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 Reward signaling in a recurrent circuit of dopaminergic neurons and Kenyon cells

2018 ◽  
Author(s):  
Radostina Lyutova ◽  
Maximilian Pfeuffer ◽  
Dennis Segebarth ◽  
Jens Habenstein ◽  
Mareike Selcho ◽  
...  
Keyword(s):  
Learning And Memory ◽  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
Olfactory Learning ◽  
Mushroom Bodies ◽  
Neuronal Circuitry ◽  
Sustained Activity ◽  
Kenyon Cells ◽  
Reward Information ◽  
The Brain

1.AbstractDopaminergic neurons in the brain of theDrosophilalarva play a key role in mediating reward information to the mushroom bodies during appetitive olfactory learning and memory. Using optogenetic activation of Kenyon cells we provide evidence that a functional recurrent signaling loop exists between Kenyon cells and dopaminergic neurons of the primary protocerebral anterior (pPAM) cluster. An optogenetic activation of Kenyon cells paired with an odor is sufficient to induce appetitive memory, while a simultaneous impairment of the dopaminergic pPAM neurons abolishes memory expression. Thus, dopaminergic pPAM neurons mediate reward information to the Kenyon cells, but in turn receive feedback from Kenyon cells. We further show that the activation of recurrent signaling routes within mushroom body circuitry increases the persistence of an odor-sugar memory. Our results suggest that sustained activity in a neuronal circuitry is a conserved mechanism in insects and vertebrates to consolidate memories.

scholarly journals Brain composition in Heliconius butterflies, post-eclosion growth and experience dependent neuropil plasticity

2015 ◽  
Author(s):  
Stephen H Montgomery ◽  
Richard M Merrill ◽  
Swidbert R Ott
Keyword(s):  
Behavioral Ecology ◽  
Neural Development ◽  
Mushroom Body ◽  
Brain Regions ◽  
Mushroom Bodies ◽  
Heliconius Butterflies ◽  
Sensory Adaptations ◽  
Differential Expansion ◽  
The Brain

Behavioral and sensory adaptations are often based in the differential expansion of brain components. These volumetric differences represent changes in investment, processing capacity and/or connectivity, and can be used to investigate functional and evolutionary relationships between different brain regions, and between brain composition and behavioral ecology. Here, we describe the brain composition of two species of Heliconius butterflies, a long-standing study system for investigating ecological adaptation and speciation. We confirm a previous report of striking mushroom body expansion, and explore patterns of post-eclosion growth and experience-dependent plasticity in neural development. This analysis uncovers age- and experience-dependent post-emergence mushroom body growth comparable to that in foraging hymenoptera, but also identifies plasticity in several other neuropil. An interspecific analysis indicates that Heliconius display remarkable levels of investment in mushroom bodies for a lepidopteran, and indeed rank highly compared to other insects. Our analyses lay the foundation for future comparative and experimental analyses that will establish Heliconius as a useful case study in evolutionary neurobiology.

scholarly journals Predictive olfactory learning in Drosophila

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chang Zhao ◽  
Yves F. Widmer ◽  
Sören Diegelmann ◽  
Mihai A. Petrovici ◽  
Simon G. Sprecher ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
Trace Conditioning ◽  
Fruit Fly ◽  
Olfactory Learning ◽  
Shock Strength ◽  
Behavioral Experiments ◽  
Kenyon Cells ◽  
Output Neurons

AbstractOlfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.

scholarly journals Dissecting neural pathways for forgetting in Drosophila olfactory aversive memory

2015 ◽  
Vol 112 (48) ◽  
pp. E6663-E6672 ◽  
Author(s):  
Yichun Shuai ◽  
Areekul Hirokawa ◽  
Yulian Ai ◽  
Min Zhang ◽  
Wanhe Li ◽  
...  
Keyword(s):  
Reversal Learning ◽  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
Biologically Active ◽  
Molecular Pathways ◽  
Neural Pathways ◽  
Active Process ◽  
Glutamatergic Neurons ◽  
Memory Decay ◽  
Over Time

Recent studies have identified molecular pathways driving forgetting and supported the notion that forgetting is a biologically active process. The circuit mechanisms of forgetting, however, remain largely unknown. Here we report two sets of Drosophila neurons that account for the rapid forgetting of early olfactory aversive memory. We show that inactivating these neurons inhibits memory decay without altering learning, whereas activating them promotes forgetting. These neurons, including a cluster of dopaminergic neurons (PAM-β′1) and a pair of glutamatergic neurons (MBON-γ4>γ1γ2), terminate in distinct subdomains in the mushroom body and represent parallel neural pathways for regulating forgetting. Interestingly, although activity of these neurons is required for memory decay over time, they are not required for acute forgetting during reversal learning. Our results thus not only establish the presence of multiple neural pathways for forgetting in Drosophila but also suggest the existence of diverse circuit mechanisms of forgetting in different contexts.

