Filter
Associated Lab
- Aguilera Castrejon Lab (15) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (57) Apply Ahrens Lab filter
- Aso Lab (39) Apply Aso Lab filter
- Baker Lab (38) Apply Baker Lab filter
- Betzig Lab (111) Apply Betzig Lab filter
- Beyene Lab (10) Apply Beyene Lab filter
- Bock Lab (17) Apply Bock Lab filter
- Branson Lab (48) Apply Branson Lab filter
- Card Lab (40) Apply Card Lab filter
- Cardona Lab (63) Apply Cardona Lab filter
- Chklovskii Lab (13) Apply Chklovskii Lab filter
- Clapham Lab (13) Apply Clapham Lab filter
- Cui Lab (19) Apply Cui Lab filter
- Darshan Lab (12) Apply Darshan Lab filter
- Dennis Lab (1) Apply Dennis Lab filter
- Dickson Lab (46) Apply Dickson Lab filter
- Druckmann Lab (25) Apply Druckmann Lab filter
- Dudman Lab (46) Apply Dudman Lab filter
- Eddy/Rivas Lab (30) Apply Eddy/Rivas Lab filter
- Egnor Lab (11) Apply Egnor Lab filter
- Espinosa Medina Lab (16) Apply Espinosa Medina Lab filter
- Feliciano Lab (6) Apply Feliciano Lab filter
- Fetter Lab (41) Apply Fetter Lab filter
- Fitzgerald Lab (28) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (35) Apply Funke Lab filter
- Gonen Lab (91) Apply Gonen Lab filter
- Grigorieff Lab (62) Apply Grigorieff Lab filter
- Harris Lab (58) Apply Harris Lab filter
- Heberlein Lab (94) Apply Heberlein Lab filter
- Hermundstad Lab (22) Apply Hermundstad Lab filter
- Hess Lab (72) Apply Hess Lab filter
- Ilanges Lab (1) Apply Ilanges Lab filter
- Jayaraman Lab (44) Apply Jayaraman Lab filter
- Ji Lab (33) Apply Ji Lab filter
- Johnson Lab (6) Apply Johnson Lab filter
- Kainmueller Lab (19) Apply Kainmueller Lab filter
- Karpova Lab (14) Apply Karpova Lab filter
- Keleman Lab (13) Apply Keleman Lab filter
- Keller Lab (75) Apply Keller Lab filter
- Koay Lab (17) Apply Koay Lab filter
- Lavis Lab (138) Apply Lavis Lab filter
- Lee (Albert) Lab (34) Apply Lee (Albert) Lab filter
- Leonardo Lab (23) Apply Leonardo Lab filter
- Li Lab (27) Apply Li Lab filter
- Lippincott-Schwartz Lab (161) Apply Lippincott-Schwartz Lab filter
- Liu (Yin) Lab (5) Apply Liu (Yin) Lab filter
- Liu (Zhe) Lab (61) Apply Liu (Zhe) Lab filter
- Looger Lab (137) Apply Looger Lab filter
- Magee Lab (49) Apply Magee Lab filter
- Menon Lab (18) Apply Menon Lab filter
- Murphy Lab (13) Apply Murphy Lab filter
- O'Shea Lab (6) Apply O'Shea Lab filter
- Otopalik Lab (13) Apply Otopalik Lab filter
- Pachitariu Lab (42) Apply Pachitariu Lab filter
- Pastalkova Lab (18) Apply Pastalkova Lab filter
- Pavlopoulos Lab (19) Apply Pavlopoulos Lab filter
- Pedram Lab (14) Apply Pedram Lab filter
- Podgorski Lab (16) Apply Podgorski Lab filter
- Reiser Lab (49) Apply Reiser Lab filter
- Riddiford Lab (44) Apply Riddiford Lab filter
- Romani Lab (41) Apply Romani Lab filter
- Rubin Lab (139) Apply Rubin Lab filter
- Saalfeld Lab (61) Apply Saalfeld Lab filter
- Satou Lab (16) Apply Satou Lab filter
- Scheffer Lab (36) Apply Scheffer Lab filter
- Schreiter Lab (62) Apply Schreiter Lab filter
- Sgro Lab (20) Apply Sgro Lab filter
- Shroff Lab (24) Apply Shroff Lab filter
- Simpson Lab (23) Apply Simpson Lab filter
- Singer Lab (80) Apply Singer Lab filter
- Spruston Lab (91) Apply Spruston Lab filter
- Stern Lab (152) Apply Stern Lab filter
- Sternson Lab (54) Apply Sternson Lab filter
- Stringer Lab (29) Apply Stringer Lab filter
- Svoboda Lab (135) Apply Svoboda Lab filter
- Tebo Lab (31) Apply Tebo Lab filter
- Tervo Lab (9) Apply Tervo Lab filter
- Tillberg Lab (17) Apply Tillberg Lab filter
- Tjian Lab (64) Apply Tjian Lab filter
- Truman Lab (88) Apply Truman Lab filter
- Turaga Lab (46) Apply Turaga Lab filter
- Turner Lab (35) Apply Turner Lab filter
- Vale Lab (6) Apply Vale Lab filter
- Voigts Lab (2) Apply Voigts Lab filter
- Wang (Meng) Lab (10) Apply Wang (Meng) Lab filter
- Wang (Shaohe) Lab (24) Apply Wang (Shaohe) Lab filter
- Wu Lab (9) Apply Wu Lab filter
- Zlatic Lab (28) Apply Zlatic Lab filter
- Zuker Lab (25) Apply Zuker Lab filter
Associated Project Team
- CellMap (6) Apply CellMap filter
- COSEM (3) Apply COSEM filter
- Fly Descending Interneuron (10) Apply Fly Descending Interneuron filter
- Fly Functional Connectome (14) Apply Fly Functional Connectome filter
- Fly Olympiad (5) Apply Fly Olympiad filter
- FlyEM (51) Apply FlyEM filter
- FlyLight (46) Apply FlyLight filter
- GENIE (40) Apply GENIE filter
- Integrative Imaging (1) Apply Integrative Imaging filter
- Larval Olympiad (2) Apply Larval Olympiad filter
- MouseLight (16) Apply MouseLight filter
- NeuroSeq (1) Apply NeuroSeq filter
- ThalamoSeq (1) Apply ThalamoSeq filter
- Tool Translation Team (T3) (24) Apply Tool Translation Team (T3) filter
- Transcription Imaging (49) Apply Transcription Imaging filter
Publication Date
- 2024 (170) Apply 2024 filter
- 2023 (171) Apply 2023 filter
- 2022 (192) Apply 2022 filter
- 2021 (193) Apply 2021 filter
- 2020 (196) Apply 2020 filter
- 2019 (202) Apply 2019 filter
- 2018 (232) Apply 2018 filter
- 2017 (217) Apply 2017 filter
- 2016 (209) Apply 2016 filter
- 2015 (252) Apply 2015 filter
- 2014 (236) Apply 2014 filter
- 2013 (194) Apply 2013 filter
- 2012 (190) Apply 2012 filter
- 2011 (190) Apply 2011 filter
- 2010 (161) Apply 2010 filter
- 2009 (158) Apply 2009 filter
- 2008 (140) Apply 2008 filter
- 2007 (106) Apply 2007 filter
- 2006 (92) Apply 2006 filter
- 2005 (67) Apply 2005 filter
- 2004 (57) Apply 2004 filter
- 2003 (58) Apply 2003 filter
- 2002 (39) Apply 2002 filter
- 2001 (28) Apply 2001 filter
- 2000 (29) Apply 2000 filter
- 1999 (14) Apply 1999 filter
- 1998 (18) Apply 1998 filter
- 1997 (16) Apply 1997 filter
- 1996 (10) Apply 1996 filter
- 1995 (18) Apply 1995 filter
- 1994 (12) Apply 1994 filter
- 1993 (10) Apply 1993 filter
- 1992 (6) Apply 1992 filter
- 1991 (11) Apply 1991 filter
- 1990 (11) Apply 1990 filter
- 1989 (6) Apply 1989 filter
- 1988 (1) Apply 1988 filter
- 1987 (7) Apply 1987 filter
- 1986 (4) Apply 1986 filter
- 1985 (5) Apply 1985 filter
- 1984 (2) Apply 1984 filter
- 1983 (2) Apply 1983 filter
- 1982 (3) Apply 1982 filter
- 1981 (3) Apply 1981 filter
- 1980 (1) Apply 1980 filter
- 1979 (1) Apply 1979 filter
- 1976 (2) Apply 1976 filter
- 1973 (1) Apply 1973 filter
- 1970 (1) Apply 1970 filter
- 1967 (1) Apply 1967 filter
Type of Publication
3945 Publications
