scholarly journals Circuits that encode and predict alcohol associated preference

2019 ◽  
Author(s):  
Kristin M. Scaplen ◽  
Mustafa Talay ◽  
Sarah Salamon ◽  
Kavin M. Nuñez ◽  
Amanda G. Waterman ◽  
...  

AbstractSubstance use disorders are chronic relapsing disorders often impelled by enduring memories and persistent cravings. Alcohol, as well as other addictive substances, remolds neural circuits important for memory to establish obstinate preference despite aversive consequences. How pertinent circuits are selected and shaped to result in these unchanging, inflexible memories is unclear. Using neurogenetic tools available inDrosophila melanogasterwe define how circuits required for alcohol associated preference shift from population level dopaminergic activation to select dopamine neurons that predict behavioral choice. During memory expression, these dopamine neurons directly, and indirectly via the mushroom body (MB), modulate the activity of interconnected glutamatergic and cholinergic output neurons. Transsynaptic tracing of these output neurons revealed at least two regions of convergence: 1) a center of memory consolidation within the MB implicated in arousal, and 2) a structure outside the MB implicated in integration of naïve and learned responses. These findings provide a circuit framework through which dopamine neuron activation shifts from reward delivery to cue onset, and provides insight into the inflexible, maladaptive nature of alcohol associated memories.

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Kristin M Scaplen ◽  
Mustafa Talay ◽  
Kavin M Nunez ◽  
Sarah Salamon ◽  
Amanda G Waterman ◽  
...  

A powerful feature of adaptive memory is its inherent flexibility. Alcohol and other addictive substances can remold neural circuits important for memory to reduce this flexibility. However, the mechanism through which pertinent circuits are selected and shaped remains unclear. We show that circuits required for alcohol-associated preference shift from population level dopaminergic activation to select dopamine neurons that predict behavioral choice in Drosophila melanogaster. During memory expression, subsets of dopamine neurons directly and indirectly modulate the activity of interconnected glutamatergic and cholinergic mushroom body output neurons (MBON). Transsynaptic tracing of neurons important for memory expression revealed a convergent center of memory consolidation within the mushroom body (MB) implicated in arousal, and a structure outside the MB implicated in integration of naïve and learned responses. These findings provide a circuit framework through which dopamine neuronal activation shifts from reward delivery to cue onset, and provide insight into the maladaptive nature of memory.


2021 ◽  
Vol 118 (42) ◽  
pp. e2023674118
Author(s):  
Jia Jia ◽  
Lei He ◽  
Junfei Yang ◽  
Yichun Shuai ◽  
Jingjing Yang ◽  
...  

Chronic stress could induce severe cognitive impairments. Despite extensive investigations in mammalian models, the underlying mechanisms remain obscure. Here, we show that chronic stress could induce dramatic learning and memory deficits in Drosophila melanogaster. The chronic stress–induced learning deficit (CSLD) is long lasting and associated with other depression-like behaviors. We demonstrated that excessive dopaminergic activity provokes susceptibility to CSLD. Remarkably, a pair of PPL1-γ1pedc dopaminergic neurons that project to the mushroom body (MB) γ1pedc compartment play a key role in regulating susceptibility to CSLD so that stress-induced PPL1-γ1pedc hyperactivity facilitates the development of CSLD. Consistently, the mushroom body output neurons (MBON) of the γ1pedc compartment, MBON-γ1pedc>α/β neurons, are important for modulating susceptibility to CSLD. Imaging studies showed that dopaminergic activity is necessary to provoke the development of chronic stress–induced maladaptations in the MB network. Together, our data support that PPL1-γ1pedc mediates chronic stress signals to drive allostatic maladaptations in the MB network that lead to CSLD.


2019 ◽  
Author(s):  
James E. M. Bennett ◽  
Andrew Philippides ◽  
Thomas Nowotny

AbstractEffective decision making in a changing environment demands that accurate predictions are learned about decision outcomes. In Drosophila, such learning is or-chestrated in part by the mushroom body (MB), where dopamine neurons (DANs) signal reinforcing stimuli to modulate plasticity presynaptic to MB output neurons (MBONs). Here, we extend previous MB models, in which DANs signal absolute rewards, proposing instead that DANs signal reward prediction errors (RPEs) by utilising feedback reward predictions from MBONs. We formulate plasticity rules that minimise RPEs, and use simulations to verify that MBONs learn accurate reward predictions. We postulate as yet unobserved connectivity, which not only overcomes limitations in the experimentally constrained model, but also explains additional experimental observations that connect MB physiology to learning. The original, experimentally constrained model and the augmented model capture a broad range of established fly behaviours, and together make five predictions that can be tested using established experimental methods.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
James E. M. Bennett ◽  
Andrew Philippides ◽  
Thomas Nowotny

AbstractEffective decision making in a changing environment demands that accurate predictions are learned about decision outcomes. In Drosophila, such learning is orchestrated in part by the mushroom body, where dopamine neurons signal reinforcing stimuli to modulate plasticity presynaptic to mushroom body output neurons. Building on previous mushroom body models, in which dopamine neurons signal absolute reinforcement, we propose instead that dopamine neurons signal reinforcement prediction errors by utilising feedback reinforcement predictions from output neurons. We formulate plasticity rules that minimise prediction errors, verify that output neurons learn accurate reinforcement predictions in simulations, and postulate connectivity that explains more physiological observations than an experimentally constrained model. The constrained and augmented models reproduce a broad range of conditioning and blocking experiments, and we demonstrate that the absence of blocking does not imply the absence of prediction error dependent learning. Our results provide five predictions that can be tested using established experimental methods.


