scholarly journals Projection-specific visual feature encoding by layer 5 cortical subnetworks

2015 ◽  
Author(s):  
Gyorgy Lur ◽  
Martin A. Vinck ◽  
Lan Tang ◽  
Jessica A. Cardin ◽  
Michael J. Higley
Keyword(s):  
Visual Information ◽  
Sensory Information ◽  
Projection Neurons ◽  
Visual Response ◽  
Subcortical Structures ◽  
Downstream Target ◽  
Afferent Information ◽  
Contrast Thresholds ◽  
Lower Contrast

SummaryPrimary neocortical sensory areas act as central hubs, distributing afferent information to numerous cortical and subcortical structures. However, it remains unclear whether each downstream target receives distinct versions of sensory information. We used in vivo calcium imaging combined with retrograde tracing to monitor visual response properties of three distinct subpopulations of projection neurons in primary visual cortex. While there is overlap across the groups, on average corticotectal (CT) cells exhibit lower contrast thresholds and broader tuning for orientation and spatial frequency in comparison to corticostriatal (CS) cells, while corticocortical (CC) cells have intermediate properties. Noise correlational analyses support the hypothesis that CT cells integrate information across diverse layer 5 populations, whereas CS and CC cells form more selectively interconnected groups. Overall, our findings demonstrate the existence of functional subnetworks within layer 5 that may differentially route visual information to behaviorally relevant downstream targets.

scholarly journals The anterior paired lateral neuron normalizes odour-evoked activity at the mushroom body calyx

2021 ◽  
Author(s):  
Luigi Prisco ◽  
Stephan Hubertus Deimel ◽  
Hanna Yeliseyeva ◽  
Andre Fiala ◽  
Gaia Tavosanis
Keyword(s):  
Mushroom Body ◽  
Activity Patterns ◽  
Sensory Information ◽  
Input Circuit ◽  
Projection Neurons ◽  
Neuronal Populations ◽  
Kenyon Cells ◽  
Presynaptic Boutons ◽  
Evoked Activity

To identify and memorize discrete but similar environmental inputs, the brain needs to distinguish between subtle differences of activity patterns in defined neuronal populations. The Kenyon cells of the Drosophila adult mushroom body (MB) respond sparsely to complex olfactory input, a property that is thought to support stimuli discrimination in the MB. To understand how this property emerges, we investigated the role of the inhibitory anterior paired lateral neuron (APL) in the input circuit of the MB, the calyx. Within the calyx, presynaptic boutons of projection neurons (PNs) form large synaptic microglomeruli (MGs) with dendrites of postsynaptic Kenyon cells (KCs). Combining EM data analysis and in vivo calcium imaging, we show that APL, via inhibitory and reciprocal synapses targeting both PN boutons and KC dendrites, normalizes odour-evoked representations in MGs of the calyx. APL response scales with the PN input strength and is regionalized around PN input distribution. Our data indicate that the formation of a sparse code by the Kenyon cells requires APL-driven normalization of their MG postsynaptic responses. This work provides experimental insights on how inhibition shapes sensory information representation in a higher brain centre, thereby supporting stimuli discrimination and allowing for efficient associative memory formation.

scholarly journals A projection specific logic to sampling visual inputs in mouse superior colliculus

2018 ◽  
Author(s):  
Katja Reinhard ◽  
Chen Li ◽  
Quan Do ◽  
Emily Burke ◽  
Steven Heynderickx ◽  
...  
Keyword(s):  
Superior Colliculus ◽  
Ganglion Cells ◽  
Ex Vivo ◽  
Sensory Information ◽  
Cell Types ◽  
Brain Regions ◽  
Visual Response ◽  
Retinal Ganglion ◽  
Parabigeminal Nucleus

AbstractUsing sensory information to trigger different behaviours relies on circuits that pass-through brain regions. However, the rules by which parallel inputs are routed to different downstream targets is poorly understood. The superior colliculus mediates a set of innate behaviours, receiving input from ~30 retinal ganglion cell types and projecting to behaviourally important targets including the pulvinar and parabigeminal nucleus. Combining transsynaptic circuit tracing with in-vivo and ex-vivo electrophysiological recordings we observed a projection specific logic where each collicular output pathway sampled a distinct set of retinal inputs. Neurons projecting to the pulvinar or parabigeminal nucleus uniquely sampled 4 and 7 cell types, respectively. Four others innervated both pathways. The visual response properties of retinal ganglion cells correlated well with those of their disynaptic targets. These findings suggest that projection specific sampling of retinal inputs forms a mechanistic basis for the selective triggering of visually guided behaviours by the superior colliculus.

scholarly journals The anterior paired lateral neuron normalizes odour-evoked activity in the Drosophila mushroom body calyx

