Skoglund, M. | Search bioRxiv

bioRxiv2022

Multilevel Modelling of Gaze from Hearing-impaired Listeners following a Realistic Conversation

PurposeThere is a need for outcome measures that predict real-world communication abilities in hearing-impaired people. We outline a potential method for this and use it to answer the question of when, and how much, hearing-impaired listeners look towards a new talker in a conversation. MethodTwenty-two older hearing-impaired adults followed a pre-recorded two-person audiovisual conversation in the presence of babble noise. We compared their eye-gaze direction to the conversation in two multilevel logistic regression (MLR) analyses. First, we split the conversation into events classified by the number of active talkers within a turn or a transition, and we tested if these predicted the listeners gaze. Second, we mapped the odds that a listener gazed towards a new talker over time during a conversation transition. ResultsWe found no evidence that our conversation events predicted changes in the listeners gaze, but the listeners gaze towards the new talker during a silent-transition was predicted by time: The odds of looking at the new talker increased in an s-shaped curve from at least 0.4 seconds before to 1 second after the onset of the new talkers speech. A comparison of models with different random effects indicated that more variance was explained by differences between individual conversation events than by differences between individual listeners. ConclusionMLR modelling of eye-gaze during talker transitions is a promising approach to study a listeners perception of realistic conversation. Our experience provides insight to guide future research with this method.

neuroscience↗

bioRxiv2022

How short decoding times, stimulus dimensionality and spontaneous activity constrain the shape of tuning curves: A speed-accuracy trade-off

According to the efficient coding hypothesis, sensory neurons are adapted to provide maximal information about the environment given some biophysical constraints. Early sensory neurons modulate their average firing rates in response to some features of the external stimulus, creating tuned responses. In early visual areas, these modulations (or tunings) are predominantly single-peaked. However, periodic tuning, as exhibited by grid cells, has been linked to a significant increase in decoding performance. Does this imply that the tuning curves in early visual areas are sub-optimal? We argue that the time scale at which neurons encode information is imperative to understanding the relative advantages of single-peaked and periodic tuning curves. Because, if decoding ability scales differently with time for the different shapes of tuning curves, the time scale at which the neurons operate becomes critical. Here, we show that the possibility of catastrophic (large) errors due to overlapping neural responses for distinct stimulus conditions creates a trade-off between decoding time and decoding ability. Unfortunately, standard theoretical measures such as Fisher information do not capture these errors. We investigate how (very) short decoding times and stimulus dimensionality affect the optimal shape of tuning curves for stimuli with finite domains. In particular, we focus on the spatial periods of the tuning curves (or the number of "peaks") for a class of circular tuning curves. We show a general trend for minimal decoding time, i.e., the shortest decoding time required to produce a statistically reliable signal, to increase with increasing Fisher information implying a trade-off between accuracy and speed. This trade-off is reinforced whenever the stimulus dimensionality is high or there is ongoing activity. Thus, given constraints on processing speed, we present normative arguments for the existence of single-peaked, rather than a periodic, tuning organization observed in early visual areas.

neuroscience↗