Toward locating the source of serotonergic axons in the tail nerve of Aplysia

Nociceptive Biology of Molluscs and Arthropods: Evolutionary Clues About Functions and Mechanisms Potentially Related to Pain

Important insights into the selection pressures and core molecular modules contributing to the evolution of pain-related processes have come from studies of nociceptive systems in several molluscan and arthropod species. These phyla, and the chordates that include humans, last shared a common ancestor approximately 550 million years ago. Since then, animals in these phyla have continued to be subject to traumatic injury, often from predators, which has led to similar adaptive behaviors (e.g., withdrawal, escape, recuperative behavior) and physiological responses to injury in each group. Comparisons across these taxa provide clues about the contributions of convergent evolution and of conservation of ancient adaptive mechanisms to general nociceptive and pain-related functions. Primary nociceptors have been investigated extensively in a few molluscan and arthropod species, with studies of long-lasting nociceptive sensitization in the gastropod, Aplysia, and the insect, Drosophila, being especially fruitful. In Aplysia, nociceptive sensitization has been investigated as a model for aversive memory and for hyperalgesia. Neuromodulator-induced, activity-dependent, and axotomy-induced plasticity mechanisms have been defined in synapses, cell bodies, and axons of Aplysia primary nociceptors. Studies of nociceptive sensitization in Drosophila larvae have revealed numerous molecular contributors in primary nociceptors and interacting cells. Interestingly, molecular contributors examined thus far in Aplysia and Drosophila are largely different, but both sets overlap extensively with those in mammalian pain-related pathways. In contrast to results from Aplysia and Drosophila, nociceptive sensitization examined in moth larvae (Manduca) disclosed central hyperactivity but no obvious peripheral sensitization of nociceptive responses. Squid (Doryteuthis) show injury-induced sensitization manifested as behavioral hypersensitivity to tactile and especially visual stimuli, and as hypersensitivity and spontaneous activity in nociceptor terminals. Temporary blockade of nociceptor activity during injury subsequently increased mortality when injured squid were exposed to fish predators, providing the first demonstration in any animal of the adaptiveness of nociceptive sensitization. Immediate responses to noxious stimulation and nociceptive sensitization have also been examined behaviorally and physiologically in a snail (Helix), octopus (Adopus), crayfish (Astacus), hermit crab (Pagurus), and shore crab (Hemigrapsus). Molluscs and arthropods have systems that suppress nociceptive responses, but whether opioid systems play antinociceptive roles in these phyla is uncertain.

Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period

Oscillatory neurons integrate their synaptic inputs in fundamentally different ways than normally quiescent neurons. We show that the oscillation period of invertebrate endogenous pacemaker neurons wanders, producing random fluctuations in the interspike intervals (ISI) on a time scale of seconds to minutes, which decorrelates pairs of neurons in hybrid circuits constructed using the dynamic clamp. The autocorrelation of the ISI sequence remained high for many ISIs, but the autocorrelation of the ΔISI series had on average a single nonzero value, which was negative at a lag of one interval. We reproduced these results using a simple integrate and fire (IF) model with a stochastic population of channels carrying an adaptation current with a stochastic component that was integrated with a slow time scale, suggesting that a similar population of channels underlies the observed wander in the period. Using autoregressive integrated moving average (ARIMA) models, we found that a single integrator and a single moving average with a negative coefficient could simulate both the experimental data and the IF model. Feeding white noise into an integrator with a slow time constant is sufficient to produce the autocorrelation structure of the ISI series. Moreover, the moving average clearly accounted for the autocorrelation structure of the ΔISI series and is biophysically implemented in the IF model using slow stochastic adaptation. The observed autocorrelation structure may be a neural signature of slow stochastic adaptation, and wander generated in this manner may be a general mechanism for limiting episodes of synchronized activity in the nervous system.