Author(s):  
Margaret Driscoll ◽  
Steven Buchert ◽  
Victoria Coleman ◽  
Morgan McLaughlin ◽  
Amanda Nguyen ◽  
...  

AbstractNeural circuits involved in regulation of sleep play a critical role in sleep-wake transition and ability of an organism to engage in other behaviors critical for survival. The fruit fly, Drosophila melanogaster is a powerful system for the study of sleep and circuit mechanisms underlying sleep and co-regulation of sleep with other behaviors. In Drosophila, two neuropils in the central brain, mushroom body (MB) and central complex (CX) have been shown to influence sleep homeostasis and receive neuromodulator input critical to sleep-wake switch.Dopamine neurons (DANs) are the primary neuromodulator inputs to the MB but the mechanisms by which they regulate sleep- and wake-promoting neurons within MB are unknown. Here we investigate the role of subsets of DANs that signal wakefulness and project to wake-promoting compartments of the MB. We find that inhibition of specific subsets of PAM and PPL1 DANs projecting to the MB increase sleep in the presence of strong wake-inducing stimuli that reduces GABA transmission, although activity of these neurons is not directly modulated by GABA signaling. Of these subsets we find that DANs innervating the γ5 and β’2 MB compartments require both DopR1 and DopR2 receptors located in downstream Kenyon cells and mushroom body output neurons (MBONs). Further, we report that unlike the activity of wake-promoting MBONs and KCs, whose activity is modulated by sleep-need and PAM-DAN activity is independent of sleep-need. We have characterized a dopamine mediated sleep-circuit providing an inroad into understanding how common circuits within MB regulate sleep, wakefulness and behavioral arousal.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chang Zhao ◽  
Yves F. Widmer ◽  
Sören Diegelmann ◽  
Mihai A. Petrovici ◽  
Simon G. Sprecher ◽  
...  

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.


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Jessica Mitchell ◽  
Carlas S Smith ◽  
Josh Titlow ◽  
Nils Otto ◽  
Pieter van Velde ◽  
...  

Memory-relevant neuronal plasticity is believed to require local translation of new proteins at synapses. Understanding this process requires the visualization of the relevant mRNAs within these neuronal compartments. Here we used single-molecule fluorescence in situ hybridization (smFISH) to localize mRNAs at subcellular resolution in the adult Drosophila brain. mRNAs for subunits of nicotinic acetylcholine receptors and kinases could be detected within the dendrites of co-labelled Mushroom Body Output Neurons (MBONs) and their relative abundance showed cell-specificity. Moreover, aversive olfactory learning produced a transient increase in the level of CaMKII mRNA within the dendritic compartments of the 52a MBONs. Localization of specific mRNAs in MBONs before and after learning represents a critical step towards deciphering the role of dendritic translation in the neuronal plasticity underlying behavioural change in Drosophila.


2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Jie-Kai Wu ◽  
Chu-Yi Tai ◽  
Kuan-Lin Feng ◽  
Shiu-Ling Chen ◽  
Chun-Chao Chen ◽  
...  

2018 ◽  
Vol 5 (2) ◽  
pp. 171785 ◽  
Author(s):  
Martin F. Strube-Bloss ◽  
Wolfgang Rössler

Flowers attract pollinating insects like honeybees by sophisticated compositions of olfactory and visual cues. Using honeybees as a model to study olfactory–visual integration at the neuronal level, we focused on mushroom body (MB) output neurons (MBON). From a neuronal circuit perspective, MBONs represent a prominent level of sensory-modality convergence in the insect brain. We established an experimental design allowing electrophysiological characterization of olfactory, visual, as well as olfactory–visual induced activation of individual MBONs. Despite the obvious convergence of olfactory and visual pathways in the MB, we found numerous unimodal MBONs. However, a substantial proportion of MBONs (32%) responded to both modalities and thus integrated olfactory–visual information across MB input layers. In these neurons, representation of the olfactory–visual compound was significantly increased compared with that of single components, suggesting an additive, but nonlinear integration. Population analyses of olfactory–visual MBONs revealed three categories: (i) olfactory, (ii) visual and (iii) olfactory–visual compound stimuli. Interestingly, no significant differentiation was apparent regarding different stimulus qualities within these categories. We conclude that encoding of stimulus quality within a modality is largely completed at the level of MB input, and information at the MB output is integrated across modalities to efficiently categorize sensory information for downstream behavioural decision processing.


Author(s):  
Lina Engelen ◽  
Erika Bohn-Goldbaum ◽  
Melanie Crane ◽  
Martin Mackey ◽  
Chris Rissel

Active travel can support the achievement of recommended levels of physical activity. Monitoring travel behavior of university students and staff provides a useful insight into patterns of regional travel and population level changes in physical activity. This study sought to evaluate current travel and physical activity behaviors in a university population and to determine whether these changed over time. An online survey of travel behavior and physical activity was conducted at the University of Sydney, Australia. The survey was actively promoted for three weeks prior to the release of the survey among staff and students, which asked about travel behavior on a specific day in September 2017. The survey questions were the same as those used in a similar online survey conducted across the University in 2012. In total, 4359 People completed the survey, representing 10.8% of staff and 4.1% of students. Approximately two thirds of survey respondents were students, in both the 2012 and 2017 surveys. Compared with 2012, there was an increase in active travel to the University in 2017 from increased walking and train travel. Compared to 2012, in 2017 there was an increase in average minutes walked by about nine minutes, and less time spent sitting. Trip lengths increased, with 68% of trips taking longer than 30 min in 2017. The amount of time spent in low–moderate levels physical activity increased between 2012 and 2017, potentially related to active travel behavior. Citywide changes towards a system-wide transport fare structure was the biggest change in the transport environment between the two surveys and may have contributed to increased train travel.


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