scholarly journals Decision letter: Direct neural pathways convey distinct visual information to Drosophila mushroom bodies

2016 ◽  
Keyword(s):  
Visual Information ◽  
Mushroom Bodies ◽  
Neural Pathways

scholarly journals Direct neural pathways convey distinct visual information to Drosophila mushroom bodies

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Katrin Vogt ◽  
Yoshinori Aso ◽  
Toshihide Hige ◽  
Stephan Knapek ◽  
Toshiharu Ichinose ◽  
...  
Keyword(s):  
Visual Information ◽  
Mushroom Body ◽  
Mushroom Bodies ◽  
Small Subset ◽  
Projection Neurons ◽  
Neural Pathways ◽  
Associative Memories ◽  
Visual Projection ◽  
Olfactory Input ◽  
Odor Representation

Previously, we demonstrated that visual and olfactory associative memories of Drosophila share mushroom body (MB) circuits (<xref ref-type="bibr" rid="bib46">Vogt et al., 2014</xref>). Unlike for odor representation, the MB circuit for visual information has not been characterized. Here, we show that a small subset of MB Kenyon cells (KCs) selectively responds to visual but not olfactory stimulation. The dendrites of these atypical KCs form a ventral accessory calyx (vAC), distinct from the main calyx that receives olfactory input. We identified two types of visual projection neurons (VPNs) directly connecting the optic lobes and the vAC. Strikingly, these VPNs are differentially required for visual memories of color and brightness. The segregation of visual and olfactory domains in the MB allows independent processing of distinct sensory memories and may be a conserved form of sensory representations among insects.

scholarly journals Author response: Direct neural pathways convey distinct visual information to Drosophila mushroom bodies

2016 ◽  
Author(s):  
Katrin Vogt ◽  
Yoshinori Aso ◽  
Toshihide Hige ◽  
Stephan Knapek ◽  
Toshiharu Ichinose ◽  
...  
Keyword(s):  
Visual Information ◽  
Author Response ◽  
Mushroom Bodies ◽  
Neural Pathways

Compensating time delays with neural predictions: are predictions sensory or motor?

2009 ◽  
Vol 367 (1891) ◽  
pp. 1063-1078 ◽  
Author(s):  
Romi Nijhawan ◽  
Si Wu
Keyword(s):  
Visual System ◽  
Visual Information ◽  
Moving Objects ◽  
Early Stage ◽  
Adaptive Behaviour ◽  
Neural Pathways ◽  
Neural Signals ◽  
Multiple Resources ◽  
Compensation Mechanisms ◽  
The Future

Neural delays are a general property of computations carried out by neural circuits. Delays are a natural consequence of temporal summation and coding used by the nervous system to integrate information from multiple resources. For adaptive behaviour, however, these delays must be compensated. In order to sense and interact with moving objects, for example, the visual system must predict the future position of the object to compensate for delays. In this paper, we address two critical questions concerning the implementation of the compensation mechanisms in the brain, namely, where does compensation occur and how is it realized. We present evidence showing that compensation can happen in both the motor and sensory systems, and that compensation using ‘diagonal neural pathways’ is a suitable strategy for implementing compensation in the visual system. In this strategy, neural signals in the early stage of information processing are sent to the future cortical positions that correspond to the distance the object will travel in the period of transmission delay. We propose a computational model to elucidate this using the retinal visual information pathway.

The brain of the honeybee Apis mellifera . I. The connections and spatial organization of the mushroom bodies

1982 ◽  
Vol 298 (1091) ◽  
pp. 309-354 ◽  
Keyword(s):  
Visual Information ◽  
Spatial Organization ◽  
Short Term Memory ◽  
Single Layer ◽  
Mushroom Bodies ◽  
After Effects ◽  
Kenyon Cells ◽  
The Individual ◽  
Polar Organization ◽  
The Brain