scholarly journals Experience, but not age, is associated with volumetric mushroom body expansion in solitary alkali bees

2021 ◽  
pp. jeb.238899
Author(s):  
Mallory A. Hagadorn ◽  
Makenna M. Johnson ◽  
Adam R. Smith ◽  
Marc A. Seid ◽  
Karen M. Kapheim
Keyword(s):  
Structural Changes ◽  
Evolutionary Relationship ◽  
Brain Regions ◽  
Mushroom Bodies ◽  
Order Processing ◽  
Social Species ◽  
Evolution Of Sociality ◽  
Foraging Experience ◽  
Brain Changes ◽  
The Brain

In social insects, changes in behavior are often accompanied by structural changes in the brain. This neuroplasticity may come with experience (experience-dependent) or age (experience-expectant). Yet, the evolutionary relationship between neuroplasticity and sociality is unclear, because we know little about neuroplasticity in the solitary relatives of social species. We used confocal microscopy to measure brain changes in response to age and experience in a solitary halictid bee (Nomia melanderi). First, we compared the volume of individual brain regions among newly-emerged females, laboratory females deprived of reproductive and foraging experience, and free-flying, nesting females. Experience, but not age, led to significant expansion of the mushroom bodies—higher-order processing centers associated with learning and memory. Next, we investigated how social experience influences neuroplasticity by comparing the brains of females kept in the laboratory either alone or paired with another female. Paired females had significantly larger olfactory regions of the mushroom bodies. Together, these experimental results indicate that experience-dependent neuroplasticity is common to both solitary and social taxa, whereas experience-expectant neuroplasticity may be an adaptation to life in a social colony. Further, neuroplasticity in response to social chemical signals may have facilitated the evolution of sociality.

Symptoms, Related Brain Regions, and Diagnosis

2013 ◽  
Author(s):  
J. Eric Ahlskog
Keyword(s):  
Spinal Cord ◽  
Nervous System ◽  
Basal Ganglia ◽  
Brain Stem ◽  
Muscle Activation ◽  
Sensory Information ◽  
Brain Regions ◽  
Electrical Signal ◽  
Brain And Spinal Cord ◽  
The Brain

As a prelude to the treatment chapters that follow, we need to define and describe the types of problems and symptoms encountered in DLB and PDD. The clinical picture can be quite varied: problems encountered by one person may be quite different from those encountered by another person, and symptoms that are problematic in one individual may be minimal in another. In these disorders, the Lewy neurodegenerative process potentially affects certain nervous system regions but spares others. Affected areas include thinking and memory circuits, as well as movement (motor) function and the autonomic nervous system, which regulates primary functions such as bladder, bowel, and blood pressure control. Many other brain regions, by contrast, are spared or minimally involved, such as vision and sensation. The brain and spinal cord constitute the central nervous system. The interface between the brain and spinal cord is by way of the brain stem, as shown in Figure 4.1. Thought, memory, and reasoning are primarily organized in the thick layers of cortex overlying lower brain levels. Volitional movements, such as writing, throwing, or kicking, also emanate from the cortex and integrate with circuits just below, including those in the basal ganglia, shown in Figure 4.2. The basal ganglia includes the striatum, globus pallidus, subthalamic nucleus, and substantia nigra, as illustrated in Figure 4.2. Movement information is integrated and modulated in these basal ganglia nuclei and then transmitted down the brain stem to the spinal cord. At spinal cord levels the correct sequence of muscle activation that has been programmed is accomplished. Activated nerves from appropriate regions of the spinal cord relay the signals to the proper muscles. Sensory information from the periphery (limbs) travels in the opposite direction. How are these signals transmitted? Brain cells called neurons have long, wire-like extensions that interface with other neurons, effectively making up circuits that are slightly similar to computer circuits; this is illustrated in Figure 4.3. At the end of these wire-like extensions are tiny enlargements (terminals) that contain specific biological chemicals called neurotransmitters. Neurotransmitters are released when the electrical signal travels down that neuron to the end of that wire-like process.

scholarly journals The Antennal Pathway of Dragonfly Nymphs, from Sensilla to the Brain

Insects ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 886
Author(s):  
Silvana Piersanti ◽  
Manuela Rebora ◽  
Gianandrea Salerno ◽  
Sylvia Anton
Keyword(s):  
Brain Structure ◽  
Antennal Lobe ◽  
Sensory Information ◽  
Brain Structures ◽  
Brain Regions ◽  
Adult Brain ◽  
Published Data ◽  
Antennal Sensilla ◽  
Aquatic Life ◽  
The Brain

