Abstract
The activity of multifunctional networks is configured by neuromodulators that exert persistent effects. This raises a question, does this impact the ability of a network to switch from one type of activity to another? We review studies that have addressed this question in the Aplysia feeding circuit. Task switching in this system occurs ‘asymmetrically’. When there is a switch from egestion to ingestion neuromodulation impedes switching (creates a ‘negative bias’). When there is a switch from ingestion to egestion the biasing is ‘positive’. Ingestion promotes subsequent egestion. We contrast mechanisms responsible for the two types of biasing and show that the observed asymmetry is a consequence of the fact that there is more than one set of egestive circuit parameters.
Introduction
Like many neural networks the feeding network in Aplysia is multi-functional. It generates both ingestive and egestive motor programs. To a large extent this is a consequence of the fact that activity is configured by modulatory neurotransmitters (for review see [1] and for very recent characterizations of feeding peptides see [2,3]). This is not an unusual arrangement; in fact, all networks appear to be subject to neuromodulation [4]. Although this has been most extensively documented in motor networks, it is becoming apparent that neuromodulation plays a role in configuring network activity in many other contexts such as human cognition [5].
The induction of a persistent state in the feeding network is an advantage under some circumstances. For example, when Aplysia encounter patches of seaweed they generate bouts of ingestive reponses [6]. Additionally, however they are capable of task switching. For example, if they ingest a piece of food that is attached to a substrate the attached food can be egested and another piece of seaweed ingested [7].
Task switching is a common phenomenon and even occurs during the execution of innate behaviors (e.g., [8,9]). Mechanistic studies of how task switching occurs have primarily focused on circuit level questions, e.g. how they are triggered by changes in afferent input [10–13]. A question less commonly addressed is, can the persistence of an internal state impact the ability of a network to task switch quickly? Studies of the feeding circuit of Aplysia that speak to this issue are described below.
The feeding circuit is multi-functional
As Aplysia animals feed, they adapt to changes in the external environment and modify behavior [14,15]. For example, one type of ingestive response (a bite) can be converted to a second type of ingestive response (a swallow) if an animal successfully grasps food. These types of adjustments in ongoing behavior are often mediated by dynamic changes in afferent input.
This review will focus on a further complication; the fact that the network operates in at least two different modes [1]. Namely, it can generate a bout of ingestive activity or a bout of egestive activity. How this is achieved has been the subject of much investigation and it has become apparent that these two network configurations are to a large extent induced via actions of modulatory neurotransmitters [1].
State changes in the feeding network
Some neuromodulator induced alterations of the Aplysia feeding circuit are long-term and are important for learning and memory (recent description of this include [16–23]). This review will focus on modifications that are not as long lasting, but persist for minutes. On this time scale persistence produces a change in the internal state of the animal in that responses to external stimuli are impacted until modulatory effects dissipate [24]. The state change creates a ‘bias’ in that there is an increase in the probability that a certain type of response will be generated. In another mollusc, Lymnaea, biasing can even cause satiated animals to reject stimuli that are palatable to food deprived animals [25]**. When state changes are induced, afferent input can be integrated over a relatively long time scale and brief ‘distractions’ can be ignored (also see [26]**).
Internal states are not always a product of neuromodulator release. For example, in other contexts recurrent connections can be important [27,28]*. Comparisons of state induction across species have however noted that in most cases persistent neuromodulation does play an important role [29]. An issue we address in this review is how does this impact the ability of the network to task switch?
Asymmetries in task switching in the feeding network
Even in mammals it has become apparent that feeding as a whole can be surprisingly complex. It can be fragmented, and include behaviors that are not strictly related to food intake [30]**. Studies of switches between ingestive and egestive activity in the isolated feeding network of Aplysia have shown that there is a pronounced asymmetry. After a bout of egestive activity it is not immediately possible to generate ingestive activity, i.e., negative biasing is observed [31] (Fig. 1A). In contrast, after a bout of ingestive activity, the biasing is positive [32] (Fig. 1B). A stimulus that would trigger an intermediate response in a naïve preparation triggers a fully egestive response. Asymmetries in task switching have also been described in other systems (e.g., [33,34]). A question addressed in the feeding network is, how do they arise?
Figure 1.
(A) Negative biasing. If an ingestive input to the CPG is activated under control conditions a weakly ingestive (or intermediate) cycle of activity is generated (light green) [31]. In contrast, if the same input is used to trigger a cycle of activity after egestion the cycle triggered is egestive (dark red) [31]. Negative biasing is a consequence of the fact that the induction of egestive activity produces a persistent increase in the excitability of the egestive interneuron B20 [36]. Consequently, B20 is ‘overactive’ when there is an attempt to trigger an ingestive cycle of activity. (B) Positive biasing. If an egestive input to the CPG is activated under control conditions a weakly egestive (or intermediate) cycle of activity is generated (light red) [31]. In contrast, if the same input is used to trigger activity after a bout of ingestive activity the cycle triggered is egestive (dark red) [32]. Positive biasing is a consequence of the fact that the induction of ingestive activity produces a persistent increase in the excitability of the egestive interneuron B65 [32]. B65 is, however, actively inhibited so it does not fire during ingestion. When a cycle of activity is subsequently triggered by stimulating the egestive input to the CPG B65 is excited and the latent effect on its excitability becomes apparent. B65 fires and cycles of activity are egestive (dark red) [32].
Negative biasing
Negative biasing is perhaps what would be expected when a task switch occurs after a persistent state has been created. In the feeding network it is a consequence of the fact that modulators are released during bouts of egestive activity [1] which produce persistent increases in the excitability and synaptic outputs of an egestive interneuron (the cell B20) [35].
These persistent modifications make B20 overactive when there is a subsequent attempt to generate ingestive motor programs [36] (Fig. 1A).
A recent study demonstrated that there is an additional ‘anticipatory’ circuit modification that also contributes to negative biasing [37]*. During bouts of egestive activity an outward current is induced in a motor neuron that is required for all types of feeding motor programs (the neuron B8). B8 is active during egestion, but only because it receives excitatory synaptic input. Thus, induction of the outward current is counterproductive during egestion. Because the current persists, the B8 excitability is still low when there is a subsequent attempt to task switch and B8 fires at a reduced frequency. This is now a ‘desirable’ effect since it contributes to negative biasing by making motor programs less ingestive. Although apparently counterproductive circuit modifications have not been widely reported, a recent computational study of the feeding network suggests that they may be more common than is currently recognized [38]*.
In summary, studies of egestive-ingestive task switching in Aplysia have characterized mechanisms that can impede task switching and lead to negative biasing. These mechanisms operate at both the motor neuron and interneuron level. At the interneuron level, negative biasing occurs when there is a persistent increase in the excitability of a neuron that promotes egestive activity. This neuron is then overactive when there is a subsequent attempt to task switch.
Positive biasing
In the other direction the biasing that is observed is positive, i.e., ingestive activity promotes the subsequent induction of at least a short bout of egestive activity [32]. To a large extent, positive biasing results from the fact that B20 is not the only egestive interneuron. A second interneuron, B65, can serve a similar function[39,40]. When ingestive motor programs are repeatedly induced, there is a persistent peptide-induced increase in the B65 excitability [32] (Fig. 1B). Since B65 is an egestive interneuron, it might be expected that this would disrupt ongoing ingestive activity. This does not happen because B65 is actively inhibited. As a result, the excitability increase has no immediate effect. However, when there is a subsequent switch to egestive activity B65 is excited rather than inhibited and the latent effect on excitability becomes apparent [32]. B65 fires at an elevated frequency and motor programs are highly egestive (Fig. 1B).
In essence, the asymmetry in task switching is a consequence of what has been referred to as network degeneracy, i.e., there is more than one set of circuit parameters that will produce a certain type of motor activity [41,42]. In particular, the egestive interneuron that patterns activity during positive biasing (B65) is not the same as the interneuron that patterns activity during negative biasing (B20) [43]. B65 differs from B20 in that during ingestive behavior it receives excitatory and inhibitory input in parallel. Previous descriptions of this type of arrangement have established that it can be important for generating sequences of behavior. For example, it is an important part of the suppression hierarchy that drives grooming in Drosophila [44–46]. Research in the feeding system extends these findings in that it shows that in addition to playing a role in ordering behavior, latent excitation can also play a role in determining parametric features of the behaviors in a sequence.
Positive biasing presumably occurs when animals make temporary alterations in feeding movements [7]. They would be analogous to the adjustments that vertebrates make when they alter locomotion to compensate for obstacles in the environment [47]. Although switching involves a cessation of one behavior and initiation of another, it differs from ‘quitting’ in that it is likely to be followed by a return to ingestion (rather than a period of inactivity). Thus, behavior is maintained despite the switching. A further question that has been addressed in the feeding network is, how does this occur?
Maintenance of feeding behavior during task switching
Data suggest that the ability of the feeding circuit to maintain activity is facilitated by its modular design. In particular, some modules in the feeding network are ‘behavior independent’, and are utilized during all types of motor programs [48]. This is the case for the neurons that move the radula back and forth in the buccal cavity. Radula protraction precedes radula retraction during both ingestive and egestive motor programs [49,50]. Consequently, a modification of the protraction (or retraction) circuitry will similarly impact all types of motor programs.
Because radula protraction occurs first, the processes that determine its induction constitute the ‘decision to feed’. These processes have been the subject of much investigation [51,52] and it has become apparent that the neuron B63 plays a key role. When ingestive and egestive inputs to the feeding CPG are activated, modulators are released that exert divergent effects that are important for selectively configuring activity (e.g., [35,53–55]). Additionally, however a recent study demonstrated that ingestive and egestive modulators also act convergently [56]*. Both types of substances increase the B63 excitability, a circuit modification that promotes program induction [57,58]. This suggests that as task switching occurs modulatory effects on B63 will be additive. Thus, activity is likely to be maintained by a type of feedforward excitation that does not depend on the nature of the behavior induced.
Retention of the ingestive state during task switching
A final question that we address here is, can a state be maintained during a brief switch to a different type of motor activity? Experiments that explored this issue in the feeding circuit focused on an experimentally advantageous motor neuron (the neuron B48). B48 is selectively active during ingestion, and there are persistent increases in its excitability when an ingestive state is induced [59,60]. Excitability changes persist for ~ 40 minutes (Fig. 2A) [60]. During this time task switching is possible, i.e., activation of an egestive input to the feeding CPG produces an immediate decrease in the B48 excitability and firing frequency (Fig. 2C) [60]. To determine whether the original (ingestive) state is retained during switches to egestive activity, excitability was measured after allowing time for the effects of egestive stimulation to dissipate (Fig. 2B, 2C) [60]. Excitability was still elevated (Fig. 2C). Thus, in B48, the ingestive state can be retained during a bout of egestive activity.
Figure 2.
(A) Ingestive state in neuron B48. Stimulation of an ingestive input to the feeding CPG (green bar) produces an increase in the excitability of B48 that persists for ~ 40 minutes (green plot to the right of the bar) [60]. As shown in the inset the increase is mediated by the induction of an inward sodium current [54,60]. The induction of the current is not PKA dependent and presumably results from direct gating of the channel by cAMP. (B) Egestive state in B48. Stimulation of an egestive input to the feeding CPG (red bar) produces a shorter lasting decrease in B48 excitability (red plot to the right of the bar) [60]. As shown in the inset the decrease is mediated by the induction of an outward potassium current [60]. (C) Retention of the ingestive state during ingestive-egestive task switching. Immediately after an ingestive-egestive switch (green/red bar) excitability is depressed (black plot to the immediate right of the bars) [60]. As shown in the top inset this is presumably a consequence of the induction of both the inward sodium and outward potassium current [60]. After effects of egestive input activation have dissipated excitability is still elevated and is the same as the excitability at a matched time point when is no switch (overlapping black and light green plots), i.e., the ingestive state is retained [60]. As shown in the bottom inset this is a consequence of the persistent induction of the inward sodium current [54,60]. The excitability plots are after Fig. 3 in [60].
Mechanistic experiments have demonstrated that increases in B48 excitability are mediated by the induction of a cAMP-dependent inward current (Fig. 2A, inset) [54,60]. Data strongly suggest that this current is directly gated by cAMP and is similar to a current characterized in other invertebrate neurons [61–66]. Retention of the ingestive state occurs as a result of the persistence of the cAMP signalling. (It does not, however, require PKA induction [54,60] as is commonly the case [9,67,68].)
When there is a switch to egestive activity the B48 firing frequency (and excitability) decrease (Fig. 2C). This occurs because an outward potassium current is induced (along with the inward current) (Fig. 2C, top inset) [54,60]. Thus, there is a brief period of time when there an overall decrease in net current. The outward current is not as persistent as the inward current. Effects of its induction wear off while the inward current is still present. Consequently, there is a return to a situation where the net current is inward (Fig. 2C, bottom inset). Thus, there is an interaction between persistent modulation and relatively short-lasting inhibition. This type of interaction also occurs in Drosophila where it determines the duration of a behavior (copulation) [69]. The feeding system data make an additional point. As long as the brief inhibition does not negatively impact the original modulatory effect it will be possible to return to the original state after a task switch.
In summary, studies of ingestive-egestive task switching have characterized a mechanism that can promote rather than impede task switching. This type of positive biasing occurs because the induction of ingestive activity has a latent effect. In addition to increases in the excitability of interneurons that promote ingestive activity, there is also an increase in the excitability of an egestive interneuron. Under physiological conditions positive biasing presumably occurs during ingestive behavior and allows animals to make brief adjustments that allow them to cope with difficulties that are encountered when they try to pull food into the buccal cavity. In this situation it is presumably beneficial for the original state to be maintained despite the task switching.
Concluding Remarks
Although task switching has been most extensively studied in the context of motor control it has been described in other contexts. For example, it occurs when humans are performing cognitive tasks [5,70]. Often task switching results in some type of biasing, i.e., the execution of the behavior that occurs after the switch is impacted by the behavior that occurs before the switch. Biasing can be either negative or positive. Negative effects often have undesirable consequences and are referred to as the ‘cost’ of task switching. It has been argued that mechanistic studies that seek to determine how costs arise are valuable since they provide insight into strategies that can be used to minimize them (e.g., [70]). Work in experimentally advantageous model systems such as the feeding system of Aplysia are likely to make an important contribution in this regard.
Highlights.
Neuromodulators induce persistent ingestive and egestive states that impact subsequent task switching
Negative biasing is observed after an egestive-ingestive switch
Positive biasing is observed after an ingestive-egestive switch
The asymmetry in biasing is a consequence of network degeneracy (there is more than one set of egestive circuit parameters)
Acknowledgements
This research was supported by the National Institutes of Health (Grants NS066587, NS070583, and NS118606) and the National Natural Science Foundation of China (Grants 32171011, 62250004, 31861143036, 31671097, 31371104).
Footnotes
The authors declare no competing financial interests.
There are no declarations of interest for any of the authors.
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References
- 1.Cropper EC, Jing J, Vilim FS, Weiss KR: Peptide Cotransmitters as Dynamic, Intrinsic Modulators of Network Activity. Front Neural Circuits 2018, 12:78. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Chan-Andersen PC, Romanova EV, Rubakhin SS, Sweedler JV: Profiling 26,000 Aplysia californica neurons by single cell mass spectrometry reveals neuronal populations with distinct neuropeptide profiles. J Biol Chem 2022, 298:102254. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Jiang HM, Yang Z, Xue YY, Wang HY, Guo SQ, Xu JP, Li YD, Fu P, Ding XY, Yu K, et al. : Identification of an allatostatin C signaling system in mollusc Aplysia. Sci Rep 2022, 12:1213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Marder E, Kedia S, Morozova EO: New insights from small rhythmic circuits. Curr Opin Neurobiol 2022, 76:102610. [DOI] [PubMed] [Google Scholar]
- 5.Shine JM, Breakspear M, Bell PT, Ehgoetz Martens KA, Shine R, Koyejo O, Sporns O, Poldrack RA: Human cognition involves the dynamic integration of neural activity and neuromodulatory systems. Nat Neurosci 2019, 22:289–296. [DOI] [PubMed] [Google Scholar]
- 6.Hurwitz I, Harel A, Markowitz S, Noy O, Susswein AJ: Control of feeding in aplysia with ad libitum access to food: presence of food increases the intervals between feeding bouts. J Neurophysiol 2006, 95:106–118. [DOI] [PubMed] [Google Scholar]
- 7.Proekt A, Wong J, Zhurov Y, Kozlova N, Weiss KR, Brezina V: Predicting adaptive behavior in the environment from central nervous system dynamics. PLoS One 2008, 3:e3678. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Wei D, Talwar V, Lin D: Neural circuits of social behaviors: Innate yet flexible. Neuron 2021, 109:1600–1620. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Bodas DS, Maduskar A, Kaniganti T, Wakhloo D, Balasubramanian A, Subhedar N, Ghose A: Convergent Energy State-Dependent Antagonistic Signaling by Cocaine- and Amphetamine-Regulated Transcript (CART) and Neuropeptide Y (NPY) Modulates the Plasticity of Forebrain Neurons to Regulate Feeding in Zebrafish. J Neurosci 2023, 43:1089–1110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Harnie J, Audet J, Klishko AN, Doelman A, Prilutsky BI, Frigon A: The Spinal Control of Backward Locomotion. J Neurosci 2021, 41:630–647. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Hsu LJ, Zelenin PV, Lyalka VF, Vemula MG, Orlovsky GN, Deliagina TG: Neural mechanisms of single corrective steps evoked in the standing rabbit. Neuroscience 2017, 347:85–102. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ji N, Madan GK, Fabre GI, Dayan A, Baker CM, Kramer TS, Nwabudike I, Flavell SW: A neural circuit for flexible control of persistent behavioral states. Elife 2021, 10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Marques JC, Li M, Schaak D, Robson DN, Li JM: Internal state dynamics shape brainwide activity and foraging behaviour. Nature 2020, 577:239–243. [DOI] [PubMed] [Google Scholar]
- 14.Gill JP, Chiel HJ: Rapid Adaptation to Changing Mechanical Load by Ordered Recruitment of Identified Motor Neurons. eNeuro 2020, 7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Webster-Wood VA, Gill JP, Thomas PJ, Chiel HJ: Control for multifunctionality: bioinspired control based on feeding in Aplysia californica. Biol Cybern 2020, 114:557–588. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Momohara Y, Neveu CL, Chen HM, Baxter DA, Byrne JH: Specific Plasticity Loci and Their Synergism Mediate Operant Conditioning. J Neurosci 2022, 42:1211–1223. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Costa RM, Baxter DA, Byrne JH: Neuronal population activity dynamics reveal a low-dimensional signature of operant learning in Aplysia. Commun Biol 2022, 5:90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.McManus JM, Chiel HJ, Susswein AJ: Successful and unsuccessful attempts to swallow in a reduced Aplysia preparation regulate feeding responses and produce memory at different neural sites. Learn Mem 2019, 26:151–165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Tam S, Hurwitz I, Chiel HJ, Susswein AJ: Multiple Local Synaptic Modifications at Specific Sensorimotor Connections after Learning Are Associated with Behavioral Adaptations That Are Components of a Global Response Change. J Neurosci 2020, 40:4363–4371. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Chatterji R, Khoury S, Salas E, Wainwright ML, Mozzachiodi R: Critical role of protein kinase G in the long-term balance between defensive and appetitive behaviors induced by aversive stimuli in Aplysia. Behav Brain Res 2020, 383:112504. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Farruggella J, Acebo J, Lloyd L, Wainwright ML, Mozzachiodi R: Role of nitric oxide in the induction of the behavioral and cellular changes produced by a common aversive stimulus in Aplysia. Behav Brain Res 2019, 360:341–353. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Goldner A, Farruggella J, Wainwright ML, Mozzachiodi R: cGMP mediates short- and long-term modulation of excitability in a decision-making neuron in Aplysia. Neurosci Lett 2018, 683:111–118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Briskin-Luchinsky V, Tam S, Shabbat S, Hurwitz I, Susswein AJ: NO is required for memory formation and expression of memory, and for minor behavioral changes during training with inedible food in Aplysia. Learn Mem 2018, 25:206–213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Cropper EC, Friedman AK, Jing J, Perkins MH, Weiss KR: Neuromodulation as a mechanism for the induction of repetition priming. Curr Opin Neurobiol 2014, 29:33–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.**.Crossley M, Staras K, Kemenes G: A central control circuit for encoding perceived food value. Sci Adv 2018, 4:eaau9180. [DOI] [PMC free article] [PubMed] [Google Scholar]; These experiments, conducted in the freshwater snail Lymnaea, demonstrate that the activity of a dopaminergic neuron can bias network activity towards the induction of egestive activity. For example, if the actions of these neurons are blocked satiated animals can exhibit a hungry phenotype.
- 26.**.Sorrells TR, Pandey A, Rosas-Villegas A, Vosshall LB: A persistent behavioral state enables sustained predation of humans by mosquitoes. Elife 2022, 11. [DOI] [PMC free article] [PubMed] [Google Scholar]; This report studies host seeking behavior in female mosquitoes and demonstrates that brief application of a stimulus induces a persistent predatory state that persists for minutes. As a result of the induction of this state host seeking behavior is maintained despite the fact that sensory cues are brief and intermittent under natural conditions.
- 27.*.Deutsch D, Pacheco D, Encarnacion-Rivera L, Pereira T, Fathy R, Clemens J, Girardin C, Calhoun A, Ireland E, Burke A, et al. : The neural basis for a persistent internal state in Drosophila females. Elife 2020, 9. [DOI] [PMC free article] [PubMed] [Google Scholar]; In the feeding network internal states are induced by neuromodulation. Although this is often the case, this report and [28] illustrate that persistent changes in behavior can also be driven by persistent neural activity. In particular, this study identifies a circuit of neurons that is persistently active in the female brain that impacts behavior in the presence of males.
- 28.*.Zhang SX, Rogulja D, Crickmore MA: Recurrent Circuitry Sustains Drosophila Courtship Drive While Priming Itself for Satiety. Curr Biol 2019, 29:3216–3228 e3219. [DOI] [PMC free article] [PubMed] [Google Scholar]; These experiments study males and demonstrate that mating drive is stored in a recurrent excitation loop.
- 29.Flavell SW, Gogolla N, Lovett-Barron M, Zelikowsky M: The emergence and influence of internal states. Neuron 2022, 110:2545–2570. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.**.Liu Q, Yang X, Luo M, Su J, Zhong J, Li X, Chan RHM, Wang L: An iterative neural processing sequence orchestrates feeding. Neuron 2023. [DOI] [PubMed] [Google Scholar]; These investigators analyze mouse behavior using a machine-learning-assisted feeding behavior tracking system that also allows optogenetic manipulation of neurons. They show that feeding behavior in general can be surprisingly fragmented and include bouts of exploratory activity.
- 31.Proekt A, Brezina V, Weiss KR: Dynamical basis of intentions and expectations in a simple neuronal network. Proc Natl Acad Sci U S A 2004, 101:9447–9452. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Dacks AM, Weiss KR: Latent modulation: a basis for non-disruptive promotion of two incompatible behaviors by a single network state. J Neurosci 2013, 33:3786–3798. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Iwanir S, Ruach R, Itskovits E, Pritz CO, Bokman E, Zaslaver A: Irrational behavior in C. elegans arises from asymmetric modulatory effects within single sensory neurons. Nat Commun 2019, 10:3202. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Hoffmann MA, Koch I, Huestegge L: Are some effector systems harder to switch to? In search of cost asymmetries when switching between manual, vocal, and oculomotor tasks. Mem Cognit 2022, 50:1563–1577. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Wu JS, Vilim FS, Hatcher NG, Due MR, Sweedler JV, Weiss KR, Jing J: Composite modulatory feedforward loop contributes to the establishment of a network state. J Neurophysiol 2010, 103:2174–2184. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Proekt A, Jing J, Weiss KR: Multiple contributions of an input-representing neuron to the dynamics of the aplysia feeding network. J Neurophysiol 2007, 97:3046–3056. [DOI] [PubMed] [Google Scholar]
- 37.*.Wang Y, Barry MA, Cambi M, Weiss KR, Cropper EC: An Anticipatory Circuit Modification That Modifies Subsequent Task Switching. J Neurosci 2021, 41:2152–2163. [DOI] [PMC free article] [PubMed] [Google Scholar]; In part, negative biasing in the feeding network is a result of a persistent increase in the excitability of an interneuron. This study demonstrates that there is an additional contribution that results from a persistent modification of the excitability of a motor neuron. The motor neuron effect is interesting in that it is counterproductive at the time that it is induced. Its impact is only desireable after the task switch. Thus it serves an ‘anticipatory ‘ function.
- 38.*.Costa RM, Baxter DA, Byrne JH: Computational model of the distributed representation of operant reward memory: combinatoric engagement of intrinsic and synaptic plasticity mechanisms. Learn Mem 2020, 27:236–249. [DOI] [PMC free article] [PubMed] [Google Scholar]; In this computational report the investigators study learning induced changes in the feeding network and manipulate individual sites of plasticity to determine how each site impacted the establishment of the overall engram. Although most sites positively contributed to the engram one did not.
- 39.Diaz-Rios M, Miller MW: Rapid dopaminergic signaling by interneurons that contain markers for catecholamines and GABA in the feeding circuitry of Aplysia. J Neurophysiol 2005, 93:2142–2156. [DOI] [PubMed] [Google Scholar]
- 40.Jing J, Weiss KR: Neural mechanisms of motor program switching in Aplysia. J Neurosci 2001, 21:7349–7362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Cropper EC, Dacks AM, Weiss KR: Consequences of degeneracy in network function. Curr Opin Neurobiol 2016, 41:62–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Calabrese RL: Neuronal networks: Degeneracy unleashed. Curr Biol 2021, 31:R1439–R1441. [DOI] [PubMed] [Google Scholar]
- 43.**.Wang Y, Weiss KR, Cropper EC: Network Degeneracy and the Dynamics of Task Switching in the Feeding Circuit in Aplysia. J Neurosci 2019, 39:8705–8716. [DOI] [PMC free article] [PubMed] [Google Scholar]; This report demonstrates that there is degeneracy in the feeding network in that there are two sets of circuit parameters that induce egestive activity. Further, these experiments demonstrate that the mechanisms used to pattern activity can determine how readily subsequent task switching occurs.
- 44.Zhang N, Guo L, Simpson JH: Spatial Comparisons of Mechanosensory Information Govern the Grooming Sequence in Drosophila. Curr Biol 2020, 30:988–1001 e1004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Mueller JM, Zhang N, Carlson JM, Simpson JH: Variation and Variability in Drosophila Grooming Behavior. Front Behav Neurosci 2021, 15:769372. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Seeds AM, Ravbar P, Chung P, Hampel S, Midgley FM Jr., Mensh BD, Simpson JH: A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila. Elife 2014, 3:e02951. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Berg EM, Mrowka L, Bertuzzi M, Madrid D, Picton LD, El Manira A: Brainstem circuits encoding start, speed, and duration of swimming in adult zebrafish. Neuron 2023, 111:372–386 e374. [DOI] [PubMed] [Google Scholar]
- 48.Jing J, Cropper EC, Hurwitz I, Weiss KR: The construction of movement with behavior-specific and behavior-independent modules. J Neurosci 2004, 24:6315–6325. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Morton DW, Chiel HJ: The timing of activity in motor neurons that produce radula movements distinguishes ingestion from rejection in Aplysia. J Comp Physiol A 1993, 173:519–536. [DOI] [PubMed] [Google Scholar]
- 50.Morton DW, Chiel HJ: In vivo buccal nerve activity that distinguishes ingestion from rejection can be used to predict behavioral transitions in Aplysia. J Comp Physiol A 1993, 172:17–32. [DOI] [PubMed] [Google Scholar]
- 51.Susswein AJ, Hurwitz I, Thorne R, Byrne JH, Baxter DA: Mechanisms underlying fictive feeding in aplysia: coupling between a large neuron with plateau potentials activity and a spiking neuron. J Neurophysiol 2002, 87:2307–2323. [DOI] [PubMed] [Google Scholar]
- 52.Hurwitz I, Kupfermann I, Susswein AJ: Different roles of neurons B63 and B34 that are active during the protraction phase of buccal motor programs in Aplysia californica. J Neurophysiol 1997, 78:1305–1319. [DOI] [PubMed] [Google Scholar]
- 53.Friedman AK, Weiss KR, Cropper EC: Specificity of repetition priming: the role of chemical coding. J Neurosci 2015, 35:6326–6334. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Perkins MH, Weiss KR, Cropper EC: Persistent effects of cyclic adenosine monophosphate are directly responsible for maintaining a neural network state. Sci Rep 2019, 9:9058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Siniscalchi MJ, Cropper EC, Jing J, Weiss KR: Repetition priming of motor activity mediated by a central pattern generator: the importance of extrinsic vs. intrinsic program initiators. J Neurophysiol 2016, 116:1821–1830. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Due MR, Wang Y, Barry MA, Jing J, Reaver CN, Weiss KR, Cropper EC: Convergent effects of neuropeptides on the feeding central pattern generator of Aplysia californica. J Neurophysiol 2022, 127:1445–1459. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Bedecarrats A, Puygrenier L, Castro O’Byrne J, Lade Q, Simmers J, Nargeot R: Organelle calcium-derived voltage oscillations in pacemaker neurons drive the motor program for food-seeking behavior in Aplysia. Elife 2021, 10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Sieling F, Bedecarrats A, Simmers J, Prinz AA, Nargeot R: Differential roles of nonsynaptic and synaptic plasticity in operant reward learning-induced compulsive behavior. Curr Biol 2014, 24:941–950. [DOI] [PubMed] [Google Scholar]
- 59.Friedman AK, Zhurov Y, Ludwar B, Weiss KR: Motor outputs in a multitasking network: relative contributions of inputs and experience-dependent network states. J Neurophysiol 2009, 102:3711–3727. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Perkins MH, Cropper EC, Weiss KR: Cellular Effects of Repetition Priming in the Aplysia Feeding Network Are Suppressed during a Task-Switch But Persist and Facilitate a Return to the Primed State. J Neurosci 2018, 38:6475–6490. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Gillette R, Green DJ: Calcium dependence of voltage sensitivity in adenosine 3’,5’-cyclic phosphate-stimulated sodium current in Pleurobranchaea. J Physiol 1987, 393:233–245. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Green DJ, Gillette R: Regulation of cAMP-stimulated ion current by intracellular pH, Ca2+, and calmodulin blockers. J Neurophysiol 1988, 59:248–258. [DOI] [PubMed] [Google Scholar]
- 63.Green DJ, Gillette R: Patch- and voltage-clamp analysis of cyclic AMP-stimulated inward current underlying neurone bursting. Nature 1983, 306:784–785. [DOI] [PubMed] [Google Scholar]
- 64.Huang RC, Gillette R: Co-regulation of cAMP-activated Na+ current by Ca2+ in neurones of the mollusc Pleurobranchaea. J Physiol 1993, 462:307–320. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Sudlow LC, Huang RC, Green DJ, Gillette R: cAMP-activated Na+ current of molluscan neurons is resistant to kinase inhibitors and is gated by cAMP in the isolated patch. J Neurosci 1993, 13:5188–5193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Kehoe J: Cyclic AMP-induced slow inward current: its synaptic manifestation in Aplysia neurons. J Neurosci 1990, 10:3208–3218. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Zhang SX, Lutas A, Yang S, Diaz A, Fluhr H, Nagel G, Gao S, Andermann ML: Hypothalamic dopamine neurons motivate mating through persistent cAMP signalling. Nature 2021, 597:245–249. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Thornquist SC, Pitsch MJ, Auth CS, Crickmore MA: Biochemical evidence accumulates across neurons to drive a network-level eruption. Mol Cell 2021, 81:675–690 e678. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Crickmore MA, Vosshall LB: Opposing dopaminergic and GABAergic neurons control the duration and persistence of copulation in Drosophila. Cell 2013, 155:881–893. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Leber AB, Turk-Browne NB, Chun MM: Neural predictors of moment-to-moment fluctuations in cognitive flexibility. Proc Natl Acad Sci U S A 2008, 105:13592–13597. [DOI] [PMC free article] [PubMed] [Google Scholar]