Here we developed Facemap, a framework consisting of a keypoint tracking algorithm and a deep neural network encoder for predicting neural activity. We used the Facemap keypoints as input for the deep neural network to predict the activity of ∼50,000 simultaneously-recorded neurons and in visual cortex we doubled the amount of explained variance compared to previous methods. Our keypoint tracking algorithm was more accurate than existing pose estimation tools, while the inference speed was several times faster, making it a powerful tool for closed-loop behavioral experiments. The Facemap tracker was easy to adapt to data from new labs, requiring as few as 10 annotated frames for near-optimal performance. We used Facemap to find that the neuronal activity clusters which were highly driven by behaviors were more spatially spread-out across cortex. We also found that the deep keypoint features inferred by the model had time-asymmetrical state dynamics that were not apparent in the raw keypoint data. In summary, Facemap provides a stepping stone towards understanding the function of the brainwide neural signals and their relation to behavior.

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11/13/23 | High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuation.
Laine RF, Heil HS, Coelho S, Nixon-Abell J, Jimenez A, Wiesner T, Martínez D, Galgani T, Régnier L, Stubb A, Follain G, Webster S, Goyette J, Dauphin A, Salles A, Culley S, Jacquemet G, Hajj B, Leterrier C, Henriques R
Nature Methods. 2023 Nov 13:. doi: 10.1038/s41592-023-02057-w

Live-cell super-resolution microscopy enables the imaging of biological structure dynamics below the diffraction limit. Here we present enhanced super-resolution radial fluctuations (eSRRF), substantially improving image fidelity and resolution compared to the original SRRF method. eSRRF incorporates automated parameter optimization based on the data itself, giving insight into the trade-off between resolution and fidelity. We demonstrate eSRRF across a range of imaging modalities and biological systems. Notably, we extend eSRRF to three dimensions by combining it with multifocus microscopy. This realizes live-cell volumetric super-resolution imaging with an acquisition speed of ~1 volume per second. eSRRF provides an accessible super-resolution approach, maximizing information extraction across varied experimental conditions while minimizing artifacts. Its optimal parameter prediction strategy is generalizable, moving toward unbiased and optimized analyses in super-resolution microscopy.

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11/08/23 | Preserved neural dynamics across animals performing similar behaviour.
Safaie M, Chang JC, Park J, Miller LE, Dudman JT, Perich MG, Gallego JA
Nature. 2023 Nov 08:. doi: 10.1038/s41586-023-06714-0

Animals of the same species exhibit similar behaviours that are advantageously adapted to their body and environment. These behaviours are shaped at the species level by selection pressures over evolutionary timescales. Yet, it remains unclear how these common behavioural adaptations emerge from the idiosyncratic neural circuitry of each individual. The overall organization of neural circuits is preserved across individuals because of their common evolutionarily specified developmental programme. Such organization at the circuit level may constrain neural activity, leading to low-dimensional latent dynamics across the neural population. Accordingly, here we suggested that the shared circuit-level constraints within a species would lead to suitably preserved latent dynamics across individuals. We analysed recordings of neural populations from monkey and mouse motor cortex to demonstrate that neural dynamics in individuals from the same species are surprisingly preserved when they perform similar behaviour. Neural population dynamics were also preserved when animals consciously planned future movements without overt behaviour and enabled the decoding of planned and ongoing movement across different individuals. Furthermore, we found that preserved neural dynamics extend beyond cortical regions to the dorsal striatum, an evolutionarily older structure. Finally, we used neural network models to demonstrate that behavioural similarity is necessary but not sufficient for this preservation. We posit that these emergent dynamics result from evolutionary constraints on brain development and thus reflect fundamental properties of the neural basis of behaviour.