Showing 351-360 of 3945 resultsAnimals strategically scan the environment to form an accurate perception of their surroundings. Here we investigated the neuronal representations that mediate this behavior. Ca imaging and selective optogenetic manipulation during an active sensing task reveals that layer 5 pyramidal neurons in the vibrissae cortex produce a diverse and distributed representation that is required for mice to adapt their whisking motor strategy to changing sensory cues. The optogenetic perturbation degraded single-neuron selectivity and network population encoding through a selective inhibition of active dendritic integration. Together the data indicate that active dendritic integration in pyramidal neurons produces a nonlinearly mixed network representation of joint sensorimotor parameters that is used to transform sensory information into motor commands during adaptive behavior. The prevalence of the layer 5 cortical circuit motif suggests that this is a general circuit computation.
UNLABELLED: Neurons respond to specific features of sensory stimuli. In the visual system, for example, some neurons respond to motion of small but not large objects, whereas other neurons prefer motion of the entire visual field. Separate neurons respond equally to local and global motion but selectively to additional features of visual stimuli. How and where does response selectivity emerge? Here, we show that wide-field (WF) cells in retino-recipient layers of the mouse superior colliculus (SC) respond selectively to small moving objects. Moreover, we identify two mechanisms that contribute to this selectivity. First, we show that input restricted to a small portion of the broad dendritic arbor of WF cells is sufficient to trigger dendritic spikes that reliably propagate to the soma/axon. In vivo whole-cell recordings reveal that nearly every action potential evoked by visual stimuli has characteristics of spikes initiated in dendrites. Second, inhibitory input from a different class of SC neuron, horizontal cells, constrains the range of stimuli to which WF cells respond. Horizontal cells respond preferentially to the sudden appearance or rapid movement of large stimuli. Optogenetic reduction of their activity reduces movement selectivity and broadens size tuning in WF cells by increasing the relative strength of responses to stimuli that appear suddenly or cover a large region of space. Therefore, strongly propagating dendritic spikes enable small stimuli to drive spike output in WF cells and local inhibition helps restrict responses to stimuli that are both small and moving. SIGNIFICANCE STATEMENT: How do neurons respond selectively to some sensory stimuli but not others? In the visual system, a particularly relevant stimulus feature is object motion, which often reveals other animals. Here, we show how specific cells in the superior colliculus, one synapse downstream of the retina, respond selectively to object motion. These wide-field (WF) cells respond strongly to small objects that move slowly anywhere through a large region of space, but not to stationary objects or full-field motion. Action potential initiation in dendrites enables small stimuli to trigger visual responses and inhibitory input from cells that prefer large, suddenly appearing, or quickly moving stimuli restricts responses of WF cells to objects that are small and moving.
