Differential Roles of Nonsynaptic and Synaptic Plasticity in Operant Reward Learning-Induced Compulsive Behavior

Sieling, Fred H.; Bédécarrats, Alexis; Simmers, John; Prinz, Astrid A.; Nargeot, Romuald

doi:10.1016/j.cub.2014.03.004

Cited by 35 publications

(47 citation statements)

References 40 publications

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“…Second, because many of the key sensory neurons that provide chemoafferent or mechanoafferent inputs to the feeding apparatus have been characterized (Evans et al 2003;Evans and Cropper 1998;Rosen et al 2000aRosen et al , 2000b, working out the cellular mechanism by which sensory feedback can shape motor neuronal activity can focus on both identified sensory and motor neurons. Finally, the studies by Nargeot and his colleagues have elegantly demonstrated that it is possible to work out, at the level of individual identified neurons, the mechanisms by which variability can be reduced in the feeding neural circuitry (Sieling et al 2014), suggesting that similar studies can be done to understand how variability is regulated by sensory feedback. Studies by Benjamin and his colleagues have demonstrated the power of invertebrate systems for exploring the neural mechanisms of behavioral hierarchy (Pirger et al 2014), and the extent to which central pattern generators are hierarchical or distributed systems (Benjamin 2012).…”

Section: Controlling and Exploiting Neuronal And Biomechanical Variabmentioning

confidence: 99%

Motor neuronal activity varies least among individuals when it matters most for behavior

Cullins

Shaw

Gill

et al. 2015

Journal of Neurophysiology

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How does motor neuronal variability affect behavior? To explore this question, we quantified activity of multiple individual identified motor neurons mediating biting and swallowing in intact, behaving Aplysia californica by recording from the protractor muscle and the three nerves containing the majority of motor neurons controlling the feeding musculature. We measured multiple motor components: duration of the activity of identified motor neurons as well as their relative timing. At the same time, we measured behavioral efficacy: amplitude of grasping movement during biting and amplitude of net inward food movement during swallowing. We observed that the total duration of the behaviors varied: Within animals, biting duration shortened from the first to the second and third bites; between animals, biting and swallowing durations varied. To study other sources of variation, motor components were divided by behavior duration (i.e., normalized). Even after normalization, distributions of motor component durations could distinguish animals as unique individuals. However, the degree to which a motor component varied among individuals depended on the role of that motor component in a behavior. Motor neuronal activity that was essential for the expression of biting or swallowing was similar among animals, whereas motor neuronal activity that was not essential for that behavior varied more from individual to individual. These results suggest that motor neuronal activity that matters most for the expression of a particular behavior may vary least from individual to individual. Shaping individual variability to ensure behavioral efficacy may be a general principle for the operation of motor systems.

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Section: Controlling and Exploiting Neuronal And Biomechanical Variabmentioning

confidence: 99%

Motor neuronal activity varies least among individuals when it matters most for behavior

Cullins

Shaw

Gill

et al. 2015

Journal of Neurophysiology

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“…Using RTXI, Sieling et al [35] used the dynamic-clamp technique, in which simulated membrane and synaptic currents are artificially added or subtracted from neurons, to examine whether selective changes in single conductances governing cell excitability and electrical coupling are responsible for the associative modification of feeding circuit output and behavior (Fig 6). Using in vitro preparations of buccal ganglia isolated from naive and operantly trained animals, Sieling et al either enhanced or diminished neuronal excitability and coupling strengths in RT to test for causation and determine respective contributions of synaptic and non-synaptic processes by which associative learning leads to expression of compulsive behavior.…”

Section: Resultsmentioning

confidence: 99%

“…In (D), G leak was introduced into a B63 and current pulses for measuring coupling coefficients were injected into either postjunctional B30 or B65. (For details, see [35] Fig. S1.)…”

Section: Resultsmentioning

confidence: 99%

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)

et al. 2017

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The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available; however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols.

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“…16, 2017; cellular/molecular components or forms of plasticity in the process of achieving certain learning goals. This also implies significant animal-to-animal and trial-to-trial variability in the mechanisms that mediate learning, thereby calling for utmost caution in assigning one-to-one relationships between behavioral learning and specific forms of plasticity in any single brain region (Bailey et al, 2006;Bennett and Hacker, 2003;Jazayeri and Afraz, 2017;Krakauer et al, 2017;Mayford et al, 2012;Sieling et al, 2014;Tsokas et al, 2016;Vogelstein et al, 2014).…”

Section: Degeneracy In Learning and Memorymentioning

confidence: 99%

“…http://dx.doi.org/10.1101/203943 doi: bioRxiv preprint first posted online Oct. 16, 2017;Jazayeri and Afraz, 2017;Krakauer et al, 2017;Mayford et al, 2012;Sieling et al, 2014;Tsokas et al, 2016;Vogelstein et al, 2014).…”

Section: The Causality Conundrummentioning

confidence: 99%

Degeneracy in hippocampal physiology and plasticity

Rathour

Narayanan

2017

Preprint

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Degeneracy, defined as the ability of structurally disparate elements to perform analogous function, has largely been assessed from the perspective of maintaining robustness of physiology or plasticity. How does the framework of degeneracy assimilate into an encoding system where the ability to change is an essential ingredient for storing new incoming information? Could degeneracy maintain the balance between the apparently contradictory goals of the need to change for encoding and the need to resist change towards maintaining homeostasis? In this review, we explore these fundamental questions with the mammalian hippocampus as an example encoding system. We systematically catalog lines of evidence, spanning multiple scales of analysis, that demonstrate the expression of degeneracy in hippocampal physiology and plasticity. We assess the potential of degeneracy as a framework to achieve encoding and homeostasis without cross-interferences, and postulate that multiscale parametric and interactional complexity could establish disparate routes towards accomplishing these conjoint goals. These disparate routes then provide several degrees of freedom to the encodinghomeostasis system in accomplishing its tasks in an input-and state-dependent manner. Finally, the expression of degeneracy spanning multiple scales offers an ideal reconciliation to several outstanding controversies, through the recognition that the seemingly contradictory disparate observations are merely alternate routes that the system might recruit towards accomplishment of its goals. Juxtaposed against the ubiquitous prevalence of degeneracy and its strong links to evolution, it is perhaps apt to add a corollary to Theodosius Dobzhansky's famous quote and state "nothing in physiology makes sense except in the light of degeneracy".peer-reviewed)

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Differential Roles of Nonsynaptic and Synaptic Plasticity in Operant Reward Learning-Induced Compulsive Behavior

Abstract: These data establish direct causality for the contributions of distinct synaptic and nonsynaptic adaptive processes to complementary facets of a compulsive behavior resulting from operant reward learning.

Cited by 35 publications

References 40 publications

Motor neuronal activity varies least among individuals when it matters most for behavior

Motor neuronal activity varies least among individuals when it matters most for behavior

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)

Degeneracy in hippocampal physiology and plasticity

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