scholarly journals Functional divisions for visual processing in the central brain of flying Drosophila

2015 ◽  
Vol 112 (40) ◽  
pp. E5523-E5532 ◽  
Author(s):  
Peter T. Weir ◽  
Michael H. Dickinson
Keyword(s):  
Visual Processing ◽  
Visual Stimuli ◽  
Automated Analysis ◽  
Fruit Fly ◽  
Cell Types ◽  
Visual Responses ◽  
Behavioral Context ◽  
Central Brain ◽  
Brain Circuit ◽  
The Brain

Although anatomy is often the first step in assigning functions to neural structures, it is not always clear whether architecturally distinct regions of the brain correspond to operational units. Whereas neuroarchitecture remains relatively static, functional connectivity may change almost instantaneously according to behavioral context. We imaged panneuronal responses to visual stimuli in a highly conserved central brain region in the fruit fly, Drosophila, during flight. In one substructure, the fan-shaped body, automated analysis revealed three layers that were unresponsive in quiescent flies but became responsive to visual stimuli when the animal was flying. The responses of these regions to a broad suite of visual stimuli suggest that they are involved in the regulation of flight heading. To identify the cell types that underlie these responses, we imaged activity in sets of genetically defined neurons with arborizations in the targeted layers. The responses of this collection during flight also segregated into three sets, confirming the existence of three layers, and they collectively accounted for the panneuronal activity. Our results provide an atlas of flight-gated visual responses in a central brain circuit.

scholarly journals A Connectome of the Adult Drosophila Central Brain

2020 ◽  
Author(s):  
C. Shan Xu ◽  
Michal Januszewski ◽  
Zhiyuan Lu ◽  
Shin-ya Takemura ◽  
Kenneth J. Hayworth ◽  
...  
Keyword(s):  
Large Fraction ◽  
Large Data ◽  
Fruit Fly ◽  
Cell Types ◽  
Brain Regions ◽  
Central Complex ◽  
Data Set ◽  
New Methods ◽  
Central Brain ◽  
The Brain

AbstractThe neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions.Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

scholarly journals Specific excitatory connectivity for feature integration in mouse primary visual cortex

2016 ◽  
Author(s):  
Dylan R Muir ◽  
Patricia Molina-Luna ◽  
Morgane M Roth ◽  
Fritjof Helmchen ◽  
Björn M Kampa
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Processing ◽  
Visual Stimuli ◽  
Visual Representations ◽  
Feature Binding ◽  
Local Network ◽  
Visual Responses ◽  
Visual Properties ◽  
The Brain

AbstractLocal excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a ‘like-to-like’ scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a ‘feature binding’ scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by a assuming ‘feature binding’ connectivity. Unlike under the ‘like-to-like’ scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1.Author summaryThe brain is a highly complex structure, with abundant connectivity between nearby neurons in the neocortex, the outermost and evolutionarily most recent part of the brain. Although the network architecture of the neocortex can appear disordered, connections between neurons seem to follow certain rules. These rules most likely determine how information flows through the neural circuits of the brain, but the relationship between particular connectivity rules and the function of the cortical network is not known. We built models of visual cortex in the mouse, assuming distinct rules for connectivity, and examined how the various rules changed the way the models responded to visual stimuli. We also recorded responses to visual stimuli of populations of neurons in anaesthetised mice, and compared these responses with our model predictions. We found that connections in neocortex probably follow a connectivity rule that groups together neurons that differ in simple visual properties, to build more complex representations of visual stimuli. This finding is surprising because primary visual cortex is assumed to support mainly simple visual representations. We show that including specific rules for non-random connectivity in cortical models, and precisely measuring those rules in cortical tissue, is essential to understanding how information is processed by the brain.

Three-Dimensional Time-Lapse Digital Movie Analysis of the Developing Fruit Fly Eye in Organ Culture

1997 ◽  
Vol 3 (S2) ◽  
pp. 1129-1130
Author(s):  
John Archie Pollock ◽  
Bejon T. Maneckshana ◽  
Teresa E. Leonardo
Keyword(s):  
Organ Culture ◽  
Compound Eye ◽  
Eye Development ◽  
Larval Instar ◽  
Three Dimensional ◽  
Fruit Fly ◽  
Time Lapse ◽  
Cell Types ◽  
Specific Cell ◽  
The Brain

The compound eye of the fruit fly, Drosophila melanogaster, is composed of a highly ordered array of facets (FIG. 1), each containing a precise set of neurons and supporting cells. The eye arises during the third larval instar from an undifferentiated epithelium, the eye imaginai disc, which is connected to the brain via the optic stalk (FIG. 2). During eye development, movement of the morphogenetic furrow, progressive recruitment of specific cell types and the growth of photoreceptor axons into the brain are each dynamic processes that are routinely studied indirectly in fixed tissues. While stereotyped development and the ‘crystalline’ like structure of the eye facilitates this analysis, certain experiments are hindered by the inability to observe developmental processes as they occur. To overcome this limitation, we have combined organ culture with advanced microscopy tools to enable the observation of eye development in living tissue.

scholarly journals Single circuit in V1 capable of switching contexts during movement using VIP population as a switch

2020 ◽  
Author(s):  
Doris Voina ◽  
Stefano Recanatesi ◽  
Brian Hu ◽  
Eric Shea-Brown ◽  
Stefan Mihalas
Keyword(s):  
Visual System ◽  
Visual Processing ◽  
Visual Space ◽  
Cell Types ◽  
Flexible Architecture ◽  
Multiple Cell ◽  
Context Dependent ◽  
Spatio Temporal ◽  
Context Integration ◽  
The Brain

AbstractAs animals adapt to their environments, their brains are tasked with processing stimuli in different sensory contexts. Whether these computations are context dependent or independent, they are all implemented in the same neural tissue. A crucial question is what neural architectures can respond flexibly to a range of stimulus conditions and switch between them. This is a particular case of flexible architecture that permits multiple related computations within a single circuit.Here, we address this question in the specific case of the visual system circuitry, focusing on context integration, defined as the integration of feedforward and surround information across visual space. We show that a biologically inspired microcircuit with multiple inhibitory cell types can switch between visual processing of the static context and the moving context. In our model, the VIP population acts as the switch and modulates the visual circuit through a disinhibitory motif. Moreover, the VIP population is efficient, requiring only a relatively small number of neurons to switch contexts. This circuit eliminates noise in videos by using appropriate lateral connections for contextual spatio-temporal surround modulation, having superior denoising performance compared to circuits where only one context is learned. Our findings shed light on a minimally complex architecture that is capable of switching between two naturalistic contexts using few switching units.Author SummaryThe brain processes information at all times and much of that information is context-dependent. The visual system presents an important example: processing is ongoing, but the context changes dramatically when an animal is still vs. running. How is context-dependent information processing achieved? We take inspiration from recent neurophysiology studies on the role of distinct cell types in primary visual cortex (V1).We find that relatively few “switching units” — akin to the VIP neuron type in V1 in that they turn on and off in the running vs. still context and have connections to and from the main population — is sufficient to drive context dependent image processing. We demonstrate this in a model of feature integration, and in a test of image denoising. The underlying circuit architecture illustrates a concrete computational role for the multiple cell types under increasing study across the brain, and may inspire more flexible neurally inspired computing architectures.

scholarly journals Effect of Brightness of Visual Stimuli on EEG Signals

2019 ◽  
Author(s):  
Kübra Eroğlu ◽  
Temel Kayıkçıoğlu ◽  
Onur Osman
Keyword(s):  
Visual Processing ◽  
Time Window ◽  
Time Windows ◽  
Visual Stimuli ◽  
Average Power ◽  
Power Spectra ◽  
Brain Regions ◽  
Behavioral Data ◽  
Brain Responses ◽  
The Brain

The aim of this study was to examine brightness effect, which is the perceptual property of visual stimuli, on brain responses obtained during visual processing of these stimuli. For this purpose, brain responses of the brain to changes in brightness were explored comparatively using different emotional images (pleasant, unpleasant and neutral) with different luminance levels. Moreover, electroencephalography recordings from 12 different electrode sites of 31 healthy participants were used. The power spectra obtained from the analysis of the recordings using short time Fourier transform were analyzed, and a statistical analysis was performed on features extracted from these power spectra. Statistical findings obtained from electrophysiological data were compared with those obtained from behavioral data. The results showed that the brightness of visual stimuli affected the power of brain responses depending on frequency, time and location. According to the statistically verified findings, the distinctive effect of brightness occurred in the parietal and occipital regions for all the three types of stimuli. Accordingly, the increase in the brightness of pleasant and neutral images increased the average power of responses in the parietal and occipital regions whereas the increase in the brightness of unpleasant images decreased the average power of responses in these regions. However, the increase in brightness for all the three types of stimuli reduced the average power of frontal and central region responses (except for 100-300 ms time window for unpleasant stimuli). The statistical results obtained for unpleasant images were found to be in accordance with the behavioral data. The results also revealed that the brightness of visual stimuli could be represented by changing the activity power of the brain cortex. The main contribution of this research was to comprehensively examine brightness effect on brain activity for images with different emotional content and different frequency bands at different time windows of visual processing for different brain regions. The findings emphasized that the brightness of visual stimuli should be viewed as an important parameter in studies using emotional image techniques such as image classification, emotion evaluation and neuro-marketing.

scholarly journals Microstimulation in the primary visual cortex: activity patterns and their relation to visual responses and evoked saccades

2020 ◽  
Author(s):  
R. Oz ◽  
H. Edelman-Klapper ◽  
S. Nivinsky-Margalit ◽  
H. Slovin
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Neural Activity ◽  
Visual Processing ◽  
Visual Stimuli ◽  
Temporal Patterns ◽  
Visual Responses ◽  
Population Activity ◽  
Spatio Temporal ◽  
Saccade Generation

AbstractIntra cortical microstimulation (ICMS) in the primary visual cortex (V1) can generate the visual perception of phosphenes and evoke saccades directed to the stimulated location in the retinotopic map. Although ICMS is widely used, little is known about the evoked spatio-temporal patterns of neural activity and their relation to neural responses evoked by visual stimuli or saccade generation. To investigate this, we combined ICMS with Voltage Sensitive Dye Imaging in V1 of behaving monkeys and measured neural activity at high spatial (meso-scale) and temporal resolution. Small visual stimuli and ICMS evoked population activity spreading over few mm that propagated to extrastriate areas. The population responses evoked by ICMS showed faster dynamics and different spatial propagation patterns. Neural activity was higher in trials w/saccades compared with trials w/o saccades. In conclusion, our results uncover the spatio-temporal patterns evoked by ICMS and their relation to visual processing and saccade generation.

scholarly journals Brain state-dependent modulation of thalamic visual processing by cortico-thalamic feedback

2021 ◽  
Author(s):  
Kimberly Reinhold ◽  
Arbora Resulaj ◽  
Massimo Scanziani
Keyword(s):  
Visual Stimulus ◽  
Visual Processing ◽  
Visual Information ◽  
Early Stage ◽  
Visual Stimuli ◽  
Brain State ◽  
Spatial Features ◽  
State Dependent ◽  
Temporal And Spatial ◽  
The Brain

The behavioral state of a mammal impacts how the brain responds to visual stimuli as early as in the dorsolateral geniculate nucleus of the thalamus (dLGN), the primary relay of visual information to the cortex. A clear example of this is the markedly stronger response of dLGN neurons to higher temporal frequencies of the visual stimulus in alert as compared to quiescent animals. The dLGN receives strong feedback from the visual cortex, yet whether this feedback contributes to these state-dependent responses to visual stimuli is poorly understood. Here we show that in mice, silencing cortico-thalamic feedback abolishes state-dependent differences in the response of dLGN neurons to visual stimuli. This holds true for dLGN responses to both temporal and spatial features of the visual stimulus. These results reveal that the state-dependent shift of the response to visual stimuli in an early stage of visual processing depends on cortico-thalamic feedback.

scholarly journals A Connectome and Analysis of the Adult Drosophila Central Brain

2020 ◽  
Author(s):  
Louis K. Scheffer ◽  
C. Shan Xu ◽  
Michal Januszewski ◽  
Zhiyuan Lu ◽  
Shin-ya Takemura ◽  
...  
Keyword(s):  
Large Fraction ◽  
Large Data ◽  
Fruit Fly ◽  
Cell Types ◽  
Large Data Sets ◽  
Data Sets ◽  
Central Brain ◽  
Chemical Synapses ◽  
New Procedures ◽  
Improved Methods

AbstractThe neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain.

Effects of brain stem parabrachial activation on receptive field properties of cells in the cat's lateral geniculate nucleus

1995 ◽  
Vol 73 (6) ◽  
pp. 2428-2447 ◽  
Author(s):  
D. J. Uhlrich ◽  
N. Tamamaki ◽  
P. C. Murphy ◽  
S. M. Sherman
Keyword(s):  
Receptive Field ◽  
Brain Stem ◽  
Spontaneous Activity ◽  
Lateral Geniculate Nucleus ◽  
Visual Stimuli ◽  
Visual Responses ◽  
Burst Stimulation ◽  
Lateral Geniculate ◽  
Almost All ◽  
The Brain

1. The lateral geniculate nucleus is the primary thalamic relay for the transfer of retinal signals to the visual cortex. Geniculate cells are heavily innervated from nonretinal sources, and these modify retinogeniculate transmission. A major ascending projection to the lateral geniculate nucleus arises from cholinergic cells in the parabrachial region of the brain stem. This is an important pathway in the ascending control of arousal. In an in vivo preparation, we used extracellular recordings to study the effects of electrical activation of the parabrachial region on the spontaneous activity and visual responses of X and Y cells in the lateral geniculate nucleus of the cat. 2. We studied the effects of two patterns of parabrachial activation on the spontaneous activity of geniculate cells. Burst stimulation consisted of a short pulse at high frequency (16 ms at 250 Hz). Train stimulation was of longer duration at lower frequency (e.g., 1 s at 50 Hz). The firing rate of almost all geniculate cells was enhanced by either pattern of stimulation. However, the burst pattern of stimulation elicited a short, modulated response with excitatory and inhibitory epochs. We found that the different epochs could differentially modulate the visual responses to drifting gratings. Thus the temporal alignment of the brain stem and visual stimuli was critical with burst stimulation, and varied alignments could dramatically confound the results. In comparison, the train pattern of stimulation consistently produced a relatively flat plateau of increased firing, after a short initial period of more variable effects. We used the less confounding pattern of train stimuli to study the effects of parabrachial activation on visual responses. 3. Our main emphasis was to examine the parabrachial effects on the visual responses of geniculate cells. For most visual stimuli, we used drifting sine wave gratings that varied in spatial frequency; these evoked modulated responses from the geniculate cells. Parabrachial activation enhanced the visual responses of almost all geniculate cells, and this enhancement included both increased depth of modulation and greater response rates. 4. Our results were incorporated quantitatively into a difference-of-Gaussians model of visual receptive fields in order to study the parabrachial effects on the spatial structure of the receptive field. This model fit our data well and provided measures of the response amplitude and radius of the receptive field center (Kc and Rc, respectively) and the response amplitude and radius of the receptive field surround (Ks and Rs, respectively).(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Autism sensory dysfunction in an evolutionarily conserved system

2018 ◽  
Vol 285 (1893) ◽  
pp. 20182255 ◽  
Author(s):  
Greta Vilidaite ◽  
Anthony M. Norcia ◽  
Ryan J. H. West ◽  
Christopher J. H. Elliott ◽  
Francesca Pei ◽  
...  
Keyword(s):  
Visual Processing ◽  
Autistic Traits ◽  
Fruit Fly ◽  
Functional Domain ◽  
Visual Response ◽  
Visual Responses ◽  
Development Trajectory ◽  
Human Participants ◽  
Cognitive Behaviours ◽  
Adults With Asd

There is increasing evidence for a strong genetic basis for autism, with many genetic models being developed in an attempt to replicate autistic symptoms in animals. However, current animal behaviour paradigms rarely match the social and cognitive behaviours exhibited by autistic individuals. Here, we instead assay another functional domain—sensory processing—known to be affected in autism to test a novel genetic autism model in Drosophila melanogaster . We show similar visual response alterations and a similar development trajectory in Nhe3 mutant flies (total n = 72) and in autistic human participants (total n = 154). We report a dissociation between first- and second-order electrophysiological visual responses to steady-state stimulation in adult mutant fruit flies that is strikingly similar to the response pattern in human adults with ASD as well as that of a large sample of neurotypical individuals with high numbers of autistic traits. We explain this as a genetically driven, selective signalling alteration in transient visual dynamics. In contrast to adults, autistic children show a decrease in the first-order response that is matched by the fruit fly model, suggesting that a compensatory change in processing occurs during development. Our results provide the first animal model of autism comprising a differential developmental phenotype in visual processing.

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