Dragonflies are hemimetabolous insects, switching from an aquatic life style as nymphs to aerial life as adults, confronted to different environmental cues. How sensory structures on the antennae and the brain regions processing the incoming information are adapted to the reception of fundamentally different sensory cues has not been investigated in hemimetabolous insects. Here we describe the antennal sensilla, the general brain structure, and the antennal sensory pathways in the last six nymphal instars of Libellula depressa, in comparison with earlier published data from adults, using scanning electron microscopy, and antennal receptor neuron and antennal lobe output neuron mass-tracing with tetramethylrhodamin. Brain structure was visualized with an anti-synapsin antibody. Differently from adults, the nymphal antennal flagellum harbors many mechanoreceptive sensilla, one olfactory, and two thermo-hygroreceptive sensilla at all investigated instars. The nymphal brain is very similar to the adult brain throughout development, despite the considerable differences in antennal sensilla and habitat. Like in adults, nymphal brains contain mushroom bodies lacking calyces and small aglomerular antennal lobes. Antennal fibers innervate the antennal lobe similar to adult brains and the gnathal ganglion more prominently than in adults. Similar brain structures are thus used in L. depressa nymphs and adults to process diverging sensory information.

scholarly journals Neural Correlates of Group Bias During Natural Viewing

2018 ◽  
Vol 29 (8) ◽  
pp. 3380-3389
Author(s):  
Timothy J Andrews ◽  
Ryan K Smith ◽  
Richard L Hoggart ◽  
Philip I N Ulrich ◽  
Andre D Gouws
Keyword(s):  
Time Course ◽  
Social Groups ◽  
Sensory Information ◽  
Brain Regions ◽  
Group Differences ◽  
Neural Basis ◽  
Brain Responses ◽  
The World ◽  
High Level ◽  
The Brain

Abstract Individuals from different social groups interpret the world in different ways. This study explores the neural basis of these group differences using a paradigm that simulates natural viewing conditions. Our aim was to determine if group differences could be found in sensory regions involved in the perception of the world or were evident in higher-level regions that are important for the interpretation of sensory information. We measured brain responses from 2 groups of football supporters, while they watched a video of matches between their teams. The time-course of response was then compared between individuals supporting the same (within-group) or the different (between-group) team. We found high intersubject correlations in low-level and high-level regions of the visual brain. However, these regions of the brain did not show any group differences. Regions that showed higher correlations for individuals from the same group were found in a network of frontal and subcortical brain regions. The interplay between these regions suggests a range of cognitive processes from motor control to social cognition and reward are important in the establishment of social groups. These results suggest that group differences are primarily reflected in regions involved in the evaluation and interpretation of the sensory input.

scholarly journals Predictive olfactory learning in Drosophila

2019 ◽  
Author(s):  
Chang Zhao ◽  
Yves F Widmer ◽  
Soeren Diegelmann ◽  
Mihai Petrovici ◽  
Simon G Sprecher ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Dopaminergic Neurons ◽  
Mushroom Body ◽  
Trace Conditioning ◽  
Fruit Fly ◽  
Olfactory Learning ◽  
Shock Strength ◽  
Behavioral Experiments ◽  
Kenyon Cells ◽  
Output Neurons

AbstractOlfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offer a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.

scholarly journals Multi-sensory integration in the mouse cortical connectome using a network diffusion model

2019 ◽  
Author(s):  
Kamal Shadi ◽  
Eva Dyer ◽  
Constantine Dovrolis
Keyword(s):  
Diffusion Model ◽  
Temporal Cortex ◽  
Sensory Information ◽  
Brain Regions ◽  
Evoked Activity ◽  
Communication Dynamics ◽  
Activation Cascade ◽  
Alt Model ◽  
The Brain ◽  
Network Diffusion

AbstractHaving a structural network representation of connectivity in the brain is instrumental in analyzing communication dynamics and information processing in the brain. In this work, we make steps towards understanding multi-sensory information flow and integration using a network diffusion approach. In particular, we model the flow of evoked activity, initiated by stimuli at primary sensory regions, using the Asynchronous Linear Threshold (ALT) diffusion model. The ALT model captures how evoked activity that originates at a given region of the cortex “ripples through” other brain regions (referred to as an activation cascade). By comparing the model results to functional datasets based on Voltage Sensitive Dye (VSD) imaging, we find that in most cases the ALT model predicts the temporal ordering of an activation cascade correctly. Our results on the Mouse Connectivity Atlas from the Allen Institute for Brain Science show that a small number of brain regions are involved in many primary sensory streams – the claustrum and the parietal temporal cortex being at the top of the list. This suggests that the cortex relies on an hourglass architecture to first integrate and compress multi-sensory information from multiple sensory regions, before utilizing that lower-dimensionality representation in higher-level association regions and more complex cognitive tasks.

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