Flexible processing of sensory information induced by axo-axonic synapses on afferent fibers

Presynaptic inhibition of olfactory sensory neurons: new mechanisms and potential functions

Presynaptic inhibition is the suppression of neurotransmitter release from a neuron by inhibitory input onto its presynaptic terminal. In the olfactory system, the primary sensory afferents from the olfactory neuroepithelium to the brain's olfactory bulb are strongly modulated by a presynaptic inhibition that has been studied extensively in brain slices and in vivo. In rodents, this inhibition is mediated by γ-amino butyric acid (GABA) and dopamine released from bulbar interneurons. The specialized GABAergic circuit is now well understood to include a specific subset of GAD65-expressing periglomerular interneurons that stimulate presynaptic GABAB receptors to reduce presynaptic calcium conductance. This inhibition is organized to permit the selective modulation of neurotransmitter release from specific populations of olfactory sensory neurons based on their odorant receptor expression, includes specialized microcircuits to create a tonically active inhibition and a separate feedback inhibition evoked by sensory input, and can be modulated by centrifugal projections from other brain regions. Olfactory nerve output can also be modulated by dopaminergic circuitry, but this literature is more difficult to interpret. Presynaptic inhibition of olfactory afferents may extend their dynamic range but could also create state-dependent or odorant-specific sensory filters on primary sensory representations. New directions exploring this circuit's role in olfactory processing are discussed.

Inhibition of afferent transmission in the feeding circuitry of aplysia: persistence can be as important as size

We are studying afferent transmission from a mechanoafferent, B21, to a follower, B8. During motor programs, afferent transmission is regulated so that it does not always occur. Afferent transmission is eliminated when spike propagation in B21 fails, i.e., when spike initiation is inhibited in one output region-B21's lateral process. Spike initiation in the lateral process is inhibited by the B52 and B4/5 cells. Individual B52 and B4/5-induced inhibitory postsynaptic potentials (IPSPs) in B21 differ. For example, the peak amplitude of a B4/5-induced IPSP is four times the amplitude of a B52 IPSP. Nevertheless, when interneurons fire in bursts at physiological (i.e., low) frequencies, afferent transmission is most effectively reduced by B52. Although individual B52-induced IPSPs are small, they have a long time constant and summate at low firing frequencies. Once IPSPs summate, they effectively block afferent transmission. In contrast, individual B4/5-induced IPSPs have a relatively short time constant and do not summate at low frequencies. B52 and B4/5 therefore differ in that once synaptic input from B52 becomes effective, afferent transmission is continuously inhibited. In contrast, periods of B4/5-induced inhibition are interspersed with relatively long intervals in which inhibition does not occur. Consequently, the probability that afferent transmission will be inhibited is low. In conclusion, it is widely recognized that afferent transmission can be regulated by synaptic input. Our experiments are, however, unusual in that they relate specific characteristics of postsynaptic potentials to functional inhibition. In particular we demonstrate the potential importance of the IPSP time constant.

Frequency-dependent selection of alternative spinal pathways with common periodic sensory input

Electrical stimulation of the lumbar cord at distinct frequency ranges has been shown to evoke either rhythmical, step-like movements (25-50 Hz) or a sustained extension (5-15 Hz) of the paralysed lower limbs in complete spinal cord injured subjects. Frequency-dependent activation of previously "silent" spinal pathways was suggested to contribute to the differential responsiveness to distinct neuronal "codes" and the modifications in the electromyographic recordings during the actual implementation of the evoked motor tasks. In the present study we examine this suggestion by means of a simplified biology-based neuronal network. Involving two basic mechanisms, temporal summation of synaptic input and presynaptic inhibition, the model exhibits several patterns of mono- and/or oligo-synaptic motor output in response to different interstimulus intervals. It thus reproduces fundamental input-output features of the lumbar cord isolated from the brain. The results confirm frequency-dependent spinal pathway selection as a simple mechanism which enables the cord to respond to distinct neuronal codes with different motor behaviours and to control the actual performance of the latter.

Adaptive motor control in crayfish

This article reviews the principles that rule the organization of motor commands that have been described over the past five decades in crayfish. The adaptation of motor behaviors requires the integration of sensory cues into the motor command. The respective roles of central neural networks and sensory feedback are presented in the order of increasing complexity. The simplest circuits described are those involved in the control of a single joint during posture (negative feedback-resistance reflex) and movement (modulation of sensory feedback and reversal of the reflex into an assistance reflex). More complex integration is required to solve problems of coordination of joint movements in a pluri-segmental appendage, and coordination of different limbs and different motor systems. In addition, beyond the question of mechanical fitting, the motor command must be appropriate to the behavioral context. Therefore, sensory information is used also to select adequate motor programs. A last aspect of adaptability concerns the possibility of neural networks to change their properties either temporarily (such on-line modulation exerted, for example, by presynaptic mechanisms) or more permanently (such as plastic changes that modify the synaptic efficacy). Finally, the question of how "automatic" local component networks are controlled by descending pathways, in order to achieve behaviors, is discussed.

Axons as computing devices: basic insights gained from models

Detailed models of single neurons are typically focused on the dendritic tree and ignore the axonal tree, assuming that the axon is a simple transmission line. In the last 40 years, however, several theoretical and experimental studies have suggested that axons could implement information processing tasks by exploiting: 1) the time delay in action potential (AP) propagation along the axon; 2) the differential filtering of APs into the axonal subtrees; and 3) their activity-dependent excitability. Models for axonal trees have attempted to examine the feasibility of these ideas. However, because the physiological and anatomical data on axons are seriously limited, realistic models of axons have not been developed. The present paper summarizes the main insights that were gained from simplified models of axons; it also highlights the stochastic nature of axons, a topic that was largely neglected in classical models of axons. The advance of new experimental techniques makes it now possible to pay a very close experimental visit to axons. Theoretical tools and fast computers enable to go beyond the simplified models and to construct realistic models of axons. When tightly linked, experiments and theory will help to unravel how axons share the information processing tasks that single neurons implement.