Visual cues from faces provide important social information relating to individual identity, sexual attraction and emotional state. Behavioural and neurophysiological studies on both monkeys and sheep have shown that specialized skills and neural systems for processing these complex cues to guide behaviour have evolved in a number of mammals and are not present exclusively in humans. Indeed, there are remarkable similarities in the ways that faces are processed by the brain in humans and other mammalian species. While human studies with brain imaging and gross neurophysiological recording approaches have revealed global aspects of the face-processing network, they cannot investigate how information is encoded by specific neural networks. Single neuron electrophysiological recording approaches in both monkeys and sheep have, however, provided some insights into the neural encoding principles involved and, particularly, the presence of a remarkable degree of high-level encoding even at the level of a specific face. Recent developments that allow simultaneous recordings to be made from many hundreds of individual neurons are also beginning to reveal evidence for global aspects of a population-based code. This review will summarize what we have learned so far from these animalbased studies about the way the mammalian brain processes the faces and the emotions they can communicate, as well as associated capacities such as how identity and emotion cues are dissociated and how face imagery might be generated. It will also try to highlight what questions and advances in knowledge still challenge us in order to provide a complete understanding of just how brain networks perform this complex and important social recognition task.
BackgroundHow oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes.ResultsFollowing learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance.ConclusionsFace discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs.
In the stick insect, Cuniculina impigra, intracellular recordings from mesothoracic motoneurons that control flexion and extension of the tibia and depression and levation of the trochantero-femur were made while the leg performed walking-like movements on a treadband or stereotyped rhythmic searching movements. We were interested in how synaptic input and intrinsic properties contribute to form the activity pattern of motoneurons during rhythmic leg movements without sensory feedback from other legs. During searching and walking, motoneurons expressed a rhythmic bursting pattern that was formed by a depolarizing input followed by a hyperpolarizing input in the inter-burst interval. This basic pattern was similar in all fast, semi-fast, and slow motoneurons that were recorded. Hyperpolarizations were in synchrony with activity in the antagonistic motoneurons. De- and hyperpolarizations were associated with a decrease in input resistance. All motoneurons showed spike frequency adaptation when depolarized by current injection to a membrane potential similar to that observed during walking. In the hyperpolarizing phase of fast flexor motoneurons, the initial maximum hyperpolarization was followed by a sag in potential toward more depolarized values. Consistent with this observation, only fast flexor motoneurons developed a depolarizing sag potential when hyperpolarized by injection of constant negative current.
This study focused on the contribution of different adrenoreceptor subtypes to the modulation of fictive swimming activity in a relatively simple, yet intact, lower vertebrate system, the immobilized Xenopus laevis tadpole and explored their possible role in mediating the noradrenergic modulation of spinal motor networks. In Xenopus embryos, near the time of hatching, activation of alpha(1) adrenoreceptors increased the duration of episodes of fictive swimming, whilst in larvae, 24 h after hatching, they were decreased. Activation of alpha(2) adrenoreceptors, however, markedly reduced episode duration at both developmental stages. Cycle periods in both stages were increased by the activation of alpha(1) and/or alpha(2) receptor subclasses, whereas beta adrenoreceptors were not apparently involved in the modulation of cycle periods or the duration of swim episodes. However, both beta and alpha(1) receptor activation decreased the intersegmental delay in the head-to-tail propagation of swimming activity, while alpha(2) receptors did not influence these rostro-caudal delays. Activation of neither alpha, nor beta, receptor subclasses had any consistent effect on the duration of ventral motor bursts. Our findings suggest that noradrenergic modulation of the swim-pattern generator in Xenopus tadpoles is mediated through the activation of alpha and beta adrenoreceptors. In addition, activation of particular receptor subclasses might enable the selective modulation of either the segmental rhythm generating networks, the intersegmental coordination of those networks or control at both levels simultaneously.
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