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11/06/23 | A complete reconstruction of the early visual system of an adult insect.
Chua NJ, Makarova AA, Gunn P, Villani S, Cohen B, Thasin M, Wu J, Shefter D, Pang S, Xu CS, Hess HF, Polilov AA, Chklovskii DB
Current Biology. 2023 Nov 06;33(21):4611-4623. doi: 10.1016/j.cub.2023.09.021

For most model organisms in neuroscience, research into visual processing in the brain is difficult because of a lack of high-resolution maps that capture complex neuronal circuitry. The microinsect Megaphragma viggianii, because of its small size and non-trivial behavior, provides a unique opportunity for tractable whole-organism connectomics. We image its whole head using serial electron microscopy. We reconstruct its compound eye and analyze the optical properties of the ommatidia as well as the connectome of the first visual neuropil-the lamina. Compared with the fruit fly and the honeybee, Megaphragma visual system is highly simplified: it has 29 ommatidia per eye and 6 lamina neuron types. We report features that are both stereotypical among most ommatidia and specialized to some. By identifying the "barebones" circuits critical for flying insects, our results will facilitate constructing computational models of visual processing in insects.

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11/03/23 | Volitional activation of remote place representations with a hippocampal brain-machine interface.
Lai C, Tanaka S, Harris TD, Lee AK
Science. 2023 Nov 03;382(6670):566-573. doi: 10.1126/science.adh5206

The hippocampus is critical for recollecting and imagining experiences. This is believed to involve voluntarily drawing from hippocampal memory representations of people, events, and places, including maplike representations of familiar environments. However, whether representations in such "cognitive maps" can be volitionally accessed is unknown. We developed a brain-machine interface to test whether rats can do so by controlling their hippocampal activity in a flexible, goal-directed, and model-based manner. We found that rats can efficiently navigate or direct objects to arbitrary goal locations within a virtual reality arena solely by activating and sustaining appropriate hippocampal representations of remote places. This provides insight into the mechanisms underlying episodic memory recall, mental simulation and planning, and imagination and opens up possibilities for high-level neural prosthetics that use hippocampal representations.

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11/01/23 | Nanometer-scale views of visual cortex reveal anatomical features of primary cilia poised to detect synaptic spillover
Carolyn M Ott , Russel Torres , Tung-Sheng Kuan , Aaron T Kuan , JoAnn Buchanan , Leila Elabbady , Sharmishtaa Seshamani , Agnes L Bodor , Forrest C Collman , Davi D Bock , Wei-Chung Allen Lee , Nuno Macarico da Costa , Jennifer Lippincott-Schwartz
bioRxiv. 2023 Nov 01:. doi: 10.1101/2023.10.31.564838

A primary cilium is a thin membrane-bound extension off a cell surface that contains receptors for perceiving and transmitting signals that modulate cell state and activity. While many cell types have a primary cilium, little is known about primary cilia in the brain, where they are less accessible than cilia on cultured cells or epithelial tissues and protrude from cell bodies into a deep, dense network of glial and neuronal processes. Here, we investigated cilia frequency, internal structure, shape, and position in large, high-resolution transmission electron microscopy volumes of mouse primary visual cortex. Cilia extended from the cell bodies of nearly all excitatory and inhibitory neurons, astrocytes, and oligodendrocyte precursor cells (OPCs), but were absent from oligodendrocytes and microglia. Structural comparisons revealed that the membrane structure at the base of the cilium and the microtubule organization differed between neurons and glia. OPC cilia were distinct in that they were the shortest and contained pervasive internal vesicles only occasionally observed in neuron and astrocyte cilia. Investigating cilia-proximal features revealed that many cilia were directly adjacent to synapses, suggesting cilia are well poised to encounter locally released signaling molecules. The internal anatomy, including microtubule changes and centriole location, defined key structural features including cilium placement and shape. Together, the anatomical insights both within and around neuron and glia cilia provide new insights into cilia formation and function across cell types in the brain.

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11/01/23 | Vagal sensory neurons mediate the Bezold-Jarisch reflex and induce syncope.
Lovelace JW, Ma J, Yadav S, Chhabria K, Shen H, Pang Z, Qi T, Sehgal R, Zhang Y, Bali T, Vaissiere T, Tan S, Liu Y, Rumbaugh G, Ye L, Kleinfeld D, Stringer C, Augustine V
Nature. 2023 Nov 01;623(7986):387-396. doi: 10.1038/s41586-023-06680-7

Visceral sensory pathways mediate homeostatic reflexes, the dysfunction of which leads to many neurological disorders. The Bezold-Jarisch reflex (BJR), first described in 1867, is a cardioinhibitory reflex that is speculated to be mediated by vagal sensory neurons (VSNs) that also triggers syncope. However, the molecular identity, anatomical organization, physiological characteristics and behavioural influence of cardiac VSNs remain mostly unknown. Here we leveraged single-cell RNA-sequencing data and HYBRiD tissue clearing to show that VSNs that express neuropeptide Y receptor Y2 (NPY2R) predominately connect the heart ventricular wall to the area postrema. Optogenetic activation of NPY2R VSNs elicits the classic triad of BJR responses-hypotension, bradycardia and suppressed respiration-and causes an animal to faint. Photostimulation during high-resolution echocardiography and laser Doppler flowmetry with behavioural observation revealed a range of phenotypes reflected in clinical syncope, including reduced cardiac output, cerebral hypoperfusion, pupil dilation and eye-roll. Large-scale Neuropixels brain recordings and machine-learning-based modelling showed that this manipulation causes the suppression of activity across a large distributed neuronal population that is not explained by changes in spontaneous behavioural movements. Additionally, bidirectional manipulation of the periventricular zone had a push-pull effect, with inhibition leading to longer syncope periods and activation inducing arousal. Finally, ablating NPY2R VSNs specifically abolished the BJR. Combined, these results demonstrate a genetically defined cardiac reflex that recapitulates characteristics of human syncope at physiological, behavioural and neural network levels.

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10/31/23 | Effects of stochastic coding on olfactory discrimination in flies and mice.
Srinivasan S, Daste S, Modi MN, Turner GC, Fleischmann A, Navlakha S
PLoS Biology. 2023 Oct 31;21(10):e3002206. doi: 10.1371/journal.pbio.3002206

Sparse coding can improve discrimination of sensory stimuli by reducing overlap between their representations. Two factors, however, can offset sparse coding's benefits: similar sensory stimuli have significant overlap and responses vary across trials. To elucidate the effects of these 2 factors, we analyzed odor responses in the fly and mouse olfactory regions implicated in learning and discrimination-the mushroom body (MB) and the piriform cortex (PCx). We found that neuronal responses fall along a continuum from extremely reliable across trials to extremely variable or stochastic. Computationally, we show that the observed variability arises from noise within central circuits rather than sensory noise. We propose this coding scheme to be advantageous for coarse- and fine-odor discrimination. More reliable cells enable quick discrimination between dissimilar odors. For similar odors, however, these cells overlap and do not provide distinguishing information. By contrast, more unreliable cells are decorrelated for similar odors, providing distinguishing information, though these benefits only accrue with extended training with more trials. Overall, we have uncovered a conserved, stochastic coding scheme in vertebrates and invertebrates, and we identify a candidate mechanism, based on variability in a winner-take-all (WTA) inhibitory circuit, that improves discrimination with training.

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10/31/23 | Tensor formalism for predicting synaptic connections with ensemble modeling or optimization.
Tirthabir Biswas , Tianzhi Lambus Li , James E. Fitzgerald
arXiv. 2023 Oct 31:. doi: 10.48550/arXiv.2310.20309

Theoretical neuroscientists often try to understand how the structure of a neural network relates to its function by focusing on structural features that would either follow from optimization or occur consistently across possible implementations. Both optimization theories and ensemble modeling approaches have repeatedly proven their worth, and it would simplify theory building considerably if predictions from both theory types could be derived and tested simultaneously. Here we show how tensor formalism from theoretical physics can be used to unify and solve many optimization and ensemble modeling approaches to predicting synaptic connectivity from neuronal responses. We specifically focus on analyzing the solution space of synaptic weights that allow a thresholdlinear neural network to respond in a prescribed way to a limited number of input conditions. For optimization purposes, we compute the synaptic weight vector that minimizes an arbitrary quadratic loss function. For ensemble modeling, we identify synaptic weight features that occur consistently across all solutions bounded by an arbitrary quadratic function. We derive a common solution to this suite of nonlinear problems by showing how each of them reduces to an equivalent linear problem that can be solved analytically. Although identifying the equivalent linear problem is nontrivial, our tensor formalism provides an elegant geometrical perspective that allows us to solve the problem numerically. The final algorithm is applicable to a wide range of interesting neuroscience problems, and the associated geometric insights may carry over to other scientific problems that require constrained optimization.

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