The sound-evoked responses of extracellularly recorded cat primary auditory cortical neurons usually consist of a single spike or a short-term burst of 2-4 spikes, irrespective of the nature of the acoustic signal. In the cat's auditory cortex, the properties of such responses have to date been described only for cells in the primary field (AI). The purpose of the present study was to describe the properties of stimulus-evoked spike-burst responses seen in neurons of the posterior auditory field (P) and to compare those properties with those of a sample of AI neurons studied under similar conditions. The data come from 80 field P and 31 AI neurons studied with tonal and noise-burst stimuli in barbiturate-anesthetized cats, using calibrated, sealed stimulus delivery systems and conventional extracellular recording techniques. The mean inter-spike intervals (ISI) seen in the transient burst responses of posterior field cells were typically short (2-5 ms) and, where it was possible to test them, independent of the rise time of tonal signals, suggesting that they were also independent of the onset spectrum of the stimulus. The mean ISIs were often independent of the stimulus amplitude, even though the signal level had profound effects on the number of spikes evoked and the latency and regularity with which the responses were initiated. Each neuron was assigned a 'characteristic ISI', i.e., the mean ISI seen in the most vigorous responses. The distribution of characteristic ISIs for AI and P neurons overlapped, but were significantly different, with the characteristic ISIs of field P neurons being longer. In both AI and P populations, characteristic ISI was significantly correlated with minimal first-spike latency. The slopes of the regression lines of characteristic ISI on minimal latency for AI and for P cells were not significantly different from each other. Since the minimal latencies of AI neurons were usually shorter than those of field P neurons, the shorter characteristic ISIs of AI cells may thus be interpreted as secondary to their shorter latent periods. The general properties of stimulus-evoked spike bursts seen in field P neurons were thus very similar those previously described for AI cells. These data are consistent with the view that the majority of extracellular recordings in the cat's auditory cortex come from pyramidal neurons and are appropriate as a specialization for transfer of information to nonpyramidal, inhibitory interneurons.
Achieving the potential of widespread sharing of open research data requires that sharing data is straightforward, supported, and well-understood; and that data is discoverable by researchers. Our literature review and environment scan suggest that while substantial effort is dedicated to structured descriptions of research data, unstructured fields are commonly available (title, description) yet poorly understood. There is no clear description of what information should be included, in what level of detail, and in what order. These human-readable fields, routinely used in indexing and search features and reliably federated, are essential to the research data user experience. We propose a set of high-level best practices for unstructured description of datasets, to serve as the essential starting point for more granular, discipline-specific guidance. We based these practices on extensive review of literature on research article abstracts; archival practice; experience in supporting research data management; and grey literature on data documentation. They were iteratively refined based on comments received in a webinar series with researchers, data curators, data repository managers, and librarians in Canada. We demonstrate the need for information research to more closely examine these unstructured fields and provide a foundation for a more detailed conversation.
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