Individual Differences in the Use of Acoustic-Phonetic Versus Lexical Cues for Speech Perception

Previous research suggests that individuals with weaker receptive language show increased reliance on lexical information for speech perception relative to individuals with stronger receptive language, which may reflect a difference in how acoustic-phonetic and lexical cues are weighted for speech processing. Here we examined whether this relationship is the consequence of conflict between acoustic-phonetic and lexical cues in speech input, which has been found to mediate lexical reliance in sentential contexts. Two groups of participants completed standardized measures of language ability and a phonetic identification task to assess lexical recruitment (i.e., a Ganong task). In the high conflict group, the stimulus input distribution removed natural correlations between acoustic-phonetic and lexical cues, thus placing the two cues in high competition with each other; in the low conflict group, these correlations were present and thus competition was reduced as in natural speech. The results showed that 1) the Ganong effect was larger in the low compared to the high conflict condition in single-word contexts, suggesting that cue conflict dynamically influences online speech perception, 2) the Ganong effect was larger for those with weaker compared to stronger receptive language, and 3) the relationship between the Ganong effect and receptive language was not mediated by the degree to which acoustic-phonetic and lexical cues conflicted in the input. These results suggest that listeners with weaker language ability down-weight acoustic-phonetic cues and rely more heavily on lexical knowledge, even when stimulus input distributions reflect characteristics of natural speech input.

A model of naturalistic decision making in preference tests

Decisions as to whether to continue with an ongoing activity or to switch to an alternative are a constant in an animal’s natural world, and in particular underlie foraging behavior and performance in food preference tests. Stimuli experienced by the animal both impact the choice and are themselves impacted by the choice, in a dynamic back and forth. Here, we present model neural circuits, based on spiking neurons, in which the choice to switch away from ongoing behavior instantiates this back and forth, arising as a state transition in neural activity. We analyze two classes of circuit, which differ in whether state transitions result from a loss of hedonic input from the stimulus (an “entice to stay” model) or from aversive stimulus input (a “repel to leave” model). In both classes of model, we find that the mean time spent sampling a stimulus decreases with increasing value of the alternative stimulus, a fact that we linked to the inclusion of depressing synapses in our model. The competitive interaction is much greater in “entice to stay” model networks, which has qualitative features of the marginal value theorem, and thereby provides a framework for optimal foraging behavior. We offer suggestions as to how our models could be discriminatively tested through the analysis of electrophysiological and behavioral data.Author summaryMany decisions are of the ilk of whether to continue sampling a stimulus or to switch to an alternative, a key feature of foraging behavior. We produce two classes of model for such stay-switch decisions, which differ in how decisions to switch stimuli can arise. In an “entice-to-stay” model, a reduction in the necessary positive stimulus input causes switching decisions. In a “repel-to-leave” model, a rise in aversive stimulus input produces a switch decision. We find that in tasks where the sampling of one stimulus follows another, adaptive biological processes arising from a highly hedonic stimulus can reduce the time spent at the following stimulus, by up to ten-fold in the “entice-to-stay” models. Along with potentially observable behavioral differences that could distinguish the classes of networks, we also found signatures in neural activity, such as oscillation of neural firing rates and a rapid change in rates preceding the time of choice to leave a stimulus. In summary, our model findings lead to testable predictions and suggest a neural circuit-based framework for explaining foraging choices.

Effects of Spatial Location of Auditory Tones on Pitch Discrimination

Pitch discrimination accuracy has been found to be affected by many factors, including handedness, musical training, interfering stimuli, and spatial location of the auditory stimulus. Separating the stimulus input location of interference tones from initial (reference) and final (comparison) tones leads to more accurate pitch discrimination, but the effects of spatial location relationships between the reference, interference, and comparison tones have not been fully explored. This study examined the impact of stimulus spatial location in 24 young, nonmusician females. Participants determined whether the pitch of reference and comparison tones were the same or different in 20 pitch discrimination conditions with varied interference, spatial relationships, and frequencies. Findings revealed that pitch discrimination accuracy was significantly better when (a) there was no interference, (b) the comparison tone was presented to the contralateral brain hemisphere from reference and interference tones, and (c) the comparison tone was presented to the left ear. We discussed the implications of these findings for therapy programs to strengthen pitch discrimination abilities.

Visual mismatch negativity to disappearing parts of objects and textures

Visual mismatch negativity (vMMN), an event-related signature of automatic detection of events violating sequential regularities is traditionally investigated to the onset of frequent (standard) and rare (deviant) events. In a previous study [4] we obtained vMMN to vanishing parts of continuously presented objects (diamonds with diagonals), and we concluded that the offset-related vMMN is a model of sensitivity to irregular partial occlusion of objects. In the present study we replicated the previous results, but to test the object-related interpretation we applied a new condition with a set of separate visual stimuli: a texture of bars with two orientations. In the texture condition (offset of bars with irregular vs. regular orientation) we obtained vMMN, showing that the continuous presence of objects is unnecessary for offset-related vMMN. However, unlike in the object-related condition, reappearance of the previously vanishing lines also elicited vMMN. In a formal way reappearance of the stimuli is an event with probability 1.0, and according to the results, object condition reappearance is an expected event. However, offset and onset of texture elements seems to be treated separately by the system underlying vMMN. As an advantage of the present method, the whole stimulus set during the inter-stimulus interval saturates the visual structures sensitive to stimulus input. Accordingly, the offset-related vMMN is less sensitive to low-level adaptation difference between the deviant and standard stimuli.

Measuring the World

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus regularities on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes.

The Positivity Offset Theory of Anhedonia in Schizophrenia

Prior studies have concluded that schizophrenia patients are not anhedonic because they do not report reduced experience of positive emotion to pleasant stimuli. The current study challenged this view by applying quantitative methods validated in the evaluative space model of emotional experience to test the hypothesis that schizophrenia patients evidence a reduction in the normative “positivity offset” (i.e., the tendency to experience higher levels of positive than negative emotional output when stimulus input is absent or weak). Participants included 76 schizophrenia patients and 60 healthy controls who completed an emotional experience task that required reporting the level of positive emotion, negative emotion, and arousal to photographs. Results indicated that although schizophrenia patients evidenced intact capacity to experience positive emotion at high levels of stimulus input, they displayed a diminished positivity offset. Reductions in the positivity offset may underlie volitional disturbance, limiting approach behaviors toward novel stimuli in neutral environments.

An Algorithm for Forward Reduction in Sequence-Based Software Specification

Sequence-based software specification is a rigorous method for deriving a formal system model based on informal requirements, through a systematic process called sequence enumeration. Under this process, stimulus (input) sequences are considered in a breadth-first manner, with the expected system response to each sequence given. Not every sequence needs to be further extended by the enumeration rules. The completed specification encodes a Mealy machine and forms a basis for other activities including code development and testing. This paper presents a forward reduction algorithm for sequence-based specification. The need for such an algorithm has been identified by field applications. We used the state machine as an intermediate tool to comprehend and analyze all change impacts resulted from a forward reduction, and used an axiom system for its development. We present the algorithm both mathematically in functional form and procedurally in pseudocode, illustrate it with a symbolic example, and report a larger case study from the published literature in which the algorithm is applied. The algorithm will prove useful and effective in deriving a system-level specification as well as in merging and combining partial work products towards a formal system model in field applications.

A computational framework for temporal sharpening of stimulus input in the olfactory system

The olfactory bulb glomerulus is a dense amalgamation of many unique and interconnected cell types. The mechanisms by which these neurons transform incoming information from the sensory periphery have been extensively studied but often with conflicting findings. A recent study by Carey et al. ( J Neurophysiol 113: 3112–3129, 2015) details the computational framework for parallel modes of temporal refinement of stimulus input to the olfactory system mediated by local neurons within individual glomeruli.