In this work we present a novel technique we term active graph matching, which integrates the popular active shape model into a sparse graph matching problem. This way we are able to combine the benefits of a global, statistical deformation model with the benefits of a local deformation model in form of a second-order random field. We present a new iterative energy minimization technique which achieves empirically good results. This enables us to exceed state-of-the art results for the task of annotating nuclei in 3D microscopic images of C. elegans. Furthermore with the help of the generalized Hough transform we are able to jointly segment and annotate a large set of nuclei in a fully automatic fashion for the first time.
For the analysis of neuronal networks it is an important yet unresolved task to relate the neurons’ activities to their morphology. Here we introduce activity correlation imaging to simultaneously visualize the activity and morphology of populations of neurons. To this end we first stain the network’s neurons using a membrane-permeable [Ca(2+)] indicator (e.g., Fluo-4/AM) and record their activities. We then exploit the recorded temporal activity patterns as a means of intrinsic contrast to visualize individual neurons’ dendritic morphology. The result is a high-contrast, multicolor visualization of the neuronal network. Taking the Xenopus olfactory bulb as an example we show the activities of the mitral/tufted cells of the olfactory bulb as well as their projections into the olfactory glomeruli. This method, yielding both functional and structural information of neuronal populations, will open up unprecedented possibilities for the investigation of neuronal networks.
The CA3 and CA1 pyramidal neurons are the major principal cell types of the hippocampus proper. The strongly recurrent collateral system of CA3 cells and the largely parallel-organized CA1 neurons suggest that these regions perform distinct computations. However, a comprehensive comparison between CA1 and CA3 pyramidal cells in terms of firing properties, network dynamics, and behavioral correlations is sparse in the intact animal. We performed large-scale recordings in the dorsal hippocampus of rats to quantify the similarities and differences between CA1 (n > 3,600) and CA3 (n > 2,200) pyramidal cells during sleep and exploration in multiple environments. CA1 and CA3 neurons differed significantly in firing rates, spike burst propensity, spike entrainment by the theta rhythm, and other aspects of spiking dynamics in a brain state-dependent manner. A smaller proportion of CA3 than CA1 cells displayed prominent place fields, but place fields of CA3 neurons were more compact, more stable, and carried more spatial information per spike than those of CA1 pyramidal cells. Several other features of the two cell types were specific to the testing environment. CA3 neurons showed less pronounced phase precession and a weaker position versus spike-phase relationship than CA1 cells. Our findings suggest that these distinct activity dynamics of CA1 and CA3 pyramidal cells support their distinct computational roles.
Cortical-feedback projections to primary sensory areas terminate most heavily in layer 1 (L1) of the neocortex, where they make synapses with tuft dendrites of pyramidal neurons. L1 input is thought to provide ‘contextual’ information, but the signals transmitted by L1 feedback remain uncharacterized. In the rodent somatosensory system, the spatially diffuse feedback projection from vibrissal motor cortex (vM1) to vibrissal somatosensory cortex (vS1, also known as the barrel cortex) may allow whisker touch to be interpreted in the context of whisker position to compute object location. When mice palpate objects with their whiskers to localize object features, whisker touch excites vS1 and later vM1 in a somatotopic manner. Here we use axonal calcium imaging to track activity in vM1–>vS1 afferents in L1 of the barrel cortex while mice performed whisker-dependent object localization. Spatially intermingled individual axons represent whisker movements, touch and other behavioural features. In a subpopulation of axons, activity depends on object location and persists for seconds after touch. Neurons in the barrel cortex thus have information to integrate movements and touches of multiple whiskers over time, key components of object identification and navigation by active touch.
The temporal and spatial profile of activity-evoked changes in membrane potential and intracellular calcium concentration in the dendrites of hippocampal CA1 pyramidal neurons was examined with simultaneous somatic and dendritic patch-pipette recording and calcium imaging experiments. Action potentials are initiated close to the soma of these neurons and backpropagate into the dendrites in an activity-dependent manner; those occurring early in a train propagate actively, whereas those occurring later fail to actively invade the distal dendrites. Consistent with this finding, dendritic calcium transients evoked by single action potentials do not significantly attenuate with distance from the soma, whereas those evoked by trains attenuate substantially. Failure of action potential propagation into the distal dendrites often occurs at branch points. Consequently, neighboring regions of the dendritic tree can experience different voltage and calcium signals during repetitive action potential firing. The influence of backpropagating action potentials on synaptic integration and plasticity will therefore depend on both the extent of dendritic branching and the pattern of neuronal activity.