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Luigi Prisco ◽  
Stephan Hubertus Deimel ◽  
Hanna Yeliseyeva ◽  
André Fiala ◽  
Gaia Tavosanis
Keyword(s):  
Mushroom Body ◽  
Activity Patterns ◽  
Sensory Information ◽  
Input Circuit ◽  
Projection Neurons ◽  
Neuronal Populations ◽  
Kenyon Cells ◽  
Presynaptic Boutons ◽  
Evoked Activity

To identify and memorize discrete but similar environmental inputs, the brain needs to distinguish between subtle differences of activity patterns in defined neuronal populations. The Kenyon cells of the Drosophila adult mushroom body (MB) respond sparsely to complex olfactory input, a property that is thought to support stimuli discrimination in the MB. To understand how this property emerges, we investigated the role of the inhibitory anterior paired lateral neuron (APL) in the input circuit of the MB, the calyx. Within the calyx, presynaptic boutons of projection neurons (PNs) form large synaptic microglomeruli (MGs) with dendrites of postsynaptic Kenyon cells (KCs). Combining EM data analysis and in vivo calcium imaging, we show that APL, via inhibitory and reciprocal synapses targeting both PN boutons and KC dendrites, normalizes odour-evoked representations in MGs of the calyx. APL response scales with the PN input strength and is regionalized around PN input distribution. Our data indicate that the formation of a sparse code by the Kenyon cells requires APL-driven normalization of their MG postsynaptic responses. This work provides experimental insights on how inhibition shapes sensory information representation in a higher brain centre, thereby supporting stimuli discrimination and allowing for efficient associative memory formation.

scholarly journals A projection specific logic to sampling visual inputs in mouse superior colliculus

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Katja Reinhard ◽  
Chen Li ◽  
Quan Do ◽  
Emily G Burke ◽  
Steven Heynderickx ◽  
...  
Keyword(s):  
Superior Colliculus ◽  
Ex Vivo ◽  
Sensory Information ◽  
Cell Types ◽  
Brain Regions ◽  
Biased Sampling ◽  
Visual Response ◽  
Retinal Ganglion ◽  
Parabigeminal Nucleus

Using sensory information to trigger different behaviors relies on circuits that pass through brain regions. The rules by which parallel inputs are routed to downstream targets are poorly understood. The superior colliculus mediates a set of innate behaviors, receiving input from >30 retinal ganglion cell types and projecting to behaviorally important targets including the pulvinar and parabigeminal nucleus. Combining transsynaptic circuit tracing with in vivo and ex vivo electrophysiological recordings, we observed a projection-specific logic where each collicular output pathway sampled a distinct set of retinal inputs. Neurons projecting to the pulvinar or the parabigeminal nucleus showed strongly biased sampling from four cell types each, while six others innervated both pathways. The visual response properties of retinal ganglion cells correlated well with those of their disynaptic targets. These findings open the possibility that projection-specific sampling of retinal inputs forms a basis for the selective triggering of behaviors by the superior colliculus.

The Control of Sequential Goal-Directed Movement: Learning to Use Feedback or Central Planning?

Motor Control ◽  
1998 ◽  
Vol 2 (1) ◽  
pp. 61-80 ◽  
Author(s):  
Digby Elliott ◽  
Kathryn L. Ricker ◽  
James Lyons
Keyword(s):  
Visual Information ◽  
The Other ◽  
Visual Response ◽  
Directed Movement ◽  
Kinematic Data ◽  
Movement Trajectories ◽  
Vision Condition ◽  
Afferent Information ◽  
Aiming Movement ◽  
Sequential Aiming

Fifteen participants practiced a two-target sequential aiming movement with either full vision of the movement environment, vision during flight, or vision while in contact with the first target. After 100 acquisition trials, participants performed a retention test in their own condition and then were transferred to each of the other two vision conditions. Both performance and kinematic data indicated that rather than becoming less dependent on visual information with practice, subjects learned to adjust their movement trajectories to use the visual information available in their particular vision condition. Although transfer to a degraded vision condition disrupted performance, when vision was augmented participants quickly adjusted their aiming trajectories to use the added information. The findings suggest that at least part of learning involves the development of rapid and efficient procedures for processing afferent information, including visual response-produced feedback.

scholarly journals Hierarchical Spatial Search Strategies in Drosophila

2020 ◽  
Author(s):  
Nicola Meda ◽  
Giulio M. Menti ◽  
Aram Megighian ◽  
Mauro A. Zordan
Keyword(s):  
Visual Information ◽  
Visual Cues ◽  
Brain Activity ◽  
Sensory System ◽  
Sensory Information ◽  
Fruit Flies ◽  
Neural Basis ◽  
Other Information ◽  
Local Search Strategy

