Handbook of psychopharmacology

Until recently, it has been impossible to approach learning with the techniques of cell biology. During the past several years, elementary forms of learning have been analyzed in higher invertebrates. Their nervous systems allow the experimental study of behavioral, neurophysiological, morphological, biochemical, and genetic components of the functional (plastic) changes underlying learning. In this review, we focus primarily on short-term sensitization of the gill and siphon reflex in the marine mollusk, Aplysia californica. Analyses of this form of learning provide direct evidence that protein phosphorylation dependent on cyclic adenosine monophosphate can modulate synaptic action. These studies also suggest how the molecular mechanisms for this short-term form of synaptic plasticity can be extended to explain both long-term memory and classical conditioning.

https://science.sciencemag.org/content/sci/218/4571/433.full.pdf

Molecular Biology of Learning: Modulation of Transmitter Release.

Cognitive Neuroscience and the Study of Memory

Recent studies of animals with complex nervous systems, including humans and other primates, have improved our understanding of how the brain accomplishes learning and memory. Major themes of recent work include the locus of memory storage, the taxonomy of memory, the distinction between declarative and procedural knowledge, and the question of how memory changes with time, that is, the concepts of forgetting and consolidation. An important recent advance is the development of an animal model of human amnesia in the monkey. The animal model, together with newly available neuropathological information from a well-studied human patient, has permitted the identification of brain structures and connections involved in memory functions.

Mechanisms of memory

In the search for principles of pattern generation in complex biological systems, an operational approach is presented that embraces both theory and experiment. The central mathematical concepts of self-organization in nonequilibrium systems (including order parameter dynamics, stability, fluctuations, and time scales) are used to show how a large number of empirically observed features of temporal patterns can be mapped onto simple low-dimensional (stochastic, nonlinear) dynamical laws that are derivable from lower levels of description. The theoretical framework provides a language and a strategy, accompanied by new observables, that may afford an understanding of dynamic patterns at several scales of analysis (including behavioral patterns, neural networks, and individual neurons) and the linkage among them.

https://science.sciencemag.org/content/sci/239/4847/1513.full.pdf

Dynamic pattern generation in behavioral and neural systems

1.

Lobsters that are tethered in place on a treadmill (Fig. 3) walk against the direction of belt movement (Table 2). Forward and backward locomotion over the full range of step frequencies can be controlled by this method, even in the absence of visual input. The passive traction provided by a moving substrate is therefore an effective stimulus for walking and presumably operates in parallel with previously described optomotor pathways to provide positive feedback reinforcement of locomotory behavior.




2.

The movements (Figs. 1, 6) and muscular anatomy (Fig. 2) of a lobster walking leg are described. On the basis of simultaneous extracellular recording from several leg muscles (Fig. 5), and motion picture analysis, the overall patterns of joint movement and muscular coordination underlying forward and backward walking are described (Figs. 5, 6, 7).




3.

Some muscles that are synergic for forward walking are antagonistic for backward walking (Figs. 6, 7). Similarly movements that are synergic for lateral walking on the leading side are antagonistic for lateral walking on the trailing side (Fig. 6).




4.

Quantitative analysis of leg movements (Fig. 9) and electromyograms (Fig. 10) have shown that the walking muscles can be subdivided into three different functional classes: return stroke muscles, which exhibit bursts of relatively constant duration irrespective of step frequency (Fig. 10A); power stroke muscles in which burst duration varies linearly with step frequency (Fig. 10B); and bifunctional muscles, which exhibit the discharge characteristics of either return or power stroke muscles, depending on the direction of walking (Fig. 10C).




5.

Several lines of evidence (Table 3, Figs. 6, 7, 9, 10, 12) suggest that the limb elevator motoneurones (or their central antecedents) function as the central pacemaker of the walking system, and that other cyclic leg movements are appended to the basic elevation/depression cycle as appropriate to the direction of walking. Evidence is presented that proprioceptive inputs provided by passive traction are capable of controlling the direction of locomotion (Table 2), and determining the periodicity of stepping (Fig. 4), by altering the duration of powerstroke bursts (Figs. 9, 10, 15).

Neuronal control of locomotion in the lobster,Homarus americanus

Command neurons that cause rhythmic feeding behavior in the marine mollusc Pleurobranchaea californica have been identified in the cerebropleural ganglion (brain). Intracellular stimulation of single command neurons in isolated nervous systems, semi-intact prepartions, and restrained whole animals causes the same rhythmic motor output pattern as occurs during feeding. During this motor output pattern, action potentials recorded intracellularly from the command neurons occur in cyclic bursts that are phase-locked with the feeding rhythm. This modulation results from repetitive, alternating bursts of excitatory and inhibitory postsynaptic potentials, which are caused at least in part by synaptic feedback to the command neurons from identified classes of neurons in the feeding network. Central feedback to command neurons from the motor network they excite provides a possible general physiological mechanism for the sustained oscillation of neural networks controlling cyclic behavior.

https://science.sciencemag.org/content/sci/199/4330/798.full.pdf

Command neurons in Pleurobranchaea receive synaptic feedback from the motor network they excite

The metacerebral giant (MCG) neurons of the molluskPleurobranchaea have been analyzed using a wide range of methods (cobalt staining, histochemical, biophysical and electrophysiological) on several types of preparations (isolated nervous systems, semi-intact preparations, and behaving whole-animal preparations). The MCG is serotonergic. The bilaterally-symmetrical neurons have somata in the anterior brain. Each MCG neuron sends an axon out the ipsilateral mouth nerve of the brain and also into the ipsilateral cerebrobuccal connective which descends to the buccal ganglion. The descending axon sends one or more branches out most buccal nerves.

The role of the metacerebral giant neuron in the feeding behavior ofPleurobranchaea

Food stimuli normally excite the command neurons of Pleurobranchaea that cause feeding. In contrast, the same food stimuli selectively inhibit these neurons in specimens that have been trained to suppress feeding and withdraw from food by means of an avoidance conditioning paradigm consisting of paired food and conditional shock. Food stimuli excite the feeding command neurons of yoked control specimens exposed to unpaired food and shock, but inhibit the feeding command neurons of untrained specimens that have been satiated with food. These results suggest that the command neurons serve as a neural locus at which an animal's behavior is modulated by past experiences. These results also establish a neural correlate of behavioral plasticity, in the form of synaptic inhibition of the command neurons.

https://science.sciencemag.org/content/sci/199/4330/801.full.pdf

Neural correlate of behavioral plasticity in command neurons of Pleurobranchaea.

Feeding behavior and the effect of its occurrence on other, unrelated behaviors were studied in the carnivorous marine gastropodPleurobranchaea calif arnica. The threshold of the feeding response is low and stable: it does not change in a circadian fashion (Fig. 1); it does not change during different behavioral states such as mating (Table 4) and quiescence (“sleep” Table 5); the threshold does not change following aversive electric shock to the oral veil (Table 1); and it does not change with repeated application of food stimuli (Fig. 2). In the present paper only two physiological variables were found to elevate the feeding response threshold; excessive mechanical stimulation (Figs. 3, 4) and satiation with food (Fig. 5).

William J. Davis

Papers

Neuronal control of locomotion in the lobster,Homarus americanus

Command neurons in Pleurobranchaea receive synaptic feedback from the motor network they excite

The role of the metacerebral giant neuron in the feeding behavior ofPleurobranchaea

Neural correlate of behavioral plasticity in command neurons of Pleurobranchaea.

The behavioral hierarchy of the molluskPleurobranchaea