Figure 1.
Bursts of action potentials contain stimulus-specific information. A, Acridid grasshoppers produce species-specific acoustic communication signals by rasping their hindlegs across their forewings. This generates an amplitude-modulated broadband noise signal (AM signal). Shown are two such “songs” from males of the species C. biguttulus. Each song consists of many repetitions of a pair of basic patterns, called “syllable” and “pause,” episodes of high and low amplitude, respectively. B, Conspecific female grasshoppers respond to a certain range of syllable and pause durations, as tested with artificial block stimuli. Within the gray area, a female responded positively in at least 20% of all trials [data were taken from von Helversen and von Helversen (1994) with permission]. C, Enlarged AM signal with song parameters analyzed in the present study. The calculated amplitude threshold for this cell was 55.4 dB SPL. For illustrative purposes, pauses are only marked for threshold crossings that are followed by, on average, at least one spike per trial. Smaller amplitude modulations are neglected; they are also not perceived as pauses by the animal, as shown by behavioral experiments (Wohlgemuth, 2008 A. Einhäupl and B. Ronacher, unpublished results). D, Spike trains of a particular ascending auditory interneuron, the AN12. Syllable onsets trigger burst responses. The response latency of ∼12ms is attributable to acoustic delays, response latencies of the receptor neurons, axonal and synaptic delays, and the intrinsic AN12dynamics. E, IBSC as a function of the burst index (i.e., the position of the burst within the particular calling song). For the two songs in A, the black lines denote the median IBSC, and the gray lines indicate upper and lower quartiles. F, Probability of correctly classifying one of eight songs by IBSC only (chance level, 1/8). Dotted line, Classification using IBSCs from one burst index; solid line, classification by cumulating the information contained in IBSCs from the 10th burst up to the indicated burst. These data demonstrate that songs can be classified successfully in >90% of all trials if IBSCs from 12 or more bursts are used. Hence, the spike count within bursts is sufficient for conspecific song discrimination. Data shown in D–F are from one sample cell.