ABSTRACTAnimals rely on multiple sensory information systems to make decisions. The integration of information stemming from these systems is believed to result in a precise behavioural output. To what degree a single sensory system may override the others is unknown. Evidence for a hierarchical use of different systems to guide navigation is lacking. We used Drosophila melanogaster to investigate whether, in order to relieve an unpleasant stimulation, fruit flies employed an idiothetically-based local search strategy before making use of visual information, or viceversa. Fruit flies appear to initially resort to idiothetic information and only later, if the first strategy proves unsuccessful to relieve the unpleasant stimulation, make use of other information, such as visual cues. By leveraging on this innate preference for a hierarchical use of one strategy over another, we believe that in vivo recordings of brain activity during the navigation of fruit flies could provide mechanistic insights into how simultaneous information from multiple sensory modalities is evaluated, integrated, and motor responses elicited, thus shedding new light on the neural basis of decision-making.

scholarly journals Ca2+-activated K+ channels reduce network excitability, improving adaptability and energetics for transmitting and perceiving sensory information

2018 ◽  
Author(s):  
Xiaofeng Li ◽  
Ahmad Abou Tayoun ◽  
Zhuoyi Song ◽  
An Dau ◽  
Diana Rien ◽  
...  
Keyword(s):  
Visual Information ◽  
Information Transfer ◽  
Ex Vivo ◽  
Adaptive Dynamics ◽  
Sensory Information ◽  
Fruit Fly ◽  
Bk Channel ◽  
Model Organisms ◽  
Novel Approach

AbstractCa2+-activated K+ channels (BK and SK) are ubiquitous in synaptic circuits, but their role in network adaptation and sensory perception remains largely unknown. Using electrophysiological and behavioral assays and biophysical modelling, we discover how visual information transfer in mutants lacking the BK channel (dSlo−), SK channel (dSK−) or both (dSK−;;dSlo−) is shaped in the female fruit fly (Drosophila melanogaster) R1-R6 photoreceptor-LMC circuits (R-LMC-R system) through synaptic feedforward-feedback interactions and reduced R1-R6 Shaker and Shab K+ conductances. This homeostatic compensation is specific for each mutant, leading to distinctive adaptive dynamics. We show how these dynamics inescapably increase the energy cost of information and promote the mutants’ distorted motion perception, determining the true price and limits of chronic homeostatic compensation in an in vivo genetic animal model. These results reveal why Ca2+-activated K+ channels reduce network excitability (energetics), improving neural adaptability for transmitting and perceiving sensory information.Significance statementIn this study, we directly link in vivo and ex vivo experiments with detailed stochastically operating biophysical models to extract new mechanistic knowledge of how Drosophila photoreceptor-interneuron-photoreceptor (R-LMC-R) circuitry homeostatically retains its information sampling and transmission capacity against chronic perturbations in its ion-channel composition, and what is the cost of this compensation and its impact on optomotor behavior. We anticipate that this novel approach will provide a useful template to other model organisms and computational neuroscience, in general, in dissecting fundamental mechanisms of homeostatic compensation and deepening our understanding of how biological neural networks work.

Aryl Hydrocarbon Receptor: Its Regulation and Roles in Transformation and Tumorigenesis

2019 ◽  
Vol 20 (6) ◽  
pp. 625-634 ◽  
Author(s):  
Xun Che ◽  
Wei Dai
Keyword(s):  
Target Gene ◽  
Tumor Development ◽  
Environmental Response ◽  
Carcinogenic Effect ◽  
Post Translational Modifications ◽  
Downstream Target ◽  
Aryl Hydrocarbon ◽  
Downstream Target Gene ◽  
Major Mediator

AhR is an environmental response gene that mediates cellular responses to a variety of xenobiotic compounds that frequently function as AhR ligands. Many AhR ligands are classified as carcinogens or pro-carcinogens. Thus, AhR itself acts as a major mediator of the carcinogenic effect of many xenobiotics in vivo. In this concise review, mechanisms by which AhR trans-activates downstream target gene expression, modulates immune responses, and mediates malignant transformation and tumor development are discussed. Moreover, activation of AhR by post-translational modifications and crosstalk with other transcription factors or signaling pathways are also summarized.

scholarly journals A deep convolutional visual encoding model of neuronal responses in the LGN

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly
Keyword(s):  
Firing Rate ◽  
Visual Information ◽  
Visual Stimulation ◽  
Neuronal Population ◽  
Neuronal Firing ◽  
Electrode Arrays ◽  
Deep Convolutional Neural Networks ◽  
Firing Rates ◽  
Spatiotemporal Representation

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

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