Context-dependent coding and gain control in the auditory system of crickets

被引:1
作者
Clemens, Jan [1 ,2 ,3 ]
Rau, Florian [1 ]
Hennig, R. Matthias [1 ]
Hildebrandt, K. Jannis [4 ,5 ]
机构
[1] Humboldt Univ, Dept Biol, Behav Physiol Grp, Berlin, Germany
[2] Bernstein Ctr Computat Neurosci Berlin, Berlin, Germany
[3] Princeton Univ, Princeton Neurosci Inst, Princeton, NJ 08540 USA
[4] Carl von Ossietzky Univ Oldenburg, Cluster Excellence Hearing4all, Dept Neurosci, D-26111 Oldenburg, Germany
[5] Carl von Ossietzky Univ Oldenburg, Res Ctr Neurosensory Sci, D-26111 Oldenburg, Germany
关键词
adaptive coding; auditory coding; cricket; gain control; inhibition; SPECTROTEMPORAL RECEPTIVE-FIELDS; TELEOGRYLLUS-OCEANICUS; SOUND FREQUENCY; CONTRALATERAL INHIBITION; ORIENTATION SELECTIVITY; GRYLLUS-BIMACULATUS; TUNING CURVES; NERVE FIBERS; NEURONS; RESPONSES;
D O I
10.1111/ejn.13019
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Sensory systems process stimuli that greatly vary in intensity and complexity. To maintain efficient information transmission, neural systems need to adjust their properties to these different sensory contexts, yielding adaptive or stimulus-dependent codes. Here, we demonstrated adaptive spectrotemporal tuning in a small neural network, i.e. the peripheral auditory system of the cricket. We found that tuning of cricket auditory neurons was sharper for complex multi-band than for simple single-band stimuli. Information theoretical considerations revealed that this sharpening improved information transmission by separating the neural representations of individual stimulus components. A network model inspired by the structure of the cricket auditory system suggested two putative mechanisms underlying this adaptive tuning: a saturating peripheral nonlinearity could change the spectral tuning, whereas broad feed-forward inhibition was able to reproduce the observed adaptive sharpening of temporal tuning. Our study revealed a surprisingly dynamic code usually found in more complex nervous systems and suggested that stimulus-dependent codes could be implemented using common neural computations.
引用
收藏
页码:2390 / 2406
页数:17
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