The mushroom bodies of the bee are paired neuropils in the dorsal part of the brain. Each is composed of the arborizations of over 17 x 10 4 small interneurons of similar architecture called Kenyon cells. Golgi staining demonstrates that these neurons can be divided into five groups distinguished on the basis of their dendritic specializations and geometry. The mushroom body neuropils each consist of a pair of cup-shaped structures, the calyces, connected by two short fused stalks, the pedunculus, to two lobes, the α- and β-lobes. Each calyx is formed from three concentric neuropil zones, the basal ring, the collar and the lip. The calyces are organized in a polar fashion; within the calyces each of the five categories of Kenyon cell has a distribution limited to particular polar contours. The dendritic volumes of neighbouring Kenyon cells arborizing within each individual contour are greatly overlapped. Fibres from groups of neighbouring cells within a calycal contour are gathered into bundles that project into the pedunculus, each fibre dividing to enter both the the α- and β-lobes. The pedunculus and the lobes are conspicuously layered. Kenyon cells with neighbouring dendritic fields within the same calycal contour occupy a single layer in the pedunculus and lobes. Thus the two- polar organization of the calyces is transformed into a Cartesian map within the pedunculus, which continues into the α- and β-lobes. The calyx receives input fibres from both the antennal lobes and the optic neuropils. The branching patterns of these cells reflect the polar organization of the calyces as their terminals are restricted to one or more of the three gross compartments of the calycal neuropil. The course of these tracts and the morphologies of the fibres that they contain are described. Cells considered to represent outputs from the mushroom bodies arborize in the pedunculus and α- and β-lobes. Generally the arborizations of the output neurons reflect the layered organization of these neuropils. Fibres from the two lobes run to the anterior median and lateral protocerebral neuropil, and the anterior optic tubercle. Additionally there is an extensive network of feedback interneurons that inter- connect the α- and β-lobes with the ipsi- and contralateral calyces. Many individual neurons have branches in both the α- and β-lobes and in the pedunculus. The pathways and geometries of the fibres subserving the two lobes are described. The hypothesis of Vowles (1955) that the individual lobes represent a separation of sensory and motor output areas is shown to be incorrect. The anatomy of the bee’s mushroom bodies suggests that they process second-order antennal and fourth- and higher-order visual information. The feedback pathways are discussed as possible means of creating long-lasting after-effects which may be important in complex timing processes and possibly the formation of short-term memory.

8. The physiology and anatomy of the visual system

2017 ◽  
pp. 123-143
Author(s):  
Brian Rogers
Keyword(s):  
Information Processing ◽  
Visual Cortex ◽  
Visual System ◽  
Lateral Inhibition ◽  
Visual Information ◽  
Receptive Fields ◽  
Neural Pathways ◽  
Human Retina ◽  
Feature Detectors ◽  
System P

‘The physiology and anatomy of the visual system’ describes what we have learned from neurophysiology and anatomy over the past eighty years and what this tells us about the meaning of the circuits involved in visual information processing. It explains how psychologists and physiologists use the terms ‘mechanism’ and ‘process’. For physiologists, a mechanism is linked to the actions of individual neurons, neural pathways, and the ways in which the neurons are connected up. For psychologists, the term is typically used to describe the processes the neural circuits may carry out. The human retina is described with explanations of lateral inhibition, receptive fields, and feature detectors as well as the visual cortex and different visual pathways.

scholarly journals A decentralised neural model explaining optimal integration of navigational strategies in insects

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Xuelong Sun ◽  
Shigang Yue ◽  
Michael Mangan
Keyword(s):  
Visual Cues ◽  
Neural Model ◽  
Central Complex ◽  
Mushroom Bodies ◽  
Insect Brain ◽  
Neural Pathways ◽  
Neural Recordings ◽  
Insect Navigation ◽  
In The Wild ◽  
Adaptive Behaviours

Insect navigation arises from the coordinated action of concurrent guidance systems but the neural mechanisms through which each functions, and are then coordinated, remains unknown. We propose that insects require distinct strategies to retrace familiar routes (route-following) and directly return from novel to familiar terrain (homing) using different aspects of frequency encoded views that are processed in different neural pathways. We also demonstrate how the Central Complex and Mushroom Bodies regions of the insect brain may work in tandem to coordinate the directional output of different guidance cues through a contextually switched ring-attractor inspired by neural recordings. The resultant unified model of insect navigation reproduces behavioural data from a series of cue conflict experiments in realistic animal environments and offers testable hypotheses of where and how insects process visual cues, utilise the different information that they provide and coordinate their outputs to achieve the adaptive behaviours observed in the wild.

Spectral sensitivity of ON and OFF responses from the optic nerve of goldfish

1991 ◽  
Vol 6 (3) ◽  
pp. 207-217 ◽  
Author(s):  
Paul J. DeMarco ◽  
Maureen K. Powers
Keyword(s):  
Optic Nerve ◽  
Spectral Sensitivity ◽  
Visual Information ◽  
Spectral Response ◽  
Neural Pathways ◽  
Vertebrate Retina ◽  
Excitatory Responses ◽  
On And Off Pathways ◽  
Algebraic Summation

AbstractThe vertebrate retina processes visual information in parallel neural pathways known as the ON and OFF pathways. These pathways encode increments and decrements of light independently as excitatory responses. We examined the photopic spectral response of ON and OFF mechanisms in goldfish by measuring the sensitivity of optic nerve responses to the onset and termination of stimuli of various wavelengths. Using various adapting backgrounds, we found that the ON and OFF responses have different spectral sensitivities. The weighting of the cone inputs to the responses was estimated by an algebraic summation model. This model suggests that for the ON response, input from S-cones is stronger and more independent than for the OFF response, and M- and L-cones show stronger antagonism in the ON response than in the OFF response. The OFF response probably receives input from all cone types, but spectral antagonism is weak and its dominant input is from L-cones.

