The psychophysics of absolute threshold and signal duration: A probabilistic approach

The absolute threshold for a tone depends on its duration; longer tones have lower thresholds. This effect has traditionally been explained in terms of ?temporal integration? involving the summation of energy or perceptual information over time. An alternative probabilistic explanation of the process is formulated in terms of simple equations that predict not only the time=duration dependence but also the shape of the psychometric function at absolute threshold. It also predicts a tight relationship between these two functions. Measurements made using listeners with either normal or impaired hearing show that the probabilistic equations adequately fit observed threshold-duration functions and psychometric functions. The mathematical formulation implies that absolute threshold can be construed as a two-valued function: (a) gain and (b) sensory threshold, and both parameters can be estimated from threshold-duration data. Sensorineural hearing impairment is sometimes associated with a smaller threshold=duration effect and sometimes with steeper psychometric functions. The equations explain why these two effects are expected to be linked. The probabilistic approach has the potential to discriminate between hearing deficits involving gain reduction and those resulting from a raised sensory threshold

Frequency decoding of periodically timed action potentials through distinct activity patterns in a random neural network

Frequency discrimination is a fundamental task of the auditory system. The mammalian inner ear, or cochlea, provides a place code in which different frequencies are detected at different spatial locations. However, a temporal code based on spike timing is also available: action potentials evoked in an auditory-nerve fiber by a low-frequency tone occur at a preferred phase of the stimulus-they exhibit phase locking-and thus provide temporal information about the tone's frequency. In an accompanying psychoacoustic study, and in agreement with previous experiments, we show that humans employ this temporal information for discrimination of low frequencies. How might such temporal information be read out in the brain? Here we demonstrate that recurrent random neural networks in which connections between neurons introduce characteristic time delays, and in which neurons require temporally coinciding inputs for spike initiation, can perform sharp frequency discrimination when stimulated with phase-locked inputs. Although the frequency resolution achieved by such networks is limited by the noise in phase locking, the resolution for realistic values reaches the tiny frequency difference of 0.2% that has been measured in humans.Comment: 16 pages, 5 figures, and supplementary informatio

Buber, educational technology, and the expansion of dialogic space

Buber’s distinction between the ‘I-It’ mode and the ‘I-Thou’ mode is seminal for dialogic education. While Buber introduces the idea of dialogic space, an idea which has proved useful for the analysis of dialogic education with technology, his account fails to engage adequately with the role of technology. This paper offers an introduction to the significance of the I-It/I-Thou duality of technology in relation to opening dialogic space. This is followed by a short schematic history of educational technology which reveals the role technology plays, not only in opening dialogic space, but also in expanding dialogic space. The expansion of dialogic space is an expansion of what it means to be ‘us’ as dialogic engagement facilitates the incorporation, into our shared sense of identity, of aspects of reality that are initially experienced as alien or ‘other’. Augmenting Buber with an alternative understanding of dialogic space enables us to see how dialogue mediated by technology, as well as dialogue with monologised fragments of technology (robots), can, through education, lead to an expansion of what it means to be human

Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation

Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing