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Updated: Jun 27, 2026

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning
Published on: June 2, 2014
Neuronal encoding of meaning: establishing category-selective response patterns in the avian 'prefrontal cortex'
Janina A Kirsch1, Ioannis Vlachos, Markus Hausmann
1Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr-University Bochum, 44780 Bochum, Germany. Janina.Kirsch@ruhr-uni-bochum.de
Abstract:
Forebrain association areas interweave perceived stimuli with acquired representations of own actions and their outcome. Often, relevant stimuli come in a bewildering variety of shapes and sizes and we slowly have to learn to group them into meaningful categories. Therefore, the aim of the present study was twofold: First, to reveal how single units in the pigeon's nidopallium caudolaterale (NCL), a functional analogue of the mammalian prefrontal cortex (PFC), encode stimuli that differ in visual features but not in behavioral relevance. The second aim was to understand how these categorical representations are established during learning. Recordings were made from NCL neurons while pigeons performed a go-nogo categorization paradigm. Responses during presentation of the two S+ stimuli and non-responding during presentation of the two S- stimuli were followed by reward. We recorded from two pigeons at different learning stages. In the beginning of the learning process, neurons were active during and shortly before reward, but only in go trials. These data suggest that during the early phase of learning avian 'prefrontal' neurons code for rewards associated with the same behavioral demand, while ignoring feature differences of stimuli within one category. When learning progressed, (1) category selectivity became stronger, (2) responses selective for nogo stimuli appeared, and (3) reward-related responses disappeared in favor of category-selective responses during the stimulus phase. This backward shift in time resembles response patterns assumed by the temporal difference (TD) model of reinforcement learning, but goes beyond it, since it reflects the neuronal correlate of functional categories.
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