Activity-driven changes in the neuronal surface glycoproteome are known to occur with synapse formation, plasticity and related diseases, but their mechanistic basis and significance are unclear. Here, we observed that N-glycans on surface glycoproteins of dendrites shift from immature to mature forms containing sialic acid in response to increased neuronal excitation. In exploring the basis of these N-glycosylation alterations, we discovered they result from the growth and proliferation of Golgi satellites scattered throughout the dendrite. Golgi satellites that formed with neuronal excitation were in close association with ER exit sites and early endosomes and contained glycosylation machinery without the Golgi structural protein, GM130. They functioned as distal glycosylation stations in dendrites, terminally modifying sugars either on newly synthesized glycoproteins passing through the secretory pathway, or on surface glycoproteins taken up from the endocytic pathway. These activities led to major changes in the dendritic surface of excited neurons, impacting binding and uptake of lectins, as well as causing functional changes in neurotransmitter receptors such as nicotinic acetylcholine receptors. Neural activity thus boosts the activity of the dendrite’s satellite micro-secretory system by redistributing Golgi enzymes involved in glycan modifications into peripheral Golgi satellites. This remodeling of the neuronal surface has potential significance for synaptic plasticity, addiction and disease.Competing Interest StatementThe authors have declared no competing interest.
Activity-driven changes in the neuronal surface glycoproteome are known to occur with synapse formation, plasticity and related diseases, but their mechanistic basis and significance are unclear. Here, we observed that -glycans on surface glycoproteins of dendrites shift from immature to mature forms containing sialic acid in response to increased neuronal activation. In exploring the basis of these -glycosylation alterations, we discovered they result from the growth and proliferation of Golgi satellites scattered throughout the dendrite. Golgi satellites that formed during neuronal excitation were in close association with ER exit sites and early endosomes and contained glycosylation machinery without the Golgi structural protein, GM130. They functioned as distal glycosylation stations in dendrites, terminally modifying sugars either on newly synthesized glycoproteins passing through the secretory pathway, or on surface glycoproteins taken up from the endocytic pathway. These activities led to major changes in the dendritic surface of excited neurons, impacting binding and uptake of lectins, as well as causing functional changes in neurotransmitter receptors such as nicotinic acetylcholine receptors. Neural activity thus boosts the activity of the dendrite's satellite micro-secretory system by redistributing Golgi enzymes involved in glycan modifications into peripheral Golgi satellites. This remodeling of the neuronal surface has potential significance for synaptic plasticity, addiction and disease.
Sepsis is a serious medical condition in which immune dysfunction plays a key role. Previous treatments focused on chemotherapy to control immune function; however, a recognized effective compound or treatment has yet to be developed. Recent advances indicate that a neuromodulation approach with nerve stimulation allows developing a therapeutic strategy to control inflammation and improve organ functions in sepsis. As a quick, non-invasive technique of peripheral nerve stimulation, acupuncture has emerged as a promising therapy to provide significant advantages for immunomodulation in acute inflammation. Acupuncture obtains its regulatory effect by activating the somatic-autonomic-immune reflexes, including the somatic-sympathetic-splenic reflex, the somatic-sympathetic-adrenal reflex, the somatic-vagal-splenic reflex and the somatic-vagal-adrenal reflex, which produces a systemic effect. The peripheral nerve stimulation also induces local reflexes such as the somatic-sympathetic-lung-reflex, which then produces local effects. These mechanisms offer scientific guidance to design acupuncture protocols for immunomodulation and inflammation control, leading to an evidence-based comprehensive therapy recommendation.