scholarly journals A Decentralised Neural Model Explaining Optimal Integration of Navigational Strategies in Insects

2019 ◽  
Author(s):  
Xuelong Sun ◽  
Shigang Yue ◽  
Michael Mangan
Keyword(s):  
Visual Cues ◽  
Neural Model ◽  
Central Complex ◽  
Mushroom Bodies ◽  
Insect Brain ◽  
Neural Pathways ◽  
Neural Recordings ◽  
Insect Navigation ◽  
In The Wild ◽  
Adaptive Behaviours

AbstractInsect navigation arises from the coordinated action of concurrent guidance systems but the neural mechanisms through which each functions, and are then coordinated, remains unknown. We propose that insects require distinct strategies to retrace familiar routes (route-following) and directly return from novel to familiar terrain (homing) using different aspects of frequency encoded views that are processed in different neural pathways. We also demonstrate how the Central Complex and Mushroom Bodies regions of the insect brain may work in tandem to coordinate the directional output of different guidance cues through a contextually switched ring-attractor inspired by neural recordings. The resultant unified model of insect navigation reproduces behavioural data from a series of cue conflict experiments in realistic animal environments and offers testable hypotheses of where and how insects process visual cues, utilise the different information that they provide and coordinate their outputs to achieve the adaptive behaviours observed in the wild.

scholarly journals Olfactory Learning in Drosophila

Physiology ◽  
2010 ◽  
Vol 25 (6) ◽  
pp. 338-346 ◽  
Author(s):  
Germain U. Busto ◽  
Isaac Cervantes-Sandoval ◽  
Ronald L. Davis
Keyword(s):  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
Sensory Information ◽  
Brain Regions ◽  
Olfactory Learning ◽  
Mushroom Bodies ◽  
Neural Pathways ◽  
Olfactory Information ◽  
Appetitive Stimuli ◽  
The Brain

Studies of olfactory learning in Drosophila have provided key insights into the brain mechanisms underlying learning and memory. One type of olfactory learning, olfactory classical conditioning, consists of learning the contingency between an odor with an aversive or appetitive stimulus. This conditioning requires the activity of molecules that can integrate the two types of sensory information, the odorant as the conditioned stimulus and the aversive or appetitive stimulus as the unconditioned stimulus, in brain regions where the neural pathways for the two stimuli intersect. Compelling data indicate that a particular form of adenylyl cyclase functions as a molecular integrator of the sensory information in the mushroom body neurons. The neuronal pathway carrying the olfactory information from the antennal lobes to the mushroom body is well described. Accumulating data now show that some dopaminergic neurons provide information about aversive stimuli and octopaminergic neurons about appetitive stimuli to the mushroom body neurons. Inhibitory inputs from the GABAergic system appear to gate olfactory information to the mushroom bodies and thus control the ability to learn about odors. Emerging data obtained by functional imaging procedures indicate that distinct memory traces form in different brain regions and correlate with different phases of memory. The results from these and other experiments also indicate that cross talk between mushroom bodies and several other brain regions is critical for memory formation.

scholarly journals Non-Contact Measurement of Motion Sickness Using Pupillary Rhythms from an Infrared Camera

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4642
Author(s):  
Sangin Park ◽  
Sungchul Mun ◽  
Jihyeon Ha ◽  
Laehyun Kim
Keyword(s):  
Virtual Reality ◽  
Motion Sickness ◽  
Visual Information ◽  
Infrared Camera ◽  
Classification Performance ◽  
Support Vector ◽  
Neural Pathways ◽  
Two Dimensional ◽  
Processing Load ◽  
Contact Measurement

Both physiological and neurological mechanisms are reflected in pupillary rhythms via neural pathways between the brain and pupil nerves. This study aims to interpret the phenomenon of motion sickness such as fatigue, anxiety, nausea and disorientation using these mechanisms and to develop an advanced non-contact measurement method from an infrared webcam. Twenty-four volunteers (12 females) experienced virtual reality content through both two-dimensional and head-mounted device interpretations. An irregular pattern of the pupillary rhythms, demonstrated by an increasing mean and standard deviation of pupil diameter and decreasing pupillary rhythm coherence ratio, was revealed after the participants experienced motion sickness. The motion sickness was induced while watching the head-mounted device as compared to the two-dimensional virtual reality, with the motion sickness strongly related to the visual information processing load. In addition, the proposed method was verified using a new experimental dataset for 23 participants (11 females), with a classification performance of 89.6% (n = 48) and 80.4% (n = 46) for training and test sets using a support vector machine with a radial basis function kernel, respectively. The proposed method was proven to be capable of quantitatively measuring and monitoring motion sickness in real-time in a simple, economical and contactless manner using an